This draft is a summary of the paper entitled: Forecasting Fuel Prices with the Chilean Exchange Rate. In that paper we show that the Chilean exchange rate has the ability to predict the returns of oil prices and of three additional oil-related products: gasoline, propane and heating oil. The...

This paper considers direct dependence of the market price autocorrelation on statistical moments of the market trades as a must necessary requirement. We regard market time-series of the trade value and volume as origin of price time-series. That determines dependence of the market-based...

An attempt is made in this paper to examine whether stock returns in two premier two exchanges in India namely, Bombay Stock Exchange (BSE), and National Stock Exchange (NSE) follow a random walk. Towards this end, data on major indices during the period 1997 to 2009 are analyzed by using...

In this paper, we show that traditional comparisons of Mean Squared Prediction Error (MSPE) between two competing forecasts may be highly controversial. This is so because when some specific conditions of efficiency are not met, the forecast displaying the lowest MSPE will also display the...

This paper assumes that the randomness of market trade values and volumes determines the properties of stochastic market prices. We derive the direct dependence of the first two price statistical moments and price volatility on statistical moments, volatilities, and correlations of market trade...

This research focuses on examining why young social media users might become trapped in a "social bubble" defined as seeking information that supports only one’s existing beliefs. We use a method called Qualitative Comparative Analysis to identify various combinations of factors that either...

Forecasting the vote share for the upcoming US presidential elections involves multiple pivotal economic and non-economic factors. Critical macroeconomic forces such as the rate of economic growth, tax burden, inflation, and unemployment significantly influence the votes gained or lost by the...

Non-Gaussian state-space models arise in several applications, and within this framework the binary time series setting provides a relevant example. However, unlike for Gaussian state-space models — where filtering, predictive and smoothing distributions are available in closed form — binary...

In this paper, I explore how fiscal policy decisions relate to the business cycle and, building on that, how the effects of policy interventions may vary depending on when policy is conducted in the business cycle. To assess this, I estimate a small to medium-sized DSGE model with expressive...

The empirical saddlepoint likelihood (ESPL) estimator is introduced. The ESPL provides improvement over one-step GMM estimators by including additional terms to automatically reduce higher order bias. The first order sampling properties are shown to be equivalent to efficient two-step GMM. New...