Institutional Forecasting: The Performance of Thin Virtual Stock Markets

We study the performance of Virtual Stock Markets (VSMs) in an institutional forecasting environment. We compare VSMs to the Combined Judgmental Forecast (CJF) and the Key Informant (KI) approach. We find that VSMs can be effectively applied in an environment with a small number of knowledgeable informants, i.e., in thin markets. Our results show that none of the three approaches differ in forecasting accuracy in a low knowledge-heterogeneity environment. However, where there is high knowledge-heterogeneity, the VSM approach outperforms the CJF approach, which in turn outperforms the KI approach. Hence, our results provide useful insight into when each of the three approaches might be most effectively applied.Forecasting;Electronic Markets;Information Markets;Virtual Stock Markets

Market Prices as Indicators of Political Events Evidence from the Experimental Market on the Czech Republic Parliamentary Election in 2002

According to efficient markets theory, the stock price on a competitive market is the best estimate of the stock’s present value. This is the basic assumption for predictions using experimental markets. The first part of the paper describes the features of such an experimental market, discusses shortly its advantages in providing predictions as compared to traditional opinion polls and identifies some assumptions that can influence its efficiency and predictive accuracy. The second part of the paper is then devoted to the results of the first experimental market organized in the Czech Republic, the political stock market on the Czech parliamentary elections into the Chamber of Deputies in June 2002.Experimental economics; political stock markets; predictions

E-logistics of agribusiness organisations

Logistics is one of the most important agribusiness functions due to the idiosyncrasy of food products and the structure of food supply chain. Companies in the food sector typically operate with poor production forecasting, inefficient inventory management, lack of coordination with supply partners. Further, markets are characterised by stern competition, increasing consumer demands and stringent regulation for food quality and safety. Large agribusiness corporations have already turned to e-logistics solutions as a means to sustain competitive advantage and meet consumer demands. There are four types of e-logistics applications: (a) Vertical alliances where supply partners forge long-term strategic alliances based on electronic sharing of critical logistics information such as sales forecasts and inventory volume. Vertical alliances often apply supply chain management (SCM) which is concerned with the relationship between a company and its suppliers and customers. The prime characteristic of SCM is interorganizational coordination: agribusiness companies working jointly with their customers and suppliers to integrate activities along the supply chain to effectively supply food products to customers. E-logistics solutions engender the systematic integration among supply partners by allowing more efficient and automatic information flow. (b) e-tailing, in which retailers give consumers the ability to order food such as groceries from home electronically i.e. using the Internet and the subsequent delivery of those ordered goods at home. (c) Efficient Foodservice Response (EFR), which is a strategy designed to enable foodservice industry to achieve profitable growth by looking at ways to save money for each level of the supply chain by eliminating inefficient practices. EFR provides solutions to common logistics problems, such as transactional inefficiency, inefficient plant scheduling, out-of-stocks, and expedited transportation. (d) Contracting, a means of coordinating procurement of food, beverages and their associated supplies. Many markets and supply chains in agriculture are buyer-driven where the buyers in the market tend to set prices and terms of trade. Those terms can include the use of electronic means of communication to support automatic replenishment of goods, management of supply and inventory. The results of the current applications of e-logistics in food sector are encouraging for Greek agribusiness. Companies need to become aware of and evaluate the value-added by those applications which are a sustainable competitive advantage, optimisation of supply chain flows, and meeting consumer demands and food safety regulations. E-business diffusion has shown that typically first-movers gain a significant competitive advantage and the rest companies either eventually adopt the new systems or see a significant decline in their trading partners and perish. E-logistics solutions typically require huge investments in hardware and software and skilled personnel, which is an overt barrier for most Greek companies. Large companies typically are first-movers but small and medium enterprises (SMEs) need institutional support in order to become aware that e-logistics systems can be fruitful for them as well

Predictive accuracy of political stock markets: Empirical evidence from an European perspective

In a meta study of 25 political stock markets conducted in Germany in the last decade we analyze their predictive success. Although the predictions of political stock markets are highly correlated with the corresponding polls, the markets are able to aggregate additional information. One explanatory variable for variations in predictive success of the German stock markets relative to the polls is market efficiency. Even though the overall predictions of the political stock markets are quite reliable on the aggregate level we find systematic prediction errors on the contract level that can be attributed to the vote share size and to individual trader biases. --political stock markets,forecasting,market efficiency,proportional representation

Oil and Product Price Dynamics in International Petroleum Markets

In this paper we investigate crude oil and products price dynamics. We present a comparison among ten price series of crude oils and fourteen price series of petroleum products, considering four distinct market areas (Mediterranean, North Western Europe, Latin America and North America) over the period 1994-2002. We provide first a complete analysis of crude oil and product price dynamics using cointegration and error correction models. Subsequently we use the error correction specification to predict crude oil prices over the horizon January 2002-June 2002.The main findings of the paper can be summarized as follows: a) differences in quality are crucial to understand the behaviour of crudes; b) prices of crude oils whose physical characteristics are more similar to the marker show the following regularities: b1) they converge more rapidly to the long-run equilibrium; b2) there is an almost monotonic relation between Mean Absolute Percentage Error values and crude quality, measured by API° gravity and sulphur concentration; c) the price of the marker is the driving variable of the crude price also in the short-run, irrespective of the specific geographical area and the quality of the crude under analysis.Oil prices, Product prices, Error correction models, Forecasting

Climate Services to Support Sustainable Tourism and Adaptation to Climate Change

Tourism is one of the largest global economic sectors, is a vital contributor to the economy of many nations, and is highly promoted as an important means of future development and poverty reduction in developing countries. The interface between climate and tourism is multifaceted and complex, with broad significance for tourist decision-making and expenditures, as well as industry marketing and operations worldwide. With the close relationship of tourism to the environment and climate, the integrated effects of climate change are anticipated to markedly affect tourism businesses and destinations, as well as the destination choices and mobility of individual tourists in the decades ahead. As recent major natural, political, and economic shocks have demonstrated, the tourism sector has relatively high adaptive capacity. Improved climate services will be vital for travelers and tourism businesses and destinations to adapt to climate change in an economically, socially, and environmentally sustainable manner. This paper outlines the range of applications of weather and climate information within the tourism sector and discusses priorities for future work to advance climate services for weather risk management and climate change adaptation for the tourism sector

Accuracy, Certainty and Surprise - A Prediction Market on the Outcome of the 2002 FIFA World Cup

In this chapter, we present our empirical investigation of the forecasting accuracy of a prediction market experiment drawn on the outcome of the World Cup 2002. We analyse the predictive accuracy of 64 markets and compare to bookmakers’ quotes and chance as benchmarks. We revisit the evaluation of Schmidt and Werwatz (Chapter 16) and compare our results directly to their findings. In addition, we propose a new method for testing predictive accuracy by means of a non-parametric test for the similarity of probability distributions and we evaluate the incorporation of information in market prices by comparing pre-match and half-time price data. We find a reversed favourite-longshot bias when analysing market prices before the start of the match and this bias does not disappear with the inflow of new information until half-time. Unlike the market based predictions bookmakers appear to be perfectly calibrated. Since there were substantial deviations in outcome between the 2000 European Championship and our data, we offer possible explanations for the much worse performance of the 2002 World Cup prediction market. Consistent with Schmidt and Werwatz (Chapter 16) prediction markets do assign relatively higher probabilities to the favourite when compared to the odds-setters. Together with a long streak of surprising outcomes this fact appears most likely to be responsible for the predictive inaccuracy.

Prediction Markets: A Systematic Review and Meta-Analysis

Prediction markets (PM) have drawn considerable attention in recent years as a tool for forecasting events. Studies surveying and examining relevant the trends of PM using traditional approaches have been reported in the literature. However, research using meta-analysis to review Prediction markets systems is very limited in Management Information System (MIS). This paper aimed to fill this gap by using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method to study Prediction markets trends over the past decades. Our results are as follows. First, we find that shows that more than 64% of academic studies on Prediction markets are published in top journals such as Journal of the Association for Information Systems, Journal of Consumer Research and Information Systems Research. Second, we showed that Prediction markets applications can be can be divided into two groups: internal use PMS and general public usage. Finally, our significant meta-analysis result show that on average prediction markets is 79% more accurate than alternative forecast methods based