Monte carlo simulation pricing based on summation of fractional Gaussian noise

Ling Liu

Monte carlo simulation pricing based on summation of fractional Gaussian noise

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Abstract

The circulant embedding method (CEM) is introduced to fast generate fractional Gaussian noise signals exactly. Fractional Brownian motion can be synthesized through summation of fractional Gaussian noise. Hence it can be applied to the pricing of financial derivatives via Monte Carlo simulation. Empirical result of pricing a warrant (Guodian CWB1) in the Chinese stock market for 100 trading days shows that the described method outperforms more accuracy than that based on standard Brownian motion.

Original language	English
Pages (from-to)	627-630
Number of pages	4
Journal	Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume	31
Issue number	5
Publication status	Published - May 2011

Keywords

Fractional Brownian motion
Fractional Gaussian noise
Monte Carlo simulation
Pricing

Cite this

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KW - Pricing

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Monte carlo simulation pricing based on summation of fractional Gaussian noise

Abstract

Keywords

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