Chance discovery in stock index option and future arbitrage

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@Article{tsang05:_chanc,
  author =       "Edward P. K. Tsang and Sheri Markose and Hakan Er",
  title =        "Chance discovery in stock index option and future
                 arbitrage",
  journal =      "New Mathematics and Natural Computation",
  year =         "2005",
  volume =       "1",
  number =       "3",
  pages =        "435--447",
  month =        nov,
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1142/S1793005705000251",
  abstract =     "The prices of the option and futures of a stock both
                 reflect the market's expectation of futures changes of
                 the stock's price. Their prices normally align with
                 each other within a limited window. When they do not,
                 arbitrage opportunities arise: an investor who spots
                 the misalignment will be able to buy (sell) options on
                 the one hand, and sell (buy) futures on the other and
                 make risk-free profits. Historical data suggest that
                 option and futures prices on the LIFFE Market do not
                 align occasionally. Arbitrage chances are rare.
                 Besides, they last for seconds only before the market
                 adjusts itself. The challenge is not only to discover
                 such chances, but to discover them ahead of other
                 arbitragers. In the past, we have introduced EDDIE as a
                 genetic programming tool for forecasting. This paper
                 describes EDDIE-ARB, a specialisation of EDDIE, for
                 forecasting arbitrage opportunities. As a tool,
                 EDDIE-ARB was designed to enable economists and
                 computer scientists to work together to identify
                 relevant independent variables. Trained on historical
                 data, EDDIE-ARB was capable of discovering rules with
                 high precision. Tested on out-of-sample data, EDDIE-ARB
                 out-performed a naive ex ante rule, which reacted only
                 when misalignments were detected. This establishes
                 EDDIE-ARB as a promising tool for arbitrage chances
                 discovery. It also demonstrates how EDDIE brings domain
                 experts and computer scientists together.",
}

Genetic Programming entries for Edward P K Tsang Sheri M Markose Hakan Er

Citations