A Test of the Arbitrage Pricing Theory in the Bombay Stock Market

Verma, Ashutosh; Rai, Chandra Kumar

doi:10.1177/2455265820150209

Cited by 3 publications

(2 citation statements)

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“…But some other studies are also there which uses only descriptive statistics or some simple estimation tools such as t -test, analysis of variance (ANOVA) to explain this behaviour of the stock market. The study of Verma and Vijay Kumar (2008) is one of them where they have used the descriptive statistics, ANOVA and regression analysis in Bombay stock exchange. The mean returns of the months are found to be positive except the month of October.…”

Section: Review Of Literaturementioning

confidence: 99%

Capturing the month of the year effect in the Indian stock market using GARCH models

Acharya

Kaliyaperumal

Mahapatra

2022

XJM

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Purpose In the research of stock market efficiency, it is argued that the stock market moves randomly and absorbs all the available information. As a result, it is quite impossible to make predictions about the possible future movement by the investors. But literatures have detected certain calendar anomalies where a day(s) in a week or month(s) in a year or a particular event in a year becomes conducive for investors to earn more than the normal. Hence, the purpose of this study is to find out the month of the year effect in the Indian stock market. Design/methodology/approach In this study, daily time series data of Sensex and Nifty from 1996 to 2021 is used. The study uses month dummies to capture the effect. Different variants of generalised autoregressive conditional heteroskedasticity (GARCH) models, both symmetric and asymmetric, are used in the study to model the conditional volatility in the presence month effect. Findings This study found the September effect in the return series of both the stock market. Apart from that, asymmetric GARCH models are found to be the best fit model to estimate conditional volatility. Originality/value This study is an endeavour to study month of the year effect in the Indian context. This research will provide valuable insight for studying the different calendar anomalies.

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Section: Review Of Literaturementioning

confidence: 99%

Capturing the month of the year effect in the Indian stock market using GARCH models

Acharya

Kaliyaperumal

Mahapatra

2022

XJM

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“…In many empirical works, researchers have identified the dynamic relationship between different markets across the globe, but there are some who did not find any such dynamic relationship (Cheung & Lee, 1993;McClure, Clayton, & Hofler, 1999). There are a number of studies which investigate volatility spillover, market efficiency and financial volatility that have significant influence on the economy growth and the decision-makers (Kalsie, 2012;Pandey, 2014;Poon & Granger, 2003;Verma & Kumar, 2015). There is a significant association between high volatilities in market and investor's confidence to invest.…”

Section: Introductionmentioning

confidence: 99%

Volatility Spillovers across Major Emerging Stock Markets

Kumar

Haque

Sharma

2017

Asia-Pacific Journal of Management Research and Innovation

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Emerging stock markets of Asia have become a matter of interest for international financial researchers and policy-makers during the last couple of decades. Series of reforms, increasing financial transparency and decreasing restrictions on transactions have made these markets better diversification opportunities for international investors. This paper examines independently as well the linkages of stock markets across the selected Asian countries. The volatility spillover is modelled through an asymmetric multivariate generalized autoregressive conditional heteroscedastic model. In large number of empirical studies of risk return analysis, it is observed that economic stability and good perspectives have been key assets for the development of emerging markets. Diversification of funds to reduce portfolio risk is also one of the point of attraction to domestic and foreign institutional investors. In this work, risk and uncertainty is studied for selected stock markets of emerging economies of Asia. Data of daily stock prices of selected markets is collected for recent decade and detail autoregressive conditional heteroskedasticity (ARCH) and its generalised models are used to estimate conditional and asymmetric volatilities.

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Testing event-based day of the week anomaly and trading opportunities: Evidence from Indian sectoral indices

Bhatia,

Sharma,

Aggarwal

et al. 2024

Investment Management and Financial Innovations

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The study is an attempt to examine the day-of-the-week anomaly of fourteen Indian sectoral indices and identify profitable opportunities, considering multiple positive and negative events. The aim of this study is to analyze the day-of-the-week effect on fourteen Indian sectoral indices and find profitable opportunities while considering multiple events that have positive and negative impacts. The study takes into consideration event-based anomalies, both national and global, and provides timing for trading to generate abnormal returns from the market. At first, dummy variable regression analysis was used to understand the initial anomalies. Later, time-varying symmetrical and asymmetrical volatility models, such as Generalized Autoregressive Conditional Heteroscedasticity (1, 1) and Exponential Generalized Autoregressive Conditional Heteroscedasticity (1, 1) were applied to determine the short-term and long-term volatility persistence. These models capture the leverage effect from various events that occurred during the study. The results showed mixed outcomes during multiple positive and negative shocks. After the recession, anomalies were observed across all sectoral indices, except for commodities, energy, and information technology. During the scam period, anomalies occurred in all sectors, except for consumer durables, financial services, and information technology. However, after the new government took over, anomalies persisted in all sectors. During the pandemic, anomalies persisted in all sectors except for finance, IT, pharmaceuticals, and services. Hence, national and global events have shown varied impacts on the Indian markets. The study provides investors with implications on strategies and timing techniques for planning their investments in different sectors of the Indian economy.

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A Test of the Arbitrage Pricing Theory in the Bombay Stock Market

Cited by 3 publications

References 0 publications

Capturing the month of the year effect in the Indian stock market using GARCH models

Capturing the month of the year effect in the Indian stock market using GARCH models

Volatility Spillovers across Major Emerging Stock Markets

Testing event-based day of the week anomaly and trading opportunities: Evidence from Indian sectoral indices

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