T paper considers two independent firms that invest in resources such as capacity or inventory based on imperfect market forecasts. As time progresses and new information becomes available, the firms update their forecasts and have the option to trade their resources. The trade contract is determined as the bargaining equilibrium or, alternatively, as the price equilibrium. Assuming a fairly ge...

study of the changes in the stock price in tehran stock exchange is of great importance. this is because of its application in forecasting the stock price in the stock exchange. the aim of this article is to investigate the forces and mechanisms that cause the dramatic changes in stock price and the formation of chaotic trend. to test whether the chaotic trend in the tehran stock exchange exist...

this paper studies the usefulness of the p-model in the analysis of the behaviour of prices in iranian economy. the p-model is based on the quantity of theory of money. this model believes that the price level tends to move towards the equilibrium price level. the model uses price gap to forecast inflation, if the equilibrium price is greater than the current price, there is a tendency for the ...

This paper examines the predictive power of weather for electricity prices in dayahead markets in real time. We find that next-day weather forecasts improve the forecast accuracy of Scandinavian day-ahead electricity prices substantially in terms of point forecasts, suggesting that weather forecasts can price the weather premium. This improvement strengthens the confidence in the forecasting mo...

Financial forecasting is a di cult task due to the intrinsic com plexity of the nancial system A simpli ed approach in forecasting is given by black box methods like neural networks that assume little about the structure of the economy In the present paper we relate our experience using neural nets as nancial time series forecast method In particular we show that a neural net able to forecast t...

In this paper, we showed a method to forecast the daily stock price using neural networks and the result of the Neural Network forecast is compared with the Statistical forecasting result. Stock price prediction is one of the emerging field in neural network forecasting area. This paper also presents the Neural Networks ability to forecast the daily Stock Market Prices. Stock market prediction ...

It is only an order quantity which is decided for a spot selling time in the classical newsboy problem. Both the purchase timing and the time-variant variance of the demand are neglected. When the vendor gives a price discount for early purchase, the buyer purchases the quantities of price discount at the cost of forecast bias. The buyer has to forecast the demand early before purchase ahead of...

Since gold prices influence international economic and monetary systems, numerous studies have been conducted to forecast prices. Nonetheless, employing the linear relationship method usually fail explain change in pattern of price. This study introduces a new paradigm that incorporates association rules long short-term memory (LSTM) as nonlinear-based method. For simulation, proposed was analy...

W conducted prediction markets designed to forecast post-initial public offering (IPO) valuations before a particularly unique IPO: Google. The prediction markets forecast Google’s post-IPO market capitalization relatively accurately. While Google’s auction-based IPO price was 15.3% below the first-day closing market capitalization, the final prediction market forecast was only 4.0% above it. T...