Nonlinear biases in the roughness of a Fractional Stochastic Regularity Model

被引：4

作者：

Angelini, Daniele ^{[1
]}

Bianchi, Sergio ^{[1
,2
]}

机构：

[1] Univ Roma La Sapienza, MEMOTEF, Rome, Italy

[2] NYU, Dept Finance & Risk Engn, Intl Affiliate, New York, NY USA

来源：

CHAOS SOLITONS & FRACTALS | 2023年 / 172卷

关键词：

Rough volatility; Fractional Ornstein-Uhlenbeck process; Multifractional process with random exponent; Hurst-Holder exponent; LONG-RANGE DEPENDENCE; MULTIFRACTIONAL PROCESSES; TIME; VOLATILITY; IDENTIFICATION; EXPONENT; MARKETS; MEMORY;

D O I：

10.1016/j.chaos.2023.113550

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

A Multifractional Process with Random Exponent (MPRE) is used to model the dynamics of log-prices in a financial market. Under this assumption, we show that the Hurst-Holder exponent of the MPRE follows the fractional Ornstein-Uhlenbeck process which in the Fractional Stochastic Volatility Model of Comte and Renault (1998) describes the dynamics of the log-volatility. We provide evidence that several biases of the estimation procedures can generate artificial rough volatility in surrogated as well as real financial data.

引用

页数：12

共 60 条

[1] Possible long-range dependence in fractional random fields [J].