<電子ブック>
Parameter Estimation in Fractional Diffusion Models / by Kęstutis Kubilius, Yuliya Mishura, Kostiantyn Ralchenko
(Bocconi & Springer Series, Mathematics, Statistics, Finance and Economics. ISSN:2039148X ; 8)
版 | 1st ed. 2017. |
---|---|
出版者 | Cham : Springer International Publishing : Imprint: Springer |
出版年 | 2017 |
大きさ | XIX, 390 p. 17 illus., 2 illus. in color : online resource |
著者標目 | *Kubilius, Kęstutis author Mishura, Yuliya author Ralchenko, Kostiantyn author SpringerLink (Online service) |
件 名 | LCSH:Probabilities LCSH:Statistics FREE:Probability Theory FREE:Statistical Theory and Methods |
一般注記 | 1 Description and properties of the basic stochastic models -- 2 The Hurst index estimators for a fractional Brownian motion -- 3 Estimation of the Hurst index from the solution of a stochastic differential equation -- 4 Parameter estimation in the mixed models via power variations -- 5 Drift parameter estimation in diffusion and fractional diffusion models -- 6 The extended Orey index for Gaussian processes -- 7 Appendix A: Selected facts from mathematical and functional analysis -- 8 Appendix B: Selected facts from probability, stochastic processes and stochastic calculus 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. The book is addressed to specialists and researchers in the theory and statistics of stochastic processes, practitioners who apply statistical methods of parameter estimation, graduate and post-graduate students who study mathematical modeling and statistics HTTP:URL=https://doi.org/10.1007/978-3-319-71030-3 |
目次/あらすじ
所蔵情報を非表示
電子ブック | 配架場所 | 資料種別 | 巻 次 | 請求記号 | 状 態 | 予約 | コメント | ISBN | 刷 年 | 利用注記 | 指定図書 | 登録番号 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
電子ブック | オンライン | 電子ブック |
|
|
Springer eBooks | 9783319710303 |
|
電子リソース |
|
EB00200237 |
書誌詳細を非表示
データ種別 | 電子ブック |
---|---|
分 類 | LCC:QA273.A1-274.9 DC23:519.2 |
書誌ID | 4000116209 |
ISBN | 9783319710303 |
類似資料
この資料の利用統計
このページへのアクセス回数:2回
※2017年9月4日以降