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on Risk Management |
| By: | Cara Marshall (Department of Economics, Queens College of the City University of New York) |
| Abstract: | This paper revisits the roots of modern portfolio theory and the recognition that a stock’s (or a stock portfolio’s) risk can be decomposed into a systematic component and an unsystematic component, and, further, that only the former should contribute to expected return. However, instead of isolating the systematic component of risk by recasting the risk in terms of a stock’s beta coefficient, I choose to decompose the standard deviation, or variance if one prefers the original risk measure, directly into its systematic and unsystematic components allowing one to focus on systematic risk and yet remain in the mean/standard deviation (or mean/variance) space. When the standard deviation of return is decomposed into its systematic and unsystematic components, an “adjusted CML” can be derived and it is easily shown that this adjusted CML is equivalent to Sharpe’s SML. This alternative way of looking at systematic and unsystematic risk offers easily accessible insights into the very nature of risk. This has a number of interesting implications including, but not limited to, reducing the computational complexities in calculating the relevant portion of a portfolio’s volatility, facilitating sophisticated dispersion trades, estimating risk-adjusted returns, and improving risk-adjusted performance measurement. This paper is, in part, pedagogical and, in part, an introduction to an alternative way of measuring systematic and unsystematic risk. |
| Keywords: | systematic risk, unsystematic risk, capital asset pricing model, dispersion trading, risk adjusted performance measurement |
| Date: | 2008–09 |
| URL: | http://d.repec.org/n?u=RePEc:quc:wpaper:0003&r=rmg |
| By: | Ruud Vermeulen |
| Abstract: | This paper examines corporate credit risks in the Netherlands at the industry-level, addressing two key questions. First, to what extent are corporate credit risks driven by idiosyncratic financial factors or systematic macroeconomic factors? Second, did debt financing in the late 1990s indeed push a large number of firms into bankruptcy in the subsequent years? To this end, bankruptcy rates are regressed on a number of industry-specific financial ratio's and macroeconomic variables in a panel-regression framework covering six industries from 1992 to 2005. I find that an industry's bankruptcy rate rises with an increase in leverage and a decrease in profitability and liquidity. Adding macroeconomic variables shows that lower GDP growth, higher interest rates, and an appreciating currency raise credit risks. Applying a model with parameter heterogeneity illustrates that systematic factors primarily account for the overall rise in bankruptcy rates between 2000 and 2003, but that idiosyncratic factors dominate in the worst-affected industries. This includes the IT industry where the build-up of debt was most pronounced and compounded losses. |
| JEL: | E44 E52 E58 |
| Date: | 2008–12 |
| URL: | http://d.repec.org/n?u=RePEc:dnb:dnbwpp:190&r=rmg |
| By: | Maximilian J. B. Hall (Dept of Economics, Loughborough University) |
| Abstract: | On 8 October 2008 the UK Government announced a far-reaching plan to restore financial stability, protect depositors and re-invigorate the flow of credit to businesses and individuals in the UK. The £400 billion bailout plan embraced three elements: a massive expansion in emergency liquidity support from the Bank of England; recapitalisation of UK banks and building societies using taxpayers' money; and the provision of a Government guarantee of new short- and medium-term debt issuance made by UK-incorporated banks and building societies. This action proved necessary in the wake of continuing and substantial weaknesses in many banks' share prices despite the temporary ban on short-selling imposed by the Financial Services Authority. It followed two revisions to domestic deposit protection arrangements, and the adoption of a piecemeal approach to failure resolution which saw the eventual nationalisation of Northern Rock in February 2008, the nationalisation of Bradford and Bingley in September 2008 and the brokering of takeover rescues of Alliance and Leicester and HBOS by Banco Santander and Lloyds TSB respectively in July and September 2008, and of the Cheshire and Derbyshire Building Societies by the Nationwide Building Society in September 2008. This metamorphosis in approach to failure resolution by the UK authorities in response to the sub-prime crisis and the credit crunch – nationalisation by default to (part) nationalisation as the preferred course of action - is duly analysed in this article, as well as their proposals for banking reforms which still have to be agreed by Parliament. |
| Keywords: | UK banks; banking regulation and supervision; failure resolution; central banking; deposit protection. |
| JEL: | E53 E58 G21 G28 |
| Date: | 2008–11 |
| URL: | http://d.repec.org/n?u=RePEc:lbo:lbowps:2008_14&r=rmg |
| By: | Charles R. Hulten; Xiaohui Hao |
| Abstract: | "What is a company really worth?" is a question asked repeatedly during the recent financial crisis. Attention has been focused on short-term valuation issues, like the "mark-to-market" controversy. Sorting out these issues is complicated by the fact that the market puts a value on shareholder equity that is consistently more than twice the reported book value of a company. Numerous observers have pointed to the absence of most intangible assets from financial statements as an important source of this puzzle. We use Compustat financial data for 617 R&D intensive firms to test this possibility. We find that conventional book value alone explains only 31 percent of the market capitalization of these firms in 2006, and that this increases to 75 percent when our estimates of intangible capital are included. The debt-equity ratio also falls from 1.46 to 0.61. These findings suggest that financial reports tend to substantially understate the long-run intrinsic value of corporate America. |
| JEL: | G3 M41 O30 |
| Date: | 2008–12 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:14548&r=rmg |
| By: | Jens Carsten Jackwerth (Universität Konstanz); James E. Hodder; Olga Kolokolova |
| Abstract: | Numerous hedge funds stop reporting to commercial databases each year. An issue for hedgefund performance estimation is: what delisting return to attribute to such funds? This would be particularly problematic if delisting returns are typically very different from continuing funds’ returns. In this paper, we use estimated portfolio holdings for funds-of-funds with reported returns to back out maximum likelihood estimates for hedge-fund delisting returns. The estimated mean delisting return for all exiting funds is small, although statistically significantly different from the average observed returns for all reporting hedge funds. These findings are robust to relaxing several underlying assumptions. |
| Date: | 2008–10–31 |
| URL: | http://d.repec.org/n?u=RePEc:knz:cofedp:0809&r=rmg |
| By: | Cara Marshall (Department of Economics, Queens College of the City University of New York) |
| Abstract: | This paper develops empirical evidence on a relatively new form of trading, known as “dispersion trading,” that is practiced by some quantitatively sophisticated hedge funds and by some proprietary bank trading desks. The results shed light on the efficiency with which U.S. options markets price volatility. Using end-of-day implied volatilities extracted from equity option prices for the stocks that comprise the S&P 500, I calculate the implied volatility of the S&P 500 using a modification of the Markowitz variance equation. I then compare this Markowitz-implied volatility to the implied volatility of the S&P 500 extracted directly from index options on the S&P 500. I then examine these contemporaneous measures of implied volatility for exploitable discrepancies both without transaction costs and with transaction costs. The study covers the period October 31, 2005 through November 1, 2007. I find that, consistent with the claims of dispersion traders, index option implied volatility tends to exceed the Markowitz-implied volatility derivable from the implied volatilities of the index components. Thus, from a trader’s perspective, index option implied volatility tends to be more often “rich” and component volatilities tend to be more often “cheap.” Nevertheless, there are times when the opposite is true, suggesting that potential dispersion trades can run in either direction. |
| Keywords: | Dispersion trading, implied volatility, volatility trading, correlation trading, hedge funds |
| Date: | 2008–09 |
| URL: | http://d.repec.org/n?u=RePEc:quc:wpaper:0004&r=rmg |
| By: | Giorgio Canarella (California State University, Los Angeles, and University of Nevada, Las Vegas); Stephen M. Miller (University of Nevada, Las Vegas, and University of Connecticut); Stephen K. Pollard (California State University, Los Angeles) |
| Abstract: | This paper explores the dynamic linkages that portray different facets of the joint probability distribution of stock market returns in NAFTA (i.e., Canada, Mexico, and the US). Our examination of interactions of the NAFTA stock markets considers three issues. First, we examine the long-run relationship between the three markets, using cointegration techniques. Second, we evaluate the dynamic relationships between the three markets, using impulse-response analysis. Finally, we explore the volatility transmission process between the three markets, using a variety of multivariate GARCH models. Our results also exhibit significant volatility transmission between the second moments of the NAFTA stock markets, albeit not homogenous. The magnitude and trend of the conditional correlations indicate that in the last few years, the Mexican stock market exhibited a tendency toward increased integration with the US market. Finally, we do note that evidence exists that the Peso and Asian financial crises as well as the stock-market crash in the US affect the return and volatility time-series relationships. |
| Keywords: | NAFTA stock markets, cointegration, impulse response, volatility transmission |
| JEL: | G10 C30 C50 |
| Date: | 2008–12 |
| URL: | http://d.repec.org/n?u=RePEc:uct:uconnp:2008-49&r=rmg |