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   -     -     -     -     -     -     -     -     -     -     -     -     -     -   10911 1137.4 5732.4 2127.7 2438.1 8981.9 5072.1 4984.1 2161.9 5732.4 19614.7 1817.4 7017.6 2174.7 Commodites Light Crude Oil Brent Crude Copper Gold Pallad Platinum Silver Dow Diamonds QQQQ   -     -     -     -     -     -     -     -     -   83.08 106.28 1.17 1758.7 730.5 1782 38.21 109.16 55.42 Last update: 11-08-2011 14:29:00 (GMT - Live)

Monte Carlo Simulations 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 One powerful, unique approach to making statistical inferences is known as the Monte Carlo Simulation, which involves repeated tests on synthetic data that are constructed to have the properties of samples taken from a random population. Except for randomness, the synthetic data are constructed to have the basic characteristics of the population from which the real sample was drawn and about which inferences must be made. This is a very powerful method. The beauty of Monte Carlo Simulations is that they can be performed in a way that avoids the dangers of assumptions (such as that of the normal distribution) being violated, which would lead to untrustworthy results. More: T H E E N C Y C L O P E D I A O F T R A D I N G S T R A T E G I E S