Forecasting volatility and volume in the Tokyo stock market: Long memory, fractality and regime switching

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Predicting Bid–Ask Spreads Using Long‐Memory Autoregressive Conditional Poisson Models (2011, unknown): “…often found in financial market data (see, among many others, Ding and Granger (1996), Andersen et al. (2003) and Corsi (2009) for volatility data, Lux and Kaizoji (2007) for traded volumes and Deo et al. (2010) for trade durations) as well as in macroeconomic time series (see Bhardwaj and…”
Daily Volume Forecasting using High Frequency Predictors (2010, background): “In [Lux and Kaizoji, 2007] the predictability of Japanese daily volume stocks and volatility are investigated.”