SSRN Author: Yuliya MishuraYuliya Mishura SSRN Content
https://privwww.ssrn.com/author=3656181
https://privwww.ssrn.com/rss/en-usSat, 18 Jul 2020 01:03:25 GMTeditor@ssrn.com (Editor)Sat, 18 Jul 2020 01:03:25 GMTwebmaster@ssrn.com (WebMaster)SSRN RSS Generator 1.0REVISION: High-Frequency Trading with Fractional Brownian MotionIn the high-frequency limit, conditional expected increments of fractional Brownian motion converge to a white noise, shedding their dependence on the path history and the forecasting horizon, and making dynamic optimization problems tractable. We find an explicit formula for locally mean-variance optimal strategies and their performance for an asset price that follows fractional Brownian motion. Without trading costs, risk-adjusted profits are linear in the trading horizon and rise asymmetrically as the Hurst exponent departs from Brownian motion, remaining finite as the exponent reaches zero while diverging as it approaches one. Trading costs penalize numerous portfolio updates from short-lived signals, leading to a finite trading frequency, which can be chosen so that the effect of trading costs is arbitrarily small, depending on the required speed of convergence to the high-frequency limit.
https://privwww.ssrn.com/abstract=3436811
https://privwww.ssrn.com/1922163.htmlFri, 17 Jul 2020 09:11:42 GMTREVISION: High-Frequency Trading with Fractional Brownian MotionIn the high-frequency limit, conditional expected increments of fractional Brownian motion converge to a white noise, shedding their dependence on the path history and the forecasting horizon, and making dynamic optimization problems tractable. We find an explicit formula for locally mean-variance optimal strategies and their performance for an asset price that follows fractional Brownian motion. Without trading costs, risk-adjusted profits are linear in the trading horizon and rise asymmetrically as the Hurst exponent departs from Brownian motion, remaining finite as the exponent reaches zero while diverging as it approaches one. Trading costs penalize numerous portfolio updates from short-lived signals, leading to a finite trading frequency, which can be chosen so that the effect of trading costs is arbitrarily small, depending on the required speed of convergence to the high-frequency limit.
https://privwww.ssrn.com/abstract=3436811
https://privwww.ssrn.com/1921579.htmlThu, 16 Jul 2020 08:12:48 GMTREVISION: High-Frequency Trading with Fractional Brownian MotionIn the high-frequency limit, conditional expected increments of fractional Brownian motion converge to a white noise, shedding their dependence on the path history and the forecasting horizon, and making dynamic optimization problems tractable. We find an explicit formula for locally mean-variance optimal strategies and their performance for an asset price that follows fractional Brownian motion. Without trading costs, risk-adjusted profits are linear in the trading horizon and rise asymmetrically as the Hurst exponent departs from Brownian motion, remaining finite as the exponent reaches zero while diverging as it approaches one. Trading costs penalize numerous portfolio updates from short-lived signals, leading to a finite trading frequency, which can be chosen so that the effect of trading costs is arbitrarily small, depending on the required speed of convergence to the high-frequency limit.
https://privwww.ssrn.com/abstract=3436811
https://privwww.ssrn.com/1815994.htmlFri, 16 Aug 2019 14:04:34 GMT