What do we know about the second moment of financial markets?

Recent research shows that the vast majority of scientific studies published in leading finance journals fails scientific replication (Hou, Xue, and Zhang, 2020; Harvey, Liu, and Zhu; 2016). This study argues that p-hacking, publication pressure and the selection bias from leading finance journals are perhaps not the underlying root cause for this issue. This study shows that standard methodologies often used in finance research are inevitably sample-specific due to the very nature of financial markets. While the consensus of earlier research postulates a rejection of the time-honored Levy hypothesis, the results of this study strongly indicate that the variance of variance does not exist in any of the financial key markets that are considered. An unexpected finding of this study is that the variance process governing the U.S. dollar foreign exchange rate market is generating more extreme events than the Bitcoin market. The results cast doubts on the validity of methodologies currently used in finance research.     

Oil price and stock market co-movement: What can we learn from time-scale approaches?

This paper study the relationship between oil and stock markets in G7 countries, by distinguishing between interactions based on fundamentals (long-term interdependence: high memory impact) and contagion (short-term interaction: transitory contamination). To do this, we propose in the first time two complementary frequency approaches based: the evolutionary co-spectral analysis and the wavelet approach allowing a time-varying measure of the dynamic correlation between the oil and stock markets over time and across time horizons. We find that interdependence between oil price and the stock market is more pronounced in the short and medium terms than in the long term. In addition, we prove that stock markets are more sensitive to oil shocks originating from demand shocks. These findings provide important policy implications for both policymakers, in terms of taking relevant actions regarding oil shocks originating from the demand side, and investors, in terms of a policy of diversification that depends on horizons.     

Fintech and banking: What do we know?

This paper is a review of the literature on fintech and its interaction with banking. Included in fintech are innovations in payment systems (including cryptocurrencies), credit markets (including P2P lending), and insurance, with Blockchain-assisted smart contracts playing a role. The paper provides a definition of fintech, examines some statistics and stylized facts, and then reviews the theoretical and empirical literature. The review is organized around four main research questions. The paper summarizes our knowledge on these questions and concludes with questions for future research.     

Credit risk and the business cycle: What do we know?

We perform a meta-regression analysis to characterize the relationship between ex post credit risk, measured through non-performing loans and real GDP growth. Although the prior empirical literature reveals a statistically significant inverse association, the precise effect of growth performance to credit quality diverges and remains subject to several qualifications. Using estimates from 56 studies and applying a Bayesian meta-regression analysis we explore the systematic patterns of the heterogeneity in the reported estimates. According to our evidence, the specification form as well as features related to the type of data, and the sample period are factors that systematically influence the estimated results.     

What do we know about the role of financial reporting in debt contracting and debt covenants?

The paper examines the role of financial reporting in debt contracting and in particular focuses on the definition, measurement, and monitoring of accounting-based covenants used to manage agency relationships arising from borrowing by firms. The paper also reviews research in areas of financial reporting where the presence of accounting-based covenants provides incentives to managers, notably choice of accounting method, lobbying on standard setters' proposals, and accounting earnings management. Although US dominated and latterly increasingly focused on large datasets and quantitative and analytical methods, relevant research is available from a range of methodologies and countries and the paper reflects this variety and identifies both inter-jurisdictional differences and inter-temporal changes in debt contracting practices. Despite the extensive research which is reviewed important areas for new research remain.     

Cryptocurrencies and stock market indices. Are they related?

In this paper, we investigate the stochastic properties of six major cryptocurrencies and their bilateral linkages with six stock market indices using fractional integration techniques. From the univariate analysis, we observe that for Bitcoin and Ethereum, the unit root null hypothesis cannot be rejected; for Litecoin, Ripple and Stellar, the order of integration is found to be significantly higher than 1; for Tether, however, we find evidence in favour of mean reversion. For the stock market indices, the results are more homogeneous and the unit root cannot be rejected in any of the series, with the exception of VIX where mean reversion is obtained. Concerning bivariate results within the cryptocurrencies and testing for cointegration, we provide evidence of no cointegration between the six cryptocurrencies. Along the same lines, testing for cointegration between the cryptocurrencies and the stock market indices, we find evidence of no cointegration, which implies that the cryptocurrencies are decoupled from the mainstream financial and economic assets. The findings in this paper indicate the significant role of cryptocurrencies in investor portfolios since they serve as a diversification option for investors, confirming that cryptocurrency is a new investment asset class.     

What do professional forecasters' stock market expectations tell us about herding,information extraction and beauty contests?

We study how professional forecasters form equity market expectations based on a new micro-level dataset which includes rich cross-sectional information about individual characteristics. We focus on testing whether agents rely on the beliefs of others, i.e., consensus expectations, when forming their own forecast. We find strong evidence that the average of all forecasters' beliefs influences an individual's own forecast. This effect is stronger for young and less experienced forecasters as well as forecasters whose pay depends more on performance relative to a benchmark. Further tests indicate that neither information extraction to incorporate dispersed private information, nor herding for reputational reasons can fully explain these results, leaving Keynes' beauty contest argument as a potential candidate for explaining forecaster behavior.     

When do investors gamble in the stock market?

Recent studies have uncovered gambling-motivated trading activities in financial markets in which investors seek lottery-type payoffs by using financial assets. Building on prospect theory, this study provides an important complement to prior research and investigates what period that investors make gambling-motivated trading in the stock market. Examining data from the Chinese stock market, investors are revealed to have asymmetric gambling preferences in gain and loss domains. Investors' gambling motivations are more easily triggered when the market is experiencing a loss. In such periods of time, investors may preferentially opt for lottery-type stocks that offer them a small chance to earn an extreme return at the risk of a likely small loss, simply due to their ‘aversion to a sure loss’.     

Which time-frequency domain dominates spillover in the Chinese energy stock market?

Previous studies detected the spillover relations among stocks and identified the spillover roles of stocks. However, due to the participants with different dealing frequencies, the spillover effects in the stock market present multiscale features, then which time-frequency domain dominates the spillover in the stock market? Take Chinese energy stocks as an example, this paper examines the return spillover effects of the energy stock market under each time-frequency domain. We find significant return spillover in the Chinese energy stock market under different time scales, and the spillover effect under the time scale of 32–64 days contributes the most to the spillover in the whole energy stock market. Then we take further research on the directional spillovers, spillovers between energy stocks and spillovers between energy industries to detect who plays leading positions under each time scale. We divide the stocks into four roles, and find that it is different role that plays a leading position under each time scale. Furthermore, a small number of spillover relationships between energy stocks carry a large part of the total spillover quantities, and coal and consumable fuel-related stocks play an important role in the spillover of Chinese energy stocks. The robustness of our results is proved by additional tests with different forecast horizons. Our paper contributes to the literature by examining the multiscale spillover effect in the Chinese energy stock market, which provides references for market participants on investment horizons choosing, stocks selection and risk aversion.     

Why do individuals not participate in the stock market?

We use a representative survey to study economic and non-economic factors that affect stock market participation. We find that many individuals suffer from inertia in the sense that they do not want to take the time and effort to invest in stocks. Inertia also explains stock market participation in addition to earlier documented factors such as actual and perceived financial literacy, trust, and the personal equity risk premium (PERP). A high percentage of non-investors (66%) assert that they will never invest in stocks. We find that inertia affects this assertion both directly and indirectly through factors such as age and gender.     

Why do companies delist voluntarily from the stock market?

We analyse the motives and market valuation of voluntarily delisting from the London Stock Exchange. We show that firms that delist voluntarily are likely to have come to the market to rebalance their leverage rather than to finance their growth opportunities. During their quotation life, their leverage and insider ownership remained very high, they did not raise equity capital, and their profitability, growth opportunities, and trading volume declined substantially. They also generate negative pre-event and announcement date excess returns. These results hold even after controlling for agency, asymmetric information, and liquidity effects, and suggest that firms delist voluntarily when they fail to benefit from listing. Overall, these firms destroyed shareholder value and they should not have come to the market.     

How does the stock market react to the announcement of green policies?

We investigate the impact of 19 announcements of environmental regulation on the equities listed on the Australian Stock Exchange over the period 2005–2011. Using a well-established event study methodology, we assess whether these announcements are value constructive or destructive for equity investors. Additionally, we estimate the change in systematic risk following the announcements. Our results show that the Australian market was particularly sensitive to the carbon pollution reduction scheme (CPRS) announcement. A cumulative abnormal return of −31% was recorded in the alternative energy sector after Australia submitted its target range to the Copenhagen Accord. We observe that a move towards a greener nation has a mixed effect on abnormal returns with apparent sector-by-sector differences. Green policies appear to affect the long-term systematic risk of industries, leading to the diamond risk phenomenon.     

What have we learnt about joint working between health and social care?

Joint working between local authorities and the National Health Service (NHS) has been an integral part of health and social care policy in the United Kingdom for many years. Using evidence from two literature reviews this paper argues that there is little indication that joint working delivers the outcomes envisaged in policy. While recent reforms may be beginning to influence improvements, they are undermined by constant reform and professional scepticism.     

Current account sustainability in the US: What did we really know about it?

We analyze the sustainability of the US current account (CA) deficit by means of unit-root tests. First, we argue that there are several reasons to believe that the CA may follow a non-linear mean-reversion behavior under the null of stationarity. Using a non-linear ESTAR model we can reject the null of non-stationarity favoring the sustainability hypothesis. Second, we ask whether unit-root tests are a useful indicator of sustainability by comparing in-sample results for the 1960–2004 period to the developments observed up to the end of 2008. We find that the non-linear model outperforms the linear and random walk models in terms of forecast performance. The large shocks to the CA observed in the last five years induced a faster speed of mean reversion, ensuring the necessary adjustment to meet the inter-temporal budget constraint.     

What should we know about momentum investing? The case of the Australian Security Exchange

This paper investigates Australian momentum strategies and their performance stability separately employing two samples a) the S&P/ASX 200 constituents and b) all market securities; for different time periods and market states. To avoid transaction intensive strategies, non-overlapping portfolios are employed. Results show that momentum performance is not sample specific and is positive in all cases, yet at varying magnitudes for different states and years. The profits are robust to univariate and multivariate risk considerations, seasonality (which is however present), and to different starting months.     

Stakeholders and the stock price crash risk: What matters in corporate social performance?

This study provides evidence for the differential impacts of corporate social responsibility (CSR) initiatives targeting different stakeholder groups on stock price crash risk. In particular, it highlights CSR's role in mitigating risk and creating shareholder value. Our results reveal that managerial bad news hoarding and the resultant stock crashes are largely determined by the social CSR dimension, and this effect is predominantly seen in undervalued firms. Moreover, social CSR subcategories aimed at specific stakeholder groups (such as the community, employees, or customers) tend to mitigate future crashes. In contrast, firms' environmental initiatives and governance characteristics seem to have trivial effects on stock crashes. Using a quasi-natural experiment, we find that the mitigating effect of social CSR dimension on crash risk is likely to be causal.     

Credit risk interconnectedness: What does the market really know?

We analyze the relation between market-based credit risk interconnectedness among banks during the crisis and the associated balance sheet linkages via funding and securities holdings. For identification, we use a proprietary dataset that has the funding positions of banks at the bank-to-bank level for 2006–2013 in conjunction with investments of banks at the security level and the credit register from Germany. We find asymmetries both cross-sectionally and over time: when banks face difficulties to raise funding, the interbank lending affects market-based bank interconnectedness. Moreover, banks with investments in securities related to troubled classes have a higher credit risk interconnectedness. Overall, our results suggest that market-based measures of interdependence can serve well as risk monitoring tools in the absence of disaggregated high-frequency bank fundamental data.     

Does the stock market affect firm investment in China? A price informativeness perspective

This paper investigates the empirical relationship between firm-level investment and the stock market in China from a price informativeness perspective. We find that firm investment does not significantly respond to the stock market valuation, because stock prices contain very little extra information about the future operating performance of firms. This finding is further supported by the relative investment response test and the relative price information content test based on the informativeness proxy of price non-synchronicity combined with firm information transparency.     

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.     

Does online interaction between firms and investors reduce stock price crash risk?

This paper examines how online interaction between firm management and investors impacts stock price crash risk. Based on the previous literature, we postulate that online interaction constrains crash risk via two channels, i.e., deterring bad news hoarding activities of managers and decreasing differences of opinion among investors. Relying on the launch of Hudongyi (the first official investor relations management platform in the world) for identification, we demonstrate that online firm-investor interaction significantly reduces future stock price crash risk and that these two channels can both explain this effect. Overall, our findings highlight the important role of online interaction in risk management.