Abel/Noser is offering the buyside customized algorithms that are based on a portfolio manager’s historical interaction with the market.
The algorithms are created by examining costs derived from post-trade analysis, which shows tendencies in a manager’s stock selection process and what happens to stocks he selects, once the order is handed to the trading desk.
Abel/Noser launched this program with J.P. Morgan Asset Management last year and has been using transaction-cost analysis data to formulate trading strategies that build on a manager’s history. "There are no one-size-fits-all algos, so we came up with this tailored approach for clients who want it," said Peter Weiler, executive vice president of global sales at Abel/Noser.
Building an algorithm takes from three to four weeks–from data collection to installation, Weiler said. Between five and 10 clients are already using the algos, and others have also shown interest, he said.
As a manager’s trading process evolves, the algorithm can be recalibrated to incorporate the new data Abel/Noser has captured through its trade-cost analysis.
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