Cross-sectional Standard Deviation Research Articles

Herd Behaviour and COVID-19 Intervention

The paper attempted to confirm the rational assets pricing model by examining the herd behaviour in extreme market returns and examining the COVID-19 intervention by comparing before COVID-19, during COVID-19 and after COVID-19 period. Cross Sectional Standard Deviation (CSSD) calculated as the index and further regressed by using dummy variables (Extreme upper tail market returns =1, otherwise = 0). For the better inferences stationarity of time series data were checked by both graphically and Augmented Dickey –Fuller test in all three states of COVID-19. Finally, the Cumulative-Sum (CUSUM) test was conducted to check the parameter stability of the regression model. The finding of the study supports the rational asset pricing models, meaning that there is no presence of herding in NEPSE in extreme upper tail returns. But it rejects the rational asset pricing models in case of extreme lower market returns and in COVID-19 period. For better affirmation of rational assets pricing models, future research can extend the work by addressing the market characteristics, such as: trading volume, volatility, and liquidity.

Asymmetry risk and herding behavior: a quantile regression study of the Egyptian mutual funds

PurposeThis paper deeply investigates the herd behavior of the Egyptian mutual funds under changing and different conditions of the market pre- and post-events and compares the impact of asymmetric risk conditions on the herding behavior of the Egyptian mutual funds in both up and down markets.Design/methodology/approachWe test for the existence of herding for the whole period from 2003 to 2022, as well as for the pre-and post-different Egyptian uprising periods. We employ two well-known models, namely the cross-sectional standard deviation (CSSD) and cross-sectional absolute deviation (CSAD) models. Additionally, we use the quantile regression approach.FindingsWe find that the behavior of mutual funds does not change following the different political and social events. For the whole period, we find evidence of herding behavior using only the model of CSAD in down-market conditions. We generalize our finding to be evidence of the existence herding behavior in different quantiles, under only the down market in specific points’ pre, post or both given events throughout the whole series. Conversely, during the upper market, we show a full absence of herding behavior considering all different quantiles. When the market is down, managers are afraid of the condition of uncertainty, neglecting their own private information, avoid acting independently and consequently, following other mutual funds. When the market is up, managers become rational and act fully independent.Research limitations/implicationsFuture research should delve deeper into the drivers of herding behavior, assess its longer-term effects, develop risk management strategies and consider regulatory measures to mitigate the potential negative impact on mutual fund performance and investor outcomes.Practical implicationsThe study reveals that the behavior of mutual funds remains consistent despite various political and social events, suggesting a degree of resilience in their investment strategies. The research uncovers evidence of herding behavior in both high and low quantiles, but exclusively in down markets. In such conditions of market decline, fund managers appear to forsake their private information, exhibiting a tendency to follow the crowd rather than acting independently.Social implicationsThe study reveals that the behavior of mutual funds remains consistent despite various political and social events, suggesting a degree of resilience in their investment strategies. The research uncovers evidence of herding behavior in both high and low quantiles, but exclusively in down markets. In such conditions of market decline, fund managers appear to forsake their private information, exhibiting a tendency to follow the crowd rather than acting independently. Future research should delve deeper into the drivers of herding behavior, assess its longer-term effects, develop risk management strategies and consider regulatory measures to mitigate the potential negative impact on mutual fund performance and investor outcomes.Originality/valueThe paper investigates the herd behavior of the Egyptian mutual funds under asymmetric risk conditions, the study follows the spectrum of the herding behavior analysis and Egyptian mutual funds, extending the research with imperial analysis of market conditions pre- and post-events including currency floating, COVID-19 and political elections. The study gives substantial recommendations for policymakers and investors in emerging markets mutual funds.

Impact of Covid-19 on Investors Herding Behavior: Evidence from Stock Market

The purpose of this research was to use a descriptive and causal-comparative approach to analyze herding behavior in the Nepalese stock market during the COVID-19 epidemic. The study employed a regression model and a cross-sectional standard deviation (CSSD) index to evaluate the herding tendency. The investigation covers a significant time period from January 1, 2018, to February 28, 2023, and involves a substantial number of observation sessions totaling 1103. It appears that there is currently no evidence to suggest that herding behavior has occurred before, during, or after the COVID-19 pandemic. This study indicates that market participants were making independent decisions based on their own analysis and assessment of the situation during the pandemic, rather than relying on the actions or decisions of others.

An Empirical Investigation of Herd Behaviour in Surplus Economy: Evidences from Muscat Stock Market

This study investigates herd behaviour in the surplus economy of the Sultanate of Oman under Bear and Bull market conditions. The first aim of the study is to determine if the investors at Muscat Stock Market (MSM) exhibit herd behavior or not. The second aim of the study is to compare the different stochastic time-series models commonly used to test and forecast herd behavior. Finally, the study aims to determine whether herd behavior in the MSM is predominantly risk-driven as measured by Cross-Sectional Standard Deviation (CSSD) or return-driven as measured by Cross-Sectional Absolute Deviation (CSAD) of stock returns from the overall market return. Our analyses are based on daily Muscat Stock Market’s (MSM) index returns for the period starting 1st of January 2010 and ending 31^st of December 2019, the pre Covide-19 pandemic. Our findings disclose: (1) that MSM exhibits herd behavior, (2) that there are statistically significant among the different stochastic time-series models used to test and forecast herd behavior in MSM, where ARIMA (1,0,0) model exhibits the highest predictive power of herd behavior in MSM (3), that MSM’s herd behavior is driven more by CSSD than CSAD in the bearish and bullish market conditions.

INVESTORS’ HERDING BEHAVIOUR IN INDIAN STOCK MARKETS DURING COVID 19: A CSSD AND CSAD APPROACH

The World has witnessed one of the most severe crises, a resulting effect of COVID 19 virus. This virus was never seen before in the human history and was declared as Pandemic by World Health Organization (WHO) on 11th March, 2020. Any crises like situation creates an imbalance in the economy which also gets penetrated in the stock markets of the country. The investors sentiments get weakened due to the negative impact of such incidences on various aspects of economy. Investors tend to exit from the market in such situation and look forward for better investment options or cash liquidity. Nevertheless, investors depict such behaviour in groups and herding tend to be me prevalent during such period of market stress (Bouri et al. 2021). Therefore, the present research tries to explore the herding behaviour of investors in Indian stock market. The study examines the presence of herding possibilities in Nifty 50 stocks of Indian stock market during the phase of Covid 19. The Cross-Sectional Standard Deviation (CSSD) methodology proposed by Christie and Huang (1995) and Cross-Sectional Absolute Deviation (CSAD) suggested by Chang et al. (2000) has been applied to detect the herding effect on stock prices of 50 composite stock of Nifty 50 index of Indian Stock Market.

Does macroeconomic environment stimulate herding behaviour among investors in Malaysia stock market? an empirical evidence

Herding behaviour could cause stock prices to deviate from the fundamentals, resulting in market instability. One of the influencing factors that stimulate herding behaviour amongst investors is macroeconomic environment. Among the major macroeconomic variables that play important role in influencing herding behaviour are economic growth, exchange rate, interest rates and inflation rate. However, empirical evidence on this is still lacking especially in the case of emerging markets such as Malaysia. Therefore, the main objective of this paper is to empirically examine the influence of macroeconomic variables on the existence of herding behaviour in the Malaysian stock market.  In this study, two measures of herding behaviour have been used: Cross-Sectional Standard Deviation (CSSD) and Cross-Sectional Absolute Deviation (CSAD).  The estimation used daily data of 346 companies listed on the Malaysian stock market from the year 2000-2019. The regression estimation results using CSSD with individual macroeconomic variable found that herding behaviour is detected in the case of interest rate and inflation. Meanwhile, for CSAD, the results demonstrate that herding behaviour is present in the case of interest rate, inflation rate and growth. Meanwhile, for the regression that consists of all macroeconomic variables, both measures are negatively and significantly related to interest rates and inflation rates. The findings offer additional evidence in supporting the existence of herding behaviour in Malaysia under the influence of selected macroeconomic variables.  Therefore, establishing better routes for economic information dissemination could assist investors to make a better investment decision. With a better understanding about herding behaviour could assist regulators to detect price efficiency issues hence to maintain market stability and efficiency.

An Investigation of Herding Prospects in the Pakistan Stock Exchange

The present study investigates investors’ herding in Pakistan Stock Exchange (PSX) and its sectors. Assumptions have been made that fundamental information causes herd behaviour; as a result, prices automatically adjust to newly-arrived information and lead to efficient markets. However, it is also believed that fundamental information does not cause herd behaviour and leads to price instability. Intraday, daily, and weekly stock returns of 528 companies listed in the PSX have been used. Market-wide herd measure, i.e., Cross-Sectional Standard Deviation (CSSD), has been employed as a herding measure. Findings revealed that neither PSX nor its sectors demonstrate herd behaviour at any level. The study has some implications for investors regarding investment decision-making.

Sentimental Herding in Stock Market: Evidence from India

The present study examines herd behaviour in the Indian equity market using daily prices of 11 broad market indices, 12 sectoral indices, 16 strategic indices and 11 thematic indices from 1 January 2016 to 31 March 2022. For examining herd behaviour, daily returns, overnight returns, intraday spread, absolute market return and squared market return are calculated. Nifty 500 is used as a proxy index for the whole market. The regression models suggested by Christie and Huang (1995) and Chang et al. (2000) are used to calculate Cross-Sectional Standard Deviation (CSSD) and Cross-Sectional Absolute Deviation (CSAD) respectively, which measure the equity return dispersions. It is observed that herding exists in the Indian equity market when we calculate return dispersions using intraday spread. However, no herd presence is found when return dispersions are calculated through daily return, overnight return, absolute market return and squared market return. These results may be useful for investors, policy makers and regulatory bodies. Investors might design their investment strategy while making investment decision. Regulators might be able to formulate their policies to ensure market efficiency in the Indian equity market.

TESTING FOR HERD BEHAVIOR IN BORSA ISTANBUL DURING THE COVID-19 PANDEMIC

The concept of herd behavior is based on the nature of decentralized acting investors’ pseudo-collaborative
 behaviors in the market. This study investigates the herd behavior phenomenon for Borsa Istanbul (BIST)
 amidst the new coronavirus outbreak. The whole period is split into symmetrical two discrete one-year
 sub-periods considering the median date of March 11th, 2020, the official announcement date of the first
 domestic COVID-19 case. The paper proceeds with the models based on the Cross-sectional mean absolute
 deviation (CSAD) and the Cross-sectional standard deviation (CSSD) test methodology to test for probable
 herd behavior, using daily stock closing prices of the BIST 100 index shares during the period from March
 11th, 2019 to March 9th, 2021.

Investor's herding behavior in Asian equity markets during COVID-19 period

In this paper we investigate herding behavior triggered by the COVID-19 outbreak in 2020 by considering six typical Asian stock markets. Cross-sectional Standard Deviation (CSSD) and Cross-sectional Absolute Deviation (CSAD) have been employed as the key indicators, which are aligned with the Markov-switching regression and HS model to identify the presence and magnitude of herding. We then elaborate our study by examining herding in specific time slots and markets with different idiosyncratic volatility. Our empirical results show a clear presence of herding in the “Feb 2020-Jan 2021” time window and we have captured a sharp rise of the magnitude of herding during the market crash in March 2020, and found herding emerged in these markets with shocks and fierce fluctuations.

Herding behaviour in Korea’s cryptocurrency market

ABSTRACT Herding behaviour is an interesting phenomenon that has a serious impact on the market, leading to inefficient asset prices and high volatility in periods of market turmoil. We analysed the existence of herding behaviour in the cryptocurrency market using hourly price data of eight major cryptocurrencies and the cross-sectional standard absolute deviation (CSAD) approach. Our findings showed anti-herding behaviour at shorter time intervals and herding behaviour during longer periods. The trading decisions of cryptocurrency investors mimic the behaviour of other traders over time. We further found that herding behaviour is stronger over longer time intervals in a down market. When a market is declining, it suggests that fear increases and investors are forced to act quickly in response to market movements rather than using their information. Thus, investors need to fix the situation as quickly as possible to avoid making losses, hence they need to make rational choices based on knowledge rather than emotion or fear.

Investigative Study of Investor’s Herding Behavior During Bullish and Bearish Market: A Case of Pakistan Stock Exchange

This study investigates the influence of herd behavior on the Pakistan stock exchange indexes KSE-100 and KSE-30 during bullish and bearish markets. Using the daily market return from 2007 to 2020. We implement the method of main herding measures, Cross-sectional absolute deviation, and Cross-sectional standard deviation, to explore the influence of herd behavior in the emerging market of Pakistan. The results indicate the presence of market-wide herd behavior: (a) along with the different direction of market positive and negative return, (b) when trading volume high, (c) when stock market highly volatile, and (d) during and the post-financial crisis. Moreover, Investors don’t herd when low trading volume and low volatility. Our study fills the gap in the literature and contributes to academic relevance by exploring the influence of herd behavior among both bull and bear periods in markets of Pakistan, it also examines the possible asymmetric effects of herding related to the market with high-low trading volume and market volatility.

Static and regime-dependent herding behavior: An emerging market case study

We contribute to behavioral finance literature by demonstrating the relative superiority of a dynamic regime-sensitive approach in unraveling herding phenomenon. Employing daily data in Bursa Malaysia from 1995 to 2016, we first apply two orthodox techniques: cross-sectional standard deviation of returns (CSSD) model of Christie and Huang (2005) and the cross-sectional absolute dispersion (CSAD) model of Chang et al. (2000). The ensuing results appear inconsistent, with only one model capturing herding. In contrast, the dynamic approach with a two-state Markov Switching model reveals that herding is a heavily regime-dependent and non-linear phenomenon. A deeper dive via sectoral decompositions shows that the financial sector and large- and mid-capitalization segments are more herding-prone.

Defusing Leverage: Liquidity Management and Labor Contracts

Rigidities in firms’ payroll structures are likely to increase the transmission of shocks to firms’ cash flows and profitability. By using Italian administrative data on workers careers and firms’ balance sheets, we study how the use of permanent and fixed-term labor contracts affects this pass-through. We document how firms use the contract composition of their workforce to manage the risk determined by their labor-induced operating leverage. First, we confirm that a higher labor share is associated with more volatile cash flows following unexpected real shocks, a telling indication of operating leverage at work through labor costs. Second, we show that firms with a greater share of temporary contracts are characterized by a smoother time-series behavior of their cash-flows. In particular, the smoothing effect is stronger for firms with higher labor share related to the permanent workforce. We complement this analysis with the study of the 2001 labor market reform that lifted constraints on the creation of temporary contracts. Exploiting the staggered implementation of the reform across different collective bargaining agreements, we show that, following the reform, firms increased on average their share of temporary contracts and decreased average labor compensation. In addition, we show that, only among firms with an ex-ante more rigid labor cost structure, earlier transition to a more flexible workforce composition led to a 1 percentage point increase in profit margins (against a -1.6pp average variation around the event) and a 5 percent decrease in the cross-sectional standard deviation of profits.

Static and Regime-Dependent Herding Behavior: An Emerging Market Case Study

We contribute to behavioral finance literature by demonstrating the relative superiority of a dynamic regime-sensitive approach in unravelling herding phenomenon. Employing daily data in Bursa Malaysia from 1995 to 2016, we first apply two orthodox techniques: cross-sectional standard deviation of returns (CSSD) model of Christie and Huang (2005) and the cross-sectional absolute dispersion (CSAD) model of Chang et al. (2000). The ensuing results appear inconsistent, with only one model capturing herding. In contrast, the dynamic approach with a two-state Markov Switching model reveals that herding is a heavily regime dependent and non-linear phenomenon. A deeper dive via sectoral decompositions shows that the financial sector and large- and mid-capitalization segments are more herding-prone.

Good vibes only: The crypto-optimistic behavior

This paper aims at investigating the relationship between news-driven sentiments and the convergence of behavior in cryptocurrencies market, contributing to the existing literature in the field. The novelty stands in the relation set between the tone of news and returns dispersion. The average daily sentiment score deriving from a worldwide online news dataset has been exploited as a proxy of market humor, in the attempt to identify how emotions spread by the press are related to traders’ actions. By employing both Cross-sectional standard (CSSD) and absolute (CSAD) deviation, it is found that the rises and falls of optimism shape returns variability. Indeed, the paper evidences how an increase of news positivity is associated with a lower returns dispersion, evidencing the convergence of beliefs among investors.

The herding behaviour on Pakistan stock exchange – using firm-level data

This paper analyses herding behaviour in the Pakistan stock exchange (PSX, formerly known as Karachi stock exchange, KSE) for a sample of 663 firms over a period of 13 years, from 2004 to 2017. For detecting herding behaviour, two dependent variables are used, i.e., cross-sectional standard deviation (CSSD) of Christie and Huang (1995) and cross-sectional absolute deviation (CSAD) of Chang et al. (2000). The results show no herding behaviour on the basis of both methods at different levels of market movements. The absence of the herding behaviour may be because these firms belong to different sectors which may follow their respective industry portfolios but not the overall market; for example, Shah et al. (2017) documented that firms in several industries herd toward their industry portfolios for Pakistani data. Future research can be done using a primary data collection method from investors about their opinion on herding behaviour.

The herding behaviour on Pakistan stock exchange – using firm-level data

This paper analyses herding behaviour in the Pakistan stock exchange (PSX, formerly known as Karachi stock exchange, KSE) for a sample of 663 firms over a period of 13 years, from 2004 to 2017. For detecting herding behaviour, two dependent variables are used, i.e., cross-sectional standard deviation (CSSD) of Christie and Huang (1995) and cross-sectional absolute deviation (CSAD) of Chang et al. (2000). The results show no herding behaviour on the basis of both methods at different levels of market movements. The absence of the herding behaviour may be because these firms belong to different sectors which may follow their respective industry portfolios but not the overall market; for example, Shah et al. (2017) documented that firms in several industries herd toward their industry portfolios for Pakistani data. Future research can be done using a primary data collection method from investors about their opinion on herding behaviour.

Herding in mutual funds: A complex network approach

The paper investigates herding in mutual funds through a complex networks approach. The detection of significant correlation coefficients constitutes the basis for the construction of the network. Some centrality measures and the assortativity are added as explanatory variables in the regression analysis of two popular indicators of herding, largely applied in finance literature. Cross-Sectional Standard Deviation and Cross-Sectional Absolute Deviation are both considered since they emphasize the bulk and the extreme values of herding. Two dummy variables designed to capture differences in investor behaviour in extreme up or down versus relatively normal markets are considered as independent variables. The results show a clear decrease of herding in stressful periods of the market. Moreover, the prevailing explanatory power of the betweenness is well evidenced, thereby highlighting the role of the network structure. In line with the literature on herding, the results also evidence a flight to safety effect.

Overconfidence Bias: Empirical Examination of Trading Turnover and Market Returns

Theory of overconfidence states that investors are highly overconfident when valuing the stocks. Self-attribution has been found by the researchers as the root cause for overconfidence bias in investors. Investors attribute the high stock prices and returns with their own art of picking up the stocks, and thus they trade more frequently. In order to test overconfidence and self-attribution Vector Autoregressive (VAR) model has been employed to find out the long-term relationship between endogenous variables: market return and market turnover and exogenous variables: volatility and dispersion. Results revealed that there exists a strong positive relationship between market returns and trading turnover. Also, the crosssectional standard deviation in market prices i-e volatility and the cross-sectional variation in stock returns i-e dispersion has a very strong impact on trading pattern and returns. Since investment decisions made by Pakistani investor largely depend upon psychological factors, giving less weightage to all the fundamentals, the trading pattern exhibited may collectively tend the market behave in an irrational manner.