Goldman upgrades trading cost prediction tool

Goldman Sachs Electronic Trading (GSET) has enhanced the Goldman Sachs Shortfall Model (GSSM), a tool that estimates the average change in stock price a trader may cause by executing an order, to cope with increased volatility and the changing US equity marketplace.
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Goldman Sachs Electronic Trading (GSET) has enhanced the Goldman Sachs Shortfall Model (GSSM), a tool that estimates the average change in stock price a trader may cause by executing an order, to cope with increased volatility and the changing US equity marketplace.

The firm has removed market capitalisation categories from the GSSM’s US equities model, and so no longer divides stocks into small-, mid-, or large-cap stocks. Goldman said these categorisations can change a lot in times of high volatility, and so has introduced a more flexible form that captures liquidity differences across the market cap spectrum and allows the model to better predict trading costs.

Goldman has also developed a version of the model that is specific to US exchange-traded funds (ETFs), which it said allows for better transaction cost prediction when trading these instruments. While the old model included ETFs as part of its estimation range for equities, ETF model coefficients are now estimated separately based on a large sample of ETF-only executed orders.

GSSM can be used for pre-trade analytics as well as daily, monthly and quarterly post-trade reports. It is based on the Goldman’s own executed orders data rather than publicly-available tick data. Both clients of GSET and the broker’s own traders use the tool.

GSSM is fully integrated into two GSET algorithms – OptimIS and Port X. Goldman clients trading electronically will be able to access the tool using version 9.1 of REDIPlus, the broker’s proprietary execution management system, which will be released in September, or via web-based reports. GSSM is also integrated with Axioma Portfolio Optimizer, a third-party optimisation and portfolio construction system provided by asset management technology firm Axioma.

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