SSRN Author: Torben G. AndersenTorben G. Andersen SSRN Content
http://www.ssrn.com/author=17696
http://www.ssrn.com/rss/en-usThu, 09 Mar 2017 01:49:05 GMTeditor@ssrn.com (Editor)Thu, 09 Mar 2017 01:49:05 GMTwebmaster@ssrn.com (WebMaster)SSRN RSS Generator 1.0REVISION: Volatility, Information Feedback and Market Microstructure Noise: A Tale of Two RegimesWe extend the classical “martingale-plus-noise” model for high-frequency prices by an error correction mechanism originating from prevailing mispricing. The speed of price reversal is a natural measure for informational efficiency. The strength of the price reversal relative to the signal-to-noise ratio determines the signs of the return serial correlation and the bias in standard realized variance estimates. We derive the model’s properties and locally estimate it based on mid-quote returns of the NASDAQ 100 constituents. There is evidence of mildly persistent local regimes of positive and negative serial correlation, arising from lagged feedback effects and sluggish price adjustments. The model performance is decidedly superior to existing stylized microstructure models. Finally, we document intraday periodicities in the speed of price reversion and noise-to-signal ratios.
http://www.ssrn.com/abstract=2921097
http://www.ssrn.com/1572263.htmlWed, 08 Mar 2017 05:10:54 GMTREVISION: Volatility, Information Feedback and Market Microstructure Noise: A Tale of Two RegimesWe extend the classical ”martingale-plus-noise” model for high-frequency prices by an error correction mechanism originating from prevailing mispricing. The speed of price reversal is a natural measure for informational efficiency. The strength of the price reversal relative to the signal-to-noise ratio determines the signs of the return serial correlation and the bias in standard realized variance estimates. We derive the model’s properties and locally estimate it based on mid-quote returns of the NASDAQ 100 constituents. There is evidence of mildly persistent local regimes of positive and negative serial correlation, arising from lagged feedback effects and sluggish price adjustments. The model performance is decidedly superior to existing stylized microstructure models. Finally, we document intraday periodicities in the speed of price reversion and noise-to-signal ratios.
http://www.ssrn.com/abstract=2921097
http://www.ssrn.com/1568685.htmlWed, 22 Feb 2017 20:01:09 GMTREVISION: Intraday Trading Invariance in the E-Mini S&P 500 Futures MarketThe intraday trading patterns in the E-mini S&P 500 futures contract between January 2008 and November 2011 are consistent with the following invariance relationship: The return variation per transaction is log-linearly related to trade size, with a slope coefficient of -2. This association applies both across the pronounced intraday diurnal pattern and across days in the time series. The documented factor of proportionality deviates sharply from prior hypotheses relating volatility to transactions count or trading volume. Intraday trading invariance is motivated a priori by the intuition that market microstructure invariance, introduced by Kyle and Obizhaeva (2016) to explain bets at low frequencies, also applies to transactions over high intraday frequencies.
http://www.ssrn.com/abstract=2693810
http://www.ssrn.com/1480296.htmlSat, 19 Mar 2016 01:54:26 GMT