Long Memory and Data Frequency in Financial Markets

Arbeitspapier

This paper investigates persistence in financial time series at three different frequencies (daily, weekly and monthly). The analysis is carried out for various financial markets (stock markets, FOREX, commodity markets) over the period from 2000 to 2016 using two different long memory approaches (R/S analysis and fractional integration) for robustness purposes. The results indicate that persistence is higher at lower frequencies, for both returns and their volatility. This is true of the stock markets (both developed and emerging) and partially of the FOREX and commodity markets examined. Such evidence against the random walk behavior implies predictability and is inconsistent with the Efficient Market Hypothesis (EMH), since abnormal profits can be made using specific option trading strategies (butterfly, straddle, strangle, iron condor, etc.).

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: CESifo Working Paper ; No. 6396

Classification and Topics

• Classification: Wirtschaft ; Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes ; Asset Pricing; Trading Volume; Bond Interest Rates
• Subject: persistence ; long memory ; R/S analysis ; fractional integration

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Caporale, Guglielmo Maria ; Gil-Alaña, Luis A. ; Plastun, Alex
• Event: Veröffentlichung
• (who): Center for Economic Studies and ifo Institute (CESifo)
• (where): Munich
• (when): 2017

Further information

• Handle: http://hdl.handle.net/10419/161835
• Last update: 10.03.2025, 11:42 AM CET