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Phi Asset Managers

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Quantitative Strategies:

Our quantitative models and strategies are based on extensive internally funded research conducted since 2007. The firm's technologies are presently deployed within investment funds managed by Phi Asset Managers, and are also used in the construction of our multi-asset class market neutral portfolios.


In the course of identifying potential profit opportunities, Phi Asset Managers algorithms generate & process an enormous amount of data associated with tens of thousands of financial risk instruments, along with various factors not associated with any particular risk instrument. Data is obtained from many countries throughout the world, and covers a wide range of asset classes. When our analytical processes yield a new model the firm believes to be of predictive value, it becomes eligible for deployment within one or more trading strategies, in some cases along with other models involving some of the same financial risk instruments, but arising from different market anomalies.


The firm's proprietary optimization technology was designed with the objective of maximizing a portfolios expected return while controlling the aggregate risk associated with a portfolio. In some cases portfolios may include simultaneous positions in several hundred securities. Rather than consider each transaction in isolation, the firm's portfolio optimization software is designed to account for complex interrelationships among a large set of financial risk instruments that may range over a number of different asset classes. In many cases, the firm's optimization algorithms are able to enhance risk-adjusted returns not only through conventional diversification, but by establishing offsetting delta exposures to various risk factors at the portfolio level.


Portfolios are often reoptimized on a more-or-less continuous basis, with a steady stream of trades executed to take advantage of newly emerging profit opportunities and/or to manage various forms of dynamically varying risk. Time-sensitive trading decisions are often made very rapidly using real-time data obtained from various sources throughout the world's financial markets.