Prediction markets, in which contract prices are used to forecast future events, are increasingly applied to various domains ranging from political contests to scientific breakthroughs. However, the dynamics of such markets are not well understood. Here, we study the return dynamics of the oldest, most data-rich prediction markets, the Iowa Electronic Presidential Election "winner-takes-all" ma...

Stock price, been studied for hundreds of years, is one of the most versatile thus hardly predictable things that is deeply rooted in the modern economy. With the trading frequency reaching sub-second and beyond, more advanced real-time stock price prediction tools would be highly demanded in addition to traditional financial analysis. In this work, we applied SVM and Naïve Bayes algorithms to ...

Bidding in e-auctions in mobile environment is a challenging task as the bidder is mobile that may cause disconnections and may not be acquainted with the emarket environment that hosts multiple concurrent e-auctions. One of the ways to ensure winning a bid is to predict the closing price of considered relevant auctions to decide the bidding strategies. Closing price prediction of an auction de...

This paper proposes an alternative approach based on a genetic algorithm and neural network (GA–NN) for the prediction of the West Texas Intermediate (WTI) crude oil price. Comparative simulation results suggested that the proposed GA–NN approach is better than the baseline algorithms in terms of prediction accuracy and computational efficiency. Mann–Whitney test results indicated that the WTI ...

Stock prices have the characteristics of nonlinearity, randomicity and uncertainty, so It is difficult to accurately depict the change rules of stock prices using traditional linear forecasting methods, which lead to low stock price prediction accuracy. In order to improve the stock price prediction precision , this paper proposed a stock price predicting model using SVM optimized by particle s...

In a market-based scheduling mechanism, the allocation of time-specific resources to tasks is governed by a competitive bidding process. Agents bidding for multiple, separately allocated time slots face the risk that they will succeed in obtaining only part of their requirement, incurring expenses for potentially worthless slots. We investigate the use of price prediction strategies to manage s...

E-consumers face biggest challenge of opting for the best bidding strategies for competing in an environment of multiple and simultaneous online auctions for same or similar items. It becomes very complicated for the bidders to make decisions of selecting which auction to participate in, place single or multiple bids, early or late bidding and how much to bid. In this paper, we present the desi...

We use laboratory experiments to examine the effect of firm size asymmetry on price leadership in a capacity constrained duopoly. The unique subgame perfect equilibrium of our duopoly game predicts that the large firm is the price leader. In the experiment, although price leadership by the large firm is frequently observed, behavior deviates significantly from the model’s prediction. Both small...

Within the last few decades, copper has been identified as one of the most applicable metals by many researchers. These researchers have also been enthusiastic to predict the price of this valuable metal. These days, the available technical analysis methods have been highly applied in the financial markets. Moreover, the researchers have used these methods to predict the suitable price tr...

Technical analysis is the forecasting of future price movement based on an examination of past prices. Some scientist found that the study of historical prices cannot predict future prices. In this research we intend to study which technical analysis tool is better for prediction of future price movement, for this purpose we are studying two the most strongest technical analysis tools is called...