This study is the first attempt to investigate both the linear and non-linear Granger causality between wavelet transformed spot and futures oil prices. Our findings consistently indicate bidirectional causality between the spot and futures oil markets at different time scales, under linear and...

The statistical estimate of the branching ratio η of the Hawkes model, when fitted to windows of mid-price changes, has been reported to approach criticality (η = 1) as the fitting window becomes large. In this study -- using price changes from the EUR/USD currency pair traded on the...

Puzzling deviations from the predictions of rational finance theory have been extensively documented empirically. In this paper, we offer an explanation for one of these anomalies, the “excess volatility puzzle”, i.e. the observation that prices fluctuate more than fundamentally justified....

This study aims to overcome the problem of dimensionality, accurate estimation, and forecasting Value-at-Risk (VaR) and Expected Shortfall (ES) uncertainty intervals in high frequency data. A Bayesian bootstrapping and backtest density forecasts, which are based on a weighted threshold and...

We model the complex global dependencies in international financial markets using spatial techniques. Our methodology allows us to go beyond conventional correlation analyses and volatility-spillover models confined to studying pairwise relationships, and improves the accuracy of return...

The endo-exo problem lies at the heart of statistical identi fication in many fields of science, and is often plagued by spurious strong-and-long memory due to improper treatment of trends, shocks and shifts in the data. A class of models that has shown to be useful in discerning exogenous and...

We investigate the evolution of co-movement and lead-lag relationships between the nominal effective European exchange rate and the largest European stock markets in the time and frequency dimension. We decompose the financial return series into different time scales and apply the cross-wavelet...

This study provides new insights on the nexus between Tweet sentiments and stock price in China. Based on machine learning, we classify the Tweets from Weibo, a Twitter's variant in China into five sentiments of anger, disgust, joyful, sadness, and fear. Using wavelet analysis, we find close...

Galvanized by the claims of Greenwood et al. in Bubbles for Fama that “a sharp price increase of an industry portfolio does not, on average, predict unusually low returns going forward”, and Fama’s quote (June, 2016) that “Statistically, people have not come up with ways of identifying...

We propose a novel class of models in which the crash hazard rate is determined by a function of a non-local estimation of mispricing. Rooted in behavioral finance, the non-local estimation embodies in particular the characteristic of "anchoring" on past price levels and the "probability...