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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Parameter Estimation in Fractional Diffusion Models

Parameter Estimation in Fractional Diffusion Models

Kubilius, Kęstutis
Mishura, Yuliya
Ralchenko, Kostiantyn

Hardcover

Series: Bocconi & Springer, Book 8

Probability & Statistics

ISBN10: 331971029X
ISBN13: 9783319710297
Publisher: Springer Nature
Published: Feb 1 2018
Pages: 390
Weight: 1.66
Height: 0.94 Width: 6.14 Depth: 9.21
Language: English

This book is devoted to parameter estimation in diffusion models involving fractional Brownian motion and related processes. For many years now, standard Brownian motion has been (and still remains) a popular model of randomness used to investigate processes in the natural sciences, financial markets, and the economy. The substantial limitation in the use of stochastic diffusion models with Brownian motion is due to the fact that the motion has independent increments, and, therefore, the random noise it generates is white, i.e., uncorrelated. However, many processes in the natural sciences, computer networks and financial markets have long-term or short-term dependences, i.e., the correlations of random noise in these processes are non-zero, and slowly or rapidly decrease with time. In particular, models of financial markets demonstrate various kinds of memory and usually this memory is modeled by fractional Brownian diffusion. Therefore, the book constructs diffusion models with memory and provides simple and suitable parameter estimation methods in these models, making it a valuable resource for all researchers in this field.

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