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
Modelling Long Memory in REITs [PDF]
One stylized feature of financial volatility impacting the modeling process is long memory. This paper examines long memory for alternative risk measures, observed absolute and squared returns for Daily REITs and compares the findings for a non- REIT ...
John Cotter
core
Long Memory in the Turkish Stock Market Return and Volatility [PDF]
This paper examines the dual long memory property of the Turkish stock market. The data set consists of daily returns, and long memory tests are carried out both for the returns and volatility.
Adnan Kasman, Erdost Torun
core
High-frequency enhanced VaR: A robust univariate realized volatility model for diverse portfolios and market conditions. [PDF]
PLoS OneKuang W.
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Value at Risk long memory volatility models with heavy-tailed distributions for cryptocurrencies. [PDF]
Front Appl Math StatSubramoney SD, Chinhamu K, Chifurira R.
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Why Do Big Data and Machine Learning Entail the Fractional Dynamics? [PDF]
Entropy (Basel), 2021 Niu H, Chen Y, West BJ.
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Commonality in the LME aluminium and copper volatility processes through a Figarch lens [PDF]
We consider dynamic representation of spot and three month aluminium and copper volatilities. These are the two most important metals traded in the London Metal Exchange (LME).
Christopher L. Gilbert +1 more
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Comparing COVID-19 with the GFC: A shockwave analysis of currency markets. [PDF]
Res Int Bus Finance, 2021 Gunay S.
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Time series properties of ARCH processes with persistent covariates [PDF]
We consider ARCH processes with persistent covariates and provide asymptotic theories that explain how such covariates affect various characteristics of volatility.
Han, Heejoon, Park, Joon Y.
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