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Transaction Cost Analysis with MATLAB: Pre-Trade, Post-Trade, Optimisation and Cost Curves

Published in Automated Trader Magazine Issue 44 Q1 2018

Comprehensive transaction cost analysis can become complex and overwhelming. One approach to simplify this task is to use a pre-defined model with parameters calibrated by a third-party provider using tools like MATLAB.

In the current trading environment, investors primarily perform transaction cost analysis (TCA) by logging into a broker-dealer or third-party server. These procedures require investors to load their trade data, portfolio holdings and/or other valuable investment ideas and proprietary research into these systems to run analyses. Unfortunately, for investors, these processes could potentially subject the fund to information leakage and allow outside persons to reverse engineer valuable investment processes, resulting in higher trading costs, lower returns and a decline in the competitive advantage for the fund.

Investors, of course, develop their own trading analytics and/or install the third party and/or broker models on their own desktop to eliminate potential information leakage. However, developing a proprietary trading analytics system is a costly endeavour and requires on-going research, development and testing. It also requires a large resource and budget commitment and a large enough data sample to ensure staatistically accurate models and results. Additionally, broker-dealer and third-party vendor systems are not readily capable to be installed on a client desktop due to proprietary transaction costs analysis (TCA) formulas and because these analytics need to interact with many different databases and other systems that reside on the broker-dealer or third-party vendor system.

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