Pricing warrant by using binomial model : comparison between historical and implied volatility / Muhammad Nasruddeen Mazlan

A warrant is a security that allows the holder to buy and sell the underlying share at a fixed price until expiry date. Warrant price will always fluctuates since the underlying share also fluctuates. Hence, determining the warrant price is the main problem among the investors in Malaysia. This rese...

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Main Author:	Mazlan, Muhammad Nasruddeen
Format:	Thesis
Language:	English
Published:	2020
Subjects:	Mathematical statistics Probabilities Prediction analysis
Online Access:	https://ir.uitm.edu.my/id/eprint/34827/1/34827.pdf
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id	my-uitm-ir.34827
record_format	uketd_dc
spelling	my-uitm-ir.348272020-09-30T07:32:00Z Pricing warrant by using binomial model : comparison between historical and implied volatility / Muhammad Nasruddeen Mazlan 2020-09-29 Mazlan, Muhammad Nasruddeen Mathematical statistics. Probabilities Prediction analysis A warrant is a security that allows the holder to buy and sell the underlying share at a fixed price until expiry date. Warrant price will always fluctuates since the underlying share also fluctuates. Hence, determining the warrant price is the main problem among the investors in Malaysia. This research is focusing on pricing the warrant for five companies that were listed in Bursa Malaysia. The companies were chosen randomly from UiTM DataStream. The selected companies are Boon Koon Sdn Bhd, Hovid Bhd, Kelington Bhd, ML Global Bhd and Tropicana Corporation Bhd. The data contains underlying share, interest rate, exercise price and actual warrant price. This research aims to define the price of warrant by using Binomial model. Historical volatility and implied volatility were used in this research whereby volatility is the movement of the underlying share price. This research also is aiming to compare the actual warrant price with the calculated warrant price. The data will be computed manually by using Microsoft Excel and the comparison will be made from those two type of volatilities to give the nearest value of calculated warrant price to the actual warrant price. The nearest value will be assumed the best value for this research. The best result can be made by analyzing the line graphs and comparing between historical volatility and implied volatility with actual warrant price. After that, the results will be error measured by using Mean Square Error to support the results that were obtained from the line graphs. In the end, implied volatility gives the better results compared to historical volatility. 2020-09 Thesis https://ir.uitm.edu.my/id/eprint/34827/ https://ir.uitm.edu.my/id/eprint/34827/1/34827.pdf text en public degree Universiti Teknologi Mara Perlis Faculty of Computer & Mathematical Sciences
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	Mathematical statistics Probabilities Prediction analysis
spellingShingle	Mathematical statistics Probabilities Prediction analysis Mazlan, Muhammad Nasruddeen Pricing warrant by using binomial model : comparison between historical and implied volatility / Muhammad Nasruddeen Mazlan
description	A warrant is a security that allows the holder to buy and sell the underlying share at a fixed price until expiry date. Warrant price will always fluctuates since the underlying share also fluctuates. Hence, determining the warrant price is the main problem among the investors in Malaysia. This research is focusing on pricing the warrant for five companies that were listed in Bursa Malaysia. The companies were chosen randomly from UiTM DataStream. The selected companies are Boon Koon Sdn Bhd, Hovid Bhd, Kelington Bhd, ML Global Bhd and Tropicana Corporation Bhd. The data contains underlying share, interest rate, exercise price and actual warrant price. This research aims to define the price of warrant by using Binomial model. Historical volatility and implied volatility were used in this research whereby volatility is the movement of the underlying share price. This research also is aiming to compare the actual warrant price with the calculated warrant price. The data will be computed manually by using Microsoft Excel and the comparison will be made from those two type of volatilities to give the nearest value of calculated warrant price to the actual warrant price. The nearest value will be assumed the best value for this research. The best result can be made by analyzing the line graphs and comparing between historical volatility and implied volatility with actual warrant price. After that, the results will be error measured by using Mean Square Error to support the results that were obtained from the line graphs. In the end, implied volatility gives the better results compared to historical volatility.
format	Thesis
qualification_level	Bachelor degree
author	Mazlan, Muhammad Nasruddeen
author_facet	Mazlan, Muhammad Nasruddeen
author_sort	Mazlan, Muhammad Nasruddeen
title	Pricing warrant by using binomial model : comparison between historical and implied volatility / Muhammad Nasruddeen Mazlan
title_short	Pricing warrant by using binomial model : comparison between historical and implied volatility / Muhammad Nasruddeen Mazlan
title_full	Pricing warrant by using binomial model : comparison between historical and implied volatility / Muhammad Nasruddeen Mazlan
title_fullStr	Pricing warrant by using binomial model : comparison between historical and implied volatility / Muhammad Nasruddeen Mazlan
title_full_unstemmed	Pricing warrant by using binomial model : comparison between historical and implied volatility / Muhammad Nasruddeen Mazlan
title_sort	pricing warrant by using binomial model : comparison between historical and implied volatility / muhammad nasruddeen mazlan
granting_institution	Universiti Teknologi Mara Perlis
granting_department	Faculty of Computer & Mathematical Sciences
publishDate	2020
url	https://ir.uitm.edu.my/id/eprint/34827/1/34827.pdf
_version_	1783734280956936192

Pricing warrant by using binomial model : comparison between historical and implied volatility / Muhammad Nasruddeen Mazlan

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