Results 131 to 140 of about 2,269 (199)

The Econometric Analysis of Microscopic Simulation Models [PDF]

Microscopic simulation models are often evaluated based on visual inspection of the results.This paper presents formal econometric techniques to compare microscopic simulation (MS) models with real-life data.A related result is a methodology to compare ...
Donkers, A.C.D., Li, Y., Melenberg, B.
core   +1 more source

How to Promote the Performance of Parametric Volatility Forecasts in the Stock Market? A Neural Networks Approach. [PDF]

Entropy (Basel), 2021
Su JB.
europepmc   +1 more source

Gaussian Semiparametric Estimation in Long Memory in Stochastic Volatility and Signal Plus Noise Models [PDF]

This paper considers the persistence found in the volatility of many financial time series by means of a local Long Memory in Stochastic Volatility model and analyzes the performance of the Gaussian semiparametric or local Whittle estimator of the memory
Arteche González, Jesús María
core  

Why Do Big Data and Machine Learning Entail the Fractional Dynamics? [PDF]

Entropy (Basel), 2021
Niu H, Chen Y, West BJ.
europepmc   +1 more source

Multivariate Fractionally Integrated APARCH Modeling of Stock Market Volatility: A multi-country study [PDF]

Tse (1998) proposes a model which combines the fractionally integrated GARCH formulation of Baillie, Bollerslev and Mikkelsen (1996) with the asymmetric power ARCH speci¯cation of Ding, Granger and Engle (1993). This paper analyzes the applicability of a
Christian Conrad, Menelaos Karanasos, Ning Zeng   +2 more
core  

AI companies' strategies with traditional vs. digital assets amid geopolitical and banking crises. [PDF]

Heliyon
Dammak W, Fakhfekh M, Alnafisah H, Jeribi A.   +3 more
europepmc   +1 more source

Comparing COVID-19 with the GFC: A shockwave analysis of currency markets. [PDF]

Res Int Bus Finance, 2021
Gunay S.
europepmc   +1 more source

The Markov-switching multi-fractal model of asset returns: GMM estimation and linear forecasting of volatility [PDF]

Multi-fractal processes have recently been proposed as a new formalism for modelling the time series of returns in finance. The major attraction of these processes is their ability to generate various degrees of long memory in different powers of returns
Lux, Thomas
core  

High-frequency enhanced VaR: A robust univariate realized volatility model for diverse portfolios and market conditions. [PDF]

PLoS One
Kuang W.
europepmc   +1 more source