Co-movement in Stock Prices in Emerging Economies: The Case of the Caricom Region

The Grand Anse Declaration of 1989 recognised the need for financial integration within the emerging economies that comprise the CARICOM region, as a way of furthering the wider process of economic integration and, indeed, economic development in that region. Using co-movement as a measure of financial integration, this paper investigates the co-movement in stock prices among the Barbados, the Jamaica and the Trinidad and Tobago Stock Exchanges, the three major exchanges within the CARICOM region. It also examines how integrated these exchanges are with the New York Stock Exchange. The GARCH-Copula methodology and, to a lesser extent, estimated correlation coefficients, are used to attain this objective. There appears to be co-movement in stock prices and returns within the CARICOM stock markets and significant dependence structures between the returns of the three CARICOM stock markets. However, there is considerably less evidence of integration between the CARICOM markets and the New York Stock Exchange.     

Effect of Price Change Alert on Perceptions of Hotel Attribute-based Room Pricing (ABP) versus Traditional Room Pricing (TRP)

Aside from marketing information on traditional room rates, hotels and online travel agents (OTAs) are trying a new pricing technique based on the attributes of guestrooms. This research investigates how attribute-based room pricing (ABP) differs from traditional room pricing (TRP) in influencing consumer reactions when consumers receive a price change alert before (vs. after) sales. Through a series of experiments, we found that TRP and ABP result in similar alert attitude, brand attitude, and visit intention for presale price change alert. However, ABP leads to more favorable results for postsale price change alert. We examined the underlying mechanism and found that perceived fairness mediates the effect of pricing strategy on brand attitude, price alert attitude, and visit intention for postsale alert only. This research provides hotel managers and OTA marketers with guidance on when to send either type of price change message to consumers.     

Revising price history: consumer price index for Norway 1492–2018

ABSTRACT

The paper presents a new combined annual cost of living and consumer price index for Norway covering 1492–2018, indicating that Norwegian price history has to be revised. The new historical price index is constructed on a significantly richer data material, which also makes it cover a longer period of price history than the existing one. This is made possible by the compilation of quantitative data from numerous sources, mostly originating from the eighteenth, nineteenth and early twentieth centuries, with grain prices stretching back to 1492. The new combined cost of living and consumer price index is constructed by a Laspeyres approach with shifting baskets for commodities and expenditure groups.

The index makes it possible to follow annual inflation and deflation in Norway for a period of 526 years. When comparing to existing indices, the new series reveals that revisions are needed in Norwegian price history. These make the historical price development more in line with those of the neighbouring countries and more in line with the pattern of wholesale prices.     

股价信息含量与投资-股价敏感性——基于融资融券的准自然实验

本文利用2006-2015年间的数据研究了融资融券对投资-股价敏感性的影响。利用融资融券作为股价信息含量的一个外生冲击变量,本文研究发现,我国A股市场确实存在反馈效应,融资融券政策的实施增强了标的公司投资-股价敏感性,这个结论在采用倾向得分模型(PSM)配对后依然成立,说明融资融券使股价融入了更多有利于管理层投资决策的信息。其次,融资融券对投资-股价敏感性的影响在机构投资者比例高、流动性高、处于新兴行业的这类管理层反馈效应更强的股票组中更显著。参照以往研究考虑了融资约束对反馈效应的调节作用,同样发现融资融券对投资-股价敏感性的影响在国有企业和规模较大的企业组中更显著。最后,融资融券交易规模越大,投资对股价的敏感性越强。     

Are USDA reports still news to changing crop markets?

This study investigates whether major USDA reports still provide important news to changing crop markets. The news component of each report, or market “surprise,” is measured as a difference between the USDA estimate and its private expectation in corn, soybeans, and wheat markets. Changes in the relevance of USDA information are assessed by examining changes in the magnitude of market surprises and shifts in the futures price reaction to these surprises, which isolates the impact of each report. The stable size of market surprises over time suggests that competition from alternative data sources has not reduced the news component of USDA crop reports. Increasing price reaction to most reports, including those facing competition from alternative information sources, suggests that value of public information may be enhanced in uncertain markets affected by structural changes.     

Volatility spillovers between WTI and Brent spot crude oil prices: an analysis of granger causality in variance patterns over time

There has been an increase in price volatility in oil prices during and since the global financial crisis (GFC). This study investigates the Granger causality patterns in volatility spillovers between West Texas International (WTI) and Brent crude oil spot prices using daily data. We use Hafner and Herwartz’s (2006) test and employ a rolling sample approach to investigate the changes in the dynamics of volatility spillovers between WTI and Brent oil prices over time. Volatility spillovers from Brent to WTI prices are found to be more pronounced at the beginning of the analysis period, around the GFC, and more recently in 2020. Between 2015 and 2019, the direction of volatility spillovers runs unidirectionally from WTI to Brent oil prices. In 2020, however, a Granger-causal feedback relation between the volatility of WTI and Brent crude oil prices is again detected. This is due to the uncertainty surrounding how the COVID-19 pandemic will evolve and how long the economies and financial markets will be affected. In this uncertain environment, commodities markets participants could be reacting to prices and volatility signals on both WTI and Brent, leading to the detection of a feedback relation.     

PITFALLS IN CROSS‐SECTION STUDIES WITH INTEGRATED REGRESSORS: A SURVEY AND NEW DEVELOPMENTS

In cross‐section studies, if the dependent variable is I(0) but the regressor is I(1), the true slope must be zero in the resulting “unbalanced regression.” A spuriously significant relationship may be found in large cross‐sections, however, if the integrated regressor is related to a stationary variable that enters the DGP but is omitted from the regression. The solution is to search for the related stationary variable, in some cases the first difference of the integrated regressor, in other cases, a categorical variable that can take on limited number of values which depend on the integrated variable. We present an extensive survey, new developments, and applications particularly in finance.     

Predictive regressions under asymmetric loss: Factor augmentation and model selection

This paper discusses the specifics of forecasting using factor-augmented predictive regressions under general loss functions. In line with the literature, we employ principal component analysis to extract factors from the set of predictors. In addition, we also extract information on the volatility of the series to be predicted, since the volatility is forecast-relevant under non-quadratic loss functions. We ensure asymptotic unbiasedness of the forecasts under the relevant loss by estimating the predictive regression through the minimization of the in-sample average loss. Finally, we select the most promising predictors for the series to be forecast by employing an information criterion that is tailored to the relevant loss. Using a large monthly data set for the US economy, we assess the proposed adjustments in a pseudo out-of-sample forecasting exercise for various variables. As expected, the use of estimation under the relevant loss is found to be effective. Using an additional volatility proxy as the predictor and conducting model selection that is tailored to the relevant loss function enhances the forecast performance significantly.     

China and international market integration: Evidence from the law of one price in the Middle East and Africa

We model market integration in the Middle East and Africa by analyzing price dispersion and testing the law of one price (LOP) on highly-comparable actual local retail prices of 135 goods and services across 23 countries in the region over the period of 1990–2016. Second-generation panel estimators are applied to four price benchmarks: Regional average, South Africa, China, and US prices. Cross-regional price dispersion diminishes considerably over time up to 2008, particularly for non-tradeables around China price. The test of LOP indicates the percentage of convergent prices is highest in China price benchmark, followed by US, South Africa, and regional average benchmarks. Direct estimation of the convergence speed confirms this order. Overall, the results show evidence of increasing market integration in Middle East and Africa but it appears to be driven by global forces and, especially, the rise of China as a new economic power. The results show that some emerging market economies, such as China, can step up and promote integration while traditional economic powerhouses, such as the USA and UK, disengage from international economic relations.     

Volatility forecasting: long memory,regime switching and heteroscedasticity

In this article, we account for the first time for long memory, regime switching and the conditional time-varying volatility of volatility (heteroscedasticity) to model and forecast market volatility using the heterogeneous autoregressive model of realized volatility (HAR-RV) and its extensions. We present several interesting and notable findings. First, existing models exhibit significant nonlinearity and clustering, which provide empirical evidence on the benefit of introducing regime switching and heteroscedasticity. Second, out-of-sample results indicate that combining regime switching and heteroscedasticity can substantially improve predictive power from a statistical viewpoint. More specifically, our proposed models generally exhibit higher forecasting accuracy. Third, these results are widely consistent across a variety of robustness tests such as different forecasting windows, forecasting models, realized measures, and stock markets. Consequently, this study sheds new light on forecasting future volatility.