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The main aim of this paper is to empirically test at market level, the investors' differential reaction to information, contribution of their confidence level and adaptive behaviour to excessive market volatility in Indian stock market.

The Bivariate Vector Autoregression and Impulse Response Analysis are used to study whether investors over/under-react to private and public information. EGARCH models are used to study the contribution of investors' over/under-confidence and adaptive behaviour to excessive market volatility.

The investors over-react to private information and under-react to public information during pre-crash period, become overconfident and contribute to excessive volatility. They under-react to both private and public information during after-crash period, become under-confident and also conform to adaptive market hypothesis (AMH).

The empirical results of the study can help investors to minimize the negative impact of over/under-confidence on their expected utility.

The investors shall perform a post-analysis of investment, become aware of their past behavioural mistakes and start adapting to changing market conditions. This shall move the markets towards a new equilibrium in long run thus conforming AMH. However, the investors sometimes display an apparently irrational behaviour during this process.

To the best of the author's knowledge, this is the first study at market level data examining investors' over/under-reaction, over/under-confidence and adaptive behaviour in the context of stock market crash.

This paper examines the effect of overconfident yield forecasting (optimism bias) on crop insurance coverage level choices across both yield and revenue insurance.

This study simulates a representative producer’s preferred coverage level for both yield and revenue insurance under three potential models of decision-making and four potential manifestations of overconfident yield forecasting. The study then uses this framework to examine how coverage level choices change as overconfidence increases (decreases).

As overconfidence increases, producers prefer lower levels of crop insurance coverage than they would otherwise prefer, with extreme overconfidence inducing farmers to buy no insurance at all. While overconfidence affects cross-coverage demand for revenue and yield insurance similarly, this effect is more pronounced for yield insurance. Cross-coverage level demand for revenue insurance is relatively stable across changes in the correlation between prices and yields.

This research has important implications for crop insurance subsidy design and crop insurance demand modeling.

There is a growing body of literature suggesting that producers are overconfident with regard to their future yield risk and that this bias reduces their willingness to pay for risk management tools such as crop insurance. This is the first study to look at how such overconfidence affects cross-coverage level demand for crop insurance.

Studies on consumer knowledge calibration have used different measures of calibration. The purpose of this paper is to undertake a comparative assessment of important measures. In addition, it seeks to identify the best performing measure.

The paper reports on three studies. The first study uses eight survey data sets. The second and third studies use experiments.

The study found that the Brier score component measure is most responsive to feedback and is the most suitable measure of knowledge calibration. The results also indicate that researchers should use measures that use item-level confidence judgements, as against an overall confidence judgement.

By documenting the relationship between the different measures of knowledge calibration, the study enables proper interpretation and accumulation of results of various studies that have used different measures. The study also provides guidance to researchers in psychology and education where this issue has been noted.

The study provides guidance to managers in knowledge intensive industries, such as finance and insurance, interested in understanding their consumers’ knowledge calibration.

This is the first study in consumer research that examines this issue.

This paper aims to revisit the issue of anchoring effects in real estate markets to consider the current dual-processing theory of mind.

The effects of high and low anchors in a price estimation task are, thus, explained by both Systems 1 and 2 as these play a key role in the guess of the “correct” list price. The authors also take into account the mediation of overconfidence in the estimates and how confidence relates to cognitive ability. Moreover, the authors nuance the field experiment by considering the decisions taken by professional real estate agents and amateur students alike because experts are expected to be less prone to cognitive biases.

The large anchoring index of 67 per cent found for the real estate agents suggests these professionals make their judgment unconsciously by priming (and thus, using their System 1), despite being overconfident. In contrast, an even larger anchoring index for the undergraduates (86 per cent) was found, as expected for nonexperts. However, the authors suggest the students’ judgments use their System 2 because they are clueless in their non-anchored estimates and, as result, consider the list prices as a heuristic to deliberately anchor and adjust.

Anchoring effects in real estate markets have not been approached so far by the dual-processing theory of mind.

In healthcare, overuse and underuse of medical treatments represent equally dangerous deviations from an optimal use equilibrium and arouse concerns about possible implications for patients’ health, and for the healthcare system in terms of both costs and access to medical care. Medical liability plays a dominant role among the elements that can affect these deviations. Therefore, a remarkable economic literature studies how medical decisions are influenced by different levels of liability. In particular, identifying the relation between liability and treatments selection, as well as disentangling the effect of liability from other incentives that might be in place, is a task for sound empirical research. Several studies have already tried to tackle this issue, but much more needs to be done. In this chapter, we offer an overview of the state of the art in the study of the relation between liability and treatments selection. First, we reason on the theoretical mechanisms underpinning the relationship under investigation by presenting the main empirical predictions of the related literature. Second, we provide a comprehensive summary of the existing empirical evidence and its main weaknesses. Finally, we conclude by offering guidelines for further research.

It has been argued in the literature that structural changes in the financial markets, such as integration, have the potential to cause herding behavior or correlated behavioral patterns in traders. The purpose of this study is to investigate whether there is any financial herding behavior in the Latin American Integrated Market (MILA), a transnational stock market composed of Chile, Peru, Colombia and Mexico stock exchanges and whether there is any ARCH or GARCH effect in the herding behavior models.

This study uses the modified return dispersion approach on daily index return data. The sample period is from January 03, 2002 to May 07, 2019. The data are obtained from the MILA database. To count time-varying volatilities in herding models, the authors run ARCH family regression with GARCH (1,1) settings. Hwang and Salmon (2004) model is used as a robustness test.

The authors found strong herding behavior under the general market conditions and moderate and partial herding behavior under some specified markets circumstances, such as bull and bear markets and high-low volatility states. Moreover, the pre-MILA period exhibits more herding behavior than the post-MILA period. The empirical results show that most of the ARCH and GARCH effects are statistically significant, implying that the past information of stock returns and market volatility significantly affect the volatility of following periods, which can also explain the formation of herding tendency among investors. Finally, the results of the robustness tests (Hwang and Salmon, 2004) confirm herding in all periods, except full sample period for Mexico and post-MILA period for Mexico and Colombia.

This study investigates the herding behavior in the MILA market in terms of market return, volatility and timing. A limitation of the paper is that the authors have not included other factors on the formation of herding behavior, such as macroeconomic factors, effects of regional or international markets and policy influences. The authors will explore the issue in the extension of the paper.

As MILA is the first virtual integration of stock exchanges without merging, the study provides useful findings and draws good inferences of herding behavior in the MILA market in terms of market return, volatility and timing which are useful for academics, investors and policymakers in their investment and decision makings.

The paper provides useful findings and draws good inferences of herding behavior in the MILA market in terms of market return, volatility and timing which are not only useful in practical implications, but also in social implications.

This study contributes to the herding literature by examining four different hypotheses in respect of the unique case of transnational stock exchange without fusions or corporate mergers, where each market maintains its independence and regulatory autonomy. The authors also contribute to the literature by including both ARCH and GARCH effects in the herding behavioral models along the Hwang and Salmon (2004) approach.

This paper aims to introduce knowledge discrimination to consumer research. It also examines the antecedent effects of objective knowledge and confidence in knowledge on consumer knowledge discrimination. Research in psychology has sought to distinguish between calibration and discrimination, two related skills in probabilistic judgments. Though consumer research has sought to examine knowledge calibration, the construct of knowledge discrimination has not attracted any attention.

The paper reports on three studies which use a cross-sectional design using a structured questionnaire. The hypotheses are tested using regression. In addition, the paper also reports the results of an experimental study.

The paper finds that the objective knowledge has a positive effect on discrimination. But confidence in knowledge does not have a consistent effect on discrimination. The paper also finds that feedback improves discrimination.

The study adds a new dimension to the examination of metaknowledge and metacognitions in the consumer domain.

The study suggests some ways in which companies/government agencies can improve consumer knowledge discrimination.

Knowledge discrimination is expected to reduce consumer vulnerability and enhance consumer competence.

This is the first study to examine knowledge discrimination in the consumer domain. Prior research has observed that there could be a trade-off between calibration and discrimination. Hence, the study of knowledge discrimination can inform the study of knowledge calibration.

The purpose of this paper is to review and discuss the literature focusing on defining and measuring sentiments so as to understand their role in stock market behavior.

Critical review of the literature by analyzing myriad scholarly articles. The study is based on an analysis of 81 scholarly articles to critically analyze the approach toward defining and measuring market sentiments. The articles have been examined to identify and critique different classification of sentiment measures. A discussion is built to scrutinize the sentiment measures under the purview of theoretical underpinnings of the investor sentiment theory as well.

With more than five decades of research, the sentiment construct in finance literature is still ill-defined. Myriad empirical proxies of sentiment measures have led to conflicting results. The sentiment construct defined in financial theories needs to be revisited from the lens of sentiments defined in psychology.

The study is limited to analyzing the role of individual and institutional sentiments in equity markets. There is a need to explore sentiments with respect to different investment styles and strategies along with the type of investors.

Developing a suitable sentiment proxy can result in devising profitable trading strategies for investors. Understanding factors driving investor sentiments will help regulators to become more proactive and frame better policies.

This paper has leveraged psychology literature to highlight the limitations in development of sentiment construct in finance literature. By identifying stylized facts from reviewing the empirical literature, it highlights areas for future research.