AI1 CTA Euro Invest : AI1 CTA Euro Invest

Summary

The proprietary trading system was developed by Mag. Dipl.Ing. Franz Wanovits and Dr. Johannes Fritz.

Franz Wanovits holds a masters degree in Business Administration from the University of Economics, Vienna, and a second masters degree in Mechanical Engineering from the Technical University, Vienna. He has more than 25 years of trading experience and is an expert in quantitative time series analysis. Since 1997 he has served as a member of the Executive Board of Euro Invest Bank AG, Vienna.

Johannes Fritz holds a graduate degree and a Ph.D. from Vienna University of economics and business administration. He also holds an undergraduate degree in electronic and communication engineering. After four years of working as system analyst and programmer in two mayor computer companies he started to develop the trading system. In 1994 he joined an offshore private pool as trading system developer (futures, options and stocks). Since 2003 he is working exclusively for Euro Invest Bank AG and is responsible for financial engineering, risk control, trading system development and portfolio management, as well as for the general financial market research.

Over the past decades the team has developed proprietary trading systems utilizing mathematical algorithms derived from advanced statistical analysis of historical market data. These dynamic, continuously evolving and quantitative systems are designed to perform in a wide spectrum of market conditions. The system is fundamentally the same system since 1989. There is a continuing fine-tuning process going on where the system parameters are constantly monitored and if necessary adapted. The primary target is high performance in every market situation with absolute returns based on proprietary technology as a factor for success. A minimum investment period of three years is highly recommended. The fully automated trading system operates independently in over 60 liquid markets worldwide. The system is a 4th generation advanced trend following system with differing time horizons, i.e., short-, medium- and long-term. The system differs not only by duration of trades, but also by the frequency of trading signals. This results in optimal exploitation of price movements for profit in both directions in a multitude of future markets. The system is automated to generate buy and sell orders according to a number of quantitative indicators within the constraints of predefined risk parameters. The system is equipped with a permanent and automated risk management and control framework. Diligent and successful money management balances between risk and reward with an emphasis on broad diversification over a large number of markets.

Investment Strategy

The applied trading approach does not forecast markets or price levels but reacts in a dynamic way to market's price movement. The buy and sell signals are generated using our proprietary quantitative models. These models are designed to exploit statistical properties of the underlying futures contracts. It is the aim of the algorithms to spot market inefficiencies and extract tradable information from the underlying price flow. As soon as the expected market inefficiency exceeds a specific limit, the system steps in and generates an order to initialize a long or a short position. Immediately after the execution of a new position a corresponding stop loss order becomes effective. One of the mayor input variables is market volatility. Volatility influences both, position size and stop loss distances in a very massive manner. The system's average trade length is about 70 days (but could be sometimes up to 200 days or even longer). Profitable trades tend to have a longer trade length then losing trades. The program is entirely based on quantitative analysis of price behavior. It is 100% systematic and 100% technical in nature. All relevant information is extracted from our database containing historical price movement. The program may enter into both long and short positions in any of the futures involved, or it may have no position (neutral). Its design is of the trend following type, and performs best in smooth trending market environments. In order to reduce the dependence of a particular optimal trend length, the algorithm uses three different time windows for the trade generation. As to keep the over all risk in a pre specified range, huge changes in market volatility result in reductions of the exposure and hence reduction of contracts traded (in a particular market or market group). Another mean to keep risk in a well defined range is to reduce the position sizes during a drawdown.