Article2013

Regimes and long memory in realized volatility

Elena Goldman · Jouahn Nam · Hiroki Tsurumi · Jun Wang

20 citations0/0 files storedStudies in Nonlinear Dynamics and Econometrics

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Financial Risk and Volatility Modeling Stochastic processes and financial applications Complex Systems and Time Series Analysis

Abstract

In this paper we model regimes and long memory in the dynamics of realized volatilities of intraday ETF and stock returns. We estimate threshold fractionally integrated (TARFIMA) models using Bayesian Markov Chain Monte Carlo (MCMC) algorithms with efficient jump. We also introduce a test based on posterior distributions of the mean squared forecast errors for model selection. Our findings are that the TARFIMA model that accounts for a different degree of long memory, persistence and variance in two regimes outperforms ARFIMA and other models using 5 day forecasts.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 20 citations exist upstream.

References

1994Comparing Predictive Accuracy 1995Comparing Predictive Accuracy 2003Modeling and Forecasting Realized Volatility 1983THE ESTIMATION AND APPLICATION OF LONG MEMORY TIME SERIES MODELS 2008A Simple Approximate Long-Memory Model of Realized Volatility 2001The distribution of realized stock return volatility 2001The Distribution of Realized Exchange Rate Volatility 2004Power and Bipower Variation with Stochastic Volatility and Jumps

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.