Abstract
Market impact cost is the most significant portion of implicit transaction costs that can reduce the overall transaction cost, although it cannot be measured directly. In this paper, we employed the state-of-the-art nonparametric machine learning models: neural networks, Bayesian neural network, Gaussian process, and support vector regression, to predict market impact cost accurately and to provide the predictive model that is versatile in the number of variables. We collected a large amount of real single transaction data of US stock market from Bloomberg Terminal and generated three independent input variables. As a result, most nonparametric machine learning models outperformed a-state-of-the-art benchmark parametric model such as I-star model in four error measures. Although these models encounter certain difficulties in separating the permanent and temporary cost directly, nonparametric machine learning models can be good alternatives in reducing transaction costs by considerably improving in prediction performance.
Highlights
Transaction cost is one of the important factors that affect the investment performance and is usually classified into two major categories: explicit costs and implicit costs
Many studies have been focused on analyzing market impact costs by the academic researchers and the practitioners because it is one of the main reducible parts of the transaction cost. [1] and [2] fitted the impacts of single transactions to a concave
NN, BNN, SVR, GP, and I-star refer to neural network, Bayesian neural network, support vector regression, Gaussian process, and I-star model, respectively
Summary
Transaction cost is one of the important factors that affect the investment performance and is usually classified into two major categories: explicit costs and implicit costs. Called direct costs, are transaction costs that can be explicitly stated and measured. These costs include commissions, transaction fees, and taxes. Indirect costs, are costs that cannot be measured directly but can be improvable by an appropriate trading strategy. They include bid-ask spreads, time risk costs, and market impact costs. One of the implicit transaction costs, is the cost caused by the difference between the price before the transaction and the actual price that the transaction is executed . Many studies have been focused on analyzing market impact costs by the academic researchers and the practitioners because it is one of the main reducible parts of the transaction cost. [1] and [2] fitted the impacts of single transactions to a concave
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