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Modeling and forecasting multifractal wavelet scale: Western market versus eastern market

Author

Listed:
  • Emrah Oral

    (Financial Economics, Yeditepe University, Istanbul, Turkey)

  • Gazanfer Unal

    (Faculty of Economics, Administrative and Social Sciences, Bahcesehir University, Istanbul, Turkey)

Abstract

This leading primary study is about modeling multifractal wavelet scale time series data using multiple wavelet coherence (MWC), continuous wavelet transform (CWT) and multifractal detrended fluctuation analysis (MFDFA) and forecasting with vector autoregressive fractionally integrated moving average (VARFIMA) model. The data is acquired from Yahoo Finances!, which is composed of 1671 daily stock market of eastern (NIKKEI, TAIEX, KOPSI) and western (SP500, FTSE, DAX) markets. Once the co-movement dependencies on time-frequency space are determined with MWC, the coherent data is extracted out of raw data at a certain scale by using CWT. The multifractal behavior of the extracted series is verified by MFDFA and its local Hurst exponents have been calculated obtaining root mean square of residuals at each scale. This inter-calculated fluctuation function time series has been re-scaled and used to estimate the process with VARFIMA model and forecasted accordingly. The results have shown that the direction of price change is determined without difficulty and the efficiency of forecasting has been substantially increased using highly correlated multifractal wavelet scale time series data.

Suggested Citation

  • Emrah Oral & Gazanfer Unal, 2018. "Modeling and forecasting multifractal wavelet scale: Western market versus eastern market," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 29(11), pages 1-37, November.
    • Handle: RePEc:wsi:ijmpcx:v:29:y:2018:i:11:n:s0129183118501097
    DOI: 10.1142/S0129183118501097
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