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on Risk Management |
| By: | ; Gilbert W. Bassett Jr; ; Roger Koenker; ; Gregory Kordas |
| Abstract: | Recent developments in the theory of choice under uncertainty and risk yield a pessimistic decision theory that replaces the classical expected utility criterion with a Choquet expectation that accentuates the likelihood of the least favorable outcomes. A parallel theory has recently emerged in the literature on risk assessment. It is shown that a general form of pessimistic portfolio optimization based on the Choquet approach may be formulated as a problem of linear quantile regression. |
| Date: | 2004–06 |
| URL: | http://d.repec.org/n?u=RePEc:ifs:ifsewp:wp09/04&r=rmg |
| By: | Morten Nalholm (Department of Finance, Copenhagen Business School); Rolf Poulsen (Institute for Mathematical Sciences, University of Copenhagen) |
| Abstract: | We investigate how sensitive a variety of dynamic and static hedge strategies for barrier options are to model risk. We find that using plain vanilla options to hedge barrier options offers considerable improvements over usual ?-hedges. Further, we show that the hedge portfolios involving options are relatively more sensitive to model risk, the Devil is in the detail, but that the degree of misspecification sensitivity is quite robust across commonly used models. |
| Date: | 2005–03 |
| URL: | http://d.repec.org/n?u=RePEc:kud:kuiefr:200502&r=rmg |
| By: | Nicholas Chan; Mila Getmansky; Shane M. Haas; Andrew W. Lo |
| Abstract: | Systemic risk is commonly used to describe the possibility of a series of correlated defaults among financial institutions---typically banks---that occur over a short period of time, often caused by a single major event. However, since the collapse of Long Term Capital Management in 1998, it has become clear that hedge funds are also involved in systemic risk exposures. The hedge-fund industry has a symbiotic relationship with the banking sector, and many banks now operate proprietary trading units that are organized much like hedge funds. As a result, the risk exposures of the hedge-fund industry may have a material impact on the banking sector, resulting in new sources of systemic risks. In this paper, we attempt to quantify the potential impact of hedge funds on systemic risk by developing a number of new risk measures for hedge funds and applying them to individual and aggregate hedge-fund returns data. These measures include: illiquidity risk exposure, nonlinear factor models for hedge-fund and banking-sector indexes, logistic regression analysis of hedge-fund liquidation probabilities, and aggregate measures of volatility and distress based on regime-switching models. Our preliminary findings suggest that the hedge-fund industry may be heading into a challenging period of lower expected returns, and that systemic risk is currently on the rise. |
| JEL: | G12 |
| Date: | 2005–03 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:11200&r=rmg |
| By: | Claude B. Erb; Campbell R. Harvey |
| Abstract: | Historically, commodity futures have had excess returns similar to those of equities. But what should we expect in the future? The usual risk factors are unable to explain the time-series variation in excess returns. In addition, our evidence suggests that commodity futures are an inconsistent, if not tenuous, hedge against unexpected inflation. Further, the historically high average returns to a commodity futures portfolio are largely driven by the choice of weighting schemes. Indeed, an equally weighted long-only portfolio of commodity futures returns has approximately a zero excess return over the past 25 years. Our portfolio analysis suggests that the a long-only strategic allocation to commodities as a general asset class is a bet on the future term structure of commodity prices, in general, and on specific portfolio weighting schemes, in particular. In contrast, we provide evidence that there are distinct benefits to an asset allocation overlay that tactically allocates using commodity futures exposures. We examine three trading strategies that use both momentum and the term structure of futures prices. We find that the tactical strategies provide higher average returns and lower risk than a long-only commodity futures exposure. |
| JEL: | G11 G12 G13 E44 |
| Date: | 2005–03 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:11222&r=rmg |
| By: | Martin Čihák |
| Abstract: | The note is a review of the literature on the quantitative methods used to assess the vulnerabilities of financial systems to risks. In particular, the author focuses on the role of system-wide stress testing. He summarizes the recent developments in the literature, highlighting topics relevant for the Czech case. He presents the key concepts relating to systemwide stress tests, overviews the stress tests performed by central banks and international financial institutions, and discusses conceptual issues relating to modeling of individual risk factors. |
| Keywords: | Financial soundness, macroprudential analysis, stress tests. |
| JEL: | G21 G28 E44 |
| URL: | http://d.repec.org/n?u=RePEc:cnb:rpnrpn:2/2004&r=rmg |
| By: | Alexis Derviz; Jiří Podpiera |
| Abstract: | In this paper we investigate the determinants of the movements in the long-term Standard & Poors and CAMELS bank ratings in the Czech Republic during the period when the three biggest banks, representing approximately 60% of the Czech banking sector’s total assets, were privatized (i.e., the time span 1998–2001). The same list of explanatory variables corresponding to the CAMELS rating inputs employed by the Czech National Bank’s banking sector regulators was examined for both ratings in order to select significant predictors among them. We employed an ordered response logit model to analyze the monthly long-run S&P rating and a panel data framework for the analysis of the quarterly CAMELS rating. The predictors for which we found significant explanatory power are: Capital Adequacy, Credit Spread, the ratio of Total Loans to Total Assets, and the Total Asset Value at Risk. Models based on these predictors exhibited a predictive accuracy of 70%. Additionally, we found that the verified variables satisfactorily predict the S&P rating one month ahead. |
| Keywords: | Bank rating, CAMELS, ordered logit model, panel data analysis. |
| JEL: | C53 E58 G21 G33 |
| URL: | http://d.repec.org/n?u=RePEc:cnb:wpaper:1/2004&r=rmg |
| By: | Mazumder, M. Imtiaz; Miller, Edward M.; Varela, Oscar Albert |
| Abstract: | The weekend effect is described as the tendency for Monday security returns to be low (or negative) compared to other days of the week. The weekend effect may not be exploited by trading individual stocks because of transactions costs. However, the institutional characteristics of the US-based international open-end mutual funds may allow investors to exploit the weekend effect because mutual funds lack much of the transactions costs associated with individual stocks. This paper extends the study of Compton and Kunkel (1999), Varela (2002), and Miller, Prather and Mazumder (2003) by examining the weekend predictability and profitable trading opportunities for international mutual funds. The rationale behind the weekend predictability and profitability of international funds lies on the fact that the Net Asset Values (NAVs) of international funds are computed from stale prices of the underlying assets of these funds. The sample of international funds is divided into two sub-samples and the initial sub-sample is used to test the weekend effect and develop trading strategies. Returns of trading strategies are then evaluated out-of-sample and compared with the returns of a buy-and-hold strategy. Empirical findings suggest that smart investors may earn higher risk-adjusted returns by following daily dynamic trading strategies. Results also document that trading strategies based on the weekend effect produce higher risk-adjusted returns. Finally market timing models are also tested for trading strategy returns and Treynor-Mazuy and Henriksson-Merton timing measures are positive and statistically significant. Moreover, the trading rules of this study may be useful in future if fair value pricing or other institutional regularities eliminate any profitable trading opportunity based on the US market signals. |
| Keywords: | Mutual funds, Weekend effect, Trading rule, Market efficiency |
| JEL: | G12 G14 |
| Date: | 2005–01 |
| URL: | http://d.repec.org/n?u=RePEc:uno:wpaper:2004-10&r=rmg |
| By: | Nam, Jouahn; Wang, Jun; Zhang, Ge |
| Abstract: | In this paper, we study a model incorporating the retail trader’s reluctance to sell into losses. We show that in this setup the informed trader always buys the asset when he receives a favorable signal. However, when the informed trader receives an unfavorable signal, he may not always sell the asset if the signal is moderately bad and the retail trader is reluctant to realize losses. Hence the good news travels faster than the bad news and the asset price exhibits steady climbs with sharp and sudden drops. |
| Keywords: | Disposition effect, Retail investors, Strategic trading |
| JEL: | G10 |
| Date: | 2004 |
| URL: | http://d.repec.org/n?u=RePEc:uno:wpaper:2004-11&r=rmg |
| By: | M. Hashem Pesaran; Paolo Zaffaroni |
| Abstract: | This paper considers the problem of model uncertainty in the case of multi-asset volatility models and discusses the use of model averaging techniques as a way of dealing with the risk of inadvertently using false models in portfolio management. In particular, it is shown that under certain conditions portfolio returns based on an average model will be more fat-tailed than if based on an individual underlying model with the same average volatility. Evaluation of volatility models is also considered and a simple Value-at-Risk (VaR) diagnostic test is proposed for individual as well as 'average' models and its exact and asymptotic properties are established. The model averaging idea and the VaR diagnostic tests are illustrated by an application to portfolios of daily returns based on twenty two of Standard & Poor's 500 industry group indices over the period January 2, 1995 to October 13, 2003, inclusive. |
| Keywords: | Model Averaging, Value-at-Risk, Decision Based Evaluations |
| JEL: | C32 C52 C53 G11 |
| Date: | 2004–10 |
| URL: | http://d.repec.org/n?u=RePEc:scp:wpaper:04-3&r=rmg |