DocumentCode :
1968801
Title :
Using least-square Monte Carlo simulation to price American multi underlying stock options
Author :
Palupi, Irma ; Sitorus, Indra Utama ; Umbara, Rian Febrian
Author_Institution :
Dept. Sch. of Comput., Telkom Univ., Bandung, Indonesia
fYear :
2015
fDate :
27-29 May 2015
Firstpage :
504
Lastpage :
509
Abstract :
Stock options is a contract which give the right (without obligation) to the owner to buy or to sell stock asset at certain price during specified time period. Stock option is derivate product of stock, created to hedge and speculate. This research use Least-Square Monte Carlo (LSM) method to estimate American put option price. Firstly, LSM method is applied to determine single asset of American put option price and its optimal exercise boundary. According to parameter volatility, the computation result using implied volatility approach market value better than using estimated volatility from historical data. In determining the value of multiple assets put option, it is used the similar algorithm scheme as single asset put option. The comparison result of multi asset option price either using implied volatility and estimated volatility from historical data, does not give a significant differences. Also, this research observe the sensitivity of option price in Stock option is a contract which gives the right (without obligation) to the owner of the option to buy or sell stocks at a specified price within a certain period of time. Contract of the option has several parameters, such as the maturity date, interest rate, volatility of the underlying asset, and dividend rate. Based on the type of the rights granted, the option can be divided into two, namely call option and put option.
Keywords :
Monte Carlo methods; least squares approximations; share prices; stock markets; American multiunderlying stock option pricing; American put option price estimation; call option; contract; dividend rate; interest rate; least-square Monte Carlo simulation; maturity date; multiasset option price; optimal exercise boundary; parameter volatility; underlying asset volatility; volatility approach market value; Contracts; Mathematical model; Monte Carlo methods; Pricing; Sensitivity; Testing; Trajectory; American Options; Least-Square Monte Carlo; Optimal Exercise Boundary; Simulation method;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Communication Technology (ICoICT ), 2015 3rd International Conference on
Conference_Location :
Nusa Dua
Type :
conf
DOI :
10.1109/ICoICT.2015.7231476
Filename :
7231476
Link To Document :
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