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on Market Microstructure |
| By: | Rezania, Omid; Rachev, Svetlozar T.; Sun, Edward; Fabozzi, Frank J. |
| Abstract: | Using four years of second-by-second executed trade data, we study the intraday effects of a representative group of scheduled economic releases on three exchange rates: EUR/$, JPY/$ and GBP/$. Using wavelets to analyze volatility behavior, we empirically show that intraday volatility clusters increase as we approach the time of the releases, and decay exponentially after the releases. Moreover, we compare our results with the results of a poll that we conducted of economists and traders. Finally, we propose a wavelet volatility estimator which is not only more efficient than a range estimator that is commonly used in empirical studies, but also captures the market dynamics as accurately as a range estimator. Our approach has practical value in high-frequency algorithmic trading, as well as electronic market making. -- |
| Keywords: | Foreign exchange,volatility estimation,economic release,wavelet,high frequency |
| JEL: | F31 G14 G15 |
| Date: | 2010 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:kitwps:3&r=mst |
| By: | Romain Allez; Jean-Philippe Bouchaud |
| Abstract: | We establish several new stylised facts concerning the intra-day seasonalities of stock dynamics. Beyond the well known U-shaped pattern of the volatility, we find that the average correlation between stocks increases throughout the day, leading to a smaller relative dispersion between stocks. Somewhat paradoxically, the kurtosis (a measure of volatility surprises) reaches a minimum at the open of the market, when the volatility is at its peak. We confirm that the dispersion kurtosis is a markedly decreasing function of the index return. This means that during large market swings, the idiosyncratic component of the stock dynamics becomes sub-dominant. In a nutshell, early hours of trading are dominated by idiosyncratic or sector specific effects with little surprises, whereas the influence of the market factor increases throughout the day, and surprises become more frequent. |
| Date: | 2010–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1009.4785&r=mst |
| By: | Vincenzo Liberatore |
| Abstract: | The log-periodic power law (LPPL) is a model of asset prices during endogenous bubbles. A major open issue is to verify the presence of LPPL in price sequences and to estimate the LPPL parameters. Estimation is complicated by the fact that daily LPPL returns are typically orders of magnitude smaller than measured price returns, suggesting that noise obscures the underlying LPPL dynamics. However, if noise is mean-reverting, it would quickly cancel out over subsequent measurements. In this paper, we attempt to reject mean-reverting noise from price sequences by exploiting frequency-domain properties of LPPL and of mean reversion. First, we calculate the spectrum of mean-reverting \ou noise and devise estimators for the noise's parameters. Then, we derive the LPPL spectrum by breaking it down into its two main characteristics of power law and of log-periodicity. We compare price spectra with noise spectra during historical bubbles. In general, noise was strong also at low frequencies and, even if LPPL underlied price dynamics, LPPL would be obscured by noise. |
| Date: | 2010–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1009.4835&r=mst |