Surprise vs anticipated information announcements: Are prices affected differently? An investigation in the context of stock splits

We compare the long run reaction to anticipated and surprise information announcements using stock splits. Although there is underreaction in both cases, anticipated splits are treated differently to those that are unforeseen. After anticipated splits, cumulative abnormal returns peak at one-and-a-half times the level observed after unanticipated splits although the time taken for the announcement to be absorbed into prices is the same. We explain the difference in underreaction by the degree to which split announcements are believed and hence invested in. The favorable signal conveyed in forecast splits is more credible owing to their better pre-split performance, resulting in a far more pronounced underreaction effect.     

A test of a disequilibrium model

It is shown that an equilibrium model can be written as a nested hypothesis of a disequilibrium model in the sense that the former restricts parameter variations over time. It is then suggested to use the stability tests proposed in the literature for the test of a disequilibrium hypothesis. Fair's (1972) monthly housing market model is used for an empirical illustration, and a sampling experiment is also conducted.     

When higher prices increase sales: How chronic and manipulated desires for conspicuousness and rarity moderate price's impact on choice of luxury brands

This study examines the impact of low, medium, and high prices on luxury brand choices by consumers very high versus very low in chronic desire for conspicuousness (CC) on selection of a luxury brand, namely, as well as the combination of very high versus very low chronic desire for rarity (CR). The research design tests and confirms the nomological validity of a system of relationships among chronic and manipulated conditions. High versus low manipulated desire for conspicuousness (MC) and manipulated desire for rarity (MR) conjoined with high versus low chronic desire for conspicuousness (CC) and chronic desire for rarity (CR) moderates the typically hypothesized negative main effect of price on demand and may cause a positive main effect of price on luxury brand choice across a relevant range of price-points. These findings confirm the applied theory that for some consumers, chronic psychological states in combination with manipulated related states allow for—perhaps demand that—merchants to charge higher prices to increase sales of luxury brands.     

The Dynamics of Appraisal Smoothing

We investigate the dynamics of appraisal smoothing in the National Council of Real Estate Investment Fiduciaries (NCREIF) index return using time‐varying asset pricing models. We find that smoothing is on average close to zero but varies substantially over time. From the inception of the NCREIF index in 1978 until the mid‐1990s, there was little evidence of smoothing. Smoothing has increased significantly since the mid‐1990s to the end of 2010. Smoothing increases when property prices or uncertainty increases. However, it decreases when sentiment in the property market is high or during recession periods. The substantial variation in the level of smoothing indicates that the volatility of unsmoothed appraisal‐based property returns would be significantly over‐ or under‐estimated for different periods if unsmoothed with a long‐run average smoothing.     

Forecasting forward defaults: a simple hazard model with competing risks

A forward default prediction method based on the discrete-time competing risk hazard model (DCRHM) is proposed. The proposed model is developed from the discrete-time hazard model (DHM) by replacing the binary response data in DHM with the multinomial response data, and thus allowing the firms exiting public markets for different causes to have different effects on forward default prediction. We show that DCRHM is a reliable and efficient model for forward default prediction through maximum likelihood analysis. We use actual panel data-sets to illustrate the proposed methodology. Using an expanding rolling window approach, our empirical results statistically confirm that DCRHM has better and more robust out-of-sample performance than DHM, in the sense of yielding more accurate predicted number of forward defaults. Thus, DCRHM is a useful alternative for studying forward default losses on portfolios.     

Capital Market Openness and Output Volatility

In this paper, using data from 21 advanced and 81 developing countries during 1971–2010, we empirically examine the impact of capital market openness on output volatility. We find that opening of capital markets increases the output volatility of developing countries. Furthermore, we find that the main channel through which capital market openness increases volatility is currency and external‐debt crisis. Finally, we find that while Asian countries are less likely to experience a crisis, they become even more unstable than other developing countries once a crisis occurs. Our evidence strengthens the case for caution in developing countries' opening up of their capital markets.     

Predicting Recurrent Financial Distresses with Autocorrelation Structure: An Empirical Analysis from an Emerging Market

The dynamic logit model (DLM) with autocorrelation structure (Liang and Zeger Biometrika 73:13–22, 1986) is proposed as a model for predicting recurrent financial distresses. This model has been applied in many examples to analyze repeated binary data due to its simplicity in computation and formulation. We illustrate the proposed model using three different panel datasets of Taiwan industrial firms. These datasets are based on the well-known predictors in Altman (J Financ 23:589–609, 1968), Campbell et al. (J Financ 62:2899–2939, 2008), and Shumway (J Bus 74:101–124, 2001). To account for the correlations among the observations from the same firm, we consider two different autocorrelation structures: exchangeable and first-order autoregressive (AR1). The prediction models including the DLM with independent structure, the DLM with exchangeable structure, and the DLM with AR1 structure are separately applied to each of these datasets. Using an expanding rolling window approach, the empirical results show that for each of the three datasets, the DLM with AR1 structure yields the most accurate firm-by-firm financial-distress probabilities in out-of-sample analysis among the three models. Thus, it is a useful alternative for studying credit losses in portfolios.     

Nondisclosure and adverse disclosure as signals of firm value

We present a model in which some of the firm's information ('news')can be disclosed verifiably and some information ('type') cannot,to show that some firms may voluntarily withhold good news anddisclose bad news. We describe an equilibrium in which high-typefirms withhold good news and disclose bad news, whereas low-typefirms disclose good news and withhold bad news. Under some parametervalues, this equilibrium exists when other more traditionalequilibria are ruled out by standard equilibrium refinements.The model explains some otherwise anomalous empirical evidenceconcerning stock price reactions to disclosure, provides somenew empirical predictions, and suggests that mandatory disclosurerequirements may have the undesirable consequence of makingit more difficult for firms to reveal information that cannotbe disclosed credibly.