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ON DERIVATIVES AND DERIVATIVES PRICING
CHEN SI
CHEN SI
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Abstract
This report studies the basics of financial derivatives – the definition, the different types, the uses, the pricing methods and the trading process of derivatives. It explains and evaluates the two different ways private banks deal with derivatives products: the closed architecture where a bank sources for the derivatives in-house or with internal investment banks; the open architecture where a bank can source for the derivative or its components from third parties. Because of the migration from closed architecture to open architecture, bank aim to improve on their pricing platforms to generate more accurate and timely pricings for derivatives. Thus, this paper also discussed briefly on the traditional option pricing methods like Binomial tree and Black-Schoes but the focus is on the 2 algorithms to price American options – which most banks have yet found an efficient way to price. From the simulation results, we could see the Longstaff Least Monte Carlo simulation method performs well for short horizon, less discretization cases. When the maturity of the option is longer and if the accuracy of price requires many discretization steps, this method would require the generation of millions of sample paths and the computational time can be long. The Least Square Policy Evaluation method can be an alternative in this case as it does not require the generation of the complete sets of sample paths and as long as we have a good basis function, the method could generate converging and accurate result as well.alternative in this case as it does not require the generation of the complete sets of sample paths and as long as we have a good basis function, the method could generate converging and accurate result as well.
Keywords
Derivatives, Open Architecture, American Option Pricing, Monte Carlo Simulation, Dynamic Programming
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Date
2009
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