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Unconditional Return Disturbances: A Non Parametric Approach
Year Of Publication: 2004
Month Of Publication: February
Pages: 32
Download Count: 1072
View Count: 9040
Comment Num: 0
Language: EN
Who Can Read: Free
Date: 4-11-2004
Publisher: Administrator
Simulation methods are extensively used in Asset Pricing and Risk Management. The most popular of these simulation approaches, the Monte Carlo, requires model selection and parameter estimation. In addition, these approaches can be extremely computer intensive. Historical simulation has been proposed as a non-parametric alternative to Monte Carlo. This approach is limited to the historical data available. In this paper, we propose an alternative historical simulation approach. Given a historical set of data, we define a set of standardized disturbances and we generate alternative price paths by perturbing the first two moments of the original path or by reshuffling the disturbances. This approach is either totally non-parametric when constant volatility is assumed; or semiparametric in presence of GARCH (1,1) volatility. Without a loss in accuracy, it is shown to be much more powerful in terms of computer efficiency than the Monte Carlo approach. It is also extremely simple to implement and can be an effective tool for the valuation of financial assets.
Tompkins, Robert G. Sign in to follow this author
DEcclesia, Rita L. Sign in to follow this author
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