Trading's New Frontier Learn from Murray Ruggiero how machine learning delivers cutting-edge analysis in below videos. These educational videos show how to use Murray's self-contained suite of Machine Learning tools to trade with the latest adaptive methods. Quantitative analyst and systems-building master Murray Ruggiero has produced a series of educational videos included below that show how everyday traders can use machine learning to trade on the cutting edge. Machine learning is a new paradigm in trading. Traders who adapt can reap the rewards. Traders who don't will suffer the consequences of trading with inferior methods. The cost of this labor-intensive approach is prohibitive for most, but Murray Ruggiero's Machine Learning Toolkit unlocks the power of these tools for everyone. Even better, the below videos show how easy it is to tap into this advanced approach. The introductory price of $249 includes access to low-cost upgrades Future enhancements will include advanced Arima/Garch models, Multicore support and even cluster computing on Amazon’s cloud computing service. Building a simple Arima/Garch model in Tradestation: Developing a trading system for Orange Juice futures: Combining models using equity-curve feedback: R is one of the most powerful and popular languages used in machine learning and artificial intelligence. This toolkit includes a complete course in learning the R programming language and applying it to trading using advance modeling and machine learning methods available for free within R. In addition to four market case studies, a basic prediction model for trading the S&P 500 is included. Also included is a fully disclosed Arima/Garch Hybrid Model that is used to predict the S&P 500,SPY as well as futures. This model can be used to predict both equities and futures markets and build simple trading system using these predictions. These models predict the returns for a given market one day into the future. Also included is the TradeStation code to show you how to use its output in a system. Murray's Machine Learning Toolkit is fully contained and includes all the training you need to take advantage of the R programming language. No prior programming knowledge is needed, and this toolkit works with any trading platform that can accept ASCII files. Compatible software includes TradeStation, TradersStudio, AMIBroker, Trading Blox and more. Don't be left in the past. Purchase Murray's Machine Learning Toolkit and get access to the methods that the big traders don't want you to have. Unlock the power of quantative analysis for yourself today. DISCLAIMER HYPOTHETICAL PERFORMANCE RESULTS HAVE MANY INHERENT LIMITATIONS, SOME OF WHICH ARE DESCRIBED BELOW. NO REPRESENTATION IS BEING MADE THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFITS OR LOSSES SIMILAR TO THOSE SHOWN. IN FACT, THERE ARE FREQUENTLY SHARP DIFFERENCES BETWEEN HYPOTHETICAL PERFORMANCE RESULTS AND THE ACTUAL RESULTS SUBSEQUENTLY ACHIEVED BY ANY PARTICULAR TRADING PROGRAM. ONE OF THE LIMITATIONS OF HYPOTHETICAL PERFORMANCE RESULTS IS THAT THEY ARE GENERALLY PREPARED WITH THE BENEFIT OF HINDSIGHT. IN ADDITION, HYPOTHETICAL TRADING DOES NOT INVOLVE FINANCIAL RISK, AND NO HYPOTHETICAL TRADING RECORD CAN COMPLETELY ACCOUNT FOR THE IMPACT OF FINANCIAL RISK IN ACTUAL TRADING. FOR EXAMPLE, THE ABILITY TO WITHSTAND LOSSES OR TO ADHERE TO A PARTICULAR TRADING PROGRAM IN SPITE OF TRADING LOSSES ARE MATERIAL POINTS WHICH CAN ALSO ADVERSELY AFFECT ACTUAL TRADING RESULTS. THERE ARE NUMEROUS OTHER FACTORS RELATED TO THE MARKETS IN GENERAL OR TO THE IMPLEMENTATION OF ANY SPECIFIC TRADING PROGRAM WHICH CANNOT BE FULLY ACCOUNTED FOR IN THE PREPARATION OF HYPOTHETICAL PERFORMANCE RESULTS AND ALL OF WHICH CAN ADVERSELY AFFECT ACTUAL TRADING RESULTS.