Monthly Performance

Period Returns

Strategy Description

Conquest Macro is a systematic trading strategy that captures short-term price movements in futures and FX markets. The program itself consists of four independent strategies: a short-term longvolatility strategy, a short-term trend-following strategy, a short-term counter-trend strategy, and a risk capture strategy. These four strategies operate in parallel to invest in approximately 30 of the most liquid global foreign exchange, fixed income, equity, and physical commodity markets. The selected markets constitute a portfolio that is balanced both in terms of geography and asset mix. This diversification of assets and non-optimized risk allocations contribute to the robustness and stability of the returns.

Conquest uses quantitative models to ensure disciplined investment decisions. In order to maximize the diversification benefits of the markets traded, Conquest uses several trading systems. Within each system, the parameters are the same for all markets traded. Each model takes advantage of market moves that occur in different time frames, and works totally independently of the other systems. What is considered trend-following in one time frame is counter-trend in another time frame. The first strategy exploits short-term price/time/volatility relationships present in fixed income, foreign exchange, energy, metal and stock index markets. The strategy looks for certain short-term price/volatility relationships to enter the market. Specifically, it takes advantage of low market volatility points where one can enter with a high reward potential (a tight stop with low likelihood of being stopped out due to market noise). The strategy uses a combination of time/price/volatility stops on all positions at all times. Trade duration varies by system but lasts up to a week, with the average trade lasting 3.3 days. The second strategy looks to capture market movements that constitute a short-term trend. The average trade length is 7.7 days. This strategy combines time and price data for exiting positions. The third strategy exploits counter-trend opportunities within longer-term trends. Again, what is considered trend-following in one time frame is counter-trend in another time frame. For example, some systems in this strategy may enter during a retracement in a long-term trend, counter to the most recent price action, while others may follow the most recent price move, but only if it is counter to a longer-term trend. Typical entry points are when trends are reversing abruptly, causing losses to long-term trend-followers. This strategy is profitable on its own and is of further advantage due to its risk reduction characteristics and its low to negative correlation with the other strategies. The average trade length is 3.1 days. The fourth strategy was integrated into the portfolio at the beginning of 2010 and leverages the sensitivity of assets and hedge fund strategies to market risk appetite. By selectively employing a variety of risk capture trades, the strategy is expected to improve performance during risk-seeking periods. The strategy is activated using a smoothing function on the Conquest Risk Aversion Index and does not trade during periods that are expected to be risk-averse. The average trade length has been approximately one month since the strategy launch. As an overlay, the weighting of the previously described strategies is adjusted based on our proprietary index of market risk appetite. In periods of high risk aversion and low risk appetite, in which the portfolio exhibits outsized positive expectation, strategies are run at full leverage. In periods of high risk appetite, the leverage of the portfolio is reduced by approximately one-third. This adjustment is made to reduce the likelihood and expected depth of drawdowns.

Risk management procedures are incorporated in the stop-loss and position size calculations for our systems. Risk management is inherent to our goal of maximizing the average return divided by the largest cumulative drawdown. After creating a robust system and a well-diversified portfolio that maximizes our return/LCD, we select our level of exposure so that the maximum hypothetical drawdown is well below our acceptable real-time drawdown level. We do not use risk management procedures that depend on portfolio rather than market information, as we did not find them to be a positive contributor to annual return/LCD. All systems have volatility-based stops for positions in the market. Position sizes are based on price volatility to equalize risk at the trade initiation time for all markets within each system.