Estimation of Price Volatility of Nifty 50 Index using ADF and GARCH (1, 1)

2021 ◽  
pp. 480-485
Keyword(s):  
Stock Market ◽  
Price Volatility ◽  
Research Area ◽  
Stock Market Index ◽  
Economic Sectors ◽  
Stock Market Returns ◽  
Market Index ◽  
Augmented Dickey Fuller ◽  
Portfolio Managers ◽  
Adf Test

Volatility is one of the critical variables to make an appropriate decision in investment. Volatility is a crucial research area in financial markets. So Portfolio managers, company treasurers, and risk arbitrageurs closely observe volatility trends resulting from changes in costs that affect their investment and decisions in risk management. The objective of the study was to examine the volatility of the Nifty 50 index based on the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model. Daily observations (3125) from March 3, 2008, to March 3, 2020, of stock market returns were used for analysis, and it helped to provide the volatility patterns. Augmented Dickey fuller was used to estimate volatility using the GARCH (1,) model to test stationary. The results of the ADF test revealed that financial data was stationary. The result indicated that the performance of the NIFTY 50 stock market index was highly volatile, leading to an excellent opportunity for long-term investment in any of the 12 economic sectors listed in the NIFTY 50 index.

scholarly journals Effect Of Macroeconomic Variables On Stock Market Returns For Four Emerging Economies: Brazil, Russia, India, And China

2011 ◽  
Vol 7 (3) ◽  
Author(s):  
Robert D. Gay, Jr.
Keyword(s):  
Stock Market ◽  
Emerging Economies ◽  
Stock Market Index ◽  
Market Returns ◽  
Stock Market Returns ◽  
Macroeconomic Variables ◽  
Share Prices ◽  
Market Index ◽  
The Relationship ◽  
India And China

The relationship between share prices and macroeconomic variables is well documented for the United States and other major economies. However, what is the relationship between share prices and economic activity in emerging economies? The goal of this study is to investigate the time-series relationship between stock market index prices and the macroeconomic variables of exchange rate and oil price for Brazil, Russia, India, and China (BRIC) using the Box-Jenkins ARIMA model. Although no significant relationship was found between respective exchange rate and oil price on the stock market index prices of either BRIC country, this may be due to the influence other domestic and international macroeconomic factors on stock market returns, warranting further research. Also, there was no significant relationship found between present and past stock market returns, suggesting the markets of Brazil, Russia, India, and China exhibit the weak-form of market efficiency.

scholarly journals The Impact of Covid-19 Spread on Stock Markets: The Case of the GCC Countries

2020 ◽  
Vol 13 (11) ◽  
pp. 16
Author(s):  
Nader Alber ◽  
Amr Saleh
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Stock Market Index ◽  
Market Returns ◽  
Stock Market Returns ◽  
Market Index ◽  
Stock Market Return ◽  
Gcc Countries ◽  
Developed Stock Markets ◽  
The Impact

This paper attempts to investigate the effects of 2020 Covid-19 world-wide spread on stock markets of GCC countries. Coronavirus spread has been measured by cumulative cases, new cases, cumulative deaths and new deaths. Coronavirus spread has been measured by numbers per million of population, while stock market return is measured by Δ in stock market index. Papers conducted in this topic tend to analyze Coronavirus spread in the highly infected countries and focus on the developed stock markets. Countries with low level of infection that have emerging financial markets seem to be less attractive to scholars concerning with Coronavirus spread on stock markets. This is why we try to investigate the GCC stock markets reaction to Covid-19 spread.   Findings show that there are significant differences among stock market indices during the research period. Besides, stock market returns seem to be sensitive to Coronavirus new deaths. Moreover, this has been confirmed for March without any evidence about these effects during April and May 2020.

scholarly journals Cointegration analysis of stock market index and exchange rate: The case of Serbian economy

2021 ◽  
pp. 59-71
Author(s):  
Milena Marjanović ◽  
Ivan Mihailović ◽  
Ognjen Dimitrijević
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Stock Market Index ◽  
Market Index ◽  
Long Run ◽  
Equilibrium Relationship ◽  
Short Run ◽  
The Exchange Rate ◽  
Adf Test ◽  
Long Run Equilibrium

Since the late 90's, the existence and direction of causality between the capital market and foreign exchange market have attracted significant attention of theoretical and empirical researchers. This is because both of these financial variables have an indisputable role in the development of each country's economy. In this paper we use Johansen procedure and Granger causality test to examine the existence and direction of short-run and long-run dynamics between the leading stock market index BELEX15 and RSD/EUR exchange rate in Serbia. Using ADF test we find that both series are integrated of order one, and since the value of Johansen trace statistics confirmed the existence of cointegration, we have proceeded with estimation of the VECM model. According to our VECM model, the BELEX15 index adjusts to the long-run equilibrium relationship at a rate of 11.72% in each period, while the exchange rate adjusts to the long-run equilibrium relationship at a rate of 2.73%. We also find that there is unidirectional causality and that the market index influences the exchange rate movements in the short-run in terms of Granger.

NONLINEARITIES AND GARCH INADEQUACY FOR MODELING STOCK MARKET RETURNS: EMPIRICAL EVIDENCE FROM LATIN AMERICA

2010 ◽  
Vol 15 (5) ◽  
pp. 713-724 ◽  
Author(s):  
Claudio A. Bonilla ◽  
Rafael Romero-Meza ◽  
Carlos Maquieira
Keyword(s):  
Stock Market ◽  
Latin American ◽  
Spillover Effects ◽  
Stock Index ◽  
Output Volatility ◽  
Stock Market Index ◽  
Market Returns ◽  
Stock Market Returns ◽  
Market Index ◽  
Data Generating Process

In this paper, we analyze the adequacy of using GARCH as the data-generating process to model conditional volatility of stock market index rates-of-return series. Using the Hinich portmanteau bicorrelation test, we find that a GARCH formulation or any of its variants fail to provide an adequate characterization for the underlying process of the main Latin American stock market indices. Policymakers need to be careful when using autoregressive models for policy analysis and forecast because the inadequacy of GARCH models has strong implications for the pricing of stock index options, portfolio selection, and risk management. In particular, measures of spillover effects and output volatility may not be correct when GARCH-type models are used to evaluate economic policy.

scholarly journals Oil Price And Stock Market Linkages In A Small And Oil Dependent Economy: The Case Of Greece

2010 ◽  
Vol 26 (4) ◽  
Author(s):  
Katrakilidis Constantinos ◽  
Lake Andreas Ektor ◽  
Mardas Dimitrios
Keyword(s):  
Stock Market ◽  
Oil Price ◽  
Causal Effects ◽  
Font Size ◽  
Stock Market Index ◽  
Market Returns ◽  
Stock Market Returns ◽  
Market Index ◽  
Causality Tests ◽  
Of Greece

<p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt; mso-pagination: none;"><span style="font-family: Times New Roman;"><span style="color: black; font-size: 10pt; mso-ansi-language: EN-US; mso-themecolor: text1;">We </span><span style="color: black; font-size: 10pt; mso-ansi-language: EN-GB; mso-themecolor: text1;" lang="EN-GB">investigate the dynamic linkages between oil prices and the stock market behaviour in a small and oil dependent economy. Particularly, we analyse empirically the relationships among stock market returns, the volatility of the stock market index, the oil price and the volatility of oil price in Greece. We employ VAR modelling in conjunction with Granger-causality tests. Contrary to the majority of the internationally reported evidence, our findings show the existence of significant positive causal effects from oil price changes on the stock market.</span></span><strong style="mso-bidi-font-weight: normal;"><span style="color: black; font-size: 10pt; mso-ansi-language: EN-US; mso-themecolor: text1;"></span></strong></p>

scholarly journals An Empirical Analysis of the Relationship between Oil Prices and Stock Markets

2016 ◽  
Vol 8 (12) ◽  
pp. 120 ◽  
Author(s):  
S. N. Markoulis ◽  
N. Neofytou
Keyword(s):  
Stock Market ◽  
Portfolio Management ◽  
Stock Markets ◽  
Oil Prices ◽  
Stock Market Index ◽  
Stock Market Returns ◽  
Bric Countries ◽  
Market Index ◽  
Long Run ◽  
The Relationship

This paper investigates the relationship between oil prices and stock market returns for the G7 and the BRIC countries for the period 1991-2016 using cointegration and a vector error correction model. Results reveal that there is no long-run relationship between oil prices and the stock market indices of the G7 countries. However, they also reveal that there is a long-run relationship between oil prices and the stock market indices of three out of the four BRIC countries (Brazil, China and Russia). This result appears to be broadly aligned with the idea that over the past quarter of a century emerging countries have been more exposed to oil prices (either as producers or consumers) than developed ones. Furthermore, from an investments’ and international portfolio management perspective, it seems that there might be benefits from diversification when holding the stock market index of a G7 country or India and oil assets since these appear to be segmented. On the other hand, such benefits might not be applicable in the case of the stock markets of Brazil, China or Russia and oil assets as these seem to be integrated.

scholarly journals Effect Of Macroeconomic Variables On Stock Market Returns For Four Emerging Economies: Brazil, Russia, India, And China

2016 ◽  
Vol 15 (3) ◽  
pp. 119-126 ◽  
Author(s):  
Robert D. Gay
Keyword(s):  
Stock Market ◽  
Emerging Economies ◽  
Stock Market Index ◽  
Market Returns ◽  
Stock Market Returns ◽  
Macroeconomic Variables ◽  
Share Prices ◽  
Market Index ◽  
The Relationship ◽  
India And China

The relationship between share prices and macroeconomic variables is well documented for the United States and other major economies.  However, what is the relationship between share prices and economic activity in emerging economies?  The goal of this study is to investigate the time-series relationship between stock market index prices and the macroeconomic variables of exchange rate and oil price for Brazil, Russia, India, and China (BRIC) using the Box-Jenkins ARIMA model.  Although no significant relationship was found between respective exchange rate and oil price on the stock market index prices of either BRIC country, this may be due to the influence other domestic and international macroeconomic factors on stock market returns, warranting further research.  Also, there was no significant relationship found between present and past stock market returns, suggesting the markets of Brazil, Russia, India, and China exhibit the weak-form of market efficiency.

scholarly journals Picking Buy-Sell Signals: A Practitioner’s Perspective on Key Technical Indicators for Selected Indian Firms

2019 ◽  
Vol 14 (3) ◽  
pp. 205-219 ◽  
Author(s):  
Talwar Shalini ◽  
Shah Pranav ◽  
Shah Utkarsh
Keyword(s):  
Stock Market ◽  
Stock Price ◽  
Moving Average ◽  
Relative Strength ◽  
Entry And Exit ◽  
Stock Market Index ◽  
Listed Firms ◽  
Market Index ◽  
Portfolio Managers ◽  
Good Risk

AbstractThe purpose of this study is to undertake technical analysis of selected companies included in the S&P CNX Nifty 50, a leading stock market index in India. We have used the stock price data of twenty leading listed firms in India for a period from January 1, 2012 through December 31, 2017. We have applied Guppy Multiple Moving Average (GMMA), Moving Average Convergence Divergence (MACD), Stochastic Relative Strength Index (Stoch RSI) and Average Directional Index (ADX) to Heikin Ashi charts to back test and provide entry and exit points for the players in the stock market. Analysis of the price information has revealed that the GMMA and ADX are effective indicators for most of the stocks under the study but they give late signals as compared to RSI and MACD. Further, the study has shown that though RSI and MACD give early signals, yet they are risky as the number of false signals generated by them is also found out to be quite high. The study is important as the findings can be used by investors, option traders and portfolio managers to get generate profitable trading signals and obtain good risk to reward ratios.

On the sensibility of the Pairs Trading strategy: the case of the FTS stock market index

2020 ◽  
Vol 38 (3) ◽  
Author(s):  
Ainhoa Fernández-Pérez ◽  
María de las Nieves López-García ◽  
José Pedro Ramos Requena
Keyword(s):  
Standard Deviation ◽  
Stock Market ◽  
Trading Strategy ◽  
Stock Market Index ◽  
Pairs Trading ◽  
Empirical Application ◽  
Statistical Arbitrage ◽  
Market Index ◽  
Standard Deviations ◽  
Using Data

In this paper we present a non-conventional statistical arbitrage technique based in varying the number of standard deviations used to carry the trading strategy. We will show how values of 1 and 1,2 in the standard deviation provide better results that the classic strategy of Gatev et al (2006). An empirical application is performance using data of the FST100 index during the period 2010 to June 2019.

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