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Abstract
In this article, the authors present a pretrade model and transaction cost functions that can be run in Excel and MATLAB. Currently, investors who use pretrade transaction cost analytics do so by logging into a broker/dealer or third-party server. These systems require investors to upload their trade data, portfolio holdings, and/or investment ideas for analysis. This process could, however, subject the fund to information leakage and result in higher trading costs and lower returns. Furthermore, these systems do not allow managers to incorporate their proprietary data, such as alpha estimates. The authors’ pretrade analysis functions provide investors with the ability to run analyses on their own desktop, independent of broker/dealer and third-party servers, and allow them to incorporate their own market expectations and alpha return estimates. Their process helps to preserve the funds’ valuable proprietary research and eliminate information leakage.
TOPICS: Statistical methods, quantitative methods
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