Is volatility clustering of asset returns asymmetric?

Volatility clustering is a well-known stylized feature of financial asset returns. This paper investigates asymmetric pattern in volatility clustering by employing a univariate copula approach of Chen and Fan (2006). Using daily realized kernel volatilities constructed from high frequency data from stock and foreign exchange markets, we find evidence that volatility clustering is highly nonlinear and strongly asymmetric in that clusters of high volatility occur more often than clusters of low volatility. To the best of our knowledge, this paper is the first one to address and uncover this phenomenon. In particular, the asymmetry in volatility clustering is found to be more pronounced in the stock markets than in the foreign exchange markets. Further, the volatility clusters are shown to remain persistent for over a month and asymmetric across different time periods. Our findings have important implications for risk management. A simulation study indicates that models which accommodate asymmetric volatility clustering can significantly improve the out-of-sample forecasts of Value-at-Risk.     

Does the choice of estimator matter when forecasting returns?

While the literature concerned with the predictability of stock returns is huge, surprisingly little is known when it comes to role of the choice of estimator of the predictive regression. Ideally, the choice of estimator should be rooted in the salient features of the data. In case of predictive regressions of returns there are at least three such features; (i) returns are heteroskedastic, (ii) predictors are persistent, and (iii) regression errors are correlated with predictor innovations. In this paper we examine if the accounting of these features in the estimation process has any bearing on our ability to forecast future returns. The results suggest that it does.     

Infrastructure spillovers and strategic interaction: does the size matter?

We set up a model in which the residents of two neighboring municipalities use the services provided by public infrastructures located in both jurisdictions. The outcome is that municipalities strategically interact when investing in infrastructures, with the small municipality reacting more to the expenditure of its neighbor than the big one. This theoretical prediction is tested by estimating the determinants of the stock of public infrastructures of the municipalities belonging to the Autonomous Province of Trento in Italy. By introducing the classical spatial lag-error component, we find that municipalities positively react to an increase in infrastructures by their neighbors, but the effect vanishes above a given population threshold. Such a result is confirmed when we exploit the exogenous variation in the neighbors’ stock of infrastructures induced by a strong flood that occurred in the Province of Trento in 2000.     

Do negative and positive equity returns share the same volatility dynamics?

This paper investigates whether positive and negative returns share the same dynamic volatility process. The well established stylized facts on volatility persistence and asymmetric effects are re-examined in light of such dichotomy. To analyze the dynamics of down and up volatilities estimated from daily returns I use a bivariate generalization of the standard EGARCH model. As a robustness check, I also investigate various specifications of down and up realized measures estimated from high-frequency data. The empirical findings point to the existence of a marked diversity in the volatilities of positive and negative daily returns in terms of persistence and sensitivity to good and bad news. A simple forecasting exercise highlights the striking performance of the proposed approach even during the crisis period.     

Developed markets’ business cycle dynamics and time-variation in emerging markets’ asset returns

This paper empirically studies the predictability of emerging markets’ stock returns by business cycle variables and the role of developed markets’ business cycle dynamics in this respect. The evidence shows that the link between business cycles and future stock market returns among emerging markets is considerably weaker than among developed markets. By contrast, I find strong evidence of stock return predictability by the respective country’s dividend-price ratio. This latter finding could reflect that variation in dividend-price ratios potentially reflects both the temporary impact of “hot money” inflows on emerging markets’ asset prices and rational expectations of future returns.     

Why does shareholder protection matter for abnormal returns after reported insider purchases and sales?

We use a unique data set of more than 240,000 reported insider transactions across 15 European countries and the USA to analyze the link between country-level shareholder protection and abnormal returns following insider trades. We show that abnormal returns after insider transactions are positively correlated with country-level shareholder protection against expropriation by corporate insiders, which supports the information-content hypothesis. Market reaction to insider purchases increases with shareholder protection because shareholder protection enhances the transparency and trustworthiness of insiders’ actions, and limits possibilities for direct profit diversion, so that more information is eventually reflected in stock prices. For insider sales, shareholder protection decreases their negative information content. We conjecture that this is due to the effect of greater transparency and trustworthiness strengthening the diversification and liquidity reasons for selling in better shareholder protection countries. We find limited support for the rent-extraction hypothesis that conjectures that shareholder protection is associated with insider trading dollar profits.     

The size and scope of government in the US states: does party ideology matter?

We investigate empirically how party ideology influences size and scope of government as measured by the size of government, tax structure and labor market regulation. Our dataset comprises 49 US states over the 1993–2009 period. We employ the new data on the ideological mapping of US legislatures by Shor and McCarty (Am. Polit. Sci. Rev. 105(3):530–551, 2011) that considers spatial and temporal differences in Democratic and Republican Party ideology. We distinguish between three types of divided government: overall divided government, proposal division and approval division. The main result suggests that Republican governors have been more active in deregulating labor markets. We find that ideology-induced policies were counteracted under overall divided government and proposal division.     

How does the choice of Value-at-Risk estimator influence asset allocation decisions?

Considering the growing need for managing financial risk, Value-at-Risk (VaR) prediction and portfolio optimisation with a focus on VaR have taken up an important role in banking and finance. Motivated by recent results showing that the choice of VaR estimator does not crucially influence decision-making in certain practical applications (e.g. in investment rankings), this study analyses the important question of how asset allocation decisions are affected when alternative VaR estimation methodologies are used. Focusing on the most popular, successful and conceptually different conditional VaR estimation techniques (i.e. historical simulation, peak over threshold method and quantile regression) and the flexible portfolio model of Campbell et al. [J. Banking Finance. 2001, 25(9), 1789–1804], we show in an empirical example and in a simulation study that these methods tend to deliver similar asset weights. In other words, optimal portfolio allocations appear to be not very sensitive to the choice of VaR estimator. This finding, which is robust in a variety of distributional environments and pre-whitening settings, supports the notion that, depending on the specific application, simple standard methods (i.e. historical simulation) used by many commercial banks do not necessarily have to be replaced by more complex approaches (based on, e.g. extreme value theory).     

Do asset impairments and the associated disclosures resolve uncertainty about future returns and reduce information asymmetry?

The objective of this study is to provide insights into how Australian listed firms are implementing AASB 136 Impairments of Assets. Our first concern is whether uncertainty about future returns and information asymmetry motivates the recognition of asset impairments. We find no evidence that the recognition of asset impairments is associated with higher uncertainty about future returns. Furthermore, we find no evidence that the recognition of asset impairments is associated with higher information asymmetry. Our second concern is whether asset impairments and the associated disclosures provide information that reduces uncertainty about future returns and information asymmetry. While we find some evidence that asset impairments are associated with decreases in information asymmetry before the financial crisis, during the financial crisis, asset impairments are associated with increases in both measurement uncertainty and information asymmetry.     

The relation between R&;D intensity and future market returns: does expensing versus capitalization matter?

The Australian accounting environment provides an ideal setting for examining the impact of different accounting treatments of firms’ R&D activities on their subsequent returns. Unlike US firms, which can only expense R&D, Australian GAAP permits firms to either expense or capitalize their R&D expenditure. We examine separately the market impact of the R&D intensity of all R&D active firms, ‘capitalizers’ and ‘expensers’. Our results suggest that firms with higher R&D intensity perform better, regardless of the accounting method used, consistent with the resource-based view of the firm. We also find some evidence that firms which expense R&D outperform those which capitalize R&D after controlling for R&D intensity.

When does the tone of earnings press releases matter?

The tone of a firm's financial disclosure is increasingly used as a variable in panel data regressions to predict future performance and explain investors' reaction at earnings announcement. We investigate when tone is informative, and argue that the informativeness of tone increases with the information asymmetry between firms and investors. Using a sample of over 50,000 earnings press releases of about 1800 U.S. public firms between 2004 and 2015, we find that firm growth, size, age, complexity and forecast inaccuracy are key drivers of tone informativeness. The effect is economically significant, since, compared to the reference case of a transparent firm, we find that the slope coefficient of tone doubles or even quadruples in panel data regressions when the firm operates in an environment with high information asymmetry.     

On the risk situation of financial conglomerates: does diversification matter?

In general, conglomeration leads to diversification of risk (the diversification benefit) and a decrease in shareholder value (the conglomerate discount). Diversification benefits in financial conglomerates are typically derived without explicitly accounting for reduced shareholder value. However, a comprehensive analysis requires competitive conditions within the conglomerate, i.e., shareholders and debt holders should receive risk-adequate returns on their investment. In this paper, we contribute to the literature on this topic by comparing the diversification effect in conglomerates with and without accounting for altered shareholder value. We derive results for a holding company, a parent-subsidiary structure, and an integrated model. In addition, we consider different types of capital and risk transfer instruments in the parent-subsidiary model, including intragroup retrocession and guarantees. We conclude that under competitive conditions, diversification does not matter to the extent frequently emphasized in the literature. The analysis contributes to the ongoing discussion on group solvency regulation and enterprise risk management, which is of relevance to insurance groups and other financial conglomerates.     

What does futures market interest tell us about the macroeconomy and asset prices?

Economists have traditionally viewed futures prices as fully informative about future economic activity and asset prices. We argue that open interest could be more informative than futures prices in the presence of hedging demand and limited risk absorption capacity in futures markets. We find that movements in open interest are highly pro-cyclical, correlated with both macroeconomic activity and movements in asset prices. Movements in commodity market interest predict commodity returns, bond returns, and movements in the short rate even after controlling for other known predictors. To a lesser degree, movements in open interest predict returns in currency, bond, and stock markets.     

Overvaluation and earnings management: Does the degree of overvaluation matter?

We examine whether the choice of earnings management strategies employed by managers of overvalued firms depends on the degree of market overvaluation. By distinguishing between substantially overvalued (SOV) and relatively overvalued (ROV) firms, we find that SOV firms significantly inflate earnings using both accruals-based and real earnings management. In contrast, managers of ROV firms do not engage in accruals-based earnings management and their firms’ accounts tend to report higher discretionary expenses. The reported higher discretionary expenses of ROV firms are comparable to the discretionary expenses of firms in the expanding stage of their business life cycle, a pattern consistent with ROV firms increasing discretionary expenses to finance growth and hence justify the high market valuation. Overall, we show that the existing evidence on income-increasing earnings management by overvalued firms is mainly driven by the pressure to sustain the high market valuation of firms that are substantially overvalued.     

Do industries matter in explaining stock returns and asset-pricing anomalies?

Industry returns cannot be explained fully by well-known asset pricing models. This study reveals that common factors extracted from industry returns carry significant risk premiums that go beyond the explanatory power of size, book-to-market (BM) ratios, and momentum. In particular, this study shows that (1) the small-firm effect is significant only for firms whose market capitalization is below their industry average; (2) the BM effect is an intra-industry phenomenon; (3) a one-year momentum effect is significant only for firms whose BM ratio is smaller than the industry average and limited to non-January months; and (4) there is seasonality in all effects that cannot be explained by risk-based asset-pricing models. Neither rational nor behavioral theories alone can explain industry returns, and it is perhaps too hasty to attribute asset pricing anomalies to a single driving force.     

Volatility dynamics of crypto-currencies’ returns: Evidence from asymmetric and long memory GARCH models

The objective of this paper is to select the most optimum model or set of models useful for modeling sixteen of the most popular crypto-currencies associated volatility. Five GARCH models, with different error distributions, are fitted to each of these crypto-currencies. The most effectively fit model or superior set of models is then selected through maximizing the likelihood and minimizing the AIC and BIC information criteria. The reached results prove that the majority of crypto-currencies turn out to be rather effectively modulated via the TGARCH with double exponential distribution. Indeed, the attained findings report an asymmetric effect whereby volatility turns out to increase rather by response to positive shocks than by response to negative shocks, implying an asymmetric effect that differs from that generally observed in stock markets. The increase in volatility, as emanating in response to positive shocks may well have its justification in the uninformed investors’ undertaken herding strategies.     

Mergers in the bond rating industry: does rating provider matter?

I examine whether investors favour bond ratings from established global agencies by analyzing the market response to Standard and Poor’s (S&P) acquisition of the Canadian Bond Rating Service (CBRS). As a result of the acquisition, CBRS ratings were completely eliminated and replaced with ratings from S&P. While little reaction was apparent for bonds, the stocks of firms with CBRS ratings responded positively to the acquisition announcement. Small firms and those with little institutional ownership experienced the greatest benefit. The findings suggest that ratings from S&P may increase the exposure of foreign firms to international investors.