Posts Tagged ‘volatility

04
Nov
11

Paper: Volatilidad explosiva

Explosive Volatility: A Model of Financial Contagion

This paper proposes a model of financial contagion that accounts for explosive, mutually exciting shocks to market volatility. We fit the model using country-level data during the European sovereign debt crisis, which has its roots in the period 2008–2010, and was continuing to affect global markets as of October, 2011. Our analysis shows that existing volatility models are unable to explain two key stylized features of global markets during presumptive contagion periods: shocks to aggregate market volatility can be sudden and explosive, and they are associated with specific directional biases in the cross-section of country-level returns. Our model repairs this deficit by assuming that the random shocks to volatility are heavy-tailed and correlated cross-sectionally, both with each other and with returns.
We find evidence for significant contagion effects during the major EU crisis periods of May 2010 and August 2011, where contagion is defined as excess correlation in the residuals from a factor model incorporating global and regional market risk factors. Some of this excess correlation can be explained by quantifying the impact of shocks to aggregate volatility in the cross-section of expected returns—but only, it turns out, if one is extremely careful in accounting for the explosive nature of these shocks. We show that global markets have time-varying cross-sectional sensitivities to these shocks, and that high sensitivities strongly predict periods of financial crisis. Moreover, the pattern of temporal changes in correlation structure between volatility and returns is readily interpretable in terms of the major events of the periods in question.

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12
Aug
11

Gráfico du Jour: no diría Bipolar…

(Fuente: The Big Picture)

07
Aug
11

Paper: Curtosis y predicción de retornos

Do Realized Skewness and Kurtosis Predict the Cross-Section of Equity Returns?

Abstract: 
Yes. We use intraday data to compute weekly realized variance, skewness and kurtosis for individual equities and assess whether this week’s realized moments predict next week’s stock returns in the cross-section. We sort stocks each week according to their past realized moments, form decile portfolios and analyze subsequent weekly returns. We find a very strong negative relationship between realized skewness and next week’s stock returns, and a positive relationship between realized kurtosis and next week’s stock returns. We do not find a strong relationship between realized volatility and stock returns. A trading strategy that buys stocks in the lowest realized skewness decile and sells stocks in the highest realized skewness decile generates an average weekly return of 43 basis points with a t-statistic of 8.91. A similar strategy that buys stocks with high realized kurtosis and sells stocks with low realized kurtosis produces a weekly return of 16 basis points with a t-statistic of 2.98. Our results are robust across sample periods, portfolio weightings, and proxies for firm characteristics, and they are not captured by the Fama-French and Carhart factors.

Link al Paper




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