Re-Examining the Nifty Returns after the First Decade of Derivative Trading in Indian Capital Market Using Non-Linear Asymmetric GARCH Models

2012 ◽  
Vol 3 (4) ◽  
pp. 29-52 ◽  
Author(s):  
Sunita Narang
Keyword(s):  
Capital Market ◽  
Garch Models ◽  
Conditional Heteroskedasticity ◽  
Indian Market ◽  
Total Period ◽  
Dummy Variable ◽  
Asymmetric Garch ◽  
Indian Stock Market ◽  
Surrogate Index ◽  
The Impact

This article examines the Indian stock market for conditional volatility using symmetric and asymmetric GARCH (Generalized Autoregressive Conditional Heteroskedasticity) variants with reference to a comprehensive period of 20 years from July 3, 1990 to November 30, 2010 using S&P CNX Nifty. The impact of future trading on Nifty return and volatility is assessed using dummy variable in total period and using Log (Open Interest of Nifty futures) in post-derivative period. Along with the period of two decades the analysis has also been done on a sub-period of a decade from 1995 to 2005 with NiftyJunior as surrogate index as it had no derivatives during this period. The results show that the PGARCH model is best suited to Indian market conditions.

Impact of the COVID-19 Outbreak on the Currency Exchanges of Selected Countries

2022 ◽  
Vol 14 (2) ◽  
pp. 73-91
Author(s):  
Sudhi Sharma ◽  
Miklesh Prasad Yadav ◽  
Babita Jha
Keyword(s):  
Growth Rate ◽  
Negative Impact ◽  
Annual Growth ◽  
Conditional Heteroskedasticity ◽  
Annual Growth Rate ◽  
Dummy Variable ◽  
Currency Market ◽  
Autoregressive Conditional Heteroskedasticity ◽  
The Impact

The paper aims to analyse the impact of the COVID outbreak on the currency market. The study considers spot rates of seven major currencies (i.e., EUR/USD, USD/JPY, GBP/USD, AUD/USD, USD/CAD, USD/CHF, and CHF/JPY). To capture the impact of the outbreak on returns and the volatility of returns of seven currencies during pandemic, the study has segregated in two window periods (i.e., pre- [1st Jan 2019 to 31st Dec, 2019] and post-outbreak of COVID-19 [1st Jan, 2020 to 22nd Dec, 2020]). The study has applied various methods and models (i.e., econometric-based compounded annual growth rate [CAGR], dummy variable regression, and generalized autoregressive conditional heteroskedasticity [GARCH]). The result of the study captures the negative impact of the COVID-19 pandemic on three currencies—USD/JPY, AUD/USD, and USD/CHF—and positive significant impact on EUR/USD, GBP/USD, USD/CAD, and CHF/JPY. Investors can take short position in these while having long position in other currencies. The inferences drawn from the analysis are providing insight to investors and hedgers.

scholarly journals Long-Term Effects of Expiration of Derivatives on Indian Spot Volatility

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Sunita Narang ◽  
Madhu Vij
Keyword(s):  
Stock Exchange ◽  
Volume Effect ◽  
Indian Market ◽  
Long Term Effects ◽  
Daily Data ◽  
Asymmetric Garch ◽  
Regression Techniques ◽  
The Impact ◽  
Spot Volatility

This paper examines the impact of expiration of derivatives on spot volatility of Indian capital market. The review of the literature shows that the previous Indian studies have covered a period of only 4–6 years after the introduction of derivative trading in India in 2000. They are unanimous about volume effect but not about return and volatility effect. This paper uses regression techniques and one symmetric and three asymmetric GARCH models, namely, TGARCH, EGARCH, and PGARCH, to evaluate the impact. It uses daily data on popular index S&P CNX Nifty of National Stock Exchange of India, during a period of more than a decade from June 12, 2000 to January 10, 2012. Findings of the study show that spot returns, volume, and volatility are high on expiration day and they build up further on the day after expiry which shows that the Indian market is weakly efficient. The expiration effect is mainly due to concentration of volumes in near-month contracts and absence of physical settlement.

scholarly journals Derivative Trading and Spot Market Volatility: Evidence from Indian Market

2015 ◽  
Vol 1 (3) ◽  
pp. 23-34 ◽  
Author(s):  
Dhanya Alex ◽  
Roshna Varghese
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Unit Root Test ◽  
Spot Market ◽  
Descriptive Statistics ◽  
Garch Models ◽  
Indian Market ◽  
Stock Volatility ◽  
Asymmetric Behaviour ◽  
Indian Stock Market

The present study tries to estimate the effect of introduction of individual stock derivatives on the underlying stock volatility in Indian stock market. To estimate the effect of introduction of derivatives on stock market, GARCH family models which are known for their ability to model volatility. The return series of the ten companies were tested using methods like, unit root test and descriptive statistics to confirm that GARCH models could be used. Using these models, the asymmetric nature of stock returns and the volatility of stock returns on the introduction of derivatives are checked. The results reveal that the introduction of derivatives has decreased the volatility of the underlying stock returns. It was also found that most of the stock returns show asymmetric behaviour.

scholarly journals INVESTIGATING ABNORMAL VOLATILITY TRANSMISSION PATTERNS BETWEEN EMERGING AND DEVELOPED STOCK MARKETS: A CASE STUDY

2020 ◽  
Vol 21 (6) ◽  
pp. 1561-1592
Author(s):  
Cristi Spulbar ◽  
Jatin Trivedi ◽  
Ramona Birau
Keyword(s):  
Stock Market ◽  
Financial Markets ◽  
Stock Markets ◽  
Financial Integration ◽  
Global Financial Crisis ◽  
Spillover Effects ◽  
Garch Models ◽  
Asymmetric Garch ◽  
Developed Stock Markets ◽  
The Impact

The main aim of this paper is to investigate volatility spillover effects, the impact of past volatility on present market movements, the reaction to positive and negative news, among selected financial markets. The sample stock markets are geographically dispersed on different continents, respectively North America, Europe and Asia. We also investigate whether selected emerging stock markets capture the volatility patterns of developed stock markets located in the same region. The empirical analysis is focused on seven developed stock market indices, i.e. IBEX35 (Spain), DJIA (USA), FTSE100 (UK), TSX Composite (Canada), NIKKEI225 (Japan), DAX (Germany), CAC40 (France) and five emerging stock market indices, i.e. BET (Romania), WIG20 (Poland), BSE (India), SSE Composite (China) and BUX (Hungary) from January 2000 to June 2018. The econometric framework includes symmetric and asymmetric GARCH models i.e. EGARCH and GJR which are performed in order to capture asymmetric volatility clustering, interdependence, correlations, financial integration and leptokurtosis. Symmetric and asymmetric GARCH models revealed that all selected financial markets are highly volatile, including the presence of leverage effect. The stock markets in Hungary, USA, Germany, India and Canada exhibit high positive volatility after global financial crisis.

scholarly journals Testing an Algorithm with Asymmetric Markov-Switching GARCH Models in US Stock Trading

Symmetry ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 2346
Author(s):  
Oscar V. De la Torre-Torres ◽  
Dora Aguilasocho-Montoya ◽  
José Álvarez-García
Keyword(s):  
Markov Switching ◽  
Stock Index ◽  
Garch Models ◽  
Algorithmic Trading ◽  
Stock Trading ◽  
Markov Switching Models ◽  
Switching Models ◽  
Asymmetric Garch ◽  
The Impact ◽  
T Distribution

In the present paper, we extend the current literature in algorithmic trading with Markov-switching models with generalized autoregressive conditional heteroskedastic (MS-GARCH) models. We performed this by using asymmetric log-likelihood functions (LLF) and variance models. From 2 January 2004 to 19 March 2021, we simulated 36 institutional investor’s portfolios. These used homogenous (either symmetric or asymmetric) Gaussian, Student’s t-distribution, or generalized error distribution (GED) and (symmetric or asymmetric) GARCH variance models. By including the impact of stock trading fees and taxes, we found that an institutional investor could outperform the S&P 500 stock index (SP500) if they used the suggested trading algorithm with symmetric homogeneous GED LLF and an asymmetric E-GARCH variance model. The trading algorithm had a simple rule, that is, to invest in the SP500 if the forecast probability of being in a calm or normal regime at t + 1 is higher than 50%. With this configuration in the MS-GARCH model, the simulated portfolios achieved a 324.43% accumulated return, of which the algorithm generated 168.48%. Our results contribute to the discussion on using MS-GARCH models in algorithmic trading with a combination of either symmetric or asymmetric pdfs and variance models.

scholarly journals Impact of M&A Announcement on Stock Returns of Acquirer Companies: New Evidence from Indian Stock Market

2017 ◽  
Vol 3 (1) ◽  
pp. 86
Author(s):  
Richa Vij
Keyword(s):  
Stock Market ◽  
Mergers And Acquisitions ◽  
Stock Returns ◽  
Capital Market ◽  
Stock Return ◽  
Strong Form ◽  
Business Objectives ◽  
Indian Stock Market ◽  
The Impact ◽  
New Evidence

Mergers and Acquisitions (M&As) are often used as preferred tools of corporate structuring to serve a variety of business objectives and add value for the shareholders. Earlier studies have triggered a number of questions regarding the impact of M&As for the shareholders of acquiring companies. This paper focuses on the M&A among Indian companies and the response of the Indian capital market to such attempts as reflected in the changes in the stock return for different window periods close the M&A announcement. The findings of the present study suggest that there is significant impact of M&A announcement on stock returns for almost half of the sample acquirer companies. The study offers evidence in support of the contention that Indian stock market is not efficient in the semi-strong form with respect to M&A announcement information for acquirer companies and emphasizes that  investment analyst cannot ignore the information regarding the M&A deals.

scholarly journals Modelling Market Volatility with Univariate GARCH Models: Evidence from Nasdaq-100

2019 ◽  
Author(s):  
Fuzuli Aliyev ◽  
Richard Ajayi ◽  
Nijat Gasim
Keyword(s):  
Market Volatility ◽  
Stock Index ◽  
Garch Models ◽  
Leverage Effect ◽  
Daily Data ◽  
Asymmetric Garch ◽  
The Impact

This paper models and estimates the volatility of nonfinancial, innovative and hi-tech focused stock index, the Nasdaq-100, using univariate symmetric and asymmetric GARCH models. We employ GARCH, EGARCH and GJR-GARCH using daily data over the period January 4, 2000 through March 19, 2019. We find that the volatility shocks on the index returns are quite persistent. Furthermore, our findings show that the index has leverage effect, and the impact of shocks is asymmetric, whereby the impacts of negative shocks on volatility are higher than those of positive shocks of the same magnitude.

scholarly journals Impact of COVID-19 on Stock Market and Gold Returns in India

2021 ◽  
Vol 14 (27) ◽  
pp. 29-46
Author(s):  
Sarika MAHAJAN ◽  
◽  
Priya MAHAJAN ◽  
Keyword(s):  
Stock Market ◽  
Global Economy ◽  
Global Financial Crisis ◽  
Negative Impact ◽  
Arma Model ◽  
Garch Models ◽  
Stock Market Returns ◽  
Joint Dynamics ◽  
Asymmetric Garch ◽  
The Impact

The spread of COVID-19 has caused severe damage to human lives and the global economy. The stock markets around the world have plummeted to their lowest levels since the 2008 Global Financial Crisis. This paper attempts to examine the joint dynamics of gold and stock market returns during unprecedented times of health and financial shock due to COVID-19 between January 2020 and May 2020 using granger test, ARMA model, and symmetric and asymmetric GARCH models to improve the understanding of the microstructure of investment scenario in India. The period considered in the study helps to evaluate the impact of lockdown due to coronavirus on Gold and Nifty index return. Results based on GARCH and E-GARCH models indicate a significant negative impact of gold on nifty returns during the sample period. The results also indicate investors' perception of gold as a safe-haven asset during periods of elevated uncertainty. Thus, the study is expected to enhance the understanding of market asymmetry, the behavior of investors towards these avenues of investments, and information processing.

Sign in / Sign up

Export Citation Format

Share Document