| Futures floor traders show speculative behavior in their trading not only as simple mechanical operatives or market makers but also as speculative traders. Previous studies show that floor traders take considerable risks when they undertake trades. Therefore, analyzing the risk characteristics and understanding how these risks are related to other factors may provide answers to institutional investors, other asset risk managers and regulatory bodies who supervise the trading activities of the derivative market. This study explains how traders manage these risks through dynamic trading.; With the growing concern about risk management of financial institutions, Value-at-Risk (VaR) method has drawn much attention as a risk management tool. Even for an alternative investment vehicle such as a hedge fund, the industry has employed VaR models for risk measurement. However, as a position analysis, VaR is not an appropriate measure for a dynamic trading environment due to its restrictive assumptions.; Using the S&P 500 futures data set, this study covers a comprehensive and detailed risk analysis in terms of traders' income distribution and income distribution forecasting using futures market transaction data. In particular, I will show the extent to which the income distribution is related to market variables such as market price volatility and the level of volume in both a time series and cross sectional setting. In addition, I seek to find relationships among the income distribution of trades, previous market variables, and volatilities of returns. From lagged returns and volatilities, I expect to forecast the change of income distribution for the traders. The practical application would produce criterion, based on the observable variables, for decision makers in lending institutions and regulatory bodies. Empirical study shows a positive contemporaneous relationship of income-distribution with market variables and forecasting ability of the variables for future wealth variability. It also provides positive risk and return relationship for groups of traders from cross sectional analysis. |
