The following is an excerpt from CNBC:
Now that the decision has been made in Washington to reset Cuban-American relations, it’s a good time for an outside perspective on where things may go from here. Bottom line: Cuba may well become a rising star in the region and an attractive economic partner for the U.S. if things are managed well. In financial terms, Cuba will be a “buy” when the time comes. A recent visit revealed some impressive strengths buried not far below the surface.
Excerpt
Making strategic investment decisions is not a task that should be taken haphazardly. Managers and MBA students spend time studying appropriate decision criteria such as net present value (NPV) to aid in making profit-maximizing decisions. However, in discussing investment decisions with practicing managers over the years, we sensed that managers often systematically deviated from profit maximization. In particular, we noticed that managers often equate changes in scaled profit measures (e.g., changes in return on investment [ROI]) with changes in total profits (i.e., marginal profits). This causes them to deviate systematically from profit maximization with respect to strategic investment decisions (e.g., research and development [R&D] investments, capital investments, acquisitions) by avoiding investments that increase total profits yet are less profitable than their average current investment. In other words, current levels of average profit create an anchor by which investments are assessed. This decision-making behavior, subtle but critical, was recently demonstrated by NYU Stern Management Professor Zur Shapira.
Professor Shapira, along with Carlson School of Management Professor J. Myles Shaver, devised studies that teased out this counter-productive pattern and described it in “Confounding Changes in Averages With Marginal Effects: How Anchoring Can Destroy Economic Value In Strategic Investment Assessments.”
Of all the financial markets that should be resistant to manipulation, foreign exchange surely tops the list. With $5.3 trillion traded daily by thousands of buyers and sellers across the world, this should be one hyper-efficient market.
And yet six major banks recently agreed to a $4.3 billion settlement with US, UK, and Swiss authorities over charges that the banks had failed to prevent traders from attempting to manipulate the market. In all three countries, it is possible that criminal charges against individuals may follow.
The settlement is the latest in a long line of massive legal actions that hold banks responsible for the activities of their employees. Prosecutorial efforts to hold shareholders liable for myriad problems that bank employees have caused seem to have no end in sight. The goal of these actions is to prompt boards and their managers to reform banking cultures. If banks want to avoid more floods of litigation in the future, they'll have to act fast.
Continue reading "The Best Defense to Litigation Is a Good Bank Culture" »
The ECB conducted a comprehensive assessment of banks and identified capital shortfalls for 25 banks, totalling €25 billion. In this column, the authors provide a number of benchmark stress tests to estimate capital shortfalls. The analyses suggest possible capital shortfalls between €80 billion and more than €700 billion depending on the model. They find a negative correlation between their benchmark estimates and the regulatory capital shortfall, and a positive one between the benchmarks and the regulatory estimates of losses. This suggests that regulatory stress test outcomes are potentially affected by the discretion of national regulators.
Continue reading "Making Sense of the Comprehensive Assessment" »
ABSTRACT
This paper shows that the sovereign debt crisis and the resulting credit crunch in the periphery of the Eurozone lead to negative real e ffects for borrowing firms. Using a hand matched sample of loan information from Dealscan and accounting information from Amadeus, we show that firms with a higher exposure to banks a ffected by the sovereign debt crisis become financially constrained during the crisis. As a result, these firms have signifi cantly lower employment growth, capital expenditures, and sales growth rates. We show that our results are not driven by country or industry-specifi c macroeconomic shocks or a change in the demand for credit of borrowing fi rms. Thus, the high interdependence of bank and sovereign health and the resulting credit crunch is one important contributor to the severe economic downturn in the southern European countries during the sovereign debt crisis.
–Viral V. Acharyaa, Tim Eisertb, Christian Eu ngerc, Christian Hirschd
The authors appreciate helpful comments from Matteo Crosignani, Giovanni Dell'Ariccia, Daniela Fabbri, Rainer Haselmann, Jhangkai Huang, Yi Huang, Victoria Ivashina, Augustin Landier, and Marco Pagano, Sjoerd van Bekkum, as well as from conference participants at the 2014 EFA Meeting, the Bank performance, financial stability and the real economy conference (Naples, Italy), and at the International Conference on Financial Market Reform and Regulation (Beijing, China) and seminar participants in Mainz, Konstanz, at the European Central Bank, and at the 2014 Tsinghua Finance Workshop. Eisert is grateful for financial support by the German National Scientifi c Foundation. Hirsch gratefully acknowledges support from the Research Center SAFE, funded by the State of Hessen initiative for research Loewe. Email addresses: [email protected] (Viral V. Acharya), [email protected] (Tim Eisert), [email protected] (Christian Eu nger), [email protected] (Christian Hirsch)
aNew York University, CEPR, and NBER bErasmus University Rotterdam cIESE Business School dGoethe University Frankfurt and SAFE
ABSTRACT
This 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 models 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 inflow of foreign money into domestic bond markets plays a small role in driving home prices, despite its large depressing influence on interest rates. Finally, the model implies that procyclical increases in equilibrium price-rent ratios reflect 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
Favilukis: Department of Finance, London School of Economics, Houghton Street, London WC2A 2AE; Email: [email protected], 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: [email protected]; 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: [email protected]; 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.
ABSTRACT
We show that eurozone bank risks during 2007-2013 can be understood as “carry trade” behavior. Bank equity returns load positively on peripheral (Greece, Italy, Ireland, Portugal, Spain, or GIIPS) bond returns and negatively on German government bond returns, which generated “carry” until the deteriorating GIIPS bond returns adversely affected bank balance sheets. We find support for risk-shifting and regulatory arbitrage motives at banks in that carry trade behavior is stronger for large banks and banks with low capital ratios and high risk-weighted assets. We also find evidence for home bias and moral suasion in the subsample of GIIPS banks.
–Viral V. Acharya† Sascha Steffen‡
We thank an anonymous referee, Jacob Boudoukh, Martin Brown, Filippo di Mauro, Ruediger Fahlenbrach, Mariassunta Giannetti, Paul Glasserman, Paul Heidhues, Martin Hellwig, Gur Huberman, Vasso Ioannidou, Anil Kashyap, Bryan Kelly, Jan-Pieter Krahnen, David Lesmond, Christian Leuz, Marco Pagano, Hélène Rey, Joerg Rocholl, Anthony Saunders, Phil Strahan, Anjan Thakor, Elu von Thadden, Lucy White, Andrew Winton and participants in the 2014 Moody’s / SAIF Credit Research Conference, 2014 Conference on Regulating Financial Intermediaries, 2013 SFS Cavalcade, 2013 NBER Summer Institute IFM, 2013 CAF Summer Research Conference, 2013 FIRS Conference, 12th annual FDIC / JFSR conference, 49th Bank Structure and Competition Conference, 2012 C.R.E.D.I.T., 2nd Mofir Ancona and seminar participants at Darden, Deutsche Bundesbank, ESMT, Goethe University, Indiana, Lancaster, Leeds, Mainz, Norges Bank, NYU Stern, Ohio State University, Osnabrueck, and Tulane for valuable comments and suggestions. We are grateful to Matteo Crosignani and Diane Pierret for excellent research assistance.
Continue reading "The “Greatest” Carry Trade Ever? Understanding Eurozone Bank Risks" »
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.
Continue reading "3D Risk Management: A Survivorship Framework" »
Michael Lewis’ newest Wall Street bestseller, Flash Boys, claims that equity markets are “rigged” by high frequency traders who invested millions in fiber optic cables that enabled them to shave microseconds from the time it takes to trade stocks. Launched just a week ago in a blizzard of TV interviews with unknowing, uncritical journalists, it is the latest bomb to drop on an industry still struggling to regain its balance after the financial crisis of 2008.
Like his two other very popular books about financial firms and markets (Liar’s Poker and The Big Short), Flash Boys, tells a compelling, if improbable story of how a few really smart tech guys, investing millions in their own high speed cables, have outwitted the usual bunch of dull institutional investors by hijacking billions of dollars of other people’s trades.
ABSTRACT
For decades credit rating agencies were viewed as trusted arbiters of creditworthiness and their ratings as important tools for managing risk. The common narrative is that the value of ratings was compromised by the evolution of the industry to a form where issuers pay for ratings. In this paper we show how credit ratings have value in equilibrium and how reputation insures that, in equilibrium, ratings will reflect sound assessments of credit worthiness. There will always be an information distortion because of the fact that purchasers of ratings need not reveal them. We argue that regulatory reliance on ratings and the increasing importance of risk-weighted capital in prudential regulation have more likely contributed to distorted ratings than the matter of who pays for them. In this respect, much of the regulatory obsession with the conflict created by issuers paying for ratings is a distraction.
–Harold Cole and Thomas F. Cooley
Please note that the second author was previously a member of the Board of Managers of Standard & Poor's Financial Services LLC and also serves as a consultant to the company. The opinions and views expressed in this article do not necessarily reflect the opinions and views of Standard & Poor's Financial Services LLC. We thank Steve LeRoy, Larry White for helpful comments. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
NBER working papers are circulated for discussion and comment purposes. They have not been peer eviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.
© 2014 by Harold Cole and Thomas F. Cooley. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including © notice, is given to the source.
Yermack examines Bitcoin’s historical trading behavior to determine whether or not it behaves like a traditional sovereign currency. He finds that Bitcoin’s exchange rate volatility is greater than the volatilities of widely used currencies, undermining Bitcoin’s usefulness as a unit of account or a store of value. Additionally, he finds that Bitcoin’s daily exchange rates exhibit virtually no correlation with bona fide currencies, which he argues makes Bitcoin useless for risk management purposes and difficult for its owners to hedge. Bitcoin also lacks access to a banking system with deposit insurance, and is not used to denominate consumer credit or loan contracts. Overall, he concludes that Bitcoin appears to behave more like a speculative investment than like a currency.
ABSTRACT
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
1. INTRODUCTION
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
Continue reading "Inflation Risk Premium Implied by Options" »
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.
ABSTRACT
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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"In the end, it is probably leadership more than anything else that separates winners from losers over the long term – the notion that appropriate professional behavior reinforced by a sense of belonging to a quality franchise constitutes a decisive competitive advantage." |
The epic financial crisis of a few years ago inflicted immense damage on the process of financial intermediation, the fabric of the real economy, and the reputation of banks and bankers. Even today, some five years later, little has happened to restore financial firms to their former glory near the top of the reputational food-chain in most countries. For reasons of their own, many boards and managers in the banking industry have little good to say about the taxpayer bailouts and the inevitable regulatory tightening. In the words for former Barclays CEO Bob Diamond, "There was a period of remorse and apology for banks. I think that period is over. Frankly, the biggest issue is how do we put some of the blame game behind us? There's been apologies and remorse, now we need to build some confidence.”
Continue reading "Thoughts on Reputation and Governance in Banking" »
The London Interbank Offered Rate (Libor) and the Euro Interbank Offered Rate (Euribor) are two key market benchmark interest rates used in a plethora of financial contracts with notional amounts running into the hundreds of trillions of dollars. The integrity of the rate-setting process for these benchmarks has been under intense scrutiny ever since the first reports of attempts to manipulate these rates surfaced in 2007. In this paper, we analyze Libor and Euribor rate submissions by the individual panel banks and shed light on the underlying manipulation incentives by quantifying their potential effects on the final rate set (the “fixing”).
Furthermore, we explicitly take into account the possibility of collusion between several market participants. Our setup allows us to quantify such effects for the actual rate-setting process that is in place at present, and compare it to several alternative rate-setting procedures. We find that such alternative rate fixings, and larger sample sizes, could significantly reduce the effect of manipulation. Furthermore, we discuss the role of the particular questions asked of the panel banks, which are different for Libor and Euribor, and examine the need for a transaction database to validate individual submissions.
–Alexander Eisl, Rainer Jankowitschy, WU (Vienna University of Economics and Business); Marti G. Subrahmanyamz, New York University, Stern School of Business
Continue reading "Are Interest Rate Fixings Fixed? An Analysis of Libor and Euribor" »
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, NYUStern, CEPR, ECGI & NBER; Heitor Almeida, University of Illinois & NBER; Murillo Campello, University of Illinois & NBER
Continue reading "Aggregate Risk and the Choice between Cash and Lines of Credit" »
ABSTRACT
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.
INTRODUCTION
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:
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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NOTES
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)).
Financial services is often seen as a young person’s game. The cliché goes that banks suck in thousands of college graduates each year and spit out wealthy retirees in their mid-40s, or even earlier.
So what happens when you lose your job at 40+? Is that it? Only if you want to it to be.
WHAT CAN YOU OFFER?
The first thing you need to do is to clarify what you can offer. What’s your value? Focus on what you can bring to a new employer which will make all the difference to their business. Define and articulate your experience in a way that is unique and will differentiate you from the competition.
Let’s face it. The forecast for this year’s bonus season is down right gloomy. And judging by eFinancialCareers most recent survey on the subject, most financial professionals were not surprised.
Like we do every year around this time, eFinancialCareers took a look at the year-end payouts that begin in December and last on through February by surveying Wall Street professionals who are bonus-eligible and know the amount of their annual bonus.
Continue reading "If the Bonus Season Made a Fashion Statement, Color it Gray" »
If you ever wonder why companies take so long in deciding which candidate to hire for a particular position, consider this: the cost of selecting the wrong person can run into the hundreds of thousands or even millions of dollars, not to mention the potential negative impact to a company’s reputation, morale, and productivity.
Then there are those stories that grab media attention such as the alleged rogue trader who generated a $2.3-billion-dollar loss for UBS that also led to the resignation of the bank’s CEO who accepted responsibility for allowing it to happen on his watch.
Continue reading "Costs of Hiring the Wrong Person Go Beyond the Financial" »
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.
Markus Brunnermeier, Luis Garicano, Philip R. Lane, Marco Pagano, Ricardo Reis, Tano Santos, Stijn Van Nieuwerburgh, and Dimitri Vayanos
26th of September 2011
INTRODUCTION
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.
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.
ESBies: THEIR STRUCTURE AND USE
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.
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NOTES
*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.
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.
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