Motivated from Ross (1989) who maintains that asset volatilities are synonymous to the
information flow, we claim that cross-market volatility transmission effects are synonymous to …

This study provides a holistic and quantitative overview of over 800 mathematical methods
(eg, financial and risk models, statistical tests, statistics and advanced algorithms) taken out …

In this paper, the daily returns of the S&P 500 stock market index are predicted using a
variety of different machine learning methods. We propose a new multinomial classification …

We forecast the realized covariance matrix of asset returns in the US equity market by
exploiting the predictive information of graphs in volatility and correlation. Specifically, we …

Stock prices in financial markets rise and fall, sometimes dramatically, thus asset returns
exhibit volatility. In finance theory, volatility is synonymous with risk and as such represents …

In this paper, we have investigated the implications of the threshold effect of changes in FDI
inflows for the nexus between energy consumption and economic growth in eight under …

This study forecasts the oil volatility index (OVX) incorporating information from other implied
volatility (IV) indices. We provide evidence for the existence of long memory in the OVX in …

We introduce a novel method to forecast the realised covariances of multidimensional time
series. The central innovation of our method is a two-step procedure which first filters the …

Data-driven Methods for Simulation and Forecasting of Financial Time Series Abstract Page 1
Data-driven Methods for Simulation and Forecasting of Financial Time Series Chao Zhang The …

The method of the nearest neighbors as well as its variants have proven to be very powerful
tools in the non-parametric prediction and categorization of experimental measurements. On …