The purpose of this paper is the empirically examination of the effect of the Institutional Quality Components (Voice and Accountability, political stability and Absence of Violence and Terrorism, government effectiveness, regulatory quality, rule of law and control of corruption) on the prediction of total stock price index. The study was carried out using data extracted from 53 countries from...

Prediction markets are low volume speculative markets whose prices offer informative forecasts on particular policy topics. Observers worry that traders may attempt to mislead decision makers by manipulating prices. We adapt a Kyle-style market microstructure model to this case, adding a manipulator with an additional quadratic preference regarding the price. In this model, when other traders a...

A price reveal auction is a Dutch auction in which the current price of the item on sale remains hidden. Bidders can privately observe the price only by paying a fee, and every time a bidder does so, the price falls by a predetermined amount. We show that in equilibrium, no rational bidder should enter into such an auction. Contrary to this prediction, data about actual price reveal auctions ru...

Fluctuations in crude oil price significantly impact the global economic market. A rise or a fall leads to redistribution of wealth in both oil-exporting and importing countries. Under such background, efficient and accurate predictions for crude oil price are critical for a stable economic development. However, crude oil price forecasting has been proved to be an extremely tough task, due to i...

While much research work has been devoted to analysis and prediction of individuals’ behavior in social networks, very few studies about the analysis of business networks are conducted. Empowered by recent research on automated mining of business networks, this paper illustrates the design of a novel business network-based model called Energy Cascading Model (ECM) for the analysis and predictio...

The menu-cost interpretation of sticky prices implies that the probability of a price change should depend on the past history of prices and fundamentals only through the gap between the current price and the frictionless price. We find that this prediction is broadly consistent with the behavior of 9 Philadelphia gasoline wholesalers. We nevertheless reject the menu-cost model as a literal des...

In the last decade, prediction markets became popular forecasting tools in areas ranging from election results to movie revenues and Oscar nominations. One of the features that make prediction markets particularly attractive for decision support applications is that they can be used to answer “what if” questions and estimate probabilities of complex events. Traditional approach to answering suc...

Stock market prediction is the act of trying to determine the future value of a company stock or other financial instrument traded on a financial exchange. The successful prediction of a stock's future price will maximize investor’s gains. This paper proposes a machine learning model to predict stock market price. The proposed algorithm integrates Particle swarm optimization (PSO) and least squ...

Data Mining is being actively applied to stock market since 1980s. It has been used to predict stock prices, stock indexes, for portfolio management, trend detection and for developing recommender systems. The various algorithms which have been used for the same include ANN, SVM, ARIMA, GARCH etc. Different hybrid models have been developed by combining these algorithms with other algorithms li...