A Long-run Risks Model of Asset Pricing with Fat Tails
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Release | : 2008 |
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Release | : 2008 |
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Author | : Emmanuel Jurczenko |
Publisher | : John Wiley & Sons |
Total Pages | : 258 |
Release | : 2006-10-02 |
Genre | : Business & Economics |
ISBN | : 0470057998 |
While mainstream financial theories and applications assume that asset returns are normally distributed and individual preferences are quadratic, the overwhelming empirical evidence shows otherwise. Indeed, most of the asset returns exhibit “fat-tails” distributions and investors exhibit asymmetric preferences. These empirical findings lead to the development of a new area of research dedicated to the introduction of higher order moments in portfolio theory and asset pricing models. Multi-moment asset pricing is a revolutionary new way of modeling time series in finance which allows various degrees of long-term memory to be generated. It allows risk and prices of risk to vary through time enabling the accurate valuation of long-lived assets. This book presents the state-of-the art in multi-moment asset allocation and pricing models and provides many new developments in a single volume, collecting in a unified framework theoretical results and applications previously scattered throughout the financial literature. The topics covered in this comprehensive volume include: four-moment individual risk preferences, mathematics of the multi-moment efficient frontier, coherent asymmetric risks measures, hedge funds asset allocation under higher moments, time-varying specifications of (co)moments and multi-moment asset pricing models with homogeneous and heterogeneous agents. Written by leading academics, Multi-moment Asset Allocation and Pricing Models offers a unique opportunity to explore the latest findings in this new field of research.
Author | : Svetlozar T. Rachev |
Publisher | : John Wiley & Sons |
Total Pages | : 385 |
Release | : 2005-09-15 |
Genre | : Business & Economics |
ISBN | : 0471758906 |
While mainstream financial theories and applications assume that asset returns are normally distributed, overwhelming empirical evidence shows otherwise. Yet many professionals don’t appreciate the highly statistical models that take this empirical evidence into consideration. Fat-Tailed and Skewed Asset Return Distributions examines this dilemma and offers readers a less technical look at how portfolio selection, risk management, and option pricing modeling should and can be undertaken when the assumption of a non-normal distribution for asset returns is violated. Topics covered in this comprehensive book include an extensive discussion of probability distributions, estimating probability distributions, portfolio selection, alternative risk measures, and much more. Fat-Tailed and Skewed Asset Return Distributions provides a bridge between the highly technical theory of statistical distributional analysis, stochastic processes, and econometrics of financial returns and real-world risk management and investments.
Author | : Ravi Bansal |
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Total Pages | : 34 |
Release | : 2010 |
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The recently developed long-run risks asset pricing model shows that concerns about long-run expected growth and time-varying uncertainty (i.e., volatility) about future economic prospects drive asset prices. These two channels of economic risks can account for the risk premia and asset price fluctuations. In addition, the model can empirically account for the cross-sectional differences in asset returns. Hence, the long-run risks model provides a coherent and systematic framework for analyzing financial markets.
Author | : Prasad V. Bidarkota |
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Total Pages | : 34 |
Release | : 2003 |
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We investigate the impact of modeling fat tails observed in the empirical distributions of macroeconomic time series on the implications of theoretical macroeconomic models. We study this issue in the context of the widely used consumption-based asset-pricing model. We derive exact analytical solutions to bond prices and risk premiums on forward prices and holding period returns in this model, assuming that the endowment evolves as a stochastic process with innovations drawn alternatively from fat-tailed and Gaussian distributions. We calculate and compare the implied risk premiums for suitable parameterizations of the two versions of the model.
Author | : Prasad V. Bidarkota |
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Total Pages | : 19 |
Release | : 2004 |
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We investigate the impact of ignoring fat tails observed in the empirical distributions of macroeconomic time series on the equilibrium implications of the consumption-based asset-pricing model with habit formation. Fat tails in the empirical distributions of consumption growth rates are modeled as a dampened power law process that nevertheless guarantees finiteness of moments of all orders. This renders model-implied mean equilibrium rates of return and equity and term premia finite. Comparison with a benchmark Gaussian process reveals that accounting for fat tails lowers the model-implied mean risk-free rate by 20 percent, raises the mean equity premium by 80 percent and the term premium by 20 percent, bringing the model implications closer to their empirically observed counterparts.
Author | : Alexis Akira Toda |
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Release | : 2017 |
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Author | : Yannick Malevergne |
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Total Pages | : 38 |
Release | : 2007 |
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We derive a theoretical two-factor model which has empirically a similar explanatory power as the Fama-French three-factor model. In addition to the usual market risk, our model accounts for a diversification risk, proxied by the equally-weighted portfolio, and which results from an quot;internal consistency factorquot; appearing for arbitrary large economies, as a consequence of the concentration of the market portfolio when the distribution of the capitalization of firms is sufficiently heavy-tailed as in real economies. Our model rationalizes the superior performance of the Fama and French three-factor model in explaining the cross section of stock returns: the size factor constitutes an alternative proxy of the diversification factor while the book-to-market effect is related to the increasing sensitivity of value stocks to this factor.
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Release | : 2008 |
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Author | : Ravi Bansal |
Publisher | : |
Total Pages | : 36 |
Release | : 2009 |
Genre | : Assets (Accounting) |
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We provide an empirical evaluation of the forward-looking long-run risks (LRR) model and highlight model differences with the backward-looking habit based asset pricing model. We feature three key results: (i) Consistent with the LRR model, there is considerable evidence in the data of time-varying expected consumption growth and volatility, (ii) The LRR model matches the key asset markets data features, (iii) In the data and in the LRR model accordingly, past consumption growth does not predict future asset prices, whereas lagged consumption in the habit model forecasts future price-dividend ratios with an R2 of over 40%. Overall, our evidence implies that the LRR model provides a coherent framework to analyze and interpret asset prices.