It was demonstrated that jewelry and jewelry products price can be predicted at a several year horizon. The prediction consists of three steps. First, we show that the difference between producer price index and the index for jewelry and jewelry products is characterized by the presence of...

This paper develops and compares several methods of forecasting the S&P 500 Index using only data based on the closing value and trained over a six-decade data set. The methodologies include a C5.0 decision tree, a neural network, and a group of forecasts based on training set patterns of...

The Efficient Market Hypothesis is one of the most popular subjects in the empirical finance literature. Previous studies in the stock markets, which are mostly based on fixed time price variations, do not provide conclusive findings, in which evidence of short-term predictability varies...

This study reconsiders the role of jumps for volatility forecasting by showing that jumps have a positive and mostly significant impact on future volatility. This result becomes apparent once volatility is separated into its continuous and discontinuous component using estimators which are not...

Value-at-risk (VaR) is a useful risk measure broadly used by financial institutions all over the world. VaR has been extensively used to measure systematic risk exposure in developed markets like of the US, Europe and Asia. This paper analyzes the accuracy of VaR measure for Pakistan's emerging...

A plethora of academic papers on generalized autoregressive conditional heteroscedasticity (GARCH) models for bitcoin and other cryptocurrencies have been published in academic journals. Yet few, if indeed any, of these are employed by practitioners. Previous academic studies produce results...

Many psychology experiments show that individually judged probabilities of the same event can vary depending on the partition of the state space (a framing effect called partition-dependence). We show that these biases transfer to competitive prediction markets in which multiple informed traders...

We introduce a Nelson-Siegel type interest rate term structure model with the underlying yield factors following autoregressive processes revealing time-varying stochastic volatility. The factor volatilities capture risk inherent to the term structure and are associated with the time-varying...

Following recent advances in the non-parametric realized volatility approach, we separately measure the discontinuous jump part of the quadratic variation process for individual stocks and incorporate it into heterogeneous autoregressive volatility models. We analyze the distributional...