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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| Format: | Thesis |
| Language: | English |
| Published: |
2020
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| Online Access: | https://ir.uitm.edu.my/id/eprint/34827/ |
| _version_ | 1848808641168146432 |
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| author | Mazlan, Muhammad Nasruddeen |
| author_facet | Mazlan, Muhammad Nasruddeen |
| author_sort | Mazlan, Muhammad Nasruddeen |
| building | UiTM Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-14T23:01:56Z |
| format | Thesis |
| id | uitm-34827 |
| institution | Universiti Teknologi MARA |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T23:01:56Z |
| publishDate | 2020 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uitm-348272020-09-30T07:32:00Z https://ir.uitm.edu.my/id/eprint/34827/ Pricing warrant by using binomial model : comparison between historical and implied volatility / Muhammad Nasruddeen Mazlan 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. 2020-09-29 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/34827/1/34827.pdf Mazlan, Muhammad Nasruddeen (2020) Pricing warrant by using binomial model : comparison between historical and implied volatility / Muhammad Nasruddeen Mazlan. (2020) Degree thesis, thesis, Universiti Teknologi Mara Perlis. |
| spellingShingle | Mathematical statistics. Probabilities Prediction analysis Mazlan, Muhammad Nasruddeen Pricing warrant by using binomial model : comparison between historical and implied volatility / Muhammad Nasruddeen Mazlan |
| title | 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_short | 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 |
| topic | Mathematical statistics. Probabilities Prediction analysis |
| url | https://ir.uitm.edu.my/id/eprint/34827/ |