Abstract:This paper proposes a cluster HAR-type model that adopts the hierarchical clustering technique to form the cascade of heterogeneous volatility components. In contrast to the conventional HAR-type models, the proposed cluster models are based on the relevant lagged volatilities selected by the cluster group Lasso. Our simulation evidence suggests that the cluster group Lasso dominates other alternatives in terms of variable screening and that the cluster HAR serves as the top performer in forecasting the future realized volatility. The forecasting superiority of the cluster models are also demonstrated in an empirical application where the highest forecasting accuracy tends to be achieved by separating the jumps from the continuous sample path volatility process. (C) 2019 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.

Abstract:The literature offers various explanations to either support or refute the Ang et al. (2009) high idiosyncratic volatility low return puzzle. Fu (2006) finds a significantly positive contemporaneous relation between return and exponential generalized autoregressive conditional heteroskedastic idiosyncratic volatility. We use corporate hedging to shed light on this puzzle. Conceptually, idiosyncratic volatility matters to investors who face limits to diversification. But limits to diversification become less relevant for firms that consistently hedge. We confirm the main finding in Fu (2009), but only for firms that do not consistently hedge. For firms that adopt a consistent hedging policy, idiosyncratic volatility, whether contemporaneous or lagged, is insignificant in Fama-MacBeth regressions, controlling for size, book-to-market, momentum, liquidity, and industry effects.

Abstract:This paper examines the fractional cointegration between downside (upside) components of realized and implied variances. A positive association is found between the strength of their cofractional relation and the return predictability of their differences. That association is established via the common long-memory component of the variances that are fractionally cointegrated, which represents the volatility-of-volatility factor that determines the variance premium. Our results indicate that market fears play a critical role not only in driving the long-run equilibrium relationship between implied-realized variances but also in understanding the return predictability. A simulation study further verifies these claims.

Abstract:Different from studies that use rough proxies for aggregate accounting information quality to investigate its impact on investment efficiency, we construct a project-level measure of disclosures pertaining specifically to firms' ongoing and future investments, using a large sample of Chinese listed firms. We first validate this measurement of project-level investment disclosure, finding that more detailed investment disclosures are associated with stronger market reactions, particularly among strong-governance firms. Furthermore, we find that project-level disclosure is associated with higher future investment efficiency for strong-governance firms, but not for weak-governance firms. Investigations into underlying channels reveal that well-governed firms with more investment disclosures face less financial constraints and are more likely to abandon poorly performing investments. Cross-sectional analyses suggest that project-level disclosure and governance play a more important role in settings where firms have stronger incentives for opportunistic disclosure. Overall, our evidence indicates that project-level disclosure interacts with corporate governance to impact investment efficiency. The results have implications for disclosure regulation and practice.

Abstract:Using a new weekly blue-chip index, this article investigates the causes of stock price movements on the London market between 1823 and 1870. We find that economic fundamentals explain about 15 per cent of weekly and 34 per cent of monthly variation in share prices. Contemporary press reporting from the London Stock Exchange is used to ascertain what market participants thought was causing the largest movements on the market. The vast majority of large movements were attributed by the press to geopolitical, monetary, railway-sector, and financial-crisis news. Investigating the stock price changes on an independent list of events reaffirms these findings, suggesting that the most important specific events that moved markets were wars involving European powers.

Abstract:We develop a Bayesian network (LASSO-BN) model for firm bankruptcy prediction. We select financial ratios via the Least Absolute Shrinkage Selection Operator (LASSO), establish the BN topology, and estimate model parameters. Our empirical results, based on 32,344 US firms from 1961-2018, show that the LASSO-BN model outperforms most alternative methods except the deep neural network. Crucially, the model provides a clear interpretation of its internal functionality by describing the logic of how conditional default probabilities are obtained from selected variables. Thus our model represents a major step towards interpretable machine learning models with strong performance and is relevant to investors and policymakers.

Abstract:Why do firms pay dividends? To answer this question, we use a hand-collected data set of companies traded on the London stock market between 1825 and 1870. As tax rates were effectively zero, the capital market was unregulated, and there were no institutional stockholders, we can rule out these potential determinants ex ante. We find that, even though they were legal, share repurchases were not used by firms to return cash to shareholders. Instead, our evidence provides support for the information-communication explanation for dividends, while providing little support for agency, illiquidity, catering, or behavioral explanations.

Abstract:This paper examines whether rookie independent directors (RIDs) have an effect on corporate fraud in Chinese public companies. In firm-level analysis, we find that the presence of RIDs increases the likelihood of corporate fraud. In director-level analysis, we reveal that rookie independent directors are less likely to dissent using the voting records collected from company announcements. And the cost of dissension for RIDs is the higher likelihood of losing current board seats, compared with seasoned independent directors. Our results are robust to alternative variables about the existence of RIDs, the IV approach and the conditional model.

Abstract:We use DCC-TGARCH-M to study asymmetries in the conditional variance in FTSE100 spot and futures returns before and after cost-reducing market microstructure changes on the London Stock Exchange and the London International Financial Futures Exchange. We find bidirectional causality-in-mean and that negative shocks have a larger impact on the conditional variances than positive shocks. There is little evidence of causality-invariance. The results support a risk premium explanation of asymmetric volatility before the microstructure changes; afterwards, there is evidence of a risk premium effect in futures but a momentum effect in spot. Following the microstructure changes, the speed at which the markets absorbed news increased, as did the asymmetric volatility effect of bad news. We also document regular temporary declines in the conditional correlations following contract expiration. This is consistent with the increased uncertainty following expiration, when investors' attention switches to the next near contract, and the no-arbitrage linkage between spot and futures is temporarily reduced. (C) 2012 Elsevier Inc. All rights reserved.