Stable non-Gaussian random processes , by G. Samorodnitsky and M. S. Taqqu. Pp. 632. £49.50. 1994. ISBN 0-412-05171-0 (Chapman and Hall).

Investor Psychology and Security Market Under- and Overreactions

Feel lonely? What about reading books? Book is one of the greatest friends to accompany while in your lonely time. When you have no friends and activities somewhere and sometimes, reading book can be a great choice. This is not only for spending the time, it will increase the knowledge. Of course the b=benefits to take will relate to what kind of book that you are reading. And now, we will concern you to try reading models of man as one of the reading material to finish quickly.

Models of man

Handbook of the Economics of Finance

Annual Energy Outlook

We propose a new framework for measuring connectedness among financial variables that arise due to heterogeneous frequency responses to shocks. To estimate connectedness in short-, medium-, and long-term financial cycles, we introduce a framework based on the spectral representation of variance decompositions. In an empirical application, we document the rich time-frequency dynamics of volatility connectedness in U.S. financial institutions. Economically, periods in which connectedness is created at high frequencies are periods when stock markets seem to process information rapidly and calmly, and a shock to one asset in the system will have an impact mainly in the short term. When the connectedness is created at lower frequencies, it suggests that shocks are persistent and are being transmitted for longer periods.

Measuring the Frequency Dynamics of Financial Connectedness and Systemic Risk

Co-movement of energy commodities revisited: Evidence from wavelet coherence analysis

We propose a new framework for measuring connectedness among financial variables that arises due to heterogeneous frequency responses to shocks. To estimate connectedness in short-, medium-, and long-term financial cycles, we introduce a framework based on the spectral representation of variance decompositions. In an empirical application, we document the rich time-frequency dynamics of volatility connectedness in US financial institutions. Economically, periods in which connectedness is created at high frequencies are periods when stock markets seem to process information rapidly and calmly, and a shock to one asset in the system will have an impact mainly in the short term. When the connectedness is created at lower frequencies, it suggests that shocks are persistent and are being transmitted for longer periods.

Measuring the frequency dynamics of financial connectedness and systemic risk

https://www.econstor.eu/bitstream/10419/110804/1/cesifo_wp5305.pdf

Asymmetric connectedness on the U.S. stock market: Bad and good volatility spillovers

In this paper, we show how the sampling properties of the Hurst exponent methods of estimation change with the presence of heavy tails. We run extensive Monte Carlo simulations to find out how rescaled range analysis ( R / S ), multifractal detrended fluctuation analysis ( M F - D F A ), detrending moving average ( D M A ) and generalized Hurst exponent approach ( G H E ) estimate Hurst exponent on independent series with different heavy tails. For this purpose, we generate independent random series from stable distribution with stability exponent α changing from 1.1 (heaviest tails) to 2 (Gaussian normal distribution) and we estimate the Hurst exponent using the different methods. R / S and G H E prove to be robust to heavy tails in the underlying process. G H E provides the lowest variance and bias in comparison to the other methods regardless the presence of heavy tails in data and sample size. Utilizing this result, we apply a novel approach of the intraday time-dependent Hurst exponent and we estimate the Hurst exponent on high frequency data for each trading day separately. We obtain Hurst exponents for S&P500 index for the period beginning with year 1983 and ending by November 2009 and we discuss the surprising result which uncovers how the market’s behavior changed over this long period.

/pdf/on-hurst-exponent-estimation-under-heavy-tailed-4qwch93bis.pdf

Jozef Baruník

Papers

Measuring the Frequency Dynamics of Financial Connectedness and Systemic Risk

Co-movement of energy commodities revisited: Evidence from wavelet coherence analysis

Measuring the frequency dynamics of financial connectedness and systemic risk

Asymmetric connectedness on the U.S. stock market: Bad and good volatility spillovers

On Hurst exponent estimation under heavy-tailed distributions