Speakers of weak future-time reference (FTR) languages perceive the future as closer and more imminent. In this study, we examine the important question of whether the FTR properties of languages spoken by investors affect their demand for forward-looking information, thereby influencing...

We present the method of complementary ensemble empirical mode decomposition (CEEMD) and Hilbert-Huang transform (HHT) for analyzing nonstationary financial time series. This noise-assisted approach decomposes any time series into a number of intrinsic mode functions, along with the...

We present a multiscale analysis of the volatility of intraday prices from high-frequency data. Our multiscale framework includes a fractional Brownian motion and microstructure noise as the building blocks. The proposed noisy fractional Brownian motion model is shown to possess a variety of...