Pub Date : 2023-05-08DOI: 10.1108/rbf-09-2022-0216
C. D’Hondt, Rudy De Winne, A. Todorović
PurposeThis paper examines whether target returns act as specific goals that impact risk-taking when individuals make investment decisions.Design/methodology/approachUsing an experimental setting, the authors assign either a low or a high target return to participants and ask them to make independent investment decisions as the risk-free rate fluctuates around their target return and, for some of them, becomes negative.FindingsBuilding on cumulative prospect theory, the authors find that the prevailing reference point of participants is the target return, regardless of the level of the risk-free rate. This result still holds even when the risk-free rate is negative, suggesting that (1) the target return drives risk-taking more than does a zero-threshold and (2) negative rates are limited as a tool to stimulate appetites for risk. In a follow-up study, the authors show that these conclusions remain valid when the target return is endogenously determined.Originality/valueThe authors' original approach, which pioneers the use of target returns in both the positive and negative interest rate contexts, provides insightful results about the “reach for yield” among regular people.
{"title":"Target return as efficient driver of risk-taking","authors":"C. D’Hondt, Rudy De Winne, A. Todorović","doi":"10.1108/rbf-09-2022-0216","DOIUrl":"https://doi.org/10.1108/rbf-09-2022-0216","url":null,"abstract":"PurposeThis paper examines whether target returns act as specific goals that impact risk-taking when individuals make investment decisions.Design/methodology/approachUsing an experimental setting, the authors assign either a low or a high target return to participants and ask them to make independent investment decisions as the risk-free rate fluctuates around their target return and, for some of them, becomes negative.FindingsBuilding on cumulative prospect theory, the authors find that the prevailing reference point of participants is the target return, regardless of the level of the risk-free rate. This result still holds even when the risk-free rate is negative, suggesting that (1) the target return drives risk-taking more than does a zero-threshold and (2) negative rates are limited as a tool to stimulate appetites for risk. In a follow-up study, the authors show that these conclusions remain valid when the target return is endogenously determined.Originality/valueThe authors' original approach, which pioneers the use of target returns in both the positive and negative interest rate contexts, provides insightful results about the “reach for yield” among regular people.","PeriodicalId":44559,"journal":{"name":"Review of Behavioral Finance","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75757249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-11DOI: 10.1108/rbf-01-2023-0013
L. Nguyen, Phong Thanh Nguyen
PurposeIn this paper, the authors examine the short-term and long-term impact of general economic policy uncertainty (EPU) and crypto-specific policy uncertainty on Bitcoin’s (BTC) exchange inflows – a form of crypto investor behaviors that the authors expect to drive the cryptocurrency volatility.Design/methodology/approachThe authors use an autoregressive distributed lag (ARDL), coupled with the bounds testing approach by Pesaran et al. (2001), to analyze a weekly dataset of BTC’s exchange inflows and relevant policy uncertainty indices.FindingsThe authors observe both short-term and long-term impacts of the crypto-specific policy uncertainty on BTC’s exchange inflows, whereas the general EPU only explains these inflows in a short-term manner. In addition, the authors find exchange inflows of BTC “Granger” cause its price volatility. Furthermore, the authors document a significant and relatively persistent response of BTC volatility to shocks to its exchange inflows.Originality/valueThis study’s findings offer significant contributions to research in policy uncertainty and investor behaviors.
{"title":"Do crypto investors wait and see during policy uncertainty? An examination of the dynamic relationships between policy uncertainty and exchange inflows of Bitcoin","authors":"L. Nguyen, Phong Thanh Nguyen","doi":"10.1108/rbf-01-2023-0013","DOIUrl":"https://doi.org/10.1108/rbf-01-2023-0013","url":null,"abstract":"PurposeIn this paper, the authors examine the short-term and long-term impact of general economic policy uncertainty (EPU) and crypto-specific policy uncertainty on Bitcoin’s (BTC) exchange inflows – a form of crypto investor behaviors that the authors expect to drive the cryptocurrency volatility.Design/methodology/approachThe authors use an autoregressive distributed lag (ARDL), coupled with the bounds testing approach by Pesaran et al. (2001), to analyze a weekly dataset of BTC’s exchange inflows and relevant policy uncertainty indices.FindingsThe authors observe both short-term and long-term impacts of the crypto-specific policy uncertainty on BTC’s exchange inflows, whereas the general EPU only explains these inflows in a short-term manner. In addition, the authors find exchange inflows of BTC “Granger” cause its price volatility. Furthermore, the authors document a significant and relatively persistent response of BTC volatility to shocks to its exchange inflows.Originality/valueThis study’s findings offer significant contributions to research in policy uncertainty and investor behaviors.","PeriodicalId":44559,"journal":{"name":"Review of Behavioral Finance","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2023-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85118581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-06DOI: 10.1108/rbf-05-2022-0143
P. Grégoire, M. Dixon, I. Giroux, C. Jacques, Annie Goulet, James Eaves, S. Sévigny
PurposeOnline investment platforms offer an environment that may lead some traders into excessive behaviors akin to gambling. Over the last decade, gambling behaviors associated with the stock market have attracted the attention of many researchers but the literature on the subject remains scarce. This study aims to present the results of live interviews with a sample (N = 100) of retail investors trading online, and contrasts trading habits with gambling behaviors.Design/methodology/approachParticipants are divided in three groups according to their score on an adapted version of the Problem Gambling Severity Index (referred to as the PGSI-Trading), and their trading habits and behaviors are compared.FindingsThe authors find that traders with higher PGSI-Trading scores are more likely to display gambling-related behaviors such as trading within a short timeframe, being motivated by making money quickly and experiencing high sensations when trading.Research limitations/implicationsThe sample is small but the authors proceeded this way in order to gather some qualitative data that would be helpful to clinicians in the Province of Quebec. The questionnaire used to classify traders at risk of being gamblers (PGSI-Trading) has not been validated.Practical implicationsThe findings of this study will be helpful to clinicians who hwork with patients suffering from excessive online stock trading habits.Social implicationsClinicians observe an increasing number of patients who consult with excessive stock trading habits. This study has brought new information allowing clinicians to better understand how gambling manifests itself on the stock market.Originality/valueTo the authors’ knowledge, this study is the first to investigate the trading habits of individuals classified in terms of their score on an adapted PGSI questionnaire.
{"title":"Gambling on the stock market: the behavior of at-risk online traders","authors":"P. Grégoire, M. Dixon, I. Giroux, C. Jacques, Annie Goulet, James Eaves, S. Sévigny","doi":"10.1108/rbf-05-2022-0143","DOIUrl":"https://doi.org/10.1108/rbf-05-2022-0143","url":null,"abstract":"PurposeOnline investment platforms offer an environment that may lead some traders into excessive behaviors akin to gambling. Over the last decade, gambling behaviors associated with the stock market have attracted the attention of many researchers but the literature on the subject remains scarce. This study aims to present the results of live interviews with a sample (N = 100) of retail investors trading online, and contrasts trading habits with gambling behaviors.Design/methodology/approachParticipants are divided in three groups according to their score on an adapted version of the Problem Gambling Severity Index (referred to as the PGSI-Trading), and their trading habits and behaviors are compared.FindingsThe authors find that traders with higher PGSI-Trading scores are more likely to display gambling-related behaviors such as trading within a short timeframe, being motivated by making money quickly and experiencing high sensations when trading.Research limitations/implicationsThe sample is small but the authors proceeded this way in order to gather some qualitative data that would be helpful to clinicians in the Province of Quebec. The questionnaire used to classify traders at risk of being gamblers (PGSI-Trading) has not been validated.Practical implicationsThe findings of this study will be helpful to clinicians who hwork with patients suffering from excessive online stock trading habits.Social implicationsClinicians observe an increasing number of patients who consult with excessive stock trading habits. This study has brought new information allowing clinicians to better understand how gambling manifests itself on the stock market.Originality/valueTo the authors’ knowledge, this study is the first to investigate the trading habits of individuals classified in terms of their score on an adapted PGSI questionnaire.","PeriodicalId":44559,"journal":{"name":"Review of Behavioral Finance","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2023-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88705315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-30DOI: 10.1108/rbf-01-2023-0014
Khemaies Bougatef, Imen Nejah
PurposeThis study examines whether the Russia–Ukraine war affects herding behavior in the Moscow Exchange.Design/methodology/approachThe authors employ the daily stock closing prices of 40 firms, which constitute the MOEX Russia Index from June 16, 2021, to November 30, 2022. The period before the invasion ranges from June 16, 2021, to February 23, 2022, while the post-invasion period runs from February 24, 2022, to November 30, 2022.FindingsThe findings suggest that the Russia–Ukraine war led to the formation of herding behavior among investors in Moscow Exchange. However, this herding behavior seems to be prevalent only during market downturns.Research limitations/implicationsThe results are important for policymakers and fund managers since they help them understand behavior patterns of investors during periods of war. Given the devastating effect of herd behavior on market stability, policymakers should implement a strategy to avoid this behavior. The formation of herding behavior during the Russia–Ukraine war indicates that uncertainty and fear caused by Western sanctions lead investors to imitate others which, in turn, could lead to equity mispricing. Thus, firm managers should take into account this evidence in equity issuance decisions in order to time the market. The findings raise questions about the validity of the efficient market hypothesis during the periods of war.Originality/valueThis study represents the first attempt to explore whether the Russia–Ukraine conflict contributes to the appearance of herding behavior among investors on Moscow Exchange.
{"title":"Does Russia–Ukraine war generate herding behavior in Moscow Exchange?","authors":"Khemaies Bougatef, Imen Nejah","doi":"10.1108/rbf-01-2023-0014","DOIUrl":"https://doi.org/10.1108/rbf-01-2023-0014","url":null,"abstract":"PurposeThis study examines whether the Russia–Ukraine war affects herding behavior in the Moscow Exchange.Design/methodology/approachThe authors employ the daily stock closing prices of 40 firms, which constitute the MOEX Russia Index from June 16, 2021, to November 30, 2022. The period before the invasion ranges from June 16, 2021, to February 23, 2022, while the post-invasion period runs from February 24, 2022, to November 30, 2022.FindingsThe findings suggest that the Russia–Ukraine war led to the formation of herding behavior among investors in Moscow Exchange. However, this herding behavior seems to be prevalent only during market downturns.Research limitations/implicationsThe results are important for policymakers and fund managers since they help them understand behavior patterns of investors during periods of war. Given the devastating effect of herd behavior on market stability, policymakers should implement a strategy to avoid this behavior. The formation of herding behavior during the Russia–Ukraine war indicates that uncertainty and fear caused by Western sanctions lead investors to imitate others which, in turn, could lead to equity mispricing. Thus, firm managers should take into account this evidence in equity issuance decisions in order to time the market. The findings raise questions about the validity of the efficient market hypothesis during the periods of war.Originality/valueThis study represents the first attempt to explore whether the Russia–Ukraine conflict contributes to the appearance of herding behavior among investors on Moscow Exchange.","PeriodicalId":44559,"journal":{"name":"Review of Behavioral Finance","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84358289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-29DOI: 10.1108/rbf-12-2022-0291
S. Arzova, Ayben Koy, B. Sahin
PurposeThis study investigates the effect of unproven energy reserve news on the volatility of energy firms' stocks. Thus, investors' perception of unproven energy reserves is revealed. Additionally, the study aims to determine whether the effect of the news changes according to time and volatility level.Design/methodology/approachThe general autoregressive conditional heteroskedasticity (GARCH) and exponential generalized autoregressive conditional heteroskedasticity (EGARCH) models consist of the energy reserve exploration news in Turkey for the period 2009–2022 and the volatility of 14 energy stocks.FindingsThe results indicate energy exploration news's negative and significant effect on volatility. According to empirical results, energy stock volatility is most affected in the first ten days. Besides, the results show that the significant models of energy reserve news in low-volatility stocks are proportionally higher than in high-volatility stocks.Research limitations/implicationsOnly unproved reserve news is included in the analysis, as sufficient confirmed reserves could not be reached during the sampling period. Further studies can compare proven and unproved reserve news effects. Additionally, a similar analysis can be conducted between Turkey and another country with a similar socio-economic character to examine different investor behaviors.Practical implicationsThis research includes indications on managing investors' reactions to unproven energy reserve news.Originality/valueThis study contributes to the literature by analyzing unproven reserves. Contrary to previous studies, examining stock volatility also makes the study unique.
{"title":"The impact of unproved reserve news on the energy stock volatility: an empirical investigation on Turkey","authors":"S. Arzova, Ayben Koy, B. Sahin","doi":"10.1108/rbf-12-2022-0291","DOIUrl":"https://doi.org/10.1108/rbf-12-2022-0291","url":null,"abstract":"PurposeThis study investigates the effect of unproven energy reserve news on the volatility of energy firms' stocks. Thus, investors' perception of unproven energy reserves is revealed. Additionally, the study aims to determine whether the effect of the news changes according to time and volatility level.Design/methodology/approachThe general autoregressive conditional heteroskedasticity (GARCH) and exponential generalized autoregressive conditional heteroskedasticity (EGARCH) models consist of the energy reserve exploration news in Turkey for the period 2009–2022 and the volatility of 14 energy stocks.FindingsThe results indicate energy exploration news's negative and significant effect on volatility. According to empirical results, energy stock volatility is most affected in the first ten days. Besides, the results show that the significant models of energy reserve news in low-volatility stocks are proportionally higher than in high-volatility stocks.Research limitations/implicationsOnly unproved reserve news is included in the analysis, as sufficient confirmed reserves could not be reached during the sampling period. Further studies can compare proven and unproved reserve news effects. Additionally, a similar analysis can be conducted between Turkey and another country with a similar socio-economic character to examine different investor behaviors.Practical implicationsThis research includes indications on managing investors' reactions to unproven energy reserve news.Originality/valueThis study contributes to the literature by analyzing unproven reserves. Contrary to previous studies, examining stock volatility also makes the study unique.","PeriodicalId":44559,"journal":{"name":"Review of Behavioral Finance","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72806002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-28DOI: 10.1108/rbf-09-2022-0214
Hardeep Singh Mundi
PurposeThe paper aims to examine the effect of CEOs' social networks on capital structure complexity (CSC) and firm performance.Design/methodology/approachOrdinary Least Squares regression (OLS) and Generalized method of moments (GMM) regression results estimate the effect of CEOs' (Chief executive officer) social networks on capital structure complexity and firm performance. The number of sources of capital (NSC) and concentration ratio estimate the capital structure complexity for the sample firms.FindingsThe results show that CEOs' social networks significantly influence CSC. We suggest that the CEOs' social networks encourage them to make more complex capital structure decisions. This behavior deteriorates firm performance.Research limitations/implicationsThere is a lack of systematic conceptual reason for measuring CEO social network. Future research should use other measures of the social network to estimate the relation of the CEO's social network with CSC and firm performance.Practical implicationsThe findings support the managerial power approach and social network theory that the observable characteristics of CEOs influence CSC. The results are robust for an alternative explanation.Originality/valueBy investigating the impact of the influence of CEOs' social networks on CSC and performance, the authors extend research on strategic leadership and capital structure and firm performance.
{"title":"CEO social network, capital structure complexity and firm performance","authors":"Hardeep Singh Mundi","doi":"10.1108/rbf-09-2022-0214","DOIUrl":"https://doi.org/10.1108/rbf-09-2022-0214","url":null,"abstract":"PurposeThe paper aims to examine the effect of CEOs' social networks on capital structure complexity (CSC) and firm performance.Design/methodology/approachOrdinary Least Squares regression (OLS) and Generalized method of moments (GMM) regression results estimate the effect of CEOs' (Chief executive officer) social networks on capital structure complexity and firm performance. The number of sources of capital (NSC) and concentration ratio estimate the capital structure complexity for the sample firms.FindingsThe results show that CEOs' social networks significantly influence CSC. We suggest that the CEOs' social networks encourage them to make more complex capital structure decisions. This behavior deteriorates firm performance.Research limitations/implicationsThere is a lack of systematic conceptual reason for measuring CEO social network. Future research should use other measures of the social network to estimate the relation of the CEO's social network with CSC and firm performance.Practical implicationsThe findings support the managerial power approach and social network theory that the observable characteristics of CEOs influence CSC. The results are robust for an alternative explanation.Originality/valueBy investigating the impact of the influence of CEOs' social networks on CSC and performance, the authors extend research on strategic leadership and capital structure and firm performance.","PeriodicalId":44559,"journal":{"name":"Review of Behavioral Finance","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2023-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78720761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-10DOI: 10.1108/rbf-02-2022-0068
Mehdi Mili, Asma Yahiya Al Amoodi, H. Bawazir
PurposeThis study aims to investigate the asymmetric impact of daily announcements regarding COVID-19 on investor sentiment in the stock market.Design/methodology/approachThis study uses a Non-Linear Autoregressive Distribution Lag (NARDL) model that relies on positive and negative partial sum decompositions of the Coronavirus indicators. Five investor sentiments had been used and the analysis is conducted on the full sample period from 24th February 2020 to 25th March 2021.FindingsThe results show that new cases have a greater impact on investor sentiment compared to daily announcements of new deaths related to COVID-19. In addition to revealing a significant impact of new COVID-19 new cases and new death announcements on a daily basis on investor sentiment over the short- and long-term, this paper also highlights the nonlinearity and asymmetry of this relationship in the short and long run. Investors' sentiments are more affected by negative news regarding Covid 19 than positive news.Originality/valueFinancial markets have been severely affected by COVID-19 pandemic. This study is the first to measure the extent of reaction of investors to positive and negative announcements of COVID-19. Interestingly, this study examines the asymmetric effect of daily announcements on new cases and new deaths by COVID-19 on investor sentiments and derive many implications for portfolio managers.
{"title":"The asymmetric effect of COVID-19 on investor sentiment: evidence from NARDL model","authors":"Mehdi Mili, Asma Yahiya Al Amoodi, H. Bawazir","doi":"10.1108/rbf-02-2022-0068","DOIUrl":"https://doi.org/10.1108/rbf-02-2022-0068","url":null,"abstract":"PurposeThis study aims to investigate the asymmetric impact of daily announcements regarding COVID-19 on investor sentiment in the stock market.Design/methodology/approachThis study uses a Non-Linear Autoregressive Distribution Lag (NARDL) model that relies on positive and negative partial sum decompositions of the Coronavirus indicators. Five investor sentiments had been used and the analysis is conducted on the full sample period from 24th February 2020 to 25th March 2021.FindingsThe results show that new cases have a greater impact on investor sentiment compared to daily announcements of new deaths related to COVID-19. In addition to revealing a significant impact of new COVID-19 new cases and new death announcements on a daily basis on investor sentiment over the short- and long-term, this paper also highlights the nonlinearity and asymmetry of this relationship in the short and long run. Investors' sentiments are more affected by negative news regarding Covid 19 than positive news.Originality/valueFinancial markets have been severely affected by COVID-19 pandemic. This study is the first to measure the extent of reaction of investors to positive and negative announcements of COVID-19. Interestingly, this study examines the asymmetric effect of daily announcements on new cases and new deaths by COVID-19 on investor sentiments and derive many implications for portfolio managers.","PeriodicalId":44559,"journal":{"name":"Review of Behavioral Finance","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2023-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80592193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-03DOI: 10.1108/rbf-06-2022-0151
Merve G. Cevheroğlu-Açar, Cenk C. Karahan
Purpose This study empirically documents the effect of ambiguity on stock returns in a major emerging market along with the ambiguity attitudes under various market conditions. Design/methodology/approach Ambiguity is measured as the volatility of return probability distributions extracted from high frequency intraday data via a method developed by Brenner and Izhakian (2018). The impact of ambiguity is then tested on stock market returns. Findings The results show that ambiguity is a priced factor in Turkish stock market with a positive premium that is distinct from risk premium. In contrast with the findings in the US market, the investors in Turkey show an increasing level of ambiguity aversion as expected probability of favorable returns deviate from the mean value. The investors are effectively ambiguity neutral in lateral markets. The results are robust to testing with higher moments, sentiment measures and under recession conditions. Originality/value This study contributes to empirically documenting ambiguity and ambiguity aversion in a major emerging market along with the opportunity to observe international differences in ambiguity attitudes.
{"title":"Ambiguity and asset prices: a closer look in an emerging market","authors":"Merve G. Cevheroğlu-Açar, Cenk C. Karahan","doi":"10.1108/rbf-06-2022-0151","DOIUrl":"https://doi.org/10.1108/rbf-06-2022-0151","url":null,"abstract":"Purpose This study empirically documents the effect of ambiguity on stock returns in a major emerging market along with the ambiguity attitudes under various market conditions. Design/methodology/approach Ambiguity is measured as the volatility of return probability distributions extracted from high frequency intraday data via a method developed by Brenner and Izhakian (2018). The impact of ambiguity is then tested on stock market returns. Findings The results show that ambiguity is a priced factor in Turkish stock market with a positive premium that is distinct from risk premium. In contrast with the findings in the US market, the investors in Turkey show an increasing level of ambiguity aversion as expected probability of favorable returns deviate from the mean value. The investors are effectively ambiguity neutral in lateral markets. The results are robust to testing with higher moments, sentiment measures and under recession conditions. Originality/value This study contributes to empirically documenting ambiguity and ambiguity aversion in a major emerging market along with the opportunity to observe international differences in ambiguity attitudes.","PeriodicalId":44559,"journal":{"name":"Review of Behavioral Finance","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135604493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Editorial on Professor Robert Hudson leaving the journal","authors":"R. Hudson, G. Muradoglu","doi":"10.1108/rbf-11-2022-305","DOIUrl":"https://doi.org/10.1108/rbf-11-2022-305","url":null,"abstract":"","PeriodicalId":44559,"journal":{"name":"Review of Behavioral Finance","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83380497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-02DOI: 10.1108/rbf-07-2021-0128
C. Ciaschini, M. C. Recchioni
PurposeThis work aims at designing an indicator for detecting and forecasting price volatility and speculative bubbles in three markets dealing with agricultural and soft commodities, i.e. Intercontinental Exchange Futures market Europe, (IFEU), Intercontinental Exchange Futures market United States (IFUS) and Chicago Board of Trade (CBOT). This indicator, designed as a demand/supply odds ratio, intends to overcome the subjectivity limits embedded in sentiment indexes as the Bull and Bears ratio by the Bank of America Merrill Lynch.Design/methodology/approachData evidence allows for the parameter estimation of a Jacobi diffusion process that models the demand share and leads the forecast of speculative bubbles and realised volatility. Validation of outcomes is obtained through the dynamic regression with autoregressive integrated moving average (ARIMA) error. Results are discussed in comparison with those from the traditional generalized autoregressive conditional heteroskedasticity (GARCH) models. The database is retrieved from Thomson Reuters DataStream (nearby futures daily frequency).FindingsThe empirical analysis shows that the indicator succeeds in capturing the trend of the observed volatility in the future at medium and long-time horizons. A comparison of simulations results with those obtained with the traditional GARCH models, usually adopted in forecasting the volatility trend, confirms that the indicator is able to replicate the trend also providing turning points, i.e. additional information completely neglected by the GARCH analysis.Originality/valueThe authors' commodity demand as discrete-time process is capable of replicating the observed trend in a continuous-time framework, as well as turning points. This process is suited for estimating behavioural parameters of the agents, i.e. long-term mean, speed of mean reversion and herding behaviour. These parameters are used in the forecast of speculative bubbles and realised volatility.
本研究旨在设计一个指标，用于检测和预测欧洲洲际交易所期货市场(IFEU)、美国洲际交易所期货市场(IFUS)和芝加哥期货交易所(CBOT)三个涉及农产品和软商品的市场的价格波动和投机泡沫。该指标被设计为需求/供应优势比，旨在克服美银美林(Bank of America Merrill Lynch)的牛熊比等情绪指数中存在的主观性限制。设计/方法/方法数据证据允许对雅可比扩散过程进行参数估计，该过程对需求份额进行建模，并导致对投机泡沫和实现波动性的预测。采用自回归综合移动平均误差(ARIMA)动态回归对结果进行验证。并与传统的广义自回归条件异方差(GARCH)模型的结果进行了比较。该数据库是从汤森路透数据流(近期期货每日频率)中检索的。实证分析表明，该指标成功地捕捉到了中长期波动率在未来的趋势。将模拟结果与通常用于预测波动率趋势的传统GARCH模型的模拟结果进行比较，证实该指标能够复制趋势，并提供转折点，即GARCH分析完全忽略的附加信息。原创性/价值作者的商品需求作为离散时间过程，能够在连续时间框架中复制观察到的趋势，以及转折点。这个过程适合于估计代理的行为参数，即长期均值、均值回归速度和羊群行为。这些参数用于预测投机泡沫和实现波动率。
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