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The main principle behind the model is to hedge the option by buying and selling the underlying asset in a specific way to eliminate risk. This type of hedging is called "continuously revised delta hedging" and is the basis of more complicated hedging strategies such as those used by investment banks and hedge funds.
A related term, delta hedging, is the process of setting or keeping a portfolio as close to delta-neutral as possible. In practice, maintaining a zero delta is very complex because there are risks associated with re-hedging on large movements in the underlying stock's price, and research indicates portfolios tend to have lower cash flows if re ...
John C. Hull is a professor of Derivatives and Risk Management at the Rotman School of Management at the University of Toronto. [3] [4]He is a respected researcher in the academic field of quantitative finance (see for example the Hull-White model) and is the author of two books on financial derivatives that are widely used texts for market practitioners: "Options, Futures, and Other ...
In mathematical finance, a Monte Carlo option model uses Monte Carlo methods [Notes 1] to calculate the value of an option with multiple sources of uncertainty or with complicated features. [1] The first application to option pricing was by Phelim Boyle in 1977 (for European options ).
From the viewpoint of the option issuer, e.g. an investment bank, the gamma term is the cost of hedging the option. (Since gamma is the greatest when the spot price of the underlying is near the strike price of the option, the seller's hedging costs are the greatest in that circumstance.)
The hedge algorithm is similar to the weighted majority algorithm. However, their exponential update rules are different. [2] It is generally used to solve the problem of binary allocation in which we need to allocate different portion of resources into N different options. The loss with every option is available at the end of every iteration.