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Statistical Arbitrage: Opportunity Spotting for Financial gain in Financial Markets

thesis
posted on 2011-07-15, 13:39 authored by John Holme
The project sought to identify anomalies in the price-time relationship of historically highly correlated company stocks, and to exploit these anomalies by trading both sets of stocks in a manner so as to yield a profit independently from financial market movement. The stock positions taken upon each opportunity are those of a zero investment strategy (i.e. the same value of one stock is bought as is sold in another stock – with a net of zero outlay). The idea being that the bought stock rises and/or the sold stock falls. Either way makes money. The aim of the work was to engineer this Statistical Arbitrage system, which spots real-time opportunities, and capitalize upon the event for profit. The application has indeed been engineered, and to this end this aspect part of the work has been realized. While significant annualised percentage gains of between 6.0% and 44.1% have been achieved in later simulations, this could have be due to factors present in the market at the time and/or as yet unconsidered influences. Poor or inconsistent performance in falling and level market conditions leave, at least myself, unwilling to invest in the strategy, without more work being undertaken. While the overall outcome of this work does not bode well for a totally infallible alchemist dream, I still believe that somewhere in this method is a holy grail, and would urge other individuals to complement this work if at all possible.

History

Supervisor(s)

Schlindwein, Fernando

Date of award

2011-05-01

Awarding institution

University of Leicester

Qualification level

  • Masters

Qualification name

  • Mphil

Language

en

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