Wages and prices are closely related. Wages are an important part of businesses’ costs and are thus tied to their pricing decisions. Similarly, people take the general level of prices into account when figuring out how much pay they deserve for their work. It is intuitive, therefore, that wage data could contain important information about prices and, in particular, might be useful for forecast...

Reliable forecasts of the price of oil are of interest for a wide range of applications. For example, central banks and private sector forecasters view the price of oil as one of the key variables in generating macroeconomic projections and in assessing macroeconomic risks. Of particular interest is the question of the extent to which the price of oil is helpful in predicting recessions. This p...

In the past two decades, many forecasting models based on the concepts of fuzzy time series have been proposed for dealing with various problem domains. In this paper, we present a novel model to forecast enrollments and the close prices of stock based on particle swarm optimization and generalized fuzzy logical relationships. After that some concepts of the generalized fuzzy logical relationsh...

Recently, at the 119th European Study Group with Industry, the Energy Solutions Operator EDP proposed a challenge concerning electricity prices simulation, not only for risk measures purposes but also for scenario analysis in terms of pricing and strategy. The main purpose was short-term Electricity Price Forecasting (EPF). This analysis is contextualized in the study of time series behavior, i...

The R/S test has been extensively used in testing the long memory of financial time series, but little attentions have been paid on its validity. The paper sets the chemical raw materials styrene price time series as an example, to test the stable of the price series. It indicates that we should give prudent explanation for the R/S test, and then establish the ARFIMA model to determine the data...

This paper studies a three-layer supply chain where a manufacturer sells a product through a reseller who then relies on its own salesperson to sell to the end market. The reseller has superior capability in demand forecasting relative to the manufacturer. We explore the main tradeoffs between the risk-reduction effect and the information-asymmetry-aggravation effect of the improved forecasting...

Statistical arbitrage strategies have always been popular since the advent of algorithmic trading. In particular, Exchange traded fund (E.T.F.) arbitrage has attracted much attention. Trading houses have tried to replicate ETF arbitrage to other stocks. Thus, the objective is to be able to develop a long term pricing relationship between stocks and profit from their divergence from this relatio...

Due to the inherent non-linearity and non-stationary characteristics of financial stock market price time series, conventional modeling techniques such as the Box–Jenkins autoregressive integrated moving average (ARIMA) are not adequate for stock market price forecasting. In this paper, a forecasting model based on chaotic mapping, firefly algorithm, and support vector regression (SVR) is propo...