Indices DJIA S&P 500 DAX 30 Nasdaq 100 Nasdaq Comp Nikkei 225 FTSE 100 SMI DJ Stoxx 50 CAC 40 Hang Seng Kospi Nyse Comp AMEX   -     -     -     -     -     -     -     -     -     -     -     -     -     -   10261.1 1085.4 6087 1829.5 2187.7 9062.8 5371.4 6328.8 2715.7 6087 20868.9 1775.7 6926.2 1926.8 Commodites Light Crude Oil Brent Crude Copper Gold Pallad Platinum Silver Dow Diamonds QQQQ   -     -     -     -     -     -     -     -     -   73.63 74.85 258.96 1251.85 520.5 1543 19.57 102.7 45.02 Last update: 02-09-2010 15:29:00 (GMT - Live)

Testing speed Neural network technology and trading systems Profit Target Exits Gunning Slippage Contrarian Trading Testing speed Linear Programming Optimization & Curve-Fitting What if the Markets Change? Monte Carlo Simulations Walk-Forward Testing What are genetic algorithms? A Plan for Identifying and Trading Pullbacks Automated Trading Systems for Financial Markets and Recommendations for Their Usage Testing speed is the most significant determinant of simulation processing speed is the nature of the scripting or programming language used by the trader, that is, whether the language is compiled or interpreted. Modern optimizing compilers for generic languages, such as C++, FORTRAN, and Pascal/Delphi, translate the userwritten source code into highly efficient machine code that the processor can execute directly at full bore; this makes simulator toolkits that use such languages and compilers remarkably fast. On the other hand, proprietary, interpreted languages, such as Microsoft's VB for Applications and Omega's Easy Language, must be translated and fed to the processor line by line. Simulators that employ interpreted languages can be quite sluggish, especially when executing complex or "loopy" source code.