Peak6 Investments Deploys FlexPTS for Intra-Day Optimization

Peak6 Investments L.P. of Chicago deployed a modified version of FlexTrade Systems' FlexPTS (Portfolio Trading System) to handle accelerated, intra-day long/short portfolio rebalancing and optimization, according to FlexTrade's announcement..

"With Peak6 the focus was on ultra-fast hedging and rebalancing instead of the portfolio trade scheduling for which FlexPTS is typically used. As such, we enhanced the optimization functionality to address the specific requirements for Peak6," stated Vijay Kedia, president and CEO of FlexTrade located in Great Neck, New York, in the release.

According to Eric Moore of Peak6, the firm was looking for "an offering that could be both flexible enough and resilient enough to handle the nature of our dynamic flows." "Because of the specifications of the optimization process that we envisioned, we were concerned that outside vendors would not be able to implement the software effectively enough to be productive in our environment. We are quite happy with the results regarding FlexTrade's optimizer component," stated Moore.

Key features of portfolio optimization provided to Peak6 include: advanced optimization algorithms; an advanced non-linear market impact model (based on Almgren et al, 2005); the ability to use client/third-party market impact models; the daily risk model from Northfield Information Services, (which can also be substituted for any client/third-party risk model; minimization of the expected market impact of a trade, which will adjust the portfolio back to its risk, sector/industry and position parameters. ultra fast computation (20 seconds for 3,000 symbols allowing for rebalancing during market open and customizable integration with any client EMS or OMS.

Launched in 2007, FlexPTS is primarily known for its functionality in determining the best trading trajectory for portfolios while minimizing market impact cost and the risk of underperforming benchmarks. It accomplishes the tasks by allowing traders to build the optimal trading schedule based upon all available data, such as user inputs, risk factor correlations, implied volatility the estimated market impact cost, as well as a trader's short term alpha goals. Ivy is Editor-at-Large for Advanced Trading and Wall Street & Technology. Ivy is responsible for writing in-depth feature articles, daily blogs and news articles with a focus on automated trading in the capital markets. As an industry expert, Ivy has reported on a myriad ... View Full Bio