The Cambridge Strategy employs a blended systematic and market information process for idea generation, coupled with disciplined and dynamic risk budgeting. The three idea generation tools: a Technical Strategy, a Fundamental Strategy and a Market Information Strategy aim to identify trading opportunities in the global currency markets. These decision making tools tend to perform at different points in the market cycle; and are combined into investment portfolios; and are designed to perform across diverse market environments. A risk budget is assigned to each strategy and proprietary risk management tools focus on mitigating left-hand tail, market, liquidity and counterparty risk. The Technical Strategy tends to perform well in periods of elevated or sharply rising volatility. The strategy uses a series of proprietary trading algorithms operating across multiple 'classes' of models and over multiple look-back periods. The classes of models utilised would fall under the definition of 'pattern recognition' models. Once the models have generated signals they are passed through an expert polling array which generates an aggregate signal. In all instances, multiple parameterisations are utilised to ensure stability of trading rules and the models use 'machine learning' technologies to evolve over time to ensure they continue to work in the future. The aggregate signal is then sized using our extreme value theory, risk adjusted trade sizing methodology ('ERATS') and finally sent to a portfolio manager for execution. The Fundamental Strategy tends to perform well in periods of falling or low volatility. The strategy reflects a predetermined set of positions designed to reflect 'market' views on the relative attractiveness of these currencies versus the US dollar and will perform when higher interest rate currencies outperform lower interest rate currencies. Assets are allocated to the Systematic Fundamental Strategy based on a proprietary measure of volatility in the global currency markets (when the probability of the Strategy is low, the allocation is reduced and when the probability of the Strategy performing is high, the allocation is increased). The aggregate Strategy Portfolio is then sent to a portfolio manager for execution. The Technical and Fundamental strategies detailed above, generally have one significant deficiency, the inability to effectively manage issues like event risk, credit risk and liquidity risk. There are changes to market and relationship structures that cannot be perceived by any type of model. In its simplest form, psychology can drive markets. To that end, the Market Information Strategy seeks to leverage the experience and global contacts of our portfolio managers and allow for 'smart' implementation of trades generated by our systematic models. The MIS is a source of incremental alpha and more importantly, risk mitigation and risk exposures continuously monitored and controlled utilising extreme value theory derived tools. Individual trades are implemented by a Portfolio Manager. The Cambridge Strategy believes that long run success is achieved through successful mitigation of downside returns (with risk controlled at the portfolio, strategy and individual trade levels). While a daily EVaR limit is enforced at both the aggregate portfolio and sub-strategy level, a further layer of risk mitigation is incorporated within each separate strategy.