Semiparametric estimation and inference on the fractal index of Gaussian and conditionally Gaussian time series data
DOI10.1080/07474938.2020.1721832zbMath1490.62229arXiv1608.01895OpenAlexW3102401040MaRDI QIDQ5861006
Publication date: 4 March 2022
Published in: Econometric Reviews (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1608.01895
Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Fractional processes, including fractional Brownian motion (60G22) Economic time series analysis (91B84) Derivative securities (option pricing, hedging, etc.) (91G20)
Related Items (max. 100)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Modelling energy spot prices by volatility modulated Lévy-driven Volterra processes
- A new wavelet-based denoising algorithm for high-frequency financial data mining
- Assessing relative volatility/ intermittency/energy dissipation
- Affine fractional stochastic volatility models
- Does anything beat 5-minute RV? A comparison of realized measures across multiple asset classes
- Multipower variation for Brownian semistationary processes
- Hurst exponent estimation of locally self-similar Gaussian processes using sample quantiles
- Power variation for Gaussian processes with stationary increments
- Central limit theorems for non-linear functionals of Gaussian fields
- Fractionally integrated generalized autoregressive conditional heteroskedasticity
- A general version of the fundamental theorem of asset pricing
- Quadratic variations and estimation of the local Hölder index of a Gaussian process
- Semiparametric estimation of long-memory volatility dependencies: The role of high-frequency data
- Long memory processes and fractional integration in econometrics
- Infinite variance stable moving averages with long memory
- Long memory continuous time models
- A Hausman test for the presence of market microstructure noise in high frequency data
- Asymptotic theory for Brownian semi-stationary processes with application to turbulence
- Stochastic simulation: Algorithms and analysis
- Long memory in continuous-time stochastic volatility models
- Time Series Analysis
- THE ESTIMATION AND APPLICATION OF LONG MEMORY TIME SERIES MODELS
- Fractional differencing
- AN INTRODUCTION TO LONG-MEMORY TIME SERIES MODELS AND FRACTIONAL DIFFERENCING
- Fractal Analysis of Surface Roughness by Using Spatial Data
- Arbitrage with Fractional Brownian Motion
- On arbitrage and replication in the fractional Black–Scholes pricing model
- On VIX futures in the rough Bergomi model
- Volatility is rough
- The local fractional bootstrap
- Stochastic Models That Separate Fractal Dimension and the Hurst Effect
- Pricing under rough volatility
- Modeling and Forecasting Realized Volatility
- Fractional Brownian Motions, Fractional Noises and Applications
- A Tale of Two Time Scales
- Semiparametric bootstrap approach to hypothesis tests and confidence intervals for the Hurst coefficient
- Estimating the parameters of a fractional Brownian motion by discrete variations of its sample paths
- Estimators of fractal dimension: assessing the roughness of time series and spatial data
- Hybrid scheme for Brownian semistationary processes
This page was built for publication: Semiparametric estimation and inference on the fractal index of Gaussian and conditionally Gaussian time series data