Herd Behaviour: How Decisive is the Noise in the NSE and BSE Stock Markets?

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Paritosh Chandra Sinha
Keyword(s):  
Behavioral Finance ◽  
Stock Markets ◽  
High Frequency ◽  
Stock Exchange ◽  
Time Stamp ◽  
Trade Volume ◽  
Herding Behavior ◽  
Equilibrium Pricing ◽  
Indian Context ◽  
Herd Behaviour

Do investors in the stock markets act/react on true information or noise? Do they believe on their own information or simply herd? The study seeks to explore these typical research queries from the behavioral finance perspectives. In particular, it develops a new theory of herding behavior and extends the models of Banerjee (1992) and Bikhchandani, Hirshleifer, and Welch (1992). The study also empirically tests the same on the Indian context with the high frequency intraday trading data for the real trade-time or time-stamp, trade-volume, and trade-price of ten sample scripts listed for their trading in both markets - the Bombay Stock Exchange (BSE) and the National stock Exchange (NSE). The study contributes to the literature with original findings. It shows that investors in the two Indian stock markets show crowd of positive and negative herding as well significantly and there is huge noise along with information in the markets equilibrium pricing mechanism.

Herd Behaviour: How Decisive is the Noise in the NSE and BSE Stock Markets?

GIS Business ◽  
2016 ◽  
Vol 11 (6) ◽  
pp. 01-16
Author(s):  
Paritosh Chandra Sinha
Keyword(s):  
Behavioral Finance ◽  
Stock Markets ◽  
High Frequency ◽  
Stock Exchange ◽  
Time Stamp ◽  
Trade Volume ◽  
Herding Behavior ◽  
Equilibrium Pricing ◽  
Indian Context ◽  
Herd Behaviour

Do investors in the stock markets act/react on true information or noise? Do they believe on their own information or simply herd? The study seeks to explore these typical research queries from the behavioral finance perspectives. In particular, it develops a new theory of herding behavior and extends the models of Banerjee (1992) and Bikhchandani, Hirshleifer, and Welch (1992). The study also empirically tests the same on the Indian context with the high frequency intraday trading data for the real trade-time or time-stamp, trade-volume, and trade-price of ten sample scripts listed for their trading in both markets - the Bombay Stock Exchange (BSE) and the National stock Exchange (NSE). The study contributes to the literature with original findings. It shows that investors in the two Indian stock markets show crowd of positive and negative herding as well significantly and there is huge noise along with information in the markets equilibrium pricing mechanism.

Stochastic cost flow system for stock markets with an application in behavioral finance

2016 ◽  
Vol 03 (04) ◽  
pp. 1650026 ◽  
Author(s):  
Oliver Chan ◽  
Alfred Ka Chun Ma
Keyword(s):  
Probability Distribution ◽  
Behavioral Finance ◽  
Stock Markets ◽  
High Frequency ◽  
Flow System ◽  
Weighted Average ◽  
Financial Data ◽  
Purchase Price ◽  
Cost Flow ◽  
The Impact

We introduce a new stochastic cost flow system for stock markets in which the probability distribution of the weighted average purchase price of a stock among all of its shareholders can be explicitly determined. The stochastic system is illustrated in three empirical applications. Through the empirical results, we demonstrate the impact of choosing cost flow assumptions on the reference purchase price estimates, we show the value of high-frequency financial data, and we advocate the need for the stochastic cost flow system when estimating the proportion of gains realized (PGR) and the proportion of losses realized (PLR) which are the most important measures for the disposition effect.

scholarly journals Testing Sectoral Herding in the Jordanian Stock Market

2019 ◽  
Vol 12 (8) ◽  
pp. 88
Author(s):  
Mohammad K. Elshqirat
Keyword(s):  
Financial Crisis ◽  
Behavioral Finance ◽  
Global Financial Crisis ◽  
Least Squares Method ◽  
Stock Exchange ◽  
Ordinary Least Squares ◽  
Market Condition ◽  
Herding Behavior ◽  
Industrial Sectors ◽  
The Global Financial Crisis

The main purposes of this quantitative study were to examine the existence of herding behavior among investors in Amman stock exchange (ASE) at market and sector level in addition to testing the behavior during the market rising and falling and examining whether the behavior existence is different before and after the global financial crisis of 2008. The theoretical base of the study was the behavioral finance which assumes that investors are not completely rational and they may follow others when taking investment decisions. The main enquires of the study were about the existence of herding in the Jordanian market, whether it's affected by conditions of market rising and falling, and whether it's affected by the financial crisis. A quantitative design was employed to achieve the purposes of this study which covers the period 2000 - 2018. Data were obtained from ASE website and analyzed using ordinary least squares method. The results indicated that herding is absent in the Jordanian market if tested at market level while it exists in services and industrial sectors if tested at sectors level. The financial crisis did not affect the presence of herding at market level while it did affect the behavior in services and industrial sectors. Moreover, the results revealed that market condition of rising and falling affected herding at market level but not at sectors level. It is also concluded that the global financial crisis changed the presence of herding behavior during conditions of rising and falling in market and in each sector.

Statistical characteristics of price impact in high-frequency trading

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Can Jia ◽  
Tianmin Zhou ◽  
Handong Li
Keyword(s):  
High Frequency ◽  
Trading Volume ◽  
Stock Exchange ◽  
Price Change ◽  
Price Impact ◽  
High Frequency Trading ◽  
Statistical Characteristics ◽  
Long Term Memory ◽  
Time Interval ◽  
Trade Volume

AbstractTrading volume changes based on market microstructure will impact asset prices, which will lead to transaction price changes. Based on the extended Hasbrouck–Foster–Viswanathan (HFV) model, we study the statistical characteristics of daily permanent price impact and daily temporary price impact using high-frequency data from Chinese Stock Markets. We estimate this model using tick-by-tick data for 16 selected stocks that are traded on the Shanghai Stock Exchange. We find the following: (1) the time series of both the permanent price impact and temporary price impact exist in stationarity and long-term memory; (2) there is a strong correlation between the permanent price impact among assets, while the correlation coefficient of the temporary price impact is generally weak; (3) the time interval has no significant influence on the trade volume and the price change at the tick frequency, which means that it is not necessary to take into account the time interval between adjacent transaction in high-frequency trading; and (4) the bid-ask spread is an effective factor to explain trading price change, but has no significant impact on trade volume.

scholarly journals Remeasuring Sectoral Herding in the Financial Markets

2020 ◽  
Vol 13 (8) ◽  
pp. 1
Author(s):  
Mohammad K. Elshqirat
Keyword(s):  
Financial Crisis ◽  
Behavioral Finance ◽  
Global Financial Crisis ◽  
Stock Exchange ◽  
Industrial Sector ◽  
Rank Test ◽  
Herding Behavior ◽  
Absolute Deviation ◽  
Cross Sectional ◽  
The Cross

Herding behavior was concluded to exist in some sectors and under some market conditions in the Jordanian stock market when measured using the cross-sectional absolute deviation. The purpose of this study was to retest the existence of the sectoral herding using the cross-sectional dispersion of betas and compare the results with those reached using the measure of the cross-sectional absolute deviation. Behavioral finance theory represents the main base on which this study was built. In this study, the researcher tried to answer questions related to whether herding behavior exists in the Jordanian market and its sectors if measured using cross-sectional dispersion of betas and whether results will be different from those reached using other measures. In this quantitative study, data from Amman stock exchange were used and the period covered was from 2000 to 2018. These data were used to calculate the cross-sectional dispersion of betas which was tested using t-test, Kruskal–Wallis test, Mann-Whitney U test, and Wilcoxon Signed-Rank test. Results indicated that herding behavior existed in market and in each sector at the same level which was not affected by the financial crisis. Furthermore, the study revealed that herding level was the same when the market (sector) was rising and when it was falling and this similarity has not been changed by the occurrence of the global financial crisis. Finally, results indicated that herding was at its lowest level in the entire market and in the industrial sector during the time of financial crisis. These results are different from those of the study conducted in Jordan using cross-sectional absolute deviation which implies that using different herding measures yields different results.

Good and bad high-frequency volatility spillovers among developed and emerging stock markets

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Walid Mensi ◽  
Ramzi Nekhili ◽  
Xuan Vinh Vo ◽  
Sang Hoon Kang
Keyword(s):  
Stock Markets ◽  
High Frequency ◽  
Design Methodology ◽  
Stock Exchange ◽  
Content Type ◽  
Asymmetric Volatility ◽  
Volatility Spillovers ◽  
Emerging Stock Markets ◽  
Contagion Effects ◽  
Exchange Markets

PurposeThis paper examines dynamic return spillovers and connectedness networks among international stock exchange markets. The authors account for asymmetry by distinguishing between positive and negative returns.Design/methodology/approachThis paper employs the spillover index of Diebold and Yilmaz (2012) to measure the volatility spillover index for total, positive and negative volatility.FindingsThe results show time-varying and asymmetric volatility spillovers among the stock markets under investigation. During the coronavirus disease 2019 (COVID-19) pandemic, bad volatility spillovers are more pronounced and dominated over good volatility spillovers, indicating contagion effects.Originality/valueThe presence of confirmed COVID-19 cases positively (negatively) affects the good and bad spillovers under low and intermediate (upper) quantiles. Both types of spillovers at various quantiles agree also influenced by the number of COVID-19 deaths.

The Effect of Underreaction and Overreaction of Firm Stocks to Firm Valuation: Data from the Indonesian Stock Exchange

2019 ◽  
Author(s):  
Yohanes Indrayono
Keyword(s):  
Behavioral Finance ◽  
Firm Value ◽  
Intangible Assets ◽  
Stock Exchange ◽  
Investor Sentiment ◽  
Firm Valuation ◽  
Good News ◽  
Industrial Sectors ◽  
Tangible Assets ◽  
Firm Profitability

<p>This study contributes to the on-going studies on behavioral finance by providing a case study on underreaction and overreaction of firm stocks to firm valuation. We use the Model of Investor Sentiment (Barberis et al., 2005) to evaluate underreaction and overreaction behavior and reflect on specific findings in the Indonesian market. The result of the study is most of the stocks in the Indonesian Stock Exchange are more overreaction to the news of firm financial statements. Firms on the industry with more intangible assets measure more overreaction than firms on industries with more tangible assets. For stocks with overreaction, the stock firm value is positively affected by a change in the total assets and profitability, but not by change of book value. The result concretized no evidence that firm stocks overreacted to the news more than underreacting. In stock industrial sectors, the financial institutions and wholesale industry stocks demonstrated remarkable overreactions. Nonetheless, automotive, building construction, food and beverage as well as cement evidenced more underreaction. For better return in financial markets, investors may buy stocks of the firm on industry with more tangible assets when there is no good news about the increasing firm profitability and sales; nonetheless, they should buy stocks of the firm on industry with more intangible assets when there is no lousy news about the increasing firm profitability and sales. </p>

Analisis Komparatif Return Saham Dan Volume Perdagangan Saham Sebelum dan Sesudah Harbolnas Pada Perusahaan Dagang Yang Terdaftar Di Bei

2020 ◽  
Vol 17 (2) ◽  
Author(s):  
Devy Putri Milanda ◽  
Taufan Adi Kurniawan
Keyword(s):  
Linear Regression ◽  
Abnormal Return ◽  
Stock Return ◽  
Industrial Revolution ◽  
Online Shopping ◽  
Stock Exchange ◽  
Trade Volume ◽  
Volume Activity ◽  
Significance Level ◽  
Before And After

The industrial revolution resulted in several industries changing their management in order to survive, one of the industries that was affected quite considerably was the trading industry. This study aims to analyze stock return and Trade Volume Activity (TVA) of trading companies in Indonesia Stock Exchange (IDX) before and after Harbolnas (Hari Belanja Online Nasional) or National Online Shopping Days. The samples are all trading companies that have listed on the IDX in the year 2019. This study use multiple linear regression with a significance level of 5%. The results show there are no significant differences in the abnormal return before and after Harbolnas, and there are no significant differences in the TVA before and after the harbolnas

Momentum Effect in Stock Market: Empirical Evidence from Pakistan Stock Exchange

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Shahid Rasheed ◽  
Umar Saood ◽  
Waqar Alam
Keyword(s):  
Stock Market ◽  
Empirical Evidence ◽  
Stock Markets ◽  
Stock Exchange ◽  
Momentum Effect ◽  
Using Data

This study aims to examine the momentum effect presence in selected stocks of Pakistan stock market using data from Jan 2007 to Dec 2016. This study constructed the strategies includes docile, equal weighted and full rebalancing techniques. Data was extracted from the PSX – 100 index ranging from 2007 to 2016. STATA coding ASM software was used for calculating momentum portfolios, finally top 25 stocks were considered as a winner stocks and bottom 25 stocks were taken as a loser stocks. In conclusion, the results of the study found a strong momentum effect in Pakistan stock exchange PSX 100- index. As by results it has been observed that a substantial profit can earn by the investors or brokers in constructing a portfolio with a short formation period of three months and hold for 3, 6 and 12 months. There is hardly a study is present on the same topic on Pakistan Stock Exchange as preceding studies were only conducted on individual stock markets before merger of stock markets in Pakistan while this study leads the explanation of momentum phenomenon in new dimension i.e. Pakistan Stock Exchange. Keywords: Momentum, Portfolio, Winner Stocks, Loser Stocks

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