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Author: Hamad Alsayed
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Hamad Alsayed
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Christopher Krauß
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Category :
Languages : en
Pages :
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Author: Jozef Rudy
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Category :
Languages : en
Pages :
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Author: Johannes Stübinger
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Category :
Languages : en
Pages :
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Author: Oron Daihes
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Category :
Languages : en
Pages :
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Author: Umit Gurkan Gurun
Publisher:
ISBN:
Category : Arbitrage
Languages : en
Pages : 360
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Author: Markus Gsell
Publisher: Columbia University Press
ISBN: 3838201140
Category : Business & Economics
Languages : en
Pages : 228
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Book Description
Technological innovations are altering the traditional value chain in securities trading. Hitherto the order handling, i.e. the appropriate implementation of a general trading decision into particular orders, has been a core competence of brokers. Labeled as Algorithmic Trading, the automation of this task recently found its way both into the brokers' portfolio of service offerings as well as to their customers' trading desks. The software performing the order handling thereby constantly monitors the market(s) in real-time and further evaluates historical data to dynamically determine appropriate points in time for trading. Within only a few years, this technology propagated itself among market participants along the entire value chain and has nowadays gained a significant market share on securities markets worldwide. Surprisingly, there has been only little research analyzing the impact of this special type of trading on markets. Markus Gsell's book aims at closing this gap by analyzing the drivers for adoption of this technology, the impact the application of this technology has on markets on a macro level, i.e. how the market outcome is affected, as well as on a micro level, i.e. how the exhibited trading behavior of these automated traders differs from normal traders' behavior.
Author: Andrew Pole
Publisher: John Wiley & Sons
ISBN: 1118160738
Category : Business & Economics
Languages : en
Pages : 230
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While statistical arbitrage has faced some tough times?as markets experienced dramatic changes in dynamics beginning in 2000?new developments in algorithmic trading have allowed it to rise from the ashes of that fire. Based on the results of author Andrew Pole?s own research and experience running a statistical arbitrage hedge fund for eight years?in partnership with a group whose own history stretches back to the dawn of what was first called pairs trading?this unique guide provides detailed insights into the nuances of a proven investment strategy. Filled with in-depth insights and expert advice, Statistical Arbitrage contains comprehensive analysis that will appeal to both investors looking for an overview of this discipline, as well as quants looking for critical insights into modeling, risk management, and implementation of the strategy.
Author: Jan Becker
Publisher: Anchor Academic Publishing (aap_verlag)
ISBN: 3954895137
Category : Political Science
Languages : en
Pages : 51
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In the following study, I am going to present a short survey of the hedge fund industry, its regulation and the existent hedge fund strategies. Statistical arbitrage in particular is explained in further detail, and major performance measurement ratios are presented. In the second part, I am going to introduce a semi-variance model for statistical arbitrage. The model is compared to the standard Garch model, which is often used in daily option trading, derivate pricing and risk management. As investment returns are not equally distributed over time, sources for statistical arbitrage occur. The semi-variance model takes skewness into account and provides higher returns at lower volatility than the Garch model. The concept is aimed to be a synopsis of mean reversion and chart pattern detection. The computer model is generated with respect to Brownian motion and technical analysis and provides significant returns to the investment. While the market efficiency hypothesis states the impossibility of long-term arbitrage opportunities, market anomalies outstand significantly. Connecting both elements creates a profitable trading system. The combination of both approaches delivers a sensible hedge fund concept. The out-of-sample backtest verifies out-performance and implies the need for further research in the area of higher moment CAPM and additional market timing strategies as sources of statistical arbitrage.
Author: Jia Geng
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 88
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