An event study of price movements following realized jumps

Price jumps are mostly related to investor reactions to unexpected extreme news. We perform an event study of price movements after jumps to analyse if investors’ reactions are affected by psychological biases. We employ recent non-parametric methods based on intraday returns to separate large price movements that are related to unexpected news from those merely caused by periods of high volatility. In general, we find evidence for irrational pricing, which can be associated with investors’ optimistic behavior in a bull market and the pessimism prevailing in a bear market. Furthermore, our analysis confirms the conjecture that small firms are more subject to speculative trading than large firms.     

Statistical Approaches to Forecasting Domestic Energy Consumption and Assessing Determinants: The Case of Nordic Countries

The residential sector accounts for large share of total annual energy use in the Nordic countries due to the extremely cold climates and high household heating demand. Most domestic energy consumption in the Nordic countries is for space heating and providing hot water. The purpose of our study was to forecast the annual energy consumption of the Nordic residential sectors by 2020 as a function of socio-economic and environmental factors, and to offer a framework for the predictors in each country.

Our research models the domestic energy use in Nordic countries based on social, economic and environmental factors. Applying the multiple linear regression (MLR), multivariate adaptive regression splines (MARS), and the artificial neural network (ANN) analysis methodologies, three models have been generated for each country in the Nordic region. Using these models, we forecasted the Nordic countries domestic energy use by 2020 and assessed the causal links between energy consumption and the investigated predictors. The results showed that the ANN models have a superior capability of forecasting the domestic energy use and specifying the importance of predictors compared to the regression models. The models revealed that changes in population, unemployment rate, work force, urban population, and the amount of CO₂ emissions from the residential sectors can cause significant variations in Nordic domestic sector energy use.     

On the globalization of stock markets: An application of Vector Error Correction Model,Mutual Information and Singular Spectrum Analysis to the G7 countries

This paper analyzes stock market relationships among the G7 countries between 1973 and 2009 using three different approaches: (i) a linear approach based on cointegration, Vector Error Correction (VECM) and Granger Causality; (ii) a nonlinear approach based on Mutual Information and the Global Correlation Coefficient; and (iii) a nonlinear approach based on Singular Spectrum Analysis (SSA). While the cointegration tests are based on regression models and capture linearities in the data, Mutual Information and Singular Spectrum Analysis capture nonlinear relationships in a non-parametric way. The framework of this paper is based on the notion of market integration and uses stock market correlations and linkages both in price levels and returns. The main results show that significant co-movements occur among most of the G7 countries over the period analyzed and that Mutual Information and the Global Correlation Coefficient actually seem to provide more information about the market relationships than the Vector Error Correction Model and Granger Causality. However, unlike the latter, the direction of causality is difficult to distinguish in Mutual Information and the Global Correlation Coefficient. In this respect, the nonlinear Singular Spectrum Analysis technique displays several advantages, since it enabled us to capture nonlinear causality in both directions, while Granger Causality only captures causality in a linear way. The results also show that stock markets are closely linked both in terms of price levels and returns (as well as lagged returns) over the 36 years analyzed.     

Equipment and non-equipment private investment: a generalized Solow model

The study is an empirical attempt to shed light on which categories of private fixed investment could be relied on to provide the greatest stimulus to economic growth. Panel data, comprising 5-year periodic data over the period 1965–90 pooled across 55 countries, are employed in estimating the model through the fixed-effect technique. In addition to human capital investment ratio, five categories of private fixed investment ratios are tested for. Findings suggest that not all types of investments are conducive to growth.     

A call for weather condition revaluation in mega-events management

This article provides a new insight into knowledge-based management of mega-events by highlighting the significance of weather at destination selection and scheduling events as an adaptive strategy toward climate change. Concerning the environmental and socio-economic costs of weather ignorance in event management, which may result in cancelation and change of the event time, it is recommended that planners perform a preliminary study prior to publicizing an event plan. Doing so, the organizer and visitors can benefit from optimal weather at the destination, as this study advises the decision-makers of the Tokyo 2020 Olympic and Paralympic Games to reschedule the dates of this international event.     

Cross-sectional analysis of Swedish stock returns with time-varying beta: the Swedish stock market 1983–96

This paper analyses the ability of beta and other factors, like firm size and book-to-market, to explain cross‐sectional variation in average stock returns on the Swedish stock market for the period 1983–96. We use a bivariate GARCH(1,1) process to estimate time-varying betas for asset returns. The estimated variances of these betas, derived from a Taylor series approximation, are used for correcting errors in variables. An extreme bound analysis is utilized for testing the sensitivity of the estimated coefficients to changes in the set of included explanatory variables.
Our results show that the estimated conditional beta is a more accurate measure of the true market beta than the beta estimated by OLS. The coefficient for beta is not significantly different from zero, while the variables book-to-market and leverage have significant coefficients, and the latter coefficients are also robust to model specification. Excluding the down turn 1990–92 from the sample shows that the significance of the risk premium for leverage might be considered as an industry effect during this extreme period. Finally, we find a close dependence between the risk premium for beta and that for size and book-to-market. The omission of each of these variables may cause statistical bias in the estimated coefficient for beta.     

International Evidence on the Determinants of Private Saving

A broad set of possible determinants of private saving behavioris examined using data for a large sample of industrial anddeveloping countries. Both time-series and crosssectional estimatesare obtained. Results suggest that there is a partial offseton private saving of changes in public saving and (for developingcountries) in foreign saving, that demographics and growth areimportant determinants of private saving rates, and that interestrates and terms of trade have positive, but less robust, effects.Increases in per capita gross domestic product seem to increasesaving at low income levels (relative to the United States)but decrease it at higher ones.