An extended sequential test of Bai and Perron (1998) to a long-memory process is applied to four sets of realized volatilities (RVs) of the US dollar–EU euro, the Japan yen–US dollar, the Korea won–US dollar exchange rates and the S&P 500 index to find significant structural breaks in the means. Even after the mean breaks are adjusted out, the RVs still have persistent memories, which will be shown to produce better out-of-sample forecasts of RVs if properly addressed than ignored. Contrary to the recent report of Choi et al. (2010) that ‘short-memory + break’ models have better forecast power than ‘long-memory only’ models in forecasting some foreign exchange rate RVs, models with ‘long-memory + mean breaks’ turn out to produce better out-of-sample forecasts than models with ‘short-memory + mean breaks’ and models with ‘long-memory only’.
Bibliographical noteFunding Information:
This work was supported by the National Research Foundation of Korea grant funded by the Korean government [2012-2046157].
© 2015 Taylor & Francis.
- foreign exchange rate
- high frequency data
- volatility forecasting