nep-rmg New Economics Papers
on Risk Management
Issue of 2005‒02‒01
seven papers chosen by
Stan Miles
York University

  1. Practical Volatility and Correlation Modeling for Financial Market Risk Management By Torben G. Andersen; Tim Bollerslev; Peter F. Christoffersen; Francis X. Diebold
  2. Rethinking Risk: Aspiration as Pure Risk By Greg B. Davies
  3. Nonparametric Estimation of the Time-varying Sharpe Ratio in Dynamic Asset Pricing Models By Peter Woehrmann; Willi Semmler; Martin Lettau
  4. A dynamic model of the financial–real interaction as a model selection criterion for nonparametric stock market prediction By Peter Woehrmann
  5. Fidelity versus Vanguard: Comparing the Performance of the Two Largest Mutual Fund Families By Tower, Edward; Zheng, Wei
  6. Index Fundamentalism Revisited By Tower, Edward; Reinker, Kenneth S.
  7. Reducing the Risk of Investment-Based Social Security Reform By Martin Feldstein

  1. By: Torben G. Andersen (Department of Finance, Kellogg School of Management, Northwestern University); Tim Bollerslev (Department of Economics, Duke University); Peter F. Christoffersen (Faculty of Management, McGill University); Francis X. Diebold (Department of Economics, Univerrsity of Pennsylvania)
    Abstract: What do academics have to offer market risk management practitioners in financial institutions? Current industry practice largely follows one of two extremely restrictive approaches: historical simulation or RiskMetrics. In contrast, we favor flexible methods based on recent developments in financial econometrics, which are likely to produce more accurate assessments of market risk. Clearly, the demands of real-world risk management in financial institutions - in particular, real-time risk tracking in very high-dimensional situations - impose strict limits on model complexity. Hence we stress parsimonious models that are easily estimated, and we discuss a variety of practical approaches for high-dimensional covariance matrix modeling, along with what we see as some of the pitfalls and problems in current practice. In so doing we hope to encourage further dialog between the academic and practitioner communities, hopefully stimulating the development of improved market risk management technologies that draw on the best of both worlds.
    JEL: G10
    Date: 2005–01–11
  2. By: Greg B. Davies
    Abstract: There exists no satisfactory theory of risk in current normative decision theories. Notions based on utility curvature, loss aversion and probability weighting are derivative, cannot be applied to non-numerical consequences, and are not psychologically intuitive. I develop a Pure Risk theory which resolves these problems, is consistent with existing normative theories, and both internalises and generalises the intuitive notion of risk being related to the probability of not achieving one’s aspirations. The theory shows that existing models are misspecifed. Effects hitherto modelled as loss aversion or utility curvature may be due instead to Pure Risk.
    Keywords: Risk; Pure Risk; Aspiration Levels; Subjective Expected Utility Theory; Prospect Theory; Pure Risk Prospect Theory
    JEL: D81
    Date: 2005–01
  3. By: Peter Woehrmann; Willi Semmler; Martin Lettau
    Abstract: Economic research of the last decade linking macroeconomic fundamentals to asset prices has revealed evidence that standard intertemporal asset pricing theory is not successful in explaining (unconditional) ¯rst moments of asset market characteristics such as the risk-free interest rate, equity premium and the Sharpe-ratio. Subsequent empirical research has pursued the question whether those characteristics of asset markets are time varying and, in particular, varying over the business cycle. Recently intertemporal asset pricing models have been employed to replicate those time varying characteristics. The aim of our contribution is (1) to relax some of the assumptions that previous work has imposed on underlying economic and ¯nancial vari- ables, (2) to extend the solution technique of Marcet and Den Haan (1990) for those models by nonparametric expectations and (3) to propose a new estimation procedure based on the above solution technique. To allow for nonparametric expectations in the expectations approach for numerically solving the intertemporal economic model we employ the Local Linear Maps (LLMs) of Ritter, Martinetz and Schulten (1992) to approximate conditional expectations in the Euler equation. In our estimation approach based on non-parametric expectations we are able to use full structural information and, consequently, Monte Carlo simulations show that our estimations are less biased than the widely applied GMM procedure. Based on quarterly U.S. data we also empirically estimate structural parameters of the model and explore its time varying asset price characteristics for two types of preferences, power utility and habit persistence.
    Keywords: Nonparametric, Estimation, Time-varying Sharpe Ratio, Asset Pricing
    JEL: C1 G1
  4. By: Peter Woehrmann
    Abstract: Inspired by findings of low–dimensional nonlinearities and the Theorem of Takens (1983) forecasting models of financial time series are often built upon nonparametric, i.e. universal nonlinear, univariate relationships. Empirical investigations, however, are seriously contaminated by the problem of overfitting. Since statistical model selection theory in the nonlinear case is still in its infancy we would like to suggest the application of economic model selection criteria. It is a method of combining the flexibility of nonparametric regressions and important structural information in dynamic economic models. Therefore, conditions of economic models are imposed on the embedded nonlinear dynamical system to be estimated nonparametrically. In our empirical investigations we apply an univariate nonparametric forecasting model of stock returns, implemented via the Local Linear Maps of Ritter (1991), by an economic model selection criterion based on a discretized form of a continuous–time dynamic model on the interaction of real activity and asset markets. The dynamic economic model is estimated based on the Maximum Entropy inference since unobservable variables are involved. Results for monthly U.S. data show that nonparametric model selection is improved by this economic model selection criterion. On the other hand this result may be interpreted as support for the economic model.
    Keywords: model selection, dynamic model, interaction, nonparametric, stock market, prediction
    JEL: C1 G1
  5. By: Tower, Edward; Zheng, Wei
    Abstract: This paper compares the risk and return of investing in equity mutual funds provided by the world's two largest mutual fund families: Fidelity and Vanguard over a long horizon. We believe this will help guide investors; this study is an example of the calculations that mutual fund companies should facilitate by being required to provide accurate, accessible and free data. Over the entire period 1977 through 2003 both Fidelity's (no load) and Vanguard's diversified U.S. funds out returned the Wilshire 5000 index; Fidelity's portfolio out returned Vanguard's portfolio by 0.62 % per year but under returned it by 0.39 % when risk adjusted.
    JEL: G G2
    Date: 2004
  6. By: Tower, Edward; Reinker, Kenneth S.
    Abstract: Jared Kizer’s analysis indicates the return to stock-picking skills is not enough to offset the additional transactions costs of a managed portfolio. Thus the superior performance of Vanguard’s managed portfolio was due entirely to its tendency to overweight small stocks and value stocks relative to the index portfolio during a period when stocks with these two characteristics outperformed the market. So, it is style-picking skill rather than stock picking skill that leads to the superiority of the managed portfolio in this particular instance. Similarly, style-picking skill explains the lower risk for the managed portfolio.
    JEL: G11
    Date: 2004
  7. By: Martin Feldstein
    Abstract: This paper describes the risks implied by a mixed system of Social Security pension benefits with different combinations of pay-as-you-go taxes and personal retirement account (PRA) saving. The analysis shows how these risks can be reduced by using alternative private market guarantee strategies. The first such strategy uses a blend of equities and TIPS to guarantee at least a positive real rate or return on each year%u2019s PRA saving. The second is an explicit zero-cost collar that guarantees an annual rate of return by giving up all returns above a certain level. One variant of these guarantees uses a two stage procedure: a guaranteed return to age 66 and then a separate guarantee on the implicit return in the annuity phase. An alternative strategy provides a combined guarantee on the return during both the accumulation and the annuity phase. Simulations are presented of the probability distributions of retirement incomes relative to the %u201Cbenchmark%u201D benefits specified in current law. Calculations of expected utility show that these risk reduction techniques can raise expected utility relative to the plans with no guarantees. The ability to do so depends on the individual%u2019s risk aversion level. This underlines the idea that different individuals would rationally prefer different investment strategies and risk reduction options.
    JEL: H0 H3 H5
    Date: 2005–01

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