FlexTrade Systems, Inc., a leader in multi-asset algorithmic execution management systems, today announced PEAK6 Investments, L.P. has deployed a modified version of FlexPTS to handle accelerated, intra-day long/short portfolio rebalancing and optimization.
“Being flexible enough to tailor the functionality of our trading solutions has always been one of the company’s strengths, “said Vijay Kedia, president and CEO of FlexTrade. “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 of PEAK6.”
“We were looking for an offering that could be both flexible enough and resilient enough to handle the nature of our dynamic flows,” said Eric Moore of PEAK6. “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.”
Key features of portfolio optimization functionality provided to PEAK6 include:
State-of-the-art optimization algorithms. An advanced non-linear market impact model (based on Almgren et al, 2005). The ability to also use client/third-party market impact models. The daily risk model from Northfield Information Services, Inc. (which can also be substituted with 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 3000 symbols) allowing for rebalancing during market open. Customizable integration with any client EMS or OMS.
Launched in 2007, FlexPTS (Portfolio Trade Scheduler) 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 this task 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.
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