خرید و دانلود نسخه کامل کتاب Handbook of High-Frequency Trading and Modeling in Finance – Original PDF

High-frequency data in finance is often characterized by fast fluctuations and noise (see, e.g., [7]), a trait that is known to make the volatility of the data very hard to estimate (see, e.g., [13]). Although this characteristic creates many challenges in modeling, it offers itself to the study of distin- guishing “signal” from “noise,” a topic of interest in the area of quickest detection (see [25], [5]). One of the most popular algorithms used in quick- est detection is known as the cumulative sum (CUSUM) stopping rule first introduced by Page [24]. In this work, we employ a sequence of CUSUM stopping rules to construct an online trading strategy. This strategy takes advantage of the relatively frequent number of alarms CUSUM stopping times may provide when applied to high-frequency data as a result of the fast fluctuations present therein. The trading strategy implemented settles frequently and thus eliminates the risk of large positions