STOCK LIQUIDATION VIA STOCHASTIC APPROXIMATION USING NASDAQ DAILY AND INTRA‐DAY DATA

G. Yin, Q. Zhang, F. Liu, R. H. Liu and Y. Cheng

Mathematical Finance, 2006, vol. 16, issue 1, 217-236

Abstract: By focusing on computational aspects, this work is concerned with numerical methods for stock selling decision using stochastic approximation methods. Concentrating on the class of decisions depending on threshold values, an optimal stopping problem is converted to a parametric stochastic optimization problem. The algorithms are model free and are easily implementable on‐line. Convergence of the algorithms is established, second moment bound of estimation error is obtained, and escape probability from a neighborhood of the true parameter is also derived. Numerical examples using both daily closing prices and intra‐day data are provided to demonstrate the performance of the algorithms.

Date: 2006
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