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Research on price extremes and overreactions as potential violations of market efficiency has a long tradition in investment literature. Arguably, very few studies to date have addressed this issue in cryptocurrencies trading. The purpose of this paper is to consider the extreme value modelling for forecasting COVID-19 effects on cryptocoin markets. Additionally, this paper examines the importance of technical trading indicators in predicting the extreme price behaviour of cryptocurrencies.

This paper decomposes the daily-time series returns of four cryptocurrency returns into potential maximum gains (PMGs) and potential maximum losses (PMLs) at first and then tests their lead–lag relations under an econometric framework. This paper also investigates the non-random properties of cryptocoins by computing the incremental explanatory power of PML–PMG modelling with technical trading indicators controlled. Besides, this paper executes an event study to identify significant changes caused by COVID-19-related events, which is capable of analysing the cryptocoin market overreactions.

The findings of this paper produce the evidence of both market overreactions and trend persistence in the potential gains and losses from coins trading. Extreme price behaviour explains volatility and price trends in crypto markets before and after the outbreak of a pandemic that substantiate the non-random walk behaviour of crypto returns. The presence of technical trading indicators as control variables in the extreme value regressions significantly improves the predictive power of models. COVID-19 crisis affects the market efficiency of cryptocurrencies that improves the usefulness of extreme value predictions with technical analysis.

This paper strongly supports for the robustness of technical trading strategies in cryptocurrency markets. However, the “beast is moving quick” and uncertainty as to the new normalcy about the post-COVID-19 world puts constraint on making best predictions.

The paper contributes substantially to our understanding of the pricing efficiency of cryptocurrency markets after the COVID-19 outbreak. The findings of continuing return predictability and price volatility during COVID-19 show that profitable investment opportunities for cryptocoin traders are prevailing in pandemic times.

The paper is unique to understand extreme return reversals behaviour of cryptocurrency markets regarding events related to COVID-19 breakout.

Equity research in experimental psychology reveals investors' overreactions to bad news events. This study of asymmetric price structures in equity markets investigates whether such behavior predicts stock returns in an emerging market of India.

The research decomposes Bombay Stock Exchange (BSE) Sensex returns into Extremely Positive Returns (EPR) and Extremely Negative Returns (ENR) based on extreme values at first and then tests their lead–lag relations.

The empirical finding is consistent with the existing evidence of asymmetric news effects on stock returns in India. In precise, ENR robustly predicts one-month-ahead EPR for the sample period from January 1991 to March 2020. This predictive power persists even in the presence of popular valuation ratios and business cycle variables.

The paper explains the rationale of extreme value modeling in price forecasting. Investors can find additional utility gains from market cycle information while predicting extreme returns in Indian stock market.

The paper is unique to understand business cycle effects in extreme return reversals in emerging markets.

Purpose – The purpose of this chapter is to investigate the relationship between emotion and European energy forward prices of oil, gas, coal and electricity during normal times and periods of extreme price movements.

Methodology/Approach – We use a biorhythm approach characterized by the seasonal affective disorder (SAD) variable to study the impact of emotion on energy markets. Normal times and periods of extreme price movements are approximated by OLS and quantile estimations, respectively.

Findings – We use European energy forward prices of oil, gas, coal, and electricity. European equity future index (Dow Jones Euro Stoxx 50) and euro/dollar US exchange rate are used as control variables for economic and financial environment. Estimating OLS and quantile regressions, we find that seasonal patterns have a significant impact during extreme volatility periods only. Further investigations reveal that the SAD effect is significant during periods of price decrease, but insignificant during price increase times. The out-of-sample predictive ability properties show that our “SAD model” outperforms significantly the pure “macroeconomic” one.

Originality/Value of chapter – This topic is novel in energy finance since I use psychological background theory to understand energy price dynamics. I illustrate the relevance of our approach by comparing the out-of-sample predictive ability of our model against macroeconomic one. My results could be considered to improve energy porfolio allocation.

This study examines the impact of the Russo-Ukrainian War on the commodity markets of oil, wheat, and natural gas, in which these two countries play/have a dominant role. The author examines if during these extreme events an anti-leverage effect emerges and indicates the abnormal conditions of the markets.

The author uses daily returns from the future prices of brent oil, wheat, and natural gas for the period 31.3.2020–31.3.2022 and applies the exponential and the threshold asymmetry GARCH models.

The empirical findings confirm the existence of anti-leverage effect in the wheat and natural gas commodity markets and point to the existence of the leverage effect in the Brent market.

The existence of the anti-leverage effect means that stock prices and volatility present a positive relationship which is in contrast to the normal/conventional stylized facts which suggest the opposite. These findings could be useful for scholars and practitioners because they enable them to examine market abnormalities using the anti-leverage effect as a criterion and explore its relationship with extreme conditions and strategies that lead to skyrocketing increases in prices.

This study investigates the anti-leverage effect in commodity markets under extreme conditions, which has received little attention in the literature. Moreover, this paper links the existence of the anti-leverage effect with abnormal growth in asset prices, which shows a new direction for the behavior of assets when extreme conditions emerge.

This study aims to assess the contemporaneous dependence between euro, crude oil and gold returns and their respective implied volatility changes.

The empirical analysis relies on daily data for the period 2015–2022 and the local Gaussian correlation (LGC) approach that is suitable for estimating dependence between two stochastic processes at any point of their joint distribution.

(a) The global correlation coefficients are negative for the euro and crude oil and positive for gold, implying that in the first two markets’ traders are more concerned with sudden price downswings while in the third with sudden upswings. (b) The detailed local analysis, however, shows that traders 2019 attitudes may change with the underlying state of the market and that risk reversals are more likely to occur at the upper extremes of the joint distributions. (c) The pattern of dependence between price returns and implied volatility changes is asymmetric.

To the best of the author’s knowledge, this is the first work that uses the highly flexible LGC approach to analyze the link between price returns and implied volatility changes either in stock or in commodities futures markets. The empirical results provide useful insights into traders’ risk attitudes in different market states.

This study disentangles the investor-base effect and the information effect of investor attention. The former leads to a larger investor base and higher stock returns, while the latter facilitates the dissemination of information among investors and impacts informational trading.

Using positive volume shocks as a proxy for increased investor attention, this study evaluates the impacts of the investor-base effect and the information effect of investor attention on market correction following extreme daily returns in the US stock market from 1966 to 2018.

This study finds that the investor-base effect increases subsequent returns of both daily winner and daily loser stocks. The information effect leads to economically less significant return reversals for both the daily winner and daily loser stocks. These two effects tend to have economically more significant impacts on the daily loser stocks. The economic significance of these two effects is also related to firm size and the state of the stock market.

This study is the first to disentangle the investor-base effect and the information effect of increased investor attention. The evidence that the information effect facilitates the dissemination of new information and impacts stock returns contributes to the strand of studies on the impact of investor attention on market efficiency. This evidence also contributes to the strand of studies analyzing the impact of informational trading on stock returns. In addition, this study provides evidence for market overreaction and the subsequent correction. The results for up and down markets contribute to the literature on the investors' trading behavior.

The purpose of this paper is to study the pricing efficiency of convertible bonds and arbitrage opportunities between the convertible bonds and the underlying stocks thus improve market efficiency.

Using nonparametric fixed effect panel data model, the authors build pricing model of convertible bonds and obtain fitted value for them. Then the authors constructs simultaneous confidence band for the smooth function to identify mispricing and study the pricing efficiency and arbitrage opportunities of convertible bonds.

Result shows, convertible bonds’ prices largely depend on stock prices. Pricing efficiency does not improve during the past few years as there are quite a few trading opportunities. Arbitrage opportunities increase as the stock prices approach it maxima, and selling opportunities for convertible bonds surpass buying opportunities which indicates that investors use market neutral strategies to arbitrage. Pricing efficiencies varies a lot and it is affected by the features of the stocks and convertible bonds. Index stocks eligible for margin trading with high liquidity enjoy higher pricing efficiency.

The study does not take into account trading cost and risk management measures.

Arbitrage between the underlying and the convertible bonds is profitable and contributes to pricing efficiency therefore should be encouraged. The regulator should pay attention to the extreme mispricing of the underlying and convertible bonds which cannot be corrected by the market as there might be manipulation.

Since traditional pricing methods are based on the framework of non-arbitrage equilibrium with the assumption of balanced and perfect market, there are many restrictions in the pricing process and the practical utility is somewhat limited, and the impractical assumptions lead to model risk. This study uses nonparametric regression to study the pricing of convertible bonds thus circumvents the problem of model risk. Simultaneous confidence band for smooth function identifies mispricing and explicitly reflects the variation of pricing efficiency as well as signalizes trading opportunities. Application of nonparametric regression and simultaneous confidence band in derivative pricing is advantageous in accuracy and simplicity.

The membership in the European Union (EU) affected price perceptions of citizens in many European countries at the beginning of 2002. How did the transition from the national currency to the Euro, the new single currency of EU, actually take place? Examines the confusion among Finnish consumers concerning internal reference prices in different product and service categories immediately after the transition to the Euro. Proposes tentatively and empirically tests a framework model. Provides the relationships between the paper's key constructs of consumer price perception and some attitudinal and behavioral variables shortly after transition to Euro currency. Basically price perception took place in similar way, when Markka and Euro scales were utilized. This result was shown, first, by analyzing price perception strategies of consumers, and, second, by showing with correlation analysis that as internal reference price increases, the width of price latitude increases, and, third, by modelling reference price perception on the basis of Volkmann's range theory. Money illusion effect was found to exist to some extent.

The purpose of this paper is to examine the investment behavior of Pakistani stock market participants, specifically with respect to their tendency to exhibit herd behavior.

The study employed two different methodologies suggested by Christie and Huang (1995) and Chang et al. (2000) to test herd formation. Results are based on daily and monthly stock of KSE-100 index for the period 2002-2007.

Results based on daily and monthly stock data from Karachi Stock Exchange indicate the non-existence of herd behavior for the period 2002-2007 and find no support for the rational asset pricing model and investor behavior found inefficient. This study denied proved evidence of herding due to market return asymmetry, high and low trading volume states and asymmetric market volatility. Macroeconomic fundamentals have insignificant role in decision-making process of investor therefore has no impact on herding behavior. However, during liquidity crisis of March 2005, Pakistani stock market exhibit herding behavior due to asymmetry of information among investors, presence of speculator and questionable badla financing-local leverage financing mechanism.

In future, this study can be improved by employing stock returns portfolios based on market capitalization or sector wise portfolio returns from KSE-100. Furthermore by identifying those factors that cause market to be overall inefficient and define the pattern of the investor trading activities.

For an accurate valuation of assets investors should incorporate the herding factor.

As the assets are mispriced, investor behavior is uncertain and markets are inefficient, foreign investors should invest with caution, as large numbers of securities are needed to achieve the same level of diversification than in an otherwise normal market.

In Karachi Stock Exchange, it is first attempt to uncover the herding behavior. This paper contribute to the body of knowledge by investigating the herding behavior in the emerging markets since most of the previous study concentrate more on the developed markets. Furthermore, the study also analyzed the herding behavior in different economic condition and includes economic variables and examines asymmetric effect. This study presents an integrated model to test herding behavior in Pakistani equity market. Consideration of said behavioral effect in the decision-making process of investor will make the decisions more rational and optimal.

This study aims to investigate the relationship between oil prices and stock returns of renewable energy firms in India under different market conditions.

The authors use the panel quantile framework with Fama–French–Carhart’s (1997) four-factor asset pricing model. All renewable energy firms listed in the National Stock Exchange of India are considered in this study. Three oil prices, such as West Texas Intermediate spot price, Europe Brent oil price and Indian basket oil price, are used in the regression. The analysis is done for the whole sample and its subgroups.

In the whole sample, stock returns of renewable energy firms respond positively to oil price changes in extreme market conditions only. In the subgroups of the renewable energy firms, the relationship between stock returns and oil price is positive and more robust in higher quantiles across all subgroup firms.

The contribution of the study is explained as follows. First, this study helps to explore the relationship between oil and stock returns of the renewable energy sector under different market conditions in the Indian context. Second, existing studies explore the effect of oil prices on stock returns of the renewable energy sector at the industry level, and most of the studies are in developed countries. To the best of the authors’ knowledge, this is the first study in the context of India. Third, this is a firm-level study