Stock return autocorrelation, day of the week and volatility

2017 ◽  
Vol 16 (2) ◽  
pp. 218-238 ◽  
Author(s):  
Shah Saeed Hassan Chowdhury ◽  
M. Arifur Rahman ◽  
M. Shibley Sadique
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Price ◽  
Stock Exchange ◽  
Saudi Arabian ◽  
Content Type ◽  
Limits To Arbitrage ◽  
Portfolio Returns ◽  
Autocorrelation Structure ◽  
Day Of The Week

Purpose The main purpose of this paper is to investigate autocorrelation structure of stock and portfolio returns in a unique market setting of Saudi Arabia, where nearly all active traders are the retail individuals and the market operates under severe limits to arbitrage. Specifically, the authors examine how return autocorrelation of Saudi Arabian stock market is related to factors such as the day of the week, stock trading, performance on the preceding day and volatility. Design/methodology/approach The sample consists of the daily stock price and index data of 159 firms listed in Tadawul (Saudi Arabian Stock Exchange) for the period from January 2004 through December 2015. The methodology of Safvenblad (2000) is primarily used to investigate the autocorrelation structure of individual stock and index returns. The authors also use the Sentana and Wadhwani (1992) methodology to test for the presence of feedback traders in the Saudi stock market. Findings Results show that there is significantly positive autocorrelation in individual stock, size portfolio and market returns and that the last two are almost always larger than the first. Return autocorrelation is negatively related to firm size. Interestingly, return autocorrelation is positively related to trading frequency. For portfolios, autocorrelation of returns following a high absolute return day is significantly higher than that following a low absolute return day. Similarly, return autocorrelation during volatile periods is generally larger than that during tranquil periods. Return correlation between weekdays is usually larger than that between the first and last days of the week. Overall, the results suggest that the possible reason for positive autocorrelation in stock returns could be the presence of negative feedback traders who are engaged in frequent profit-taking activities. Originality/value This is the first paper that thoroughly investigates the autocorrelation structure of the returns of the Saudi stock market using both index and individual stock returns. As this US$583bn (as of August 21, 2014) market opened to foreign institutional investors in June 2015, the results of this paper should be of significant value for the potential uninformed foreign investors in this relatively lesser known and previously closed yet highly prospective market.

Do Indian stock market sentiments impact contemporaneous returns?

2018 ◽  
Vol 7 (3) ◽  
pp. 332-346
Author(s):  
Divya Aggarwal ◽  
Pitabas Mohanty
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Temporal Dynamics ◽  
Stock Exchange ◽  
Principal Component ◽  
Stock Index ◽  
Content Type ◽  
Investor Sentiments ◽  
Indian Stock Market ◽  
The Impact

Purpose The purpose of this paper is to analyse the impact of Indian investor sentiments on contemporaneous stock returns of Bombay Stock Exchange, National Stock Exchange and various sectoral indices in India by developing a sentiment index. Design/methodology/approach The study uses principal component analysis to develop a sentiment index as a proxy for Indian stock market sentiments over a time frame from April 1996 to January 2017. It uses an exploratory approach to identify relevant proxies in building a sentiment index using indirect market measures and macro variables of Indian and US markets. Findings The study finds that there is a significant positive correlation between the sentiment index and stock index returns. Sectors which are more dependent on institutional fund flows show a significant impact of the change in sentiments on their respective sectoral indices. Research limitations/implications The study has used data at a monthly frequency. Analysing higher frequency data can explain short-term temporal dynamics between sentiments and returns better. Further studies can be done to explore whether sentiments can be used to predict stock returns. Practical implications The results imply that one can develop profitable trading strategies by investing in sectors like metals and capital goods, which are more susceptible to generate positive returns when the sentiment index is high. Originality/value The study supplements the existing literature on the impact of investor sentiments on contemporaneous stock returns in the context of a developing market. It identifies relevant proxies of investor sentiments for the Indian stock market.

Performance and development of a thin stock market: the Stockholm Stock Exchange 1912–2017

2020 ◽  
pp. 1-19
Author(s):  
Kristian Rydqvist ◽  
Rong Guo
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Stock Selection ◽  
Data Set ◽  
Transaction Prices ◽  
Limit Orders ◽  
A Value

We estimate historical stock returns for Swedish listed companies in a newly constructed data set of daily stock prices that spans more than 100 years. Stock returns exhibit all the familiar characteristics. The growth of the public sector depressed the stock market, and the process of globalization revitalized it. Banks played an important role in the early development of the stock market. There was little trading in the past, and we examine the effects on return measurement from missing data. Stock selection and the replacement of missing transaction prices through search back procedures or limit orders make little difference to a value-weighted stock price index, while ignoring the price effects of capital operations makes a big difference.

scholarly journals Impact of gold and oil prices on the stock market in Pakistan

2020 ◽  
Vol 25 (50) ◽  
pp. 279-294
Author(s):  
Aiza Shabbir ◽  
Shazia Kousar ◽  
Syeda Azra Batool
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Exchange ◽  
Structural Break ◽  
Oil Prices ◽  
Current Data ◽  
Small Sample ◽  
Data Set ◽  
Content Type ◽  
The Impact

Purpose The purpose of the study is to find out the impact of gold and oil prices on the stock market. Design/methodology/approach This study uses the data on gold prices, stock exchange and oil prices for the period 1991–2016. This study applied descriptive statistics, augmented Dickey–Fuller test, correlation and autoregressive distributed lag test. Findings The data analysis results showed that gold and oil prices have a significant impact on the stock market. Research limitations/implications Following empirical evidence of this study, the authors recommend that investors should invest in gold because the main reason is that hike in inflation reduces the real value of money, and people seek to invest in alternative investment avenues like gold to preserve the value of their assets and earn additional returns. This suggests that investment in gold can be used as a tool to decline inflation pressure to a sustainable level. This study was restricted to use small sample data owing to the availability of data from 1991 to 2017 and could not use structural break unit root tests with two structural break and structural break cointegration approach, as these tests require high-frequency data set. Originality/value This study provides information to the investors who want to get the benefit of diversification by investing in gold, oil and stock market. In the current era, gold prices and oil prices are fluctuating day by day, and investors think that stock returns may or may not be affected by these fluctuations. This study is unique because it focusses on current issues and takes the current data in this research to help investment institutions or portfolio managers.

Forecast of stock price fluctuation based on the perspective of volume information in stock and exchange market

2018 ◽  
Vol 8 (3) ◽  
pp. 297-314 ◽  
Author(s):  
Shoudong Chen ◽  
Yan-lin Sun ◽  
Yang Liu
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Price ◽  
Sequential Monte Carlo ◽  
Efficient Estimation ◽  
Exchange Market ◽  
Content Type ◽  
Advantages And Disadvantages ◽  
Market Volume ◽  
Non Parametric

Purpose In the process of discussing the relationship between volume and price in the stock market, the purpose of this paper is to consider how to take the flow of foreign capital into consideration, to determine whether the inclusion of volume information really contributes to the prediction of the volatility of the stock price. Design/methodology/approach By comparing the relative advantages and disadvantages of the two main non-parametric methods mainstream, and taking the characteristics of the time series of the volume into consideration, the stochastic volatility with Volume (SV-VOL) model based on the APF-LW simulation method is used in the end, to explore and implement a more efficient estimation algorithm. And the volume is incorporated into the model for submersible quantization, by which the problem of insufficient use of volume information in previous research has been solved, which means that the development of the SV model is realized. Findings Through the Sequential Monte Carlo (SMC) algorithm, the effective estimation of the SV-VOL model is realized by programming. It is found that the stock market volume information is helpful to the prediction of the volatility of the stock price. The exchange market volume information affects the stock returns and the price-volume relationship, which is achieved indirectly through the net capital into stock market. The current exchange devaluation and fluctuation are not conducive to the restoration and recovery of the stock market. Research limitations/implications It is still in the exploratory stage that whether the inclusion of volume information really contributes to the prediction of the volatility of the stock price, and how to incorporate the exchange market volume information. This paper tries to determine the information weight of the exchange market volume according to the direct and indirect channels from the perspective of causality. The relevant practices and conclusions need to be tested and perfected. Practical implications Previous studies have neglected the influence of the information contained in the exchange market volume on the volatility of stock prices. To a certain extent, this research makes a useful supplement to the existing research, especially in the aspects of research problems, research paradigms, research methods and research conclusion. Originality/value SV model with volume information can not only effectively solve the inefficiency of information use problem contained in volume in traditional practice, but also further improve the estimation accuracy of the model by introducing the exchange market volume information into the model through weighted processing, which is a useful supplement to the existing literature. The SMC algorithm realized by programming is helpful to the further advancement and development of non-parametric algorithms. And this paper has made a useful attempt to determine the weight of the exchange market volume information, and some useful conclusions are drawn.

An examination of calendar anomalies: evidence from the Thai stock market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rattaphon Wuthisatian
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Exchange ◽  
January Effect ◽  
Content Type ◽  
Current State ◽  
Managerial Implications ◽  
Monthly Pattern ◽  
Calendar Anomalies ◽  
Daily Stock Returns

PurposeThe study examines the existence of calendar anomalies, including the day-of-the-week (DOW) effect and the January effect, in the Stock Exchange of Thailand.Design/methodology/approachUsing daily stock returns from March 2014 to March 2019, the study performs regression analysis to examine predictable patterns in stock returns, the DOW effect and the January effect, respectively.FindingsThere is strong evidence of a persistent monthly pattern and weekday seasonality in the Thai stock market. Specifically, Monday returns are negative and significantly lower than the returns on other trading days of the week, and January returns are positive and significantly higher than the returns on other months of the year.Practical implicationsThe findings offer managerial implications for investors seeking trading strategies to maximize the possibility of reaching investment goals and inform policymakers regarding the current state of the Thai stock market.Originality/valueFirst, the study investigates calendar anomalies in the Thai stock market, specifically the DOW effect and the January effect, which have received relatively little attention in the literature. Second, this is the first study to examine calendar anomalies in the Thai stock market across different groups of companies and stock trading characteristics using a range of composite indexes. Furthermore, the study uses data during the period 2014–2019, which should provide up-to-date information on the patterns of stock returns in Thailand.

An examination of herding behavior in Pakistani stock market

2015 ◽  
Vol 10 (3) ◽  
pp. 474-490 ◽  
Author(s):  
Zuee Javaira ◽  
Arshad Hassan
Keyword(s):  
Decision Making ◽  
Stock Market ◽  
Stock Exchange ◽  
The Body ◽  
Investor Behavior ◽  
Decision Making Process ◽  
Herd Behavior ◽  
Herding Behavior ◽  
Content Type ◽  
Portfolio Returns

Purpose – 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. Design/methodology/approach – 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. Findings – 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. Research limitations/implications – 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. Practical implications – For an accurate valuation of assets investors should incorporate the herding factor. Social implications – 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. Originality/value – 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.

scholarly journals Profitability of The Moving Averages Technical Trading Rules in an Emerging Stock Market-A Study of Individual Stocks Listed On Pakistan Stock Exchange

2018 ◽  
Vol 14 (2) ◽  
pp. 67-76
Author(s):  
Muhammad Arif ◽  
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Exchange ◽  
Moving Average ◽  
Market Development ◽  
Moving Averages ◽  
Technical Trading ◽  
Technical Trading Rules ◽  
Trading Rules ◽  
Portfolio Returns

This paper investigates the gainfulness of moving averages (MA) timing method over the purchase and hold procedure for single stocks deal in Pakistan Stock Exchange. We used (Han et al., 2013) approach of single stock returns and indeterminate evidence of MA timing methodology insightful ability to increase higher returns over the strategy of purchase and hold. In addition, we report market risk-adjusted returns to expel any market development impacts and apply elective moving averages lag lengths to check the robustness of our outcomes. We look at that individual stock returns are noisier than portfolio returns and the fundamental technical exchanging principle of moving average don't be able to anticipate single stock returns. We propose the utilization of more perplexing trading rules in future investigations to determine the gainfulness of technical trading rules in individual stocks.

Foresight for stock market volatility – a study in the Indian perspective

foresight ◽  
2019 ◽  
Vol 22 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Jitendra Kumar Dixit ◽  
Vivek Agrawal
Keyword(s):  
Stock Market ◽  
Stock Price ◽  
Stock Exchange ◽  
Investment Decision ◽  
Market Volatility ◽  
Future Research ◽  
Stock Market Volatility ◽  
Content Type ◽  
Constant Variance ◽  
Investment Decision Making

Purpose Volatility is a permanent behavior of the stock market around the globe. The presence of the volatility in the stock price makes it possible to earn abnormal profits by risk seeking investors and creates hesitancy among risk averse investors as high volatility means high return with high risk. Investors always consider market volatility before making any investment decisions. Random fluctuations are termed as volatility of stock market. Volatility in financial markets is reflected because of uncertainty in the price and return, unexpected events and non-constant variance that can be measured through the generalized autoregressive conditional heteroscedasticity family models and that will give an insight for investment decision-making. Design/methodology/approach Daily data of the closing value of Bombay Stock Exchange (BSE) (Sensex) and National Stock Exchange (NSE) (Nifty) from April 1, 2011 to March 31, 2017 is collected through the web-portal of BSE (www.bseindia.com) and NSE (www.nseindia.com) for the analysis purpose. Findings The outcome of the study suggested that P-GARCH model is most suitable to predict and forecast the stock market volatility for both the markets. Research limitations/implications Future research can be extended to other stock market segments and sectoral indices to explore and forecast the volatility to establish a trade-off between risk and return. Originality/value The results of previous studies available are not conducive to this research, and very limited scholarly work is available in the Indian context, so required to be re-explored to identify the appropriate model to predict market volatility.

Does idiosyncratic risk matter? Evidence from mergers and acquisitions

2019 ◽  
Vol 20 (4) ◽  
pp. 313-329
Author(s):  
Pascal Nguyen ◽  
Younes Ben Zaied ◽  
Thu Phuong Pham
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Prices ◽  
Firm Value ◽  
Stock Price ◽  
Negative Relationship ◽  
Idiosyncratic Risk ◽  
Idiosyncratic Volatility ◽  
Content Type ◽  
Acquisition Announcements

Purpose This paper aims to investigate whether idiosyncratic volatility is a priced risk factor in the Australian stock market. Design/methodology/approach The authors use the change in idiosyncratic volatility around acquisition announcements and the related stock price revaluation to test whether the idiosyncratic risk is priced. If the idiosyncratic risk is priced, increases (decreases) in idiosyncratic volatility should be associated with decreases (increases) in the acquirer’s stock price, as the latter’s future cash flows are discounted at a higher (lower) rate. The sample consists of 2,656 completed acquisitions by Australian listed firms over the period January 1990 to October 2014 for which deal value represents more than 5 per cent of the acquirer’s market value. Findings Increases (decreases) in idiosyncratic risk are associated with significant decreases (increases) in firm value. This negative relationship is robust to the presence of outliers; is unaffected by the incidence of the 2007-2008 financial crisis; holds using alternative measures of idiosyncratic risk; and is more significant after excluding the resources sector. Firms with a higher idiosyncratic risk prior to the acquisition, and firms avoiding stock to pay for the acquisition, experience a more significant stock price increase in relation to a decrease in idiosyncratic risk. Research limitations/implications Considering the small size of the Australian economy, investors may have less scope to mitigate idiosyncratic risk. As a consequence, idiosyncratic risk is associated with the positive excess return, contrary to what standard asset pricing theory assumes. The results support Merton’s (1987) hypothesis that investors are exposed to idiosyncratic risk due to imperfect portfolio diversification and receive compensation for bearing that risk. Practical implications The pricing of idiosyncratic risk may also explain why the Australian stock market has historically offered a high equity risk premium. A practical implication would be for international investors to take advantage of the diversification constraints of local investors to capture higher risk premiums and achieve superior returns. Originality/value While prior studies demonstrate that stocks with higher idiosyncratic risk are associated with higher subsequent returns, the authors show that an increase in idiosyncratic risk is associated with a decrease in stock prices using acquisition announcements as shocks to a firm’s idiosyncratic risk. In other words, the results arise from within-firm variations rather than from cross-sectional differences in stock returns.

The Extended Opening Session of the Futures Market and Stock Price Behavior: Evidence from the Taiwan Stock Exchange

2009 ◽  
Vol 12 (03) ◽  
pp. 403-416 ◽  
Author(s):  
Hsiu-Chuan Lee ◽  
Cheng-Yi Chien ◽  
Hsiang-Lan Chen ◽  
Yen-Sheng Huang
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Price ◽  
Stock Exchange ◽  
Futures Market ◽  
Price Behavior ◽  
Taiwan Stock Exchange ◽  
Market Opening ◽  
Opening Session ◽  
Extension Period

This paper examines how the introduction of the extended opening session of the futures market affects stock price behavior around the market opening. On January 1, 2001, the Taiwan Futures Exchange (TAIFEX) extended the trading hours by opening earlier 15 minutes than the Taiwan Stock Exchange (TWSE). This change presents an opportunity to analyze how the extended opening session of futures market affects stock price behavior. Compared with the pre-extension period, the empirical results show that stock returns are less volatile and return autocorrelations are less positively correlated around the stock market opening. Moreover, overreaction for opening prices of the stock market is mitigated in the post-extension period. Finally, unexpected futures returns during the extended opening session can predict overnight stock returns. Overall, the empirical results are consistent with Foster and Viswanathan (1990) in that informed traders will trade aggressively at the market opening.

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