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In this paper, the authors investigate the impact of the confirmation bias on returns, expectations and hedging of optimistic and pessimistic traders in the cryptocurrencies, commodities and stock markets before and during COVID-19 periods.

The authors investigate the impact of the confirmation bias on the estimated returns and the expectations of optimistic and pessimistic traders by employing the financial stochastic model with confirmation bias. Indeed, the authors compute the optimal portfolio weights, the optimal hedge ratios and the hedging effectiveness.

The authors find that without confirmation bias, during the two sub periods, the expectations of optimistic and pessimistic trader’s seem to convergence toward zero. However, when confirmation bias is particularly strong, the average distance between these two expectations are farer. The authors further show that, with and without confirmation bias, the optimal weights (the optimal hedge ratios) are found to be lower (higher) for all pairs of financial market during the COVID-19 period as compared to the pre-COVID-19 period. The authors also document that the stronger the confirmation bias is, the lower the optimal weight and the higher the optimal hedge ratio. Moreover, results reveal that the values of the optimal hedge ratio for optimistic and pessimistic traders affected or not by the confirmation bias are higher during the COVID-19 period compared to the estimates for the pre-COVID period and inversely for the optimal hedge ratios and the hedging effectiveness index. Indeed, either for optimists or pessimists, the presence of confirmation bias leads to higher optimal hedge ratio, higher optimal weights and higher hedging effectiveness index.

The findings of the study provided additional evidence for investors, portfolio managers and financial analysts to exploit confirmation bias to make an optimal portfolio allocation especially during COVID-19 and non-COVID-19 periods. Moreover, the findings of this study might be useful for investors as they help them to make successful investment decision in potential hedging strategies.

First, this is the first scientific work that conducts a stochastic analysis about the impact of emotional biases on the estimated returns and the expectations of optimists and pessimists in cryptocurrency and commodity markets. Second, the originality of this study stems from the fact that the authors make a comparative analysis of hedging behavior across different markets and different periods with and without the impact of confirmation bias. Third, this paper pays attention to the impact of confirmation bias on the expectations and hedging behavior in cryptocurrencies and commodities markets in extremely stressful periods such as the recent COVID-19 pandemic.

The purpose of this paper is to find and describe some stylized facts for foreign exchange and stock market returns, which are explored using statistical methods.

Formal statistics for testing presence of autocorrelation, asymmetry, and other deviations from normality are applied. Dynamic correlations and different kernel estimations and approximations to the empirical distributions are also under scrutiny. Furthermore, dynamic analysis of mean, standard deviation, skewness and kurtosis are also performed to evaluate time‐varying properties in return distributions.

The findings include: different types of non‐normality in both markets, fat tails, excess furtosis, return clustering and unconditional time‐varying moments. Identifiable volatility cycles in both forex and stock markets are associated to common macro financial uncertainty events.

The paper is the first work of this type in Peru.

This paper seeks to examine the long‐run financial and return performance of UK companies which are grouped according to whether or not they have changed their dividends and earnings. Prior research has been conducted using US data and they are limited to extreme dividend changes such as dividend initiations and omissions. They have also arrived at contradicting results; some report a drift in performance, while others document evidence of mean reversion in performance. The current paper hopes to resolve this conflict using data for a large sample of UK firms which disclosed more general changes in dividends and earnings.

The aims of the paper are addressed using a stock market‐based study of share price performance and a detailed analysis of company performance based on financial ratios. These analyses are conducted from five years before to five years after the announcement of dividend/earnings news.

At the time of the announcements, share returns tend to be positive (negative) where companies have increased (decreased) the dividend and earnings. There is also evidence to suggest that the stock market has anticipated some of this news in the preceding 12 months. However, the dividend/earnings news does not appear to act as a signal of long‐term future company performance; companies which cut this dividend and reported lower earnings achieved the largest excess returns over the next five years. A similar mean‐revealing pattern existed in the financial ratios. Finally, most of the future long‐term share performance was attributable to the earnings rather than to the dividend news.

The main implication of this research is that current dividend/earnings news is not a good guide to future company performance. Indeed, it is these firms which cut their dividends along with reporting a reduction of earnings which achieve excellent results over a subsequent five‐year period. Of course, there are a number of limitations with the research; it draws on data from two previous studies, looks only at the UK and does not consider sophisticated models of investors' expectations with regard to dividend and earnings information.

The main contribution of this paper is the long‐run analysis of UK company performance following joint dividend‐earnings announcements. The analysis is comprehensive in that it considers both stock market performance as well as financial ratio performance for a period of up to five years following the dividend‐earnings news. Thus, it should be of interest to most UK investors as well as to financial managers with large quoted firms. Academics will also be interested in the results since they shed some light on an existing debate in the literature.

The purpose of the paper is to investigate the price interrelationship between the Taiwanese and US financial markets.

The trivariate GJR‐GARCH (1,1) model and event study were employed to investigate volatility asymmetry and overreaction phenomenon, respectively.

The empirical results show that return volatility reveals the asymmetric phenomenon, and the holding period returns on US index futures from the opening of the US index futures electronic trading to the opening of the Taiwanese stock market are an important reference for investors in the Taiwanese stock market. Additionally, the paper presents an overreaction of the Taiwan Stock Exchange Capitalization Weighted Stock Index to a drastic price rise of E‐min NASDAQ 100 Index futures at the opening of the Taiwanese stock market.

This paper deletes the observations arising from the different national holidays of the USA and Taiwan, to have the same number of observations in both markets, which might contaminate the empirical results.

Investors in the Taiwanese stock market tend to pay more attention to the fluctuations in the share prices of high‐technological companies in the USA.

Most of the previous studies regarding price transmission between the Taiwanese and US stock markets focused mainly on the Taiwanese market reactions to the overnight returns of the US market. This paper enlarges the current field by examining the lead‐lag relationship, the volatility asymmetry, and the overreaction phenomenon between the Taiwanese and US financial markets according to the most updated US stock index information.

Investment advisors play a significant role in financial markets, yet the determinants of their behavior have not been explored in detail. The purpose of this paper is to explore the determinants of how actively advisors communicate about sustainable investing with their clients, and differences in the preferences of advisors compared to investors.

Based on a survey with 296 retail and private banking investment advisors, this study employs an ordinary least squares regression model to explore the determinants of advisors activity in communicating about sustainable investing (SI) with their clients, differences in the aspects that matter to advisors and investors, and the role of the complexity of sustainability.

Advisors activity in communicating about SI relates to their expectation of SI regarding financial return, real-world impact, and the fuzziness and trustworthiness of SI. Advisors appear not to be influenced by expected risk and their personal values, which runs against prior research findings and the interest of investors.

Future research should assess cultural differences and explore asymmetries between advisors and investors in regard to the role of volatility, values, impact measurement, and complexity.

Investment advisors underweighting aspects related to risk and self-transcendent values relative to their clients might limit the suitability of clients ' portfolios, skew capital allocation, and depress the role of SI in financial markets. Generalized to salespeople this behavior might depress the market success of products related to sustainability at large.

The findings and their generalization indicate that salespeople might systematically deviate from their clients’ interests in regard to social responsibility. Advisors and salespeople in their mediating role might be an important barrier to sustainable development.

This is the first quantitative study that explores the decision-making by investment advisors in the context of SI, and as such answers to specific calls in literature to explore the micro-foundations of decision making in regard to SI and social responsibility, and on the relationship between private investors and investment advisors. This study is based on unique and original empirical data on advisors that work with retail and wealthy private investors.

This chapter considers financial instability as a phenomenon endogenous to the functioning of capitalism. Consequently, it seeks to identify the main sources and different forms of the latter in financialised capitalism. According to Keynes, capital assets prices are conceived as the expression of financial conventions. It is, therefore, important to distinguish between the returns expected by company directors, bankers, holders of equity titles, risk-takers and, in contrast, risk-averse holders of debt securities. Minsky enriches the analysis by attributing a decisive role to the leverage effect, at the origin of an accumulation of financial weaknesses in the balance sheets of non-financial agents during the expansion phases preceding financial crises. Regulation theory leads to the introduction of a distinction between the financial accelerator and the leverage effect. The first establishes a procyclical relationship at the macroeconomic level between the price of capital assets and the debt ratio of non-financial agents; the second acts at the microeconomic level through shareholder corporate governance, which determines the institutional conditions inciting firm directors to integrate shareholder expectations into their return forecasts. The empirical analysis identifies three forms of financial instability in financialised capitalism: the long-term financial cycle governed by the debt ratio of non-financial agents; the business cycle governed by the impact of stock prices on investment; and the short-term or even very short-term expected return revisions of financial actors. Its originality is to show that these three forms of instability acquire different characteristics depending on the national economy considered.

The purpose of this paper is to explore the impact of institutional trading on the market quality during the financial crisis and short sale ban.

The following methods was applied to discuss the total impact on market quality and efficiency of short sale ban in USA from 2001 to 2010. The author examined institutional ownership and breadth of ownership while performing a mean variance tests for changes in efficiency as well as multivariate analysis.

Analyzing USA, Standard and Poor’s 500 stocks the author find increase high-low volatility, realized volatility, effective spread and relative quoted spread during January 1, 2007 to December 31, 2010. Realized volatility increases for both small and large quantile stocks. High-low volatility increases for small quantile stocks and relative quoted spread increases for large quantile stocks. Comparing the percentage change between pre and climax period we find that large quantile stocks have a negative association between breadth of institutional ownership and returns and a positive relation high-low volatility, realized effective spread and quoted spread to returns.

The present paper is the first to discuss the total impact on market quality and efficiency of short sale ban in USA from 2001 to 2010. The author find a remarkable improvement in market efficiency (variance ratios) after the crisis period for small and non-financial stocks, while the price efficiency lost during the crisis period is more persistent for large and financial stocks.

The purpose of this paper is to empirically investigate the volatility spillover between the Chinese stock market, investor’s sentiment and oil market, specifically during the 2014‒2016 turmoil period.

This study used the daily and monthly China market price index, oil-price index and composite index of Chinese investor’s sentiment. The authors first use the DCC GARCH model in order to study the correlation between variables. Second, the authors use a continuous wavelet decomposition technique so as to capture both time- and frequency-varying features of co-movement variables. Finally, the authors examine the spillover effects by estimating the BEKK GARCH model.

The wavelet coherency results indicate a substantial co-movement between oil and Chinese stock markets in the periods of high volatility. BEKK GARCH model outcomes confirm this relation and report the noteworthy bidirectional transmission of volatility between oil market shocks and the Chinese investor’s sentiment, chiefly in the crisis period. These results support the behavioral theory of contagion and highlight that the Chinese investor’s sentiment is a channel through which shocks are transmitted between the oil and Chinese equity markets. Thus, these results are important for Chinese authorities that should monitor the investor’s sentiment to better control the interaction between financial and real markets.

This study makes three major contributions to the existing literature. First, it pays attention to the recent 2015 Chinese stock market bumble. Second, it has gone some way toward enhancing our understanding of the volatility spillover between the investor’s sentiment, investor’s sentiment variation, oil prices and stock market returns (variables of interest) during oil and stock market crises. Third, it uses the continuous wavelet decomposition technique since it reveals the linkage between variables of interest at different time horizons.

This paper offers a framework for understanding the financial system using Marx’s theory of value. It examines how to interpret the Marxist concepts of the rate of profit and fictitious capital when analysing the financial sector, showing how accounting terms such as ‘return on equity’ and ‘leverage’ can also be understood in this context. The analysis argues that the capitalist system’s rate of profit should be conceptualised in a way that includes finance, but that one should not mix up the accumulation of financial assets with the accumulation of advanced capital. While the costs of finance are negative for the system’s average rate of profit, the paper concludes by noting how this is not inconsistent with financial operations being very profitable for imperialist powers that can use the financial system to appropriate surplus value from elsewhere in the global economy.

This paper aims to examine the impact of the daily growth rate of COVID-19 cases in the USA (COVIDg), the Federal Fund Rate (FFR) and the trade-weighted US dollar index (USDX) on S&P500 index daily returns and its 11 constituent sectors’ indices for the time period between January 22, 2020, until June 30, 2020.

The study uses the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) model to gauge the impacts over the whole period of study, as well as over two sub-periods; first, January 22, 2020, until March 30, 2020, reflecting uncertainty in the US markets and second, from April 1, 2020, until June 30, 2020, reflecting the lockdown.

Results of the MGARCH model reveal a negative and significant relation between COVIDg and S&P500 index daily returns over the first sub-period and the whole study period in the following sectors, namely, communications, consumer discretionary, consumer staples, health, technology and materials. Yet, COVIDg showed a positive and significant relation with S&P500 index daily returns during the second time period in the following sectors, namely, communication, consumer discretionary, financial, industrial, information technology (IT) and utilities. Besides, USDX showed a negative significant effect on S&P500 index daily returns and on the daily return on each of its 11 constituent sectors over the second sub-period and the whole period. Further, FFR showed a significant effect only in the second sub-period, specifically, a negative effect on the daily return of the financial sector and a positive effect on the daily return of the technology sector index. Nevertheless, FFR had a positive significant effect on the daily return of the utilities sector index for the whole period under study.

The impact of the crisis on the S&P500 index can be assessed only with some limitations owing to available global data and the limited time frame of the lock-down.

The study proposes supporting a smooth, functioning and resilient financial system; increasing fiscal measures by the US Government to increase liquidity on constraints; measures by The Federal Reserve to alleviate US dollar funding shortages; support market integrity; ensure continuous transparency and sharing of information; support the health sector, as well as consumer-based sectors that faced demand shocks and facilitate investments in the technology sector.

The originality of this paper lies in the examination of the impact of the novel COVID-19 pandemic on each of the 11 sectors constituting the S&P500 index separately, reflecting how the main economic sectors formulating the US economy reacted to the shock during the peak time of the pandemic to observe a full picture of the economic consequences amid the pandemic.