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on Financial Markets |
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Issue of 2012‒02‒15
three papers chosen by |
| By: | J. Shen; B. Zheng |
| Abstract: | With the daily and minutely data of the German DAX and Chinese indices, we investigate how the return-volatility correlation originates in financial dynamics. Based on a retarded volatility model, we may eliminate or generate the return-volatility correlation of the time series, while other characteristics, such as the probability distribution of returns and long-range time-correlation of volatilities etc., remain essentially unchanged. This suggests that the leverage effect or anti-leverage effect in financial markets arises from a kind of feedback return-volatility interactions, rather than the long-range time-correlation of volatilities and asymmetric probability distribution of returns. Further, we show that large volatilities dominate the return-volatility correlation in financial dynamics. |
| Date: | 2012–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1202.0342&r=fmk |
| By: | Michael C. M\"unnix; Takashi Shimada; Rudi Sch\"afer; Francois Leyvraz Thomas H. Seligman; Thomas Guhr; H. E. Stanley |
| Abstract: | The understanding of complex systems has become a central issue because complex systems exist in a wide range of scientific disciplines. Time series are typical experimental results we have about complex systems. In the analysis of such time series, stationary situations have been extensively studied and correlations have been found to be a very powerful tool. Yet most natural processes are non-stationary. In particular, in times of crisis, accident or trouble, stationarity is lost. As examples we may think of financial markets, biological systems, reactors or the weather. In non-stationary situations analysis becomes very difficult and noise is a severe problem. Following a natural urge to search for order in the system, we endeavor to define states through which systems pass and in which they remain for short times. Success in this respect would allow to get a better understanding of the system and might even lead to methods for controlling the system in more efficient ways. We here concentrate on financial markets because of the easy access we have to good data and because of the strong non-stationary effects recently seen. We analyze the S&P 500 stocks in the 19-year period 1992-2010. Here, we propose such an above mentioned definition of state for a financial market and use it to identify points of drastic change in the correlation structure. These points are mapped to occurrences of financial crises. We find that a wide variety of characteristic correlation structure patterns exist in the observation time window, and that these characteristic correlation structure patterns can be classified into several typical "market states". Using this classification we recognize transitions between different market states. A similarity measure we develop thus affords means of understanding changes in states and of recognizing developments not previously seen. |
| Date: | 2012–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1202.1623&r=fmk |
| By: | Massimo Guidolin (IGIER, Bocconi University and CAIR, Manchester Business School); Francesco Ravazzolo (Norges Bank (Central Bank of Norway)); Andrea Donato Tortora (Bocconi University, Milan) |
| Abstract: | This paper uses a multi-factor pricing model with time-varying risk exposures and premia to examine whether the 2003-2006 period has been characterized, as often claimed by a number of commentators and policymakers, by a substantial missprcing of publicly traded real estate assets (REITs). The estimation approach relies on Bayesian methods to model the latent process followed by risk exposures and idiosynchratic volatility. Our application to monthly, 1979-2009 U.S. data for stock, bond, and REIT returns shows that both market and real consumption growth risks are priced throughout the sample by the cross-section of asset returns. There is weak evidence at best of structural misspricing of REIT valuations during the 2003-2006 sample. |
| Keywords: | REIT returns, Bayesian estimation, Structural instability, Stochastic volatility, Linear factor models |
| JEL: | G11 C53 |
| Date: | 2011–12–27 |
| URL: | http://d.repec.org/n?u=RePEc:bno:worpap:2011_19&r=fmk |