Tutorial Descripton


ISSUES IN TRADING SYSTEM DESIGN
by AMIR ATIYA


Abstract
In this tutorial we will present a short introduction into the various issues involved in designing trading systems. The main emphasis here will be on the stock market. The starting point is to have a statistical model that predicts stock movements well. However, this is only a small part of the whole problem. Many other issues have to be taken into account when building a successful system. We will review some of these issues. In particular, we will consider the following issues:

  1. Types of trading systems: trend-following/contrarian/value; categories of systems: arbitrage, sector switching, intraday, etc.
  2. Inputs/indicators: technical: moving averages, patterns; fundamental: financial statement data, earnings surprises; techno-fundamental: insider sales, short ratio; market wide indicators: A/D ratio; economic indicators.
  3. Design considerations: overfitting, data snooping, test of the null hypothesis of whether being profitable, survival bias, forward looking, market regime switch.
  4. Other considerations: transactions costs, exit stops and profit targets, order types, etc.
  5. performance and risk measures: Sharpe ratio, maximum drawdown, Sterling ratio, etc.
  6. Diversification, beta.
Even though they are part of trading system design, we will not cover the topics of risk management and portfolio optimization because these are too wide of a scope to be fitted in this tutorial.


Biography
Amir Atiya has obtained his Ph.D. from Caltech, and has been active in research in the areas of machine learning and computational methods, and computational finance. He has 12 years experience in trading system design. Currently he is an Associate Professor at Cairo University. He held a Visiting Associate position at Caltech from 1997-2001, and had research positions in several financial firms, such as Qantxx, Tradelink, Simplex Technology, Countrywide. He has been active in the academic community as well, as member of the organization committee for the Computational Finance Conference, Neural Networks in the Capital Markets Conference, and currently as program cochair for CIFER-03. He has been a Guest Editor of the Special Issue of IEEE Transactions Neural Networks on Neural Networks in Financial Engineering, that appeared in July 2001.



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