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Statistical arbitrage strategies for systematic trading


statistical arbitrage strategies for systematic trading

factors. Mahdavi Damghani, Babak (2012). This is reflected in the investment products they offer their clients. What Happened to the Quants in August 2007?: Evidence from Factors and Transactions Data Mahdavi Damghani, Babak (2013).

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Shares may not even be available for shorting, or brokerages holding borrowable shares may demand a significant premium to. 8 One of the versions of the events describes how Morgan Stanley 's highly successful StatArb fund, PDT, decided to reduce meilleures plateformes de trading forex Royaume-Uni its positions in response to stresses in other parts of the firm, and how this contributed to several days of hectic trading. Mathematically speaking, the strategy is to find a pair of stocks with high correlation, cointegration, or other common factor characteristics. The details of the scoring formula vary and are highly proprietary, but, generally (as in pairs trading they involve a short term mean reversion principle so that,.g., stocks that have done unusually well in the past week receive low scores and stocks that have. Because of the large number of stocks involved, the high portfolio turnover and the fairly small size of the effects one is trying to capture, the strategy is often implemented in an automated fashion and great attention is placed on reducing trading costs. In mid-2002 the performance of stat arb strategies began to wane, and the standard methods have not recovered. Systems for countertrend trading are typically based on extremes in common technical indicators, including RSI, stochastics, and Bollinger Bands. If the stock falls, the short sale is profitable; while the bond declines less than the stock, yielding a net profit. Various statistical tools have been used in the context of pairs trading ranging from simple distance-based approaches to more complex tools such as cointegration and copula concepts. Mahdavi Damghani, Babak (2013). An important early article (along with Lehmanns) about short term return predictability, the source of StatArb returns Kolman, Joe (1998). These strategies have broad appeal, in that they can be implemented across a broad range of asset classes and instruments, including equities, ETFs, convertible bonds, futures, and options.

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