This thesis consists of three papers which cover the efficient Monte Carlo simulation in option pricing, the application of realized volatility in trading strategies and geometrical analysis of a four asset mean variance portfolio optimization problem. The first paper studies different efficient simulation methods to price options with different characters such as moneyness and maturity times. The incomplete market environments are also been considered. The second paper uses realized volatility based on high frequency data to improve the volatility trading strategy. The performance is compared with that using the implied volatility.
Monte Carlo simulations for complex option pricing
"On pricing barrier options and exotic variations" by Xiao Wang
Chen, Jilong Pricing derivatives with stochastic volatility. PhD thesis, University of Glasgow. This Ph. In Chapter 4, the applicability of the Albrecher et al. Instead of classical Levy models as in Albrecher et al. It is shown that the method delivers rather tight upper bounds for the prices of Asian Options in these models and as a by-product delivers super-hedging strategies which can be easily implemented.
Getting to the Greeks: The Comprehensive Guide to Option Pricing
The derivative asset we will be most interested in is a European call option. A call option gives the holder of the option the right to buy the underlying asset by a certain date for a certain price, but a put option gives the holder the right to sell the underlying asset by a certain date for a certain price. The date in the contract is known as the expiration date or maturity date; the price in the contract is known as the exercise price or strike price.
We just launched engagement data! Please note: This post is the fourth post in a four part series on the main pricing methodologies, highlighting the pros and cons of each. Check out the first post on cost plus pricing , second post on competitor based pricing , or third post on value based pricing.