Book Review: Financial Risk Management for Dummies

Financial Risk Management for Dummies. 2016. By Aaron Brown. John Wiley & Sons, Ltd., www.wiley.com. 384 pages, $26.99.

The dummies to whom Financial Risk Management for Dummies is addressed are not outright novices. Rather, they exemplify the maxim that a little bit of knowledge is a dangerous thing. Aaron Brown, chief risk officer of AQR Capital Management, devotes much of the book to dispelling mistaken notions about his subject.

“Risk management is not about predicting or preventing disaster,” he writes. Neither, says Brown, is it about estimating probabilities or outcomes. The “frequentist” approach, with its analogies to casino games, has only limited application. “If all risks were playing roulette or drawing cards,” Brown states, “we wouldn’t need risk managers.” There is little in the book about measuring risk because generally speaking, risk that is measurable can be avoided, insured, hedged, or neutralized via diversification. Contrary to the likely expectations of many investment professionals, Value at Risk (VaR) does not enter the discussion until Chapter 6.

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The Macroeconomic Effects of Housing Wealth, Housing Finance, and Limited Risk-Sharing in General Equilibrium


SvnieuweThis paper studies the role of time-varying risk premia as a channel for generating and propagating ‡fluctuations in housing markets, aggregate quantities, and consumption and wealth heterogeneity. We study a two-sector general equilibrium model of housing and non-housing production where heterogeneous households face limited opportunities to insure against aggregate and idiosyncratic risks. The model generates large variability in the national house price-rent ratio, both because it ‡fluctuates endogenously with the state of the economy and because it rises in response to a relaxation of credit constraints and decline in housing transaction costs (…financial market liberalization). These factors, together with a rise in foreign ownership of U.S. debt calibrated to match the actual increase over the period 2000-2006, generate ‡fluctuations in the model price-rent ratio that explains a large fraction of the increase in the national price-rent ratio observed in U.S. data over this period. The model also predicts a sharp decline in home prices starting in 2007, driven by the economic contraction and by a presumed reversal of the …financial market liberalization. Fluctuations in the model’s price-rent ratio are driven by changing risk premia, which ‡fluctuate endogenously in response to cyclical shocks, the …financial market liberalization, and its subsequent reversal. By contrast, we show that the infl‡ow of foreign money into domestic bond markets plays a small role in driving home prices, despite its large depressing infl‡uence on interest rates. Finally, the model implies that procyclical increases in equilibrium price-rent ratios re‡flect rational expectations of lower future housing returns, not higher future rents. JEL: G11, G12, E44, E21.


–Jack Favilukis, LSE; Sydney C. Ludvigson, NYU and NBER; Stijn Van Nieuwerburgh, NYU NBER CEPR

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Favilukis: Department of Finance, London School of Economics, Houghton Street, London WC2A 2AE; Email: j.favilukis@lse.ac.uk, http://pages.stern.nyu.edu/~jfaviluk. Ludvigson: Depart- ment of Economics, New York University, 19 W. 4th Street, 6th Floor, New York, NY 10012; Email: sydney.ludvigson@nyu.edu; Tel: (212) 998-8927; http://www.econ.nyu.edu/user/ludvigsons/. Van Nieuwerburgh : Department of Finance, Stern School of Business, New York University, 44 W. 4th Street, 6th Floor, New York, NY 10012; Email: svnieuwe@stern.nyu.edu; Tel: (212) 998-0673; http://pages.stern.nyu.edu/ svnieuwe/. This material is based on work supported by the National Science Foundation under Grant No. 1022915 to Ludvigson and Van Nieuwerburgh. We are grateful to Alberto Bisin, Daniele Coen-Pirani, Dean Corbae, Morris Davis, Bernard Dumas, Raquel Fernandez, Car- los Garriga, Bruno Gerard, Francisco Gomes, James Kahn, John Leahy, Chris Mayer, Jonathan McCarthy, Francois Ortalo-Magne, Stavros Panageas, Monika Piazzesi, Richard Peach, Gianluca Violante, Amir Yaron, and to seminar participants at Erasmus Rotterdam, the European Central Bank, ICEF, HEC Montreal, Lon- don School of Economics, London Business School, Manchester Business School, NYU, Stanford Economics, Stanford Finance, UCLA Finance, University of California Berkeley Finance, Université de Lausanne, Uni- versity of Michigan, University of Tilburg, University of Toronto, the University of Virginia McIntyre/Darden joint seminar, the American Economic Association annual meetings, January 2009 and January 2010, the ERID conference at Duke 2010, the London School of Economics Conference on Housing, Financial Markets, and the Macroeconomy May 18-19, 2009, the Minnesota Workshop in Macroeconomic Theory July 2009, the NBER Economic Fluctuations and Growth conference, February 2010, the European Finance Association meetings Frankfurt 2010, the NBER PERE Summer Institute meeting July 2010, the SED Montreal 2010, and the Utah Winter Finance Conference February 2010, the NBER Asset Pricing Meeting April 2011, the 2011 WFA meeting, the Baruch NYC Real Estate Meeting 2012, and the 2012 Philadephia Workshop on Macroeconomics for helpful comments. Any errors or omissions are the responsibility of the authors.


Derivatives and Systemic Risk: It’s Also about Jobs

Derivatives are the least understood component of systemic risk. Derivatives pose issues of size, measurement, and behavior—unlike loans. They string the biggest banks together in ways unseen three decades ago and even undermine job creation. Government officials may have had to bail in 2008, but nobody can claim that there will be no more bailouts until derivatives are better understood and managed.

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Recent Research: Highlights from Summer 2014

"Return Predictability and Dynamic Asset Allocation: How Often Should Investors Rebalance?"
The Journal of Portfolio Management (Summer 2014
Himanshu Almadi, David E. Rapach, and Anil Suri

To exploit return predictability via dynamic asset allocation, investors face the important practical issue of how often to rebalance their portfolios. More frequent rebalancing uses statistically and economically significant short-horizon return predictability to aggressively pursue the dynamic investment opportunities afforded by changes in expected returns. However, the degree of return predictability typically appears stronger at longer horizons, which, along with lower transaction costs, favors less frequent rebalancing. The authors analyze the performance effects of rebalancing frequency in the context of dynamic portfolios constructed from monthly, quarterly, semi-annual, and annual return forecasts for US stocks, bonds, and bills, where the dynamic portfolios rebalance at the same frequency as the forecast horizon. Along the transaction-cost/rebalancing frontier, monthly (annual) rebalancing provides the greatest outperformance when unit transaction costs are below (above) approximately 50 basis points, and dynamic portfolios based on annual rebalancing typically outperform the benchmarks for unit transaction costs well in excess of 400 basis points.

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Recent Research: Highlights from May 2014

"Constraints and Innovations for Pension Investment: The Cases of Risk Parity and Risk Premia Investing"
The Journal of Portfolio Management (Spring 2014
Wai Lee

In the current low real-yield environment, institutional investors are challenged as they try to achieve their often-fixed targeted returns within the confines of their investment policy guidelines. If much-discussed solutions, such as risk parity and risk premia investing, are the new answers, they must improve portfolio efficiency and flexibility in taking risks. This article explores the ways these proposed solutions may be successful. The author argues that the solutions neither introduce new assets that offer non-replicable, non-redundant return and risk characteristics, nor do they offer new asset-pricing theories that improve forecasts of asset returns or risks. Instead, their value proposition is more in the category of improved portfolio construction. They primarily benefit practitioners by providing more-efficient risk allocations, which they do by relaxing constraints to which pension investors are often subject, including restrictions on using leverage and short selling.

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3D Risk Management: A Survivorship Framework

Disparte, Dante picture

For most firms risk management is a necessary evil, increasingly consigned to being an adjunct to compliance, finance and other so called “business prevention” functions. Non-financial firms traditionally address risk through a series of transfer mechanisms, such as insurance, self-funded vehicles or they merely absorb unforeseen losses with their earnings. The financial sector, on the other hand, applies sophisticated statistical methods in a form of speculative risk management that captures the upside and the downside of risk-taking. These approaches are used to calculate value at risk (VaR), regulatory capital and other internal and external risk measures. Many of these methods, however, are based on backward looking book values and a permissive fox watching the chicken coop environment, wherein financial institutions often develop their own internal risk metrics with loose guidance from regulators. 

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Macroprudential Stress Tests Should Not Rely on Regulatory Risk Weights

The capital ratio of a bank1 is usually defined as the ratio of a measure of its equity to a measure of its assets. Regulatory capital ratio usually employs book value of equity and risk-weighted assets, where individual asset holdings are multiplied by corresponding regulatory ‘risk weights’. Macroprudential stress tests rely on models that translate an adverse macroeconomic scenario into losses to assets on the balance sheet of banks. These losses are assumed to be first borne by equity. The resulting capital ratios determine which banks fail the test under the stress scenario, and what supervisory or recapitalisation actions are undertaken to address this failure.

Recent concerns on the denominator of capital ratios – the risk-weighted assets – have been expressed in multiple surveys that point out the inconsistency in the calibration of risk weights (Le Lesle and Avramova 2012, Mariathasan and Merrouche 2013, BCBS 2013, Haldane 2012). This column argues that the inadequacy of risk-weighted assets is also responsible for producing an inadequate ranking of the required capitalisation of banks in stress tests. In order to establish the inadequacy of risk-weighted assets, Acharya et al. (2013) examine complementary approaches to measuring capital ratios and relate them to capital ratios based on risk-weighted assets.

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Recent Research: Highlights from February 2014

"Contribution of Pension and Retirement Savings to Retirement Income Security: More Than Meets the Eye"
The Journal of Retirement (Winter 2014)
Billie Jean Miller and Sylvester J. Schieber

Recently, much concern has been expressed about the U.S. retirement system. Social Security is underfunded, while supplemental plans reportedly provide benefits half only that of Social Security and have gained little ground over the last 40 years. The shift to defined contribution plans is often seen as problematic. Some analysts suggest scrapping tax preferences for retirement plans and expanding Social Security. Much evidence that supplemental plans are coming up short on enhancing retirement security comes from the Current Population Survey (CPS). The analysis here shows that most income from retirement plans is not captured by the CPS or the Social Security reports developed using it. Ignoring retirees’ growing private retirement savings and income distorts the role played by private pensions, resulting in inaccurate assessments of retirees’ economic status. This error may bias policymakers’ judgment as to the right policies for an aging population and underfunded pensions.

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Inflation Risk Premium Implied by Options


One of the commonly used estimates of expected inflation is the yield differential between nominal bonds and inflation-indexed bonds (breakeven inflation). Breakeven inflation is however a biased estimate of expected inflation because it includes an inflation risk premium (IRP). The novelty of our approach is that we estimate the IRP using the volatility implied from foreign exchange (FX) option prices combined with a price of risk extracted from stock prices. Purchasing Power Parity theory provides the linkage between inflation and the foreign exchange rate. Using data from the Israeli government bond market, which has a long history of liquid markets in inflation-linked and nominal bonds as well as an active FX options market, we find a statistically and economically significant positive inflation risk premium.

 JEL Classification: E31, E32, E51

Key words: Inflation expectations, inflation-indexed (linked) bonds, Inflation risk premium, foreign exchange options



Inflation expectations are a key variable for investors in capital markets and also play an important role in determining monetary policy in many countries, especially in countries with strong and independent central banks. In this paper we derive a market-based measure of unbiased inflation expectations, net of inflation risk premium (IRP), using data on inflation indexed government bonds, nominal government bonds and options on foreign exchange (FX) in lieu of options on inflation which are not available. A number of approaches are used to forecast inflation. Most models are econometric models, both structural and purely statistical. These models, however, rely on historic data and are not forward looking. Another source of inflation forecasts are surveys of professional analysts and economists. 1 Surveys are, however, based on samples that are usually small and therefore might not be representative of market expectations. In economies where inflation-indexed government bonds have been issued (e.g. TIPS in the U.S.) inflation expectations are derived from the yield differential between nominal bonds and inflation – indexed (real) government bonds. This estimate is referred to as breakeven inflation (BEI). 2 Inflation indexed bonds exist now in many countries.3 The BEI as a measure of inflation expectations is used by central banks in a number of countries (e.g., the Federal Reserve, the Bank of England, Bank of Canada and the Bank of Israel) 4 . The advantages of these estimates are that they are market based, forward looking, can be computed continuously and can provide the entire term structure of inflation expectations. Numerous papers have estimated inflation expectations in different countries from nominal and inflation indexed bonds. 5

–Eddy Azoulay, Bank of Israel; Menachem Brenner* Stern School of Business, New York University; Yoram Landskroner, College for Academic Studies Or Yehuda And School of Business dministration The Hebrew University of Jerusalem; Roy Stein, Bank of Israel

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We would like to thank Meir Sokoler, Michael Beenstock, Ami Barnea, Alex Ilek, Bill Silber, Paul Wachtel and participants of the Bank of Israel Reaserch Department seminar for their helpful comments. Thanks also to Helena Pompushko and Angela Barenholtz for their assistance.


Recent Research: Highlights from November 2013

"Are Risk-Parity Managers at Risk Parity?"
The Journal of Portfolio Management (Fall 2013)
Edward Qian

Risk parity has become an accepted investment strategy, to some degree. Its main advantage is its use of risk allocation, as opposed to the capital allocation used by the traditional asset allocation approach. A balanced risk allocation provides true diversification; therefore risk parity should deliver better risk-adjusted return over time. Despite the acceptance and the fact that the term “risk parity” has been in use for almost ten years, the investment community seems confused about risk parity’s true definition. Is it just a quantitative risk-budgeting technique? Is it about operational leverage? Or is it about high exposures to fixed income and low exposures to equities? In this paper, the author aims to define the principle of risk parity investing. He then examines a sample of risk parity managers, using the return-based style analysis pioneered by William Sharpe. The results show that, according to the defined principle, a number of risk parity managers in our sample are not using true risk parity.

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Asset Prices and Ambiguity


Modern portfolio theory, developed in the expected utility paradigm, focuses on the relationship between risk and return, assuming away ambiguity, uncertainty over the probability space. In this paper, we present an asset pricing model developed by Izhakian (2011), which incorporates ambiguity as a second factor (in addition to “risk”). Our contribution is two fold; we propose an ambiguity measure that is derived theoretically and computed from intra-day stock market prices. Second, we use it in conjunction with risk measures to test the basic relationship between risk,ambiguity and return. We find that our ambiguity measure has a consistently negative effect on returns and that our risk measure has mostly a positive effect. The best evidence, judging by statistical significance, is obtained when we use the change in volatility alongside the measure of ambiguity.

–Menachem Brenner and Yehuda Izhakian


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The ETFG Monthly Liquidation Watch List

June’s bond market rout captivated investors’ attention as fixed income ETFs saw their largest monthly redemptions in history. But this month’s ETF Liquidation Watch List, compiled by ETF Global, contains only four fixed income products, one less than last month, and they are all inverse funds.

The monthly compilation, found on ETF Global's website, quantifies all exchange traded products that hold below $5 million in AUM, have existed for at least two years and had negative performance for the trailing 12 months. That said, most fixed income ETFs that are older than two years still have positive performance for the trailing 12 months and have more than $5 million in assets. That is not the case for equity products that meet the three criteria and have seen their ranks swell on the list that contains a record 78 ETPs this month.

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Recent Research: Highlights from July 2013

"Framing Lifetime Income"
The Journal of Retirement (Summer 2013)
Jeffrey R. Brown, Jeffrey R. Kling, Sendhil Mullainathan, and Marian V. Wrobel

We provide evidence that individuals optimize imperfectly when making annuity decisions, and that this result is not driven by loss aversion. Annuities are more attractive when presented in a consumption frame rather than in an investment frame. Highlighting the purchase price in the consumption frame does not alter this result. The level of habitual spending has little interaction with preferences for annuities in the consumption frame. In an investment frame, consumers prefer annuities with principal guarantees; this result is similar for guarantee amounts below, at, and above the purchase price. We discuss implications for the retirement services industry and its regulators.

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Recent Research: Highlights from June 2013

"An Investment Strategy in Active ETFs"
The Journal of Index Investing (Summer 2013)
Sharon Garyn-Tal

Previous evidence suggests that selectivity or active management positively affects mutual fund performance, hedge fund performance, and passive ETF performance. I examine whether active ETF performance is also positively affected by active management. First, I look at active ETF performance estimated via the Fama–French–Carhart four-factor model. Second, using weekly return data on 10 active ETFs for the period 2008–2012, I find an investment strategy in active ETFs that earns a positive risk-adjusted excess return, based on R2 as extracted from the regression of the ETFs’ excess return on the four-factors’ excess return.

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Recent Research: Highlights from April 2013

"A Fund of Hedge Funds Under Regime Switching"
The Journal of Alternative Investments (Spring 2013)
David Saunders, Luis Seco, Christofer Vogt, and Rudi Zagst

This article investigates the use of a regime-switching model of returns for the asset allocation decision of a fund of hedge funds. In each time period, returns follow a multi-variate normal distribution from one of two possible regimes, corresponding to periods of “normal” and “distressed” markets. The prevailing regime in any given period is determined by the value of a two-state Markov chain. The case where serial correlation is absent and returns in different time periods are i.i.d. Gaussian mixture variables is also considered. The models are tested on empirical data and compared to a benchmark, assuming i.i.d. normally distributed returns. The results show that in a mean–variance framework, the use of regime switching can improve risk and performance measures. The importance of the sensitivity of optimal portfolio weights to the estimate of the probability of the distressed regime is discussed, and methods for calculating sensitivities are presented and illustrated on market data.

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Recent Research: Highlights from February 2013

"Volatility, Correlation, and Diversification in a Multi-Factor World"
The Journal of Portfolio Management (Winter 2013)
Richard Roll

In a multi-factor world, diversification benefits do not generally depend on correlation. Investors can restructure portfolios to align factor sensitivities. This implies that diversification benefits depend only on the idiosyncratic volatility that remains after restructuring. Similarly, the risk reduction that follows adding an asset to an existing portfolio does not depend on the asset’s correlation with the portfolio. These implications evince the fundamental importance of measuring the underlying factors and estimating factor sensitivities for every asset. Other researchers have investigated several methods for measuring factors. An easy-to-implement general method involves specifying a group of heterogeneous indexes or traded portfolios. Exchange-traded funds (ETFs) could be well suited to this purpose.

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Aggregate Risk and the Choice between Cash and Lines of Credit

We model corporate liquidity policy and show that aggregate risk exposure is a key determinant of how firms choose between cash and bank credit lines. Banks create liquidity for firms by pooling their idiosyncratic risks. As a result, firms with high aggregate risk find it costly to get credit lines and opt for cash in spite of higher opportunity costs and liquidity premium. Likewise, in times when aggregate risk is high, firms rely more on cash than on credit lines. We verify these predictions empirically. Cross-sectional analyses show that firms with high exposure to systematic risk have a higher ratio of cash to credit lines and face higher spreads on their lines. Time-series analyses show that firms' cash reserves rise in times of high aggregate volatility and in such times credit lines initiations fall, their spreads widen, and maturities shorten. Our theory and evidence shed new insights on the relation between macroeconomic risk, financial intermediation, and firm financial decisions.


–Viral V. Acharya, NYU–Stern, CEPR, ECGI & NBER; Heitor Almeida, University of Illinois & NBER; Murillo Campello, University of Illinois & NBER

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Cash Holdings and Credit Risk (1 of 2)


Intuition suggests that firms with higher cash holdings should be ‘safer’ and have lower credit spreads. Yet empirically, the correlation between cash and spreads is robustly positive. This puzzling finding can be explained by the precautionary motive for saving cash, which in our model causes riskier firms to accumulate higher cash reserves. In contrast, spreads are negatively related to the part of cash holdings that is not determined by credit risk factors. Similarly, although firms with higher cash reserves are less likely to default in the short term, endogenously determined liquidity may be related positively to the longer-term probability of default. Our empirical analysis confirms these predictions, suggesting that precautionary savings are central to understanding the effects of cash on credit risk.


Common intuition suggests that firms that have larger cash holdings in their asset and investment portfolio should be ‘safer.’ In particular, cash-rich firms should have a lower probability of default and lower credit spreads, other things equal. In this paper, we argue that, in general, other things are not equal, and that the intuitive, but na¨ıve, prediction falls prey to the confounding effects of endogeneity. We show empirically that a conservative cash policy is more likely to be pursued by a firm that finds itself close to distress. As a result, larger cash holdings are empirically associated with higher, not lower, levels of credit risk.

Our theoretical argument can be summarized as follows: The firm is a portfolio of assets, of which cash is one, and the composition of assets in the portfolio depends on the firm’s liability structure. In particular, when the risk of default increases, the firm increases its holdings of liquid assets in response. This adjustment offsets the change in risk, but only partially. As a result, a higher level of cash reflects changes across the firm’s assets and liabilities, but does not necessarily imply a safer firm overall.

We take predictions from this simple argument to the data to explore complex interactions between cash policy and credit risk. Two of our empirical results are particularly striking and counter-intuitive. First, when we replicate the reduced-form approach commonly used in empirical studies of credit spreads, we find that a one standard deviation increase in the cash-to-asset ratio is associated with an economically significant 20 basis point increase in credit spreads, after controlling for firm-specific characteristics such as leverage, volatility, and credit rating. Thus, it may appear that higher cash holdings increase credit spreads. The effect is robust and persistent.

Second, we explore the role of liquid assets in empirical default-predicting models, such as Altman’s (1968) z-score.1 While almost all such studies control for balance sheet liquidity, their findings concerning the effect of liquidity on the probability of default are inconclusive and often puzzling.2 When we re-estimate such models, we find that the correlation of liquidity with default depends crucially on the time horizon over which default is being considered. The short-term probability of default is lower when liquid asset reserves are large, consistent with the common intuition. However, for horizons over one year, the correlation between cash and default reverses sign and becomes positive and strongly statistically significant. It would appear that higher cash holdings increase the long-term probability of default.

What can explain these puzzling empirical findings? We propose a theory based on the endo- geneity of a levered firm’s cash policy. In the presence of financing constraints, riskier firms (for example, those with lower expected cash flows) optimally choose to maintain higher cash reserves as a buffer against the possible cash flow shortfall in the future. In the model, the firm firm can either invest its cash long term, or retain it as a cash buffer until the firm’s debt comes due. Market frictions restrict the firm’s access to external capital, and default is costly. The firm faces a trade-off between investing more (and getting higher cash flows in the future, conditional on not defaulting) and keeping more cash in a reserve (implying a lower probability of a cash shortage and thus a higher chance of survival).

In this model, a change in factors that affect the firm’s credit risk influences spreads and default probabilities through two channels: directly (the ‘direct’ channel), and through the adjustment in the level of cash holdings (the ‘indirect’ channel). For example, a decline in expected future cash flows leads to an increase in default probability and a corresponding rise in credit spreads. At the same time, the firm responds by optimally increasing its cash holdings, which reduces the probability of a cash shortfall and leads to lower spreads. The model’s main insight is that the direct channel dominates as long as constraints on external financing are binding. As a result, riskier firms have both higher optimal cash reserves and higher credit spreads and long-term default probability. Consistent with this prediction, we find empirically that for speculative-grade firms cash holdings increase in credit risk, as do credit spreads.

The model also implies that variations in cash holdings that are unrelated to credit risk factors (so that there is no direct effect on spreads) should be negatively related to spreads, in line with the standard intuition. Indeed, we find empirically that the correlation between cash and spreads, as well as that between cash and longer-term default probability, turns negative when we ‘instrument’ the variations in cash by such variables as proxies for managerial self-interest and firm’s long-term investment opportunities. Finally, the model also predicts that over a short horizon, higher cash reserves reduce the prob- ability of default (consistent with the findings of Davydenko (2011)), but may increase it over a longer period, reconciling the seemingly conflicting evidence of the effect of cash holdings in default- predicting studies.

Our findings highlight the importance of adopting the corporate finance prospective in asset pricing studies. For instance, extant credit risk models typically assume that should the firm find itself in a temporary cash shortage, it avoids default by costlessly selling new equity, as long as the share price remains positive, rendering cash policy irrelevant.3 This approach is mirrored in empirical credit risk studies, which also do not consider the role of cash holdings.4 Our results suggest that theoretical and empirical studies of credit risk (and likely other areas of asset pricing) should account for the endogeneity of corporate financial and investment policies.5 Otherwise, employing the most common balance-sheet ‘control’ variables (such as proxies for corporate liquidity) in standard tests (such as predictive regressions of default) may yield economically misleading conclusions.

Our paper is related to the stream of papers in corporate finance on the endogenous determination of corporate cash holdings, such as Opler, Pinkowitz, Stulz, and Williamson (1999), Almeida, Campello, and Weisbach (2004), and Bates, Kahle, and Stulz (2009). In this literature, the precau- tionary motive for hoarding cash arises because of financing frictions that restrict firms’ access to external financing. Recently, studies such as Eisfeldt and Muir (2012) have extended this approach to look into the implications of financial constraints for the dynamics of financing and cash holdings. However, extant research does not explicitly link cash holdings to credit risk or credit spreads, as we do. Moreover, we show that precautionary motives for saving cash are of first-order importance even for rated public bond issuers, suggesting that these firms exhibit behavior qualitatively similar to that of more financially constrained firms.

1. The model

This section develops a model of a firm’s optimal cash policy in the presence of costly default and restricted access to external financing. Our main goal is to show that cash holdings in equilibrium can be positively correlated with credit spreads and default risk, and to discuss the economic mechanisms behind this counter-intuitive relationship. We disentangle the intuitive, but na¨ıve, prediction that cash-rich firms should be ‘safer’ from the confounding effects of endogeneity. As discussed in Section 1.2, although the model is stylized, our conclusions are quite general. In an online appendix we develop a continuous-time model of endogenous cash policy, which delivers the same main results as outlined in this section.

1.1. Model setup

The model features a single levered firm in a three-period investment economy. The firm has both assets in place and growth opportunities. In each period t from 0 to 2, its assets in place produce a cash flow xt . For our purposes, it is important that the interim-period cash flow x1 is random and unknown at date 0. We can write x1 as x1 = x1 + u, where x1 is a known constant and u is a zero-mean random cash flow shock. The probability distribution of u is described by the density function g(u) with support [u, ∞),6 and with the associated cumulative distribution function G(u) and the hazard rate h(u), defined as:

We assume the hazard rate h(u) to be weakly monotonically increasing.7 For our purposes, it is sufficient that the cash-flow shock u is the only source of randomness in the model, and hence we assume that the cash flows at dates 0 and 2 are known. As will become clear below, the timing in the model is such that allowing for a random component in these cash flows would neither alter shareholders’ incentives nor affect our results in any way.

At date t = 0, the assets in place generate a positive cash flow x0 > 0. At this time, the firm has access to a long-term project, which in return for investment I at t = 0 yields a deterministic cash flow of f (I ) at t = 2, where f (I ) is a standard increasing concave production function. Market frictions preclude the firm from accessing outside financing, so that the firm’s disposable cash comes entirely from its internal cash flow, x0. This cash can be invested, either partially or fully, in the long-term project, or retained within the firm as a cash reserve, carried over from date 0 to date 1. We denote the cash reserve as c, so that c = x0 − I .

At date t = 1, the firm must make a debt payment of B, which is assumed to be predetermined (a legacy of the past).8 We also assume that debt cannot be renegotiated due to high bargaining costs; for example, it might be held by dispersed bondholders prone to co-ordination problems. Failure to repay the debt in full at t = 1 results in default and liquidation, in which future cash flows both from the long-term investment, f (I ), and from the assets in place, x2 , are lost. As the period-1 cash flow, x1 , is random, there is no assurance that it will be sufficient to repay the debt in full. Moreover, due to market frictions, external financing is unavailable, and hence the debt payment must be made out of the firm’s internal funds. This gives rise to incentives for the firm to retain part of its cash between periods 0 and 1 as a buffer against a possible future cash shortfall, to reduce the probability of default.

The firm’s equityholders maximize the final-period payoff. The risk-free rate of interest is nor- malized to zero, and, in the base case, managers act in the best interests of shareholders. Figure 1 illustrates the model’s timeline.

FIgure 1


The timeline of the model.

Before proceeding further, we want to stress that the exact specification of the model can vary widely without affecting the results qualitatively, as long as two assumptions are satisfied. First, default involves deadweight costs. (Although we assume that all future cash flows are lost in default, an extension to a partial loss is straightforward.) Second, external financing cannot be raised against the full value of future cash flows, meaning that there are some financing frictions at date 1. If the firm can pledge a large enough fraction of its future cash flows as collateral, then current and future cash holdings can be viewed as time substitutes, and there is no role for precautionary savings of cash. In reality, the condition of partial pledgeability is likely to be universally met. While the base-case model assumes that external financing is prohibited altogether, Subsection 1.6 extends the model by allowing the firm to borrow up to a certain fraction of its future cash flows at t = 1, and shows that our main results hold as long as financing constraints are sufficiently binding.

A related feature in our model is that a non-trivial part of the cash flow from the current investment will be realized only after a portion of the outstanding debt is due, giving rise to a time mismatch between cash flows and liabilities. Effectively, the expected long-term cash flow can neither be pledged nor used as cash to cover debt obligations. In practice, most capital expenditure items are likely to satisfy this requirement, because they usually generate cash flows after some non- trivial debt payments. In the base-case model, we assume that the investment outcome is realized in full only at date 2. This assumption can be relaxed so that the investment also can generate a cash flow at date 1. What is needed is a non-trivial fraction of cash flows expected after the debt payment is due, so that firm survival at the intermediate stage is a worthy option.

In general, in addition to saving and investing, firms can also distribute some of the cash to their shareholders. Fixed, pre-committed dividends at t = 0 amount to a reduction in the net cash flow x0, and can be easily incorporated in the model. Although modeling an optimal dividend policy at t = 0 would complicate the analysis considerably by introducing a second choice variable, the intuition is straightforward. Most firms in the model would choose not to pay any dividend, because the cash can be profitably invested in the long-term project. However, if the firm is very risky, the precautionary motive for saving cash can be dominated by the incentives to engage in ‘asset substitution’, i.e., to pay out a large immediate dividend at the expense of making the firm even riskier. In our base-case model, we assume that in order to prevent such behavior, discretionary dividends are prohibited by covenants.


If the firm has access to external capital at t = 0, it can choose to raise additional capital at that time to increase its investment and/or cash holdings. Selling equity can be viewed as making a negative dividend payment. By the same logic as above, in our model a firm should normally find it desirable to raise equity, as long as the marginal value of an additional dollar of investment is greater than one. However, if the firm is very risky, instead of investing, shareholders would have incentives to pay themselves a dividend rather than contribute additional equity. By contrast, raising debt maturing at t = 1 that is more senior than the existing debt solely in order to increase the cash reserve is value-neutral in this setting, as the increase in cash is exactly offset by the increase in the required debt repayment (i.e., cash is negative debt in our model). In our base-case model, we assume that financing constraints at t = 0 preclude the firm from accessing any additional financing. Allowing for optimally chosen financing ex ante could be an interesting extension of our model.

To assert the generality of our main results, we have constructed a fully dynamic continuous-time model that relaxes some of the assumptions of the base-case model. In the model, the firm is financed by equity and infinite-maturity debt with continuously paid coupon. In contrast with the base-case model, investment is fixed, but dividends are endogenously determined. The firm’s cash flow is first used for debt service. The remainder can be paid out as dividends or retained within the firm as a buffer against a possible cash flow shortage. The firm faces a trade-off between higher dividends and higher cash reserves that reduce the probability of default. Although this setting is very different from the base-case model, its main predictions regarding the relationship between cash and credit risk are very similar. A full description of this model can be found in the online appendix, also available from the authors upon request.

Returning to the base-case model, note that cash reserves are costly to the firm because they are financed by reductions in long-term investment. This way of modeling the cost of cash holdings is convenient, but by no means unique. For example, Kim, Mauer, and Sherman (1998), Anderson and Carverhill (2007), and Asvanunt, Broadie, and Sundaresan (2007) assume that cash has a convenience yield because of taxes or agency issues. In our model, forgone investment should be understood more broadly as the opportunity cost of cash. For example, in our continuous model outline above, investment is fixed but the dividend policy is optimally determined. In that model, the opportunity cost of retaining cash is represented by the value of unpaid dividends.

1.3. Optimal cash policy

At date 0, the firm faces the following trade-off between investing its cash in the long-term project and retaining it until the next period. On the one hand, larger retained cash holdings imply lower investment. This results in lower future cash flows generated by the long-term investment conditional on survival in the interim period. On the other hand, an increase in cash holdings reduces the probability of a cash shortage at date 1, and thus increases the likelihood that the firm survives until date 2 to reap the benefits of the long-term investment. The firm’s optimal cash and investment policies balance these costs and benefits of cash.9

The amount of cash available for debt service at date 1 is c + x1 , where c = x0 − I is the cash reserve and x1 = x1 + u is the interim-period cash flow from assets. The ‘default boundary,’ or the minimum cash flow shock that allows the firm to repay B in full and avoid default, is:10

The default boundary increases in the level of debt and sunk investment, and decreases in realized date-0 and expected date-1 cash flows. For all realizations of u between u and uB , the firm defaults and equityholders are left with nothing. The total payoff to equityholders is the sum of the cash flows from assets in place and the payoff from the long-term investment, less the invested amount and the debt repayment, provided that the firm does not default on its debt in the interim. The market value of equity is therefore:3

which can also be rewritten intuitively as:


Here, u − uB is the amount of cash left in the firm after B is repaid, and f (I ) + x2 is shareholders’ claim on period-2 cash flow, conditional on the firm not defaulting in the interim.

Managers maximize the value of equity by choosing the optimal level of investment. From Equation (3), equityholders’ optimization problem yields the following first-order condition:11

Substituting the expression for xB from Equation (2) and rearranging, we can rewrite this first-order condition as:

In the first-best case of unrestricted investment, the standard maximization solution would yield f(I) = 1. In the presence of costly default and restricted access to outside financing, investment is below its first-best level. This follows from Equation (6), given that the right-hand side is greater than one. To understand the intuition behind the optimal investment and cash policies, notice that the first-order condition (5) can be re-written as follows:

The left-hand side in Equation (7) is the net value gain from increasing investment by dI , which is equal to (f(I)− 1) dI , multiplied by 1 − G(uB) to condition on the probability of survival. The right-hand side gives shareholders’ marginal expected loss from default, equal to the value of equity at the default boundary, f(I ) + x2, multiplied by the marginal increase in the probability of default due to the shift in the default boundary, g(uB) duB.

The market value of the firm’s debt, D, is:

which equals the face value of debt B adjusted for the loss that creditors expect to incur in default states [u, uB]. (Note that creditors recover c + x1 in case of default.)

With the riskless interest rate at zero, the credit spread, denoted s, coincides with the total debt yield, given by:

1.4. Cash holdings and credit spreads

In this subsection, we study the correlation between credit spreads and cash reserves, which arises when they both adjust in response to changes in model parameters.

The effect of any variable y on the credit spread can be decomposed into two components, which we call direct and indirect effects. First, the spread may depend on y directly, for example, because yaffects the default boundary and hence the likelihood of default. Second, a change in y may induce a change in the optimal cash reserve c, which in turn alters the default boundary and thus affects spreads (an indirect effect through cash).

It is convenient to introduce a special term for variations in cash not induced by changes in credit risk factors. Formally, suppose that cash holdings depend on a variable y that does not affect spreads directly, so that ∂s/∂y = 0. In particular, within our model this condition implies that y does not enter the expression for the default boundary uB , nor does it affect the distribution of the time-1 cash flow, g(u). When all other variables are fixed, y can affect spreads only indirectly, through its effect on cash. We will refer to changes in cash holdings induced by changes in variables that do not affect spreads directly as ‘exogenous’ (to credit risk). By contrast, variations in cash are ‘endogenous’ (to credit risk) if they are induced by changes in credit risk factors. It should be emphasized that an ‘exogenous’ variation in cash need not be due to factors outside the firm’s control. Instead, it can arise as the firm optimally adjusts its cash policy in response to changes in firm characteristics that have no direct effect on credit spreads.

1.4.1. Endogenous variations in cash

A change in many variables that affect spreads directly may also cause cash to adjust in the same direction, so as to undo the direct effect partially. For example, a direct effect of a drop in the expected cash flow is to raise the yield spread. However, optimal cash holdings also increase, which in turn decreases the spread (the indirect effect of the drop in cash flow). Other variables, such as the level of debt and the volatility of cash flow, may produce similar effects. This subsection shows that such adjustments in cash can result in a positive correlation between cash holdings and credit spreads in the cross-section.

Let ‘’ denote the equilibrium values of the variables, so that I and c = x0 − I are the equilibrium levels of investment and cash holdings, and s = s(c) is the credit spread when I = I. The following Proposition summarizes the effect of changes in the expected date-1 cash flow, x1 on cash holdings and spreads (see Appendix for all proofs):

When the expected cash flow decreases, the probability of a cash flow shortage at the time of debt repayment increases, so that the direct effect is to make the firm riskier and to raise the credit spread. The first part of Proposition 1 states that the firm’s optimal response is to alleviate the increase in risk by increasing its precautionary savings. This gives rise to the indirect effect of the decrease in cash flow, which is to reduce spreads. The second part of Proposition 1 states that the direct effect dominates, so that despite their larger cash holdings, firms with lower expected cash flows have higher credit spreads. In practice, this means that when cash flow levels are allowed to vary over time or in the cross-section, this variation can induce a positive correlation between endogenously chosen cash reserves and credit spreads.

To understand why the direct effect dominates, notice that for each dollar of decline in the expected cash flow, the firm increases its cash reserves by less than a dollar. This can be seen from the first-order condition (6), which balances the marginal cost of cash due to lower investment with its marginal benefit due to lower probability of default. Suppose that the expected cash flow decreases by $1, so that without any adjustments, the default boundary would drop by $1. In response, the firm reduces investment and increases the cash reserve, so that the boundary does not drop as much. However, since the production function is concave and the hazard function h(·) is non-decreasing, for the Equation (6) to be satisfied again, investment has to drop by less than $1. Thus, the concavity of the production function makes one-for-one reductions in investment prohibitively costly. As a result, cash holdings increase by less than $1, so that the net effect of the drop in the expected cash flow is to reduce the default boundary and thus to increase the credit spread. The intuition behind this economic mechanism is quite general: If the cost of increasing cash levels to offset higher default risk is convex, the firm offsets default risk only partially, and the direct effect on spreads dominates.12

As noted above, similar effects can arise due to variations in firm characteristics other than the cash flow, if they affect both spreads and optimal cash holdings. For example, suppose that the firm’s debt level increases. The direct effect of this increase is to raise spreads. However, optimal cash holdings also rise, which dampens the effect of higher debt levels on spreads. It can be shown that the direct effect dominates, much as in the case of varying expected cash flow in Proposition 1. As a result, more indebted firms have both higher cash levels and higher spreads, implying a positive cross-sectional correlation between the two. Similar effects may also arise when the initial cash flow, x0, is allowed to vary, or when the firm pays a fixed dividend that reduces its net cash flow (see Subsection 1.2).

1.4.2. Exogenous variations in cash

This subsection considers the effect of ‘exogenous’ variations in cash, which are not induced by changes in credit risk factors. It is easy to show that such cash variations are negatively correlated with credit spreads, consistent with the simple intuition that firms with more cash should be ‘safer’ and have lower spreads.

This Proposition states that when a factor that is unrelated to credit risk causes cash holdings to increase, credit spreads fall in response. In other words, spreads are negatively related to ‘exogenous’ (to credit risk) changes in cash.

In our empirical analysis, we refer to factors y that induce an exogenous variation in cash as instruments. To be an instrument, a variable must affect cash holdings without altering creditors’ payoffs or the probability of default other than through changes in cash. Put differently, an instru- ment would not affect spreads if cash were held constant. Formally, instruments in our model are variables that enter the first-order condition (Equation (6)), but not the expression for the value of debt (Equation (8)). Assuming that external financing cannot be raised against any part of period-2 cash flow, both the cash flow from assets in place, x2, and the parameters of the production function, f(·), satisfy these requirements. Variations in cash induced by changes in these variables would be negatively correlated with spreads.

Example 1: Growth options. The long-term cash flow from assets in place, x2, can be inter- preted as the value of the firm’s growth options. An increase in the growth option increases the value of equity conditional on survival, and hence enhances shareholders’ incentives to conserve cash to avoid default. At the same time, as this cash flow is not collateralizable, it does not benefit short-term creditors directly. Since the growth option does not enter the expression for the value of debt, it affects spreads only indirectly, through the induced variation in cash holdings. It follows from Proposition 2 that the resulting cross-sectional variation in cash is negatively correlated with credit spreads.

More generally, when external financing is not fully prohibited, a fraction of the long-term cash flow can be used as collateral in order to raise external financing. Anticipating this at t = 0, the firm would substitute some of its cash reserve with future external financing, which would enter the expression for the default boundary and thus affect the probability of default directly. Thus, not every long-term cash flow can provide an instrument. Only variations in the levels of those assets that the firm does not anticipate using as collateral at the time when it chooses its cash holdings (i.e., at t = 0) can play this role.113 One example of an instrument would be any unanticipated shock to the firm’s cash that occurs between t = 0 and debt maturity.14 As discussed above, non-collateralizable long-term growth options also induce exogenous variations in cash. Other non-collateralizable assets, such as human capital, can play the same role.

It is worth emphasizing that in more general settings with multiple classes of debt, some variables can be used as an instrument for some debt obligations, but not for others. For example, if at time t a firm has two outstanding bonds with different maturities, T1 < T2, then non-collateralizable assets that produce a cash flow between T1 and T2 do not affect the value of the short-term debt but can affect the cash reserve at t, and hence can be used as an instrument for analyzing the relationship between cash and the short-term credit risk. However, the cash flow from the same assets affects the value of the long-term debt directly (by increasing the amount of cash available at T2), and hence cannot be used as a long-term instrument.15

Example 2: Managerial losses in distress. Another example of a non-collateralizable ‘asset’ is the private benefit that managers derive from avoiding default. Gilson (1989), Baird and Rasmussen (2007), and Ozelge and Saunders (2008) find that upon distress, there is a significantly higher probability of top-management dismissal, especially due to direct intervention by lending banks, and that managers dismissed in distress suffer a significant private cost in the form of diminished future employment opportunities. Eckbo and Thorburn (2003) find that in Sweden, where creditor rights include automatic firing of the manager in default, managers of bankrupt companies suffer a median (abnormal) income loss of 47%. Managers’ private costs of distress likely depend on the structure of their compensation contracts.16 Differences in managerial compensation across firms should thus result in different incentives for managers to save cash in order to avoid default, because the private costs differ. As a result, differences in compensation can induce an exogenous variation in cash holdings.

Consider the following extension of the base-case model. Assume that the firm’s risk-neutral manager owns a share θ > 0 of the equity E and incurs a fixed, private cost γ > 0 if the firm defaults. For a given ownership level θ, the manager’s incentives to retain cash increase with the private cost of distress γ. Conversely, given γγ, they decline with her ownership of the firm θ. The overall effect on the manager’s chosen cash policy depends on the ratio of managerial cost to equity stake,γ, which can be interpreted as a measure of agency problems between the manager and equityholders. The higher the manager’s private cost of default and the lower her equity stake, the more conservative the firm’s cash policy (relative to one that maximizes the overall value of equity), resulting in lower credit spreads for the same underlying level of credit risk. Formally,the manager’s objective is to choose investment I to maximize:

As shown in the Appendix, this case is technically very similar to that of the variation in x2, and the cross-sectional correlation between cash holdings and spreads induced by variations in the agency factor γ is thus negative.

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1 Other prominent studies include Ohlson (1980), Zmijewski (1984), Shumway (2001), and Chava and Jarrow (2004)

2For example, the correlation of the probability of default with the current ratio is positive in Zmijewski (1984) and negative in Shumway (2001), whereas that with the ratio of working capital to total assets is negative in Ohlson (1980) and positive in Hillegeist et al. (2004).

3This assumption is made in most prominent credit risk models, such as Black and Cox (1976), Leland (1994), Longstaff and Schwartz (1995), Collin-Dufresne and Goldstein (2001), and others. Notable exceptions include recently developed models by Acharya, Huang, Subrahmanyam, and Sundaram (2006), Anderson and Carverhill (2007), Gamba and Triantis (2008), Asvanunt, Broadie, and Sundaresan (2010), and Gryglewicz (2011), which allow for optimal cash holdings in the presence of costly external financing.

4E.g., Collin-Dufresne, Goldstein, and Martin (2001), Duffee (1998), and Schaefer and Strebulaev (2008).

5Although the endogeneity of firm characteristics is recognized as a major issue in empirical corporate finance and many other areas of economic research (Roberts and Whited (2012)), it appears to have attracted less attention in asset pricing studies.

6Although the firm’s cash flow can be negative, it is bounded from below by investors’ limited liability. We assume that the minimum cash flow shock, u, is large enough for the limited liability to be satisfied.

7This assumption is unrestrictive and often appears in economic applications, such as game theory and auctions (e.g., Fudenberg and Tirole (1991, p.267)). Bagnoli and Bergstrom (2005) show that the hazard rate is weakly monotonic if the function (1 − G(u)) is log-concave, which holds for uniform, normal, logistic, exponential, and many other probability distributions.

8Although firms can choose not only cash holdings but also debt levels, variations in cash holdings are likely to be much larger than those in leverage ratios. To test this conjecture, we use annual Compustat data between 1980 and 2006, focusing on non-financial firms with non-trivial debt amounts (book leverage above 5%). We find that for the median firm, the coefficient of variation (standard deviation divided by the mean) for cash as a proportion of total assets is 0.80, compared with 0.36 for total debt over total assets and only 0.27 for book equity over total assets, with differences significant at the 1% level. Thus, cash holdings are likely to be more easily adjusted than debt levels. Therefore, in our analysis of the optimal cash policy we treat debt as exogenous.

9Covenant restrictions may prevent the firm from investing at the optimum. Should this be the case, the firm may end up with excessive cash reserves (from equityholders’ point of view) and our results are likely to be strengthened. 10Without loss of generality, we assume that uB ≥ u.

11It is easy to show that the second-order condition for maximization is satisfied. We also assume that initial cash holdings are high enough for the first-order condition to yield an interior solution.

12This discussion underscores the importance of financing constraints. If the firm can pledge a sufficiently high proportion of its long-term cash flow to creditors as collateral, long-term income can play only a secondary role as a cash substitute. The marginal cost of cash holdings is then effectively reduced and Proposition 1 may not hold. We discuss the case of partially pledgeability in Subsection 1.6.

13We would like to thank the referee for pointing out this property of instruments.

14For example, if the firm obtains an unexpected settlement in a lawsuit (see Blanchard et al (1994)), its cash reserve increases exogenously and its debt becomes safer as a result of the change in cash.

15Simutin (2010) also finds that firms with growth options hold more cash. He suggests that if growth options are risky, then cash holdings might be positively related to firm riskiness. Our model clarifies that firm riskiness induced by growth options may not necessarily be related to credit risk, if on average growth options arrive beyond the maturity of the firm’s debt. Thus, whether cash holdings induced by growth options are independent of the firm’s credit risk depends on the debt’s maturity structure, and is ultimately an empirical question, which we examine in Section 3 below.

16Managerial incentives have also been shown to be important in studies of capital structure (Carlson and Lazrak (2010)) and corporate takeovers (Pinkowitz, Sturgess, and Williamson (2011)).


A Proposal for the Resolution of Systemically Important Assets and Liabilities: The Case of the Repo Market


One of the several regulatory failures behind the global financial crisis that started in 2007 has been the regulatory focus on individual, rather than systemic, risk of financial institutions. Focusing on systemically important assets and liabilities (SIALs) rather than individual financial institutions, we propose a set of resolution mechanisms, which is not only capable of inducing market discipline and mitigating moral hazard, but also capable of addressing the associated systemic risk, for instance, due to the risk of fire sales of collateral assets. Furthermore, because of our focus on SIALs, our proposed resolution mechanisms would be easier to implement at the global level compared to mechanisms that operate at the level of individual institutional forms. We, then, outline how our approach can be specialized to the repo market and propose a repo resolution authority for reforming this market.

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Recent Research: Highlights from September 2012

"The Most Successful Theory of Economics "
The Journal of Derivatives (Fall 2012)
Mark Kritzman

Ross has called options pricing theory “the most successful theory in all of economics.” Kritzman expands on Ross’s comment to justify this assertion and notes the role of The Journal of Derivatives in disseminating the benefits of this most successful of theories to the world at large.

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Recent Research: Highlights from August 2012

"Diversification Return and Leveraged Portfolio"
The Journal of Portfolio Management (Summer 2012)
Edward Qian

It is widely accepted that portfolio rebalancing adds diversification return to fixed-weight portfolios, but this is only true for long-only unleveraged portfolios. Qian provides analytical results regarding portfolio rebalancing and the associated diversification returns for different kinds of portfolios including long-only, long-short, and leveraged. He shows that portfolio rebalancing is linked to underlying portfolio dynamics. For long-only unleveraged portfolios, rebalancing amounts to a mean-reverting strategy, and the diversification return is always non-negative. But for short (or inverse) and leveraged portfolios, portfolio rebalancing on the top-down level amounts to a trend-following strategy that detracts from diversification return. Qian analyzes diversification returns of risk parity portfolios and shows that the diversification return of a leveraged long-only portfolio can generally be decomposed into two parts, both of which are related to a scaled unleveraged portfolio. The first part is the positive diversification return from rebalancing among individual assets at the bottom-up level, which is amplified by leverage. The second part is the negative diversification return caused by the leverage of the overall portfolio. His numerical examples show that diversification return is, in general, positive for leveraged risk parity portfolios when the leverage ratio is not too high. In addition, he shows that low correlations between different assets are crucial in achieving positive diversification return and reducing portfolio turnover for risk parity portfolios.

"The Rubber Starts to Meet the Road: Achievable Results in US Housing Finance Reform"
The Journal of Structured Finance (Summer 2012)
Chris DiAngelo

This article begins by noting that the US Congress and the Administration both remain stymied in the area of housing finance reform, notwithstanding numerous “white papers,” “requests for information,” “roundtables,” and the like. After almost four years, Fannie Mae and Freddie Mac remain in conservatorship, with no clear exit plan. Looking past the top level (Congress and the White House), however, one will see that the two government-sponsored enterprises (GSEs) themselves and their regulator/conservator, the Federal Housing Finance Agency, have begun to make real progress in several areas. In early 2012, the FHFA released a strategic plan for the GSEs and followed that up with a “scorecard” that sets forth in some detail a “to do” list of items that the FHFA intends to get done, along with target dates for those items. The article focuses on four items in particular: the REO disposition program, the “new securitization platform” initiative, the “single security” concept, and the possibility of privatizing the multifamily business. The conclusion is that more progress is being made than the public generally believes.

"Kicking the Habit: How Experience Determines Financial Risk Preferences"
The Journal of Wealth Management (Fall 2012)
Joachim Klement and Robin E. Miranda

Conventional explanations for the diversity of risk preferences among individual investors offer only limited insight. Recent research in neuroscience, genetics, and behavioral decision making underscore the importance of experience in financial risk taking. The authors review these findings and argue that not only does individual experience influence risk taking, so do the collective experiences of groups. Additionally, there seems to be a significant genetic component to financial risk taking, suggesting that “evolutionary experience” also needs to be considered when analyzing the risk preferences of individual investors. The authors introduce some simple tools to identify the influence of experience on financial risk preferences. These tools can help financial advisors to accurately assess investors’ risk preferences to help them achieve their goals at an acceptable level of risk.

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Recent Research: Highlights from July 2012

"Specification Risk and Calibration Effects of a Multifactor Credit Portfolio Model"
The Journal of Fixed Income (Summer 2012)
Gregor Dorfleitner, Matthias Fischer, and Marco Geidosch

This article examines a crucial source of specification risk when calibrating a typical industry-type, Merton-based credit portfolio model. It emerges from the necessity of having to choose a proxy for creditworthiness. In addition to equity prices and asset values, which are the classical choices, the authors consider credit default swap (CDS) spreads and expected default frequencies (EDF, from Moody’s KMV) as alternatives. Based on 40 large European companies from different industries, the authors calibrate a macroeconomic factor model with an OLS regression analysis for each specification and calculate the corresponding economic capital. Eighteen macroeconomic and financial variables are considered as risk factors. Their findings are: a) on average, 2 to 3 risk factors are needed to adequately model creditworthiness on the obligor level, b) stock market variables are the most important risk factors, c) model-implied credit correlation is extremely sensitive to the choice of the proxy for creditworthiness, and d) only the EDF specification leads to less economic capital compared with regulatory capital, according to Basel II, while it is exceeded substantially by all other specifications. In particular, credit correlation in the CDS specification by far exceeds any estimate mentioned in the literature. Most important, the authors show that the economic capital of their sample portfolio can be reduced by 78%, depending on which variable is chosen as a proxy for creditworthiness.

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Investment Management Fees Are (Much) Higher Than You Think

CFA Institute

Although some critics grouse about them, most investors have long thought that investment management fees can best be described in one word: low. Indeed, fees are seen as so low that they are almost inconsequential when choosing an investment manager. This view, however, is a delusion. Seen for what they really are, fees for active management are high—much higher than even the critics have recognized.

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Recent Research: Highlights from June 2012

"Some Like It Hot: The Role of Very Active Mandates across Equity Segments in a Core-Satellite Structure"
The Journal of Investing (Summer 2012)

Frank Nielsen, Giacomo Fachinotti, and Xiaowei Kang

This article reviews the active management opportunity in different market segments, and discusses the role of very active mandates across segments in a core–satellite portfolio structure. Research based on manager performance data over the last 10 years indicates that there is little evidence that average emerging market or small-cap managers have produced higher or more persistent risk-adjusted returns relative to their developed market large-cap peers. Therefore, institutional investors may consider active and passive management as complementary strategies across all equity segments. Due to the outperformance of high active risk mandates over the analyzed period, a simulated core–satellite structure across different equity segments achieved a higher information ratio than a combination of low active risk managers. The outperformance of high active risk mandates may reflect links between higher manager skill, higher investment conviction, and/or fewer constraints. Depending on investment beliefs, institutional investors might explore such a core–satellite structure to implement the global equity allocation.

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Recent Research: Highlights from April 2012

"Defending the “Endowment Model”: Quantifying Liquidity Risk in a Post–Credit Crisis World"
The Journal of Alternative Investments (Spring 2012)

Abdullah Z. Sheikh and Jianxiong Sun

This article sets forth the proposition that liquidity risk may be optimized in an attempt to forestall or minimize the impact of a liquidity crisis. For a generic (but typical) endowment asset allocation, the authors find that liquidity levels between 6% and 14% are optimal, all other things equal, because 95% of the time, an allocation in this range would obviate situations in which a portfolio’s payout rate exceeds its liquidity pool. The framework also provides insights for tail-risk events involving a particularly severe liquidity crisis. For a generic endowment portfolio, the analysis indicates that in order to reduce the severity of a liquidity crisis to zero (i.e., eliminate risk completely), the allocation to fixed income would have to be around 35% (close to seven times the payout rate of 5%). Such an allocation would entail a very significant opportunity cost in terms of forgone returns based solely on a desire to mitigate extreme liquidity events (the proverbial “100-year flood”). In the authors’ view, reducing the likelihood of a liquidity crisis to below 5%, may be undesirable for all but the most risk-averse and least return sensitive endowments.

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A Tale of Two Overhangs: The Nexus of Financial Sector and Sovereign Credit Risks


There has emerged in the Western economies a strong nexus between the credit risks of financial sectors and their sovereigns. We argue that this phenomenon can be understood in the context of two debt overhang problems: one affecting the financial sector due to its under-capitalization following the crisis of 2007–08; the second, affecting the non-financial sector, whose incentives are crowded out by high sovereign debt and anticipated future taxes. While the desire to resolve the financial sector overhang may make bailouts tempting, they raise the risk of exacerbating the overhang related to sovereign debt. Conversely, reduction of growth prospects due to sovereign debt overhang can make the financial sector riskier as it is highly exposed to sovereign debt both through direct holdings and indirectly through implicit government guarantees. We provide evidence on this important nexus, based on our ongoing research that exploits data on European bank and sovereign credit risks.

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Recent Research: Highlights from February 2012

"Measuring and Modeling Execution Cost and Risk"
The Journal of Portfolio Management (Winter 2012)
Robert Engle, Robert Ferstenberg, and Jeffrey Russell

Financial markets are considered to be liquid if a large quantity can be traded quickly and with minimal price impact. Although the idea of a liquid market involves both a cost as well as a time component, most measures of execution costs tend to focus on only a single number that reflects average costs and do not explicitly account for the temporal dimension of liquidity. In practice, trading takes time because larger orders are often broken up into smaller transactions or because of price limits. Recent work shows that the time taken to transact introduces a risk component in execution costs. In this setting, the decision can be viewed as a risk–reward trade-off faced by the investor who can solve for a mean-variance utility-maximizing trading strategy. Engle, Ferstenberg, and Russell introduce an econometric method to jointly model the expected cost and risk of the trade, thereby characterizing the mean-variance tradeoffs associated with different trading approaches, given market and order characteristics. They apply their methodology to a novel dataset and show that the risk component is a nontrivial part of the transaction decision.

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With the Financial Markets Growing Riskier Why Aren’t Risk Managers More in Demand?



Risk management is a lot like anger management. It’s one of those disciplines you don’t really notice until it’s no longer there and things suddenly go awry. To put it simply, risk management is tasked with assessing, mitigating, and monitoring the potential for a bad outcome. When it’s working, everything runs smoothly. When it doesn’t … well, just turn on your television to any business channel.

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Mathematical Role Models

Whether you are an aspiring risk manager, quantitative analyst, or a trader, your first order of business is to manage risk. Fundamental analysis can tell you what a company is worth or whether a sector is undervalued theoretically, but market prices and volatility have their say also. You come to find that entries and exits are important, but ultimately risk management comes down to position sizing.

From there you can purchase expensive backtesting/simulation software and a subscription to the data that you need to run through it, but unless you have been trained in what all the boxes you've checked before you click "Run" mean, you will likely have data mined and over optimized your way to hypothetical success.

At various times of my career I have used such simulation software. Admittedly, it is very helpful and still is in some ways. It is very fast in its calculations and can also run Monte Carlo simulations for you, for example. However, nothing will replace the knowledge you will get from having to learn to do it from the ground up. I have done that too. My first model was created by hand on spreadsheets: first Lotus 123 cum Excel.

Constructing a portfolio that will provide you and your clients with the best risk-adjusted returns, while suitably diversifying your holdings, is done by teams these days. Teams that have a great deal of resources and intellectual capital. You need to learn how to construct such a model in order to compete in the global marketplace that is seeming to become more and more uncertain each day, perhaps by yourself at the beginning. It may appear to be easy in theory, but it is much harder in practice. One of the best things you can do to get started in an affordable manner is to become very proficient in Excel.

Quantitative hedge funds (Quant funds), such as AQR and Renaissance, spend enormous amounts of time, money, and effort to make sure they sift through oceans of data to find the most profitable opportunities. They also invest in the best personnel...many of whom have PhD's in Quantitative Finance or hold designations such as the CQF (Certification in Quantitative Finance). The competition is brutal, and this is before you have to fight off the high frequency traders...

Successful risk managers know the limitations of VaR, the Kelly formula, and CAPM. As Aaron Brown, Risk Manager of AQR wrote in his new book, Red Blooded Risk, "Successful risk taking is not about winning a big bet or even a long series of bets. Success comes from winning a sufficient fraction of a series of bets, where your gains and losses are multiplicative.

In order to get to the place where you can affect such trades, you need to test the data. I believe that this is best accomplished these days in an affordable manner using Excel. Thankfully, Excel has dozens of built-in mathematical functions that which can utilize advanced techniques that can give you the answers you need with the statistical significance to boot.

Without these answers, you will not have the emotional nor statistical confidence to manage the risk, nor will you have the answers to the questions that are frequently being asked in today's environment: "What happens if....?"


–Michael Martin

Michael Martin has been a successful trader for over 20 years. He is the creator of "Martin Kronicle," author of The Inner Voice of Trading, and instructor of the NYSSA Certificate in Commodity Trading & Trend Following.


European Safe Bonds (ESBies)

The euro-nomics groupi,*

Markus Brunnermeier, Luis Garicano, Philip R. Lane, Marco Pagano, Ricardo Reis, Tano Santos, Stijn Van Nieuwerburgh, and Dimitri Vayanos

26th of September 2011


The European Union today faces one of the greatest challenges in its existence. The euro-zone, which just at the start of this century was lauded as Europe's great unifying achievement, has given way to states on the verge of default, financial systems that seem as solid as a deck of cards, and a great deal of disappointment with the European institutions. There are many reasons for this state of affairs, most of which fall within the realm of economics. One factor, that is crucial but under-appreciated is that Europe's problems are a consequence of a much wider, world, problem: the lack of safe assets. As a long-term trend, the impressive growth in the developing world during the last two decades has increased the demand for safe assets, as those countries' economic development outpaces their financial development yet they already need to build up reserves to smooth future shocks. As a short-term phenomenon, but one that is here to stay, the financial crisis of 2007–08 showed that financial markets can go through periods of tremendous volatility that have investors plunging towards an asset that is deemed safe.ii.

Modern financial systems rely heavily on safe assets. At the foundation of even the most complex financial securities there is usually a requirement to post as collateral some asset that is deemed safe by the parties involved. Prudent bank regulation, following Basel in its many rounds, requires banks to manage the risk in their assets in proportion to their capital. As a result, a substantial part of any bank's balance sheet must be in safe assets, as defined by the financial regulators. Pension funds are another example of a large class of investors that must hold a significant amount of safe assets, and even the least risk-averse of investors needs, even if only temporarily, to park investments in a safe vehicle. Finally, in conducting conventional monetary policy, the central bank should exchange money for safe bonds.

A safe asset for all of these purposes is one tha is liquid, that has minimal risk of default, and that is denominated in a currency with a stable purchasing power. To meet the large demand we just described, there is very little supply of assets satisfying these three characteristics. As a result, the most used of them, the U.S. Treasury bills and bonds, earn a large "safe haven" premium of as much as 0.7% per year.iii Europe, in spite of the size of its economy and its developed financial markets, and in spite of being home to one of the worlds' reserve currencies, does not supply a safe asset that rivals U.S. Treasuries. This has been noted before. What is less appreciated is that this deficiency is at the heart of the current European crisis.

In the absence of a European safe asset, bank regulators, policymakers, and investors have treated the bonds of all of the sovereign states in the euro-area as safe for the last 12 years. Bank regulators following the Basel criteria give sovereign bonds held by national banks a riskless assessment in calculating capital requirements, even as insuring against the default of some sovereign bonds using credit default swaps costs more than 5% today. The stress tests of European banks rule out, by assumption, the likely default in some of the sovereign assets held by the banks, making it difficult for investors to trust them. European policymakers have treated Greek and Dutch bonds as identically safe, even though they have traded at widely different prices in the market. The ECB accepts sovereign bonds of all its member states in its discounting operations, and while it applies different haircuts to them, they have been generous towards the riskier sovereigns. In turn, national policymakers have persuaded national banks to hold larger amounts of local national debt than prudent diversification would suggest. Finally, investors have been fervently speculating on whether sovereign states will be bailed out or not by their European partners, alternating between seeing the bonds as all equally safe, or seeing some of them as hopelessly doomed.

This situation led to two severe problems. First it created a diabolic loop, illustrated in Figure 1. Encouraged by the absence of any regulatory discrimination among bonds, European banks hold too much of their national debts, which, far from being safe, instead feeds never-ending speculation on the solvency of the banks. Sovereigns, in turn, face a constant risk of having to rescue their banks, which, combined with the uncertainty on what fiscal support they will receive from their European partners, increases the riskiness of their bonds. Finally, European policymakers lack the institutions and own resources to intervene in all of the troubled sovereign debt markets. The ECB ends up holding the riskiest of the sovereign bonds as the ECB becomes the sole source of financing for the troubled banks.

Figure 1: Diabolic Loop between Sovereign Debt Risk and Banking Debt Risk.

 Stern fig 1

Breaking this loop, and giving the euro-zone a chance to survive in the long run, requires creating a European safe asset that banks can hold without being exposed to sovereign risk. However, contrary to what is widely believed, this does not require creating Eurobonds, backed in solidarity by all the European states and their taxing power. Many Europeans are not willing to accept the fiscal integration required by Eurobonds. Moreover, without essential control mechanisms on national public accounts, hastily introduced Eurobonds may lead to a much larger debt crisis in a few years, from which there is no way back. We offer an alternative that creates a safe asset, while eliminating these problems with Eurobonds.

The second severe problem is that, in the absence of a European safe bond, the bonds of some sovereigns at Europe’s center have satisfied the demand for safe assets. In times of crisis, capital flows from the periphery to the center; in boom phases, capital flows from the center to the periphery. These alternating capital flows between searching for “yield” and searching for “safe haven”, generate large capital account imbalances in the Euro area, with associated changes in relative prices and potential disruptions in asset markets.iv

Our proposal is to create European Safe Bonds (ESB), which we will refer to as ESBies for short.v They are European, issued by a European Debt Agency in accord with existing European Treaties, and do not require more fiscal integration than the one we already have. They are Safe, by virtue of being designed to minimize the risk of default, being issued in euros and benefitting from the ECB's anti-inflation commitment, and being liquid as they are issued in large volumes and serve as safe haven for investors seeking a negative correlation with other yields. They are Bonds, freely traded in markets, and held by banks, investors and central banks to satisfy the demand that we described.

Combined with appropriate regulation that gives the correct risk weights to sovereign bonds, ESBies could solve the two problems that we just described. Banks would have an alternative to sovereign bonds, allowing them to become better diversified and less dependent on their country’ public finances. Moreover, the flight of capital to a “safe haven” would no longer be across borders, but across different financial instruments issued at the European level.

This document lays down the details of how ESBies work. The next section explains the proposal. Section 3 lists the main benefits that ESBies would bring. Section 4 to 6 go deeper into the nuts and bolts of ESBies explaining, in turn, how their composition is determined, how their safety is ensured, and how they would be issued. Section 7 compares our proposal with alternatives, the leading one being Eurobonds. Section 8 briefly concludes.


In one sentence, ESBies are securities issued by a European Debt Agency (EDA) composed of the senior tranche on a portfolio of sovereign bonds issued by European states, held by that agency and potentially further guaranteed through a credit enhancement.

In more detail, our proposal is for the EDA to buy the sovereign bonds of member nations according to some fixed weights. The weights would be set by a strict rule, to represent the relative size of the different member States. There would be no room to change the weights by discretion to respond to any crises, perceived or real. Therefore, the EDA cannot bail out a nation having difficulties placing its sovereign debt. It would typically run a boring business that does not make the headlines: It would simply passively hold sovereign bonds as assets in its balance sheet, and use them as collateral to issue two securities.

The first security, ESBies, would grant the right to a senior claim to the payments from the bonds held in the portfolio. If the tranching cut-off is X%, then the first X% lost in the pool of bonds because of potential European sovereign defaults would have no effect on the payment of the ESBies. The remaining 1-X% of revenues from holding the bonds would go to the holders of the ESBies. The number X% is relatively large, so that even in a worst-case scenario (e.g. a partial default by Greece, Portugal and Ireland and a haircut on Italian and Spanish debt), the payment on the ESBies would not be jeopardized. On top of it, the EDA, using some initial capital paid in by the member states, would offer a further guarantee on the payment of Y% of the ESBies, so that it would take losses of more than Y+X% before the ESBies did not offer a perfectly safe payment in euros to its holders. As long as this sum was picked adequately, the ESBies would be effectively safe. European banks, pension funds and the ECB would be a natural starting clientele for the ESBies, but as their reputation grows, they could be as widely used as US Treasuries are used today all over the world. They could also be used as reserve currency assets by countries such as China, Brazil, the OPEC, etc.

The second security, composed of the junior tranche on the portfolio of bonds, would be sold to willing investors in the market. In contrast with the ESBies, this is a risky security, akin to an equity claim on the EDA (but obviously without control rights). Any risk that a sovereign state may fail to honor in full its debts would be reflected in the expected return on this security. Any realized losses would be absorbed by the holders of this junior security, and not by the EDA nor the European Union nor its member States. Investors that want to hedge (or even speculate) on the ability of European member states to repay their debt would be willing to hold and trade this security.

Beyond being correctly designed and issued, the success of the ESBies depends on two regulatory changes. First, the ECB would grant strict preferential treatment to ESBies, accepting them as its main form of collateral in repo and discounting operations. In effect, the ECB would still be holding sovereign bonds as assets, but now indirectly via the ESBies; and, importantly, it would only hold the safest component of these sovereign bonds. Because of the fixed weights in the ESBies, this would be consistent with conventional monetary policy, where open market operations trade money for safe ESBies without creating credit risk for the ECB and ensuring it has a safe balance sheet. Second, banking regulators, including Basel, would give a zero risk weight to ESBies, but not automatically to other sovereign bonds. The new risk weights for European sovereign bonds will reflect their default risk just as risk weights reflect the risk on banks’ holdings of other assets such as corporate bonds or corporate loans.

Figure 2 summarizes the details in this description. There are three parts of the proposal that require further explanation: how to set the weights in the portfolio of sovereign bonds? How to choose the size of the ESBies relative to the junior tranche and the credit enhancement? And how would the EDA operate day-to-day? These are explained in more detail in sections 4 to 6. But, before discussing the details in more depth, we summarize the virtues of the proposal.

Figure 2: Graphical Representation of Tranching with Possible Credit Enhancement.


Stern fig 2

1 | 2 | 3 | 4 | APPENDIX |Next Page


*Euro-nomics is a group of concerned European economists, unaffiliated with any of their respective national governments. Their objective is to provide concrete, carefully considered, and politically feasible ideas to address the serious problems currently faced by the Eurozone. Their affiliations can be found at the end of the present document and on www.euro-nomics.com

i. This is an extract from a chapter of a book being produced as a larger project, Project Europe, by the euro-nomics group: www.euro-nomics.com. That project proposes a new institutional framework for the European financial system to overcome the current crisis. European Safe Bonds are one of the legs of that proposal, and are explained in this document. We are not sponsored by any organization or institution and are independent from any country or policy institution.

ii. Farhi, Gourinchas and Rey (2011) go in detail over the many reasons why the demand for safe assets far outstrips supply today.

iii. Krishnamurthy and Vissing-Jorgensen (2010) estimate this premium.

iv.Some empirical evidence for the “flight to safety premium” for German bunds is that their yield sank to an almost record low in August and September, while at the same time the CDS spread for German bunds increased, indicating that even Germany’s default risk was increasing.

v.ESBies has the merit of capturing the sound of two possible initials for the securities, ESB for European Safe Bonds, and ESBBS for European Sovereign Bond-backed Securities.


Recent Research: Highlights from November 2011

"Breadth, Skill, and Time"
The Journal of Portfolio Management (Fall 2011)
Richard C. Grinold and Ronald N. Kahn

The information ratio determines the potential of an investment process to add value, and according to the fundamental law of active management, adding value depends on a combination of skill and breadth. Grinold and Kahn use an equilibrium dynamic model to provide insight into the concept of breadth, as well as a refined notion of skill. In equilibrium, the arrival rate of new information exactly balances the decay rate of old information. Grinold and Kahn denote the information turnover rate g. It is relatively easy to measure for any investment process. If the investment process forecasts returns on N assets, the breadth of the strategy i is g · N. Skill—the correlation of forecasts and returns—increases with the return horizon for small horizons, but then asymptotically decays to zero for very long horizons. The authors’ main result is that the ex ante information ratio is Breadth, Skill, and Time , where κ is a measure of skill.

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Investors Step Up Pressure for Integrated Reporting

We live in a world of rapid human population growth and consumption,  heightened resource scarcity, and the attendant stresses placed by all these factors, not to mention our "business as usual" economy on the earth's ecosystem.   Corporations must acknowledge this and can no longer afford to operate without closely monitoring, managing, and disclosing their environmental, social, and [corporate] governance (ESG) risks—any one of which can explode into a crisis with very material financial consequences. Asset managers who fail to require the companies in which they invest to step up to the plate and take on this responsibility are rightfully being viewed as shirking their own fiduciary duty. 

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Portfolio Heat: When Corn Starts Popping

When your portfolio heat increases too fast, too soon, you need to cut your position size(s) down to lower the overall risk to your portfolio. Else you have a Jiffy Pop portfolio.

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Recent Research: Highlights from August 2011

Risk-Based Asset Allocation: A New Answer to an Old Question? The Journal of Portfolio Management (Summer 2011). Wai Lee.

In recent years, we have witnessed an alarmingly large and growing amount of literature on portfolio construction approaches focused on risks and diversification rather than on estimating expected returns. Numerous simulations applied to different universes have been documented in support of these approaches based on their apparent outperformance versus passive market capitalization–weighted or static fixed-weight portfolios. Many studies attribute the better performance of these risk-based asset allocation approaches to superior diversification. Given the absence of clearly defined investment objective functions behind these approaches as well as the metrics used by these studies to evaluate ex post performance, Lee puts these approaches into the same context of mean-variance efficiency in an attempt to understand their theoretical underpinnings. In doing so, he hopes to shed some light on what these approaches attempt to achieve and on the characteristics of the investment universe, if indeed these approaches are meant to approximate mean-variance efficiency. Rather than adding to the already large collection of simulation results, Lee uses some simple examples to compare and contrast the portfolio and risk characteristics of these approaches. He also reiterates that any portfolio which deviates from the market capitalization–weighted portfolio is an active portfolio. He concludes that there is no theory to predict, ex ante, that any of these risk-based approaches should outperform.

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Fully Flexible Extreme Views

Figure 1: View on CVaR: extensive search of minimum relative-entropy posteriorThe combination of subjective views within a broadly accepted risk model is one of the main challenges in quantitative portfolio management. Indeed, any risk model, be it based on historical scenarios, parametric fits, or Monte Carlo scenarios generated according to a given distribution, is subject to estimation risk and thus it is inherently flawed. Therefore, it is important to provide a framework that allows practitioners to overlay their judgement to any risk model in a statistically sound way.

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Recent Research: Highlights from July 2011

The Role of Speculators During Times of Financial Distress.” The Journal of Alternative Investments (Summer 2011). Naomi E. Boyd, Jeffrey H. Harris, and Arkadiusz Nowak.

One of the best-known and largest hedge fund failures was the 2006 failure of Amaranth Advisors, LLC. The authors use detailed, trader-level data to examine the role of speculators during times of financial distress—in this case, the failure of Amaranth. They find that speculators served as a stabilizing force during the period by maintaining or increasing long positions, even while prices fell. The authors develop two testable propositions regarding liquidation versus transfer of positions and conclude that the probability of transfer was more likely for distant contract expirations and for contracts more dominantly held by the distressed trader. The article also examines the role of speculators in providing liquidity and mitigating the effects of liquidity risk by evaluating the change in the number of traders, the size and time between trades, and a Herfindahl measure of speculative trader concentration during the crisis period.

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Fully Flexible Views: Theory and Practice

Scenario analysis allows the practitioner to explore the implications on a given portfolio of a set of subjective views on possible market realizations, see e.g. Mina and Xiao (2001). The pathbreaking approach pioneered by Black and Litterman (1990) (BL in the sequel) generalizes scenario analysis, by adding uncertainty on the views and on the reference risk model. Further generalizations have been proposed in recent years. Qian and Gorman (2001) provide a framework to stress-test volatilities and correlations in addition to expectations. Pezier (2007) processes partial views on expectations and covariances based on least discrimination. Meucci (2009) extends the above models to act on risk factors instead of returns, and thus covers highly non-linear derivative markets and views on external factors that influence the p&l only statistically.

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Robert Litterman: Who Should Hedge Tail Risk?

CFA InstituteIn a somewhat ironic turn of events, many investment banks began selling insurance against equity tail risk to institutional investors following the financial crisis. Ironic because one might expect that investment banks, with high leverage and quarterly earnings reports to worry about, would be the natural buyers of such insurance and long-horizon investors the natural sellers.

Surely, those with deep pockets and long horizons, who would be little affected by the crisis, should be selling insurance to those with short horizons and leveraged positions, who would be most highly affected.

Of course, there will always be a price low enough that a given investor would be willing to buy insurance, and there will always be a price high enough that the same investor would be willing to sell insurance. But investors who have long horizons, sufficient liquidity, and low leverage should consider carefully whether, in practice, the price at any given time is low enough that buying tail-risk insurance makes sense for them. That scenario is unlikely because long-horizon investors are not natural buyers of tail-risk insurance.

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Sustainable Mining—An Oxymoron or a Challenge to be Met?

It can be argued that the mining industry is at a decided disadvantage as it attempts to establish its creds as a sector of the economy committed to making a contribution to a more sustainable economy. As Stephen D’Esposito, former executive director of Earthworks, suggests in an article published in  Corporate Ethics Monitor, “Is Mining Sustainable?” the very fact that mining is in the business of depleting finite natural resources argues that the term sustainable mining will forever be oxymoronic. However, mine we must, and the industry has much headway to make in reducing the tremendous amounts of energy it consumes, water it pollutes, toxins it emits, solid waste it produces, landscapes it scars, and habitats it disturbs in the process of extracting minerals and metals from the earth. The challenge on all these fronts becomes greater as the process of extraction becomes technically more difficult and more environmentally damaging as the richest mineral deposits are increasingly depleted, requiring that ever-larger volumes of rock and soil be disturbed to extract a given amount of mineral or metal.

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Suggestions for Modern Security Analysts

Ben Graham Economics is the social science that most identifies itself with the natural sciences. There is much that can be written about this statement in light of the events that unfolded in the 2007–2008 credit crisis, but this article focuses on the consequences pertaining to the field of Security Analysis, which is an economics-based discipline.

Security Analysis seeks to value firms based on the goods and services sold to customers via the assets (tangible and intangible) and obligations (liabilities) generated to support those sales. Despite the simplicity of this exposition, and the related simplicity of cash flow-based valuation, assessing value can be extremely difficult. The difficulty stems from the well-known fact that value is subjective, and from the equally well-known fact that the future is uncertain. Subjectivity and uncertainty means that Security Analysis requires many working assumptions, which is important because modern economics is currently grounded in mathematics that accommodates only a limited number of assumptions. As a purely theoretical, science-like endeavor this may (or may not) work, but Security Analysis is a profession, and professions are concerned with decision-making in contrast to science, which is concerned with prediction.

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BP’s Failure to Debias: Underscoring the Importance of Behavioral Corporate Finance

“BP has a systemic problem with its culture that runs deep.”

Ending the Management Illusion, Shefrin (2008), p. 95.

“In the view of the Commission, these findings highlight the importance of organizational culture and a consistent commitment to safety by industry, from the highest management levels on down.”

Report to the President, National Commission on the BP Deepwater Horizon Oil Spill and Offshore Drilling, (2011), p. ix.


In this paper, we apply key concepts from behavioral finance to document how psychological biases and framing effects impacted corporate culture and management decisions at energy firm BP. On April 20, 2010, an accident drilling BP’s Macondo well in the Gulf of Mexico produced the worst environmental disaster in US history, an event which dominated the daily news during the spring and summer of 2010. In itself, this event makes for the study of BP’s decision making of interest, prompting the question of whether the April 20 accident was simply an unfavorable chance event or instead the result of biased decision making.

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Positions in Operational Risk On the Rise

EFinancialCareersOperational risk remains a focus for trading operations and for good reason. Banks and investment firms say they’re worried about repeating the errors of the past. But just where do the operational risk managers and the quants meet, for instance? That’s been a serious point of contention.

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Liquidity Level or Liquidity Risk? Evidence from the Financial Crisis

CFA InstituteAlthough generally considered safe assets, liquid stocks underperformed illiquid stocks during the financial crisis of 2008–2009. The performance of stocks during the crisis can be better explained by their historical liquidity betas (risk) than by their historical liquidity levels. Stocks with different historical liquidity levels did not experience different returns after controlling for liquidity risk. The authors’ findings highlight the importance of accounting for both liquidity level and liquidity risk in risk management applications.

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Sliced & Diced: A Taste of Structured Investments

A May 2009 report from Research and Markets of Dublin notes that “structured products are among the fastest growing investment classes in world financial markets.” Although not really an asset class, structured investment products represent an array of investment tools for retail and institutional investors. They can enhance the returns of traditional asset classes, provide exposure to hard-to-reach sectors and markets, and often mitigate investors’ risk of losing some or all of their principal.

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The Threat of Losing the AAA is Self-Fulfilling

On Monday, April 18, Standard and Poor’s (S&P) put the US’s sovereign rating on negative outlook. The action was prompted by the continued deterioration of the US’s fiscal imbalances and the lack of urgency with which US political leaders have approached the country’s fiscal problems. By citing that Canada, the UK, France, and Germany all have better fiscal profiles including both better financial leverage ratios and stronger political discipline to manage their countries’ finances the rating agency has signaled that the US has lost its global financial pre-eminence. Such pre-eminence has allowed it to issue bonds at a premium to comparables and have a fiat money that has served as the world’s reserve currency. The US’s reign of global financial dominance has now officially ended.

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How Your Family Office Can Practice Philanthropy Through Its Investment Practice

While “giving back through philanthropy” will be a key topic for discussion at NYSSA’s 3rd Annual Family Office Conference on May 10, it may be well worth noting that a number of family offices are now discovering that they can express their philanthropic goals not just by “giving back” in the traditional sense but also through their investment practices.

Stephen Viederman has first-hand experience with this innovative approach to philanthropy as the former president of the Jessie Smith Noyes Foundation, a family foundation that was one of the earliest to put its investment assets behind its mission. The practical guidance he has offered to family foundations like Noyes is equally applicable to family offices that are not explicitly “purpose-driven” but whose family members desire to deploy a significant portion of their assets for the social and/or environmental benefits of their community or for the world at large.

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Recent Research: Highlights from April 2011

The Impact of Illiquidity and Higher Moments of Hedge Fund Returns on Their Risk-Adjusted Performance and Diversification Potential.” The Journal of Alternative Investment (Spring 2011). Laurent Cavenaile, Alain Coën, and Georges Hübner.

This article studies the joint impact of smoothing and fat tails on the risk–return properties of hedge fund strategies. First, the authors adjust risk and performance measures for illiquidity and the non-Gaussian distribution of hedge funds returns. They use two risk metrics: the Modified Value-at-Risk and a preference-based measure retrieved from the linear exponential utility function. Second, they revisit the hedge fund diversification effect with these adjustments for illiquidity. Their results report similar fund performance rankings and optimal hedge fund strategy allocations for both adjusted metrics. They also show that the benefits of hedge funds in portfolio diversification persist but tend to weaken after adjustments for illiquidity are made.

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A New Approach to Calculating Risk-Adjusted Returns

"People don’t perceive that they are going to be the one in a crash,” laments Russ Rader, media director at the IIHS (Insurance Institute for Highway Safety). “They believe that they are in control when they’re behind the wheel. They don’t sense how high the risk actually is.” The IIHS, a Virginia-based, national nonprofit that has helped significantly increase seat belt usage in the last twenty years, has a simple objective: lessen the risk taken in everyday driving behavior. The risk-measurement approach it employs has the potential to revolutionize how the investment community evaluates manager performance.

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Reputational Risk

The global financial crisis of 2007–2009 was associated with an unprecedented degree of financial and economic damage. For investors and financial intermediaries, the estimates seem to have risen to over $4 trillion or so worldwide by the time things began to stabilize, according to the International Monetary Fund (2009). Along with the financial damage has come substantial reputational damage for the financial services industry, for financial intermediaries and asset managers, and for individuals.

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Mental Aspects of Day Trading

Day Trading Commodity Futures Throughout my years in the futures industry, I have come to a conclusion in regards to the difference between winning and losing as a trader. In my opinion, the primary characteristic of successful traders is the ability to stay calm through thick and thin. This means avoiding the panic feeling that overcomes logic when trades are going against the speculation, and resisting the over-confidence that can come with a few winning endeavors. Each of these symptoms can have a severely negative impact on future trading decisions and profitability.

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