New Economics Papers
on Risk Management
Issue of 2007‒01‒13
ten papers chosen by

  1. The Empirical Risk-Return Relation: a factor analysis approach By Sydney Ludvigson; Serena Ng
  2. Asymmetric effects and long memory in the volatility of Dow Jones stocks By Marcel Scharth; Marcelo Cunha Medeiros
  3. Reconciling the Return Predictability Evidence By Martin Lettau; Stijn Van Nieuwerburgh
  4. Hedging Housing Risk By Peter Englund; Min Hwang; John Quigley
  5. Evaluating Value-at-Risk models with desk-level data By Jeremy Berkowitz; Peter Christoffersen; Denis Pelletier
  6. Stock Market Interactions and the Impact of Macroeconomic News – Evidence from High Frequency Data of European Futures Markets By Bea Canto; Roman Kräussl
  7. Can the Stock Market be Linearized? By D Politis
  8. "On Risk Management Methods of Equity-Linked Insurance and Practical Problems"(in Japanese) By Gouta Akiyama; Naoto Kunitomo
  9. Credit Cycles and Macro Fundamentals By Siem Jan Koopman; Roman Kräussl; André Lucas; André Monteiro
  10. Default Rates in the Loan Market for SMEs:: Default Rates in the Loan Market for SMEs: Evidence from Slovakia By Fidrmuc, Jarko; Hainz, Christa; Malesich, Anton

  1. By: Sydney Ludvigson; Serena Ng (University of Michigan)
    Abstract: Financial economists have long been interested in the empirical relation between the conditional mean and conditional volatility of excess stock market returns, often referred to as the risk-return relation. Unfortunately, the body of empirical evidence on the risk-return relation is mixed and inconclusive. A key criticism of the existing empirical literature relates to the relatively small amount of conditioning information used to model the conditional mean and conditional volatility of excess stock market returns. To the extent that financial market participants have information not reflected in the chosen conditioning variables, measures of conditional mean and conditional volatility--and ultimately the risk-return relation itself--will be misspecified and possibly highly misleading. We consider one remedy to these problems using the methodology of dynamic factor analysis for large datasets, whereby a large amount of economic information can be summarized by a few estimated factors. We find that several estimated factors contain important information about one-quarter ahead excess returns and volatility that is not contained in commonly used predictor variables. Moreover, the factor-augmented specifications we examine predict an unusual 16-20 percent of the one-quarter ahead variation in excess stock market returns, and exhibit remarkably stable and strongly statistically significant out-of-sample forecasting power. Finally, in contrast to several pre-existing studies that rely on a small number of conditioning variables, we find a positive conditional correlation between risk and return that is strongly statistically significant, whereas the unconditional correlation is weakly negative and statistically snginficant
    Keywords: predictability, conditioning information, large dimension factor models
    JEL: G12 G10
    Date: 2006–12–03
  2. By: Marcel Scharth (Department of Economics - PUC-Rio); Marcelo Cunha Medeiros (Department of Economics PUC-Rio)
    Abstract: Does volatility reflect a continuous reaction to past shocks or changes in the markets induce shifts in the volatility dynamics? In this paper, we provide empirical evidence that cumulated price variations convey meaningful information about multiple regimes in the realized volatility of stocks, where large falls (rises) in prices are linked to persistent regimes of high (low) variance in stock returns. Incorporating past cumulated daily returns as a explanatory variable in a flexible and systematic nonlinear framework, we estimate that falls of different magnitudes over less than two months are associated with volatility levels 20% and 60% higher than the average of periods with stable or rising prices. We show that this effect accounts for large empirical values of long memory parameter estimates. Finally, we analyze that the proposed model significantly improves out of sample performance in relation to standard methods. This result is more pronounced in periods of high volatility.
    Keywords: Realized volatility, long memory, nonlinear models, asymmetric effects, regime switching, regression trees, smooth transition, value-at-risk, forecasting, empirical finance.
    Date: 2006–11
  3. By: Martin Lettau; Stijn Van Nieuwerburgh (Finance Department New York University)
    Abstract: Evidence of stock return predictability by financial ratios is still controversial, as documented by inconsistent results for in-sample and out-of-sample regressions and by substantial parameter instability. This paper shows that these seemingly incompatible results can be reconciled if the assumption of a fixed steady-state mean of the economy is relaxed. We find strong empirical evidence in support of shifts in the steady-state and propose simple methods to adjust financial ratios for such shifts. The forecasting relationship of adjusted price ratios and future returns is statistically significant, stable over time, and present in out-of-sample tests. We also show that shifts in the steady-state are responsible for the parameter instability and poor out-of-sample performance of unadjusted price ratios that are found in the data. Our conclusions hold for a variety of financial ratios and are robust to changes in the econometric technique used to estimate shifts in the steady-state
    Keywords: return predictability,
    JEL: G12 G14 G10
    Date: 2006–12–03
  4. By: Peter Englund (Stockholm School of Ecomonics); Min Hwang (University of California at Berkeley); John Quigley (University of California at Berkeley)
    Abstract: An unusually rich source of data on housing prices in Stockholm is used to analyze the investment implications of housing choices. This empirical analysis derives market-wide price and return series for housing investment during a 13-year period, and it also provides estimates of the individual-specific, idiosyncratic, variation in housing returns. Because the idiosyncratic component follows an autocorrelated process, the analysis of portfolio choice is dependent upon the holding period. We analyze the composition of household investment portfolios containing housing, common stocks, stocks in real estate holding companies, bonds, and t-bills. For short holding periods, the efficient portfolio contains essentially no housing. For longer periods, low risk portfolios contain 15 to 50 percent housing. These results suggest that there are large potential gains from policies or institutions that would permit households to hedge their lumpy investments in housing. We estimate the potential value of hedges in reducing risk to households, yet yielding the same investment returns. The value is surprisingly large, especially to poorer homeowners.
    Date: 2006–06–27
  5. By: Jeremy Berkowitz (University of Houston); Peter Christoffersen (McGill University); Denis Pelletier (Department of Economics, North Carolina State University)
    Abstract: We present new evidence on disaggregated profit and loss and VaR forecasts obtained from a large international commercial bank. Our dataset includes daily P/L generated by four separate business lines within the bank. All four business lines are involved in securities trading and each is observed daily for a period of at least two years. Given this rich dataset, we provide an integrated, unifying framework for assessing the accuracy of VaR forecasts. A thorough Monte Carlo comparison of the various methods is conducted to provide guidance as to which of these many tests have the best finite-sample size and power properties. The Caviar test of Engle and Manganelli (2004) performs best overall but duration-based tests also perform well in many cases.
    Keywords: risk management, backtesting, volatility, disclosure
    JEL: G21 G32
    Date: 2005–10
  6. By: Bea Canto (Watson Wyatt Brans & Co.); Roman Kräussl (Vrije Universiteit Amsterdam and CFS)
    Abstract: This study analyzes the short-term dynamic spillovers between the futures returns on the DAX, the DJ Eurostoxx 50 and the FTSE 100. It also examines whether economic news is one source of international stock return co-movements. In particular, we test whether stock market interdependencies are attributable to reactions of foreign traders to public economic information. Moreover, we analyze whether cross-market linkages remain the same or whether they do increase during periods in which economic news is released in one of the countries. Our main results can be summarized as follows: (i) there are clear short term international dynamic interactions among the European stock futures markets; (ii) foreign economic news affects domestic returns; (iii) futures returns adjust to news immediately; (iv) announcement timing of macroeconomic news matters; (v) stock market dynamic interactions do not increase at the time of the release of economic news; (vi) foreign investors react to the content of the news itself more than to the response of the domestic market to the national news; and (vii) contemporaneous correlation between futures returns changes at the time of macroeconomic releases.
    Keywords: Market Microstructure,Stock Market Dynamic Interactions, Macroeconomic News, High Frequency Data, VAR Modeling, Variance Decomposition
    JEL: G14 G15
    Date: 2006–12–06
  7. By: D Politis
    Abstract: The evolution of financial markets is a complicated real-world phenomenon that ranks at the top in terms o fdifficulty of modeling and/or prediction. One reason for this difficulty is the well-documented nonlinearity that is inherently at work. The state-of-the-art on the nonlinear modeling of financial returns is given by the popular ARCH (Auto-Regressive Conditional Heteroskedasticity) models and their generalization but they all have their short-comings. Foregoing the goal of finding the "best" model, we propose an exploratory, model-free approach in trying to understand this difficult type of data. In particular, we propose to transform the problem into a more manageable setting such as the setting of linearity. The form and properties of such a transformation are given, and the issue of one-step-ahead prediction using the new approach is explicitly addressed.
    Keywords: stock market, ARCH, finance,
    Date: 2006–05–01
  8. By: Gouta Akiyama (Mitsui Asset Trust and Banking Company,Limited); Naoto Kunitomo (Faculty of Economics, University of Tokyo)
    Abstract: Recently the various types of the equity-linked insurance have been introduced and actively traded in Japanese insurance markets. We investigate the basic problems of the actuarial risk management methods for those products based on the Markovian regime-switching time series model, which was originally proposed by Hamilton (1989) and applied to the insurance problem by Hardy (2001, 2003). We argue that they should be carefully used in Japan mainly because the macro-economic performance of Japan in the past decades have been quite different from the macro-economies of Canada and U.S..
    Date: 2005–09
  9. By: Siem Jan Koopman (Vrije Universiteit Amsterdam and Tinbergen Institute Amsterdam); Roman Kräussl (Vrije Universiteit Amsterdam and CFS); André Lucas (Vrije Universiteit Amsterdam and Tinbergen Institute Amsterdam); André Monteiro (Vrije Universiteit Amsterdam and Tinbergen Institute Amsterdam)
    Abstract: We study the relation between the credit cycle and macro economic fundamentals in an intensity based framework. Using rating transition and default data of U.S. corporates from Standard and Poor’s over the period 1980–2005 we directly estimate the credit cycle from the micro rating data. We relate this cycle to the business cycle, bank lending conditions, and financial market variables. In line with earlier studies, these variables appear to explain part of the credit cycle. As our main contribution, we test for the correct dynamic specification of these models. In all cases, the hypothesis of correct dynamic specification is strongly rejected. Moreover, accounting for dynamic mis-specification, many of the variables thought to explain the credit cycle, turn out to be insignificant. The main exceptions are GDP growth, and to some extent stock returns and stock return volatilities. Their economic significance appears low, however. This raises the puzzle of what macro-economic fundamentals explain default and rating dynamics.
    Keywords: Credit Cycles, Business Cycles, Bank Lending Conditions, Unobserved Component Models, Intensity Models, Monte Carlo Likelihood
    JEL: G11 G21
    Date: 2007–01–02
  10. By: Fidrmuc, Jarko; Hainz, Christa; Malesich, Anton
    Abstract: Banks entering an emerging market face a lot of uncertainty about the risks involved in lending. We use a unique unbalanced panel of nearly 700 short-term loans made to SMEs in Slovakia between January 2000 and June 2005. Of the loans granted, on average 6.0 per cent of the firms defaulted. Several probit models and panel probit models show that liquidity and profitability factors are important determinants of SMEs defaults, while debt factors are less robust. However, we find that above average indebtedness significantly increases the probability of default. Moreover, the legal form that determines liability has important incentive effects.
    Keywords: SME; Credit; Loan Default; Mortality Rates; Incentives; Probit; Panel Data
    JEL: G33 G21 C25
    Date: 2007–01

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