THE EARLY EXERCISE PREMIUM IN AMERICAN OPTIONS BY USING NONPARAMETRIC REGRESSIONS

Weiping Li and Su Chen
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Weiping Li: Institute of Finance and Big Data, Southwest Jiaotong University, Chengdu, Sichuan Province 611756, P. R. China2Department of Finance, Oklahoma State University, Stillwater, OK 74078-0613, USA
Su Chen: Department of Mathematical Sciences, The University of Memphis, Memphis, TN 38152, USA

International Journal of Theoretical and Applied Finance (IJTAF), 2018, vol. 21, issue 07, 1-29

Abstract: The early exercise premium and the price of an American put option are evaluated by using nonparametric regression on the time to expiration, the moneyness and the volatility of underlying assets. In terms of mean square error (MSE), our nonparametric methods of American put option pricings outperform the existing classical methods for both in-the-sample (1 September 2011–31 January 2012) and out-of-sample (1 September 2012–28 February 2013) testings on the S&P 100 Index (OEX). Our methods have better predictions and more accurate approximations. The Greek letters for both the early exercise premium and the American put option are computed numerically.

Keywords: Optimal stopping time; early exercise premium; American put option; European put option; semi-parametric method; nonparametric method (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (1)

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DOI: 10.1142/S0219024918500395

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