Bootstrapping Financial Time Series

It is well known that time series of returns are characterized by volatility clustering and excess kurtosis. Therefore, when modelling the dynamic behavior of returns, inference and prediction methods, based on independent and/or Gaussian observations may be inadequate. As bootstrap methods are not, in general, based on any particular assumption on the distribution of the data, they are well suited for the analysis of returns. This paper reviews the application of bootstrap procedures for inference and prediction of financial time series. In relation to inference, bootstrap techniques have been applied to obtain the sample distribution of statistics for testing, for example, autoregressive dynamics in the conditional mean and variance, unit roots in the mean, fractional integration in volatility and the predictive ability of technical trading rules. On the other hand, bootstrap procedures have been used to estimate the distribution of returns which is of interest, for example, for Value at Risk (VaR) models or for prediction purposes. Although the application of bootstrap techniques to the empirical analysis of financial time series is very broad, there are few analytical results on the statistical properties of these techniques when applied to heteroscedastic time series. Furthermore, there are quite a few papers where the bootstrap procedures used are not adequate.     

Economic impact of cruise activity: the case of Barcelona

ABSTRACT

This article shows the methodology and the main figures of the local and regional economic impact generated by cruise activity. This article is pioneering in combining different issues: estimating the impact of the cruise port activity, presenting these impacts disaggregated at a sectoral level, using a rigorous methodology and carrying out extensive fieldwork. It is demonstrated that all sectors, not just traditional tourism-related sectors, benefit from cruise tourism. In order to test and apply our methodology we focus the analysis on the Port of Barcelona, which has become the leading cruise port in the Mediterranean area.     

Effects of Prominence,Involvement, and Persuasion Knowledge on Children's Cognitive and Affective Responses to Advergames

The integrated and highly involving nature of advergames has led to criticism and concern among academics and caretakers. It is assumed that children are highly susceptible to persuasion via advergames, but empirical evidence is scarce. Therefore, this study examined the effects of three factors typically associated with advergames: brand prominence, game involvement, and (limited) persuasion knowledge on cognitive and affective responses. An experiment among 7 to 12 year old children (N = 105) showed that brand prominence and game involvement influenced children's responses, while persuasion knowledge did not. Brand prominence led to increased brand recall and recognition, whereas game involvement led to more positive brand attitudes. The effect of game involvement was mediated by game attitude, indicating that children are susceptible to affective mechanisms induced by the game. Crucially, our results demonstrate that brand prominence evokes cognitive responses, while game involvement leads to affective responses. Finally, our study revealed that persuasion knowledge (i.e. knowledge of the commercial source of the game and its persuasive intent) did not influence cognitive or affective responses to the brand or game. This implies that even if children understand the game's commercial and persuasive nature, they do not use this knowledge as a defense against the advergame's effects. This study has important theoretical and practical implications regarding the influence of new marketing techniques on children.     

STOCK RETURNS AND OPTION PRICES: AN EXPLORATORY STUDY

This study is an investigation of estimates of expected stock returns implicit in option data. The Lee-Rao-Auchmuty option valuation model provides a unique opportunity to examine whether return measurements derived by nonlinear estimation techniques show any correlation with future stock returns. During the short period covered in this study, the Lee-Rao-Auchmuty estimates give preliminary indications that they are better predictors of actual stock returns than are estimates obtained from historical data.     

Differentiated industries without entry barriers

Our objective is to predict the evolution of an industry without entry barriers where products are differentiated on the basis of quality. Each firm chooses a single brand whose characteristics and amount of production is determined by the firm. The analysis suggests two different stages in the evolution. The first is a stage of growth and the second is a stationary stage in terms of aggregate production. While during the first stage the entry of additional brands results in the reduction of average quality, during the second stage entry leads to increased average quality. Hotelling's principle of “minimum differentiation” is contradicted in the model.     

The Effects of Progressive Levels of Interactivity and Vividness in Web Marketing Sites

Abstract

This experiment examines interactivity and vividness in commercial web sites. We expected increased levels of interactivity and vividness would lead to more positive attitudes toward web sites, stronger feelings of telepresence, and greater attitude—behavior consistency. In addition, we expected increased levels of vividness to lead to the development of more enduring attitudes toward the site. Participants explored four web sites. Increases in interactivity and vividness were associated with increased feelings of telepresence. In addition, increases in vividness were associated with more positive and more enduring attitudes toward the web site. Implications for new media researchers and practitioners are discussed.     

Can platform competition support market segmentation? Network externalities versus matching efficiency in equity crowdfunding markets

We investigate whether, in spite of the existence of cross‐market network externalities, platform competition can lead to segmentation of the two sides of the market served by the platforms. We address this question in the context of competition between two equity crowdfunding platforms that connect startups looking for capital with prospective investors. Given the heterogeneity in the populations of startups and investors in terms of the riskiness of the former population and the degree of risk aversion of the latter population, we investigate whether there exists an equilibrium where the two populations are segmented to ensure an improved match between them. We find that the segmenting equilibrium can arise only when compatibility in terms of their risk profiles is of high importance to both populations, and compatibility is significantly more important than the size of the network externality considered by startups. Segmentation is likely to improve the welfare of both populations when the basic benefit from any kind of match is relatively high.     

Prediction intervals in conditionally heteroscedastic time series with stochastic components

Differencing is a very popular stationary transformation for series with stochastic trends. Moreover, when the differenced series is heteroscedastic, authors commonly model it using an ARMA-GARCH model. The corresponding ARIMA-GARCH model is then used to forecast future values of the original series. However, the heteroscedasticity observed in the stationary transformation should be generated by the transitory and/or the long-run component of the original data. In the former case, the shocks to the variance are transitory and the prediction intervals should converge to homoscedastic intervals with the prediction horizon. We show that, in this case, the prediction intervals constructed from the ARIMA-GARCH models could be inadequate because they never converge to homoscedastic intervals. All of the results are illustrated using simulated and real time series with stochastic levels.