scholarly journals Modelling and Estimation of Volatility Using ARCH/GARCH Models in Jordan’s Stock Market

2016 ◽  
Vol 8 (1) ◽  
pp. 152 ◽  
Author(s):  
Dana Mohammad AL-Najjar
Keyword(s):  
Stock Returns ◽  
Portfolio Management ◽  
Stock Exchange ◽  
Garch Models ◽  
Leverage Effect ◽  
Direct Role ◽  
Volatility Clustering ◽  
Financial Decisions ◽  
Stock Return Volatility ◽  
Amman Stock Exchange

<p>Financials have been concerned constantly with factors that have impact on both taking and assessing various financial decisions in firms. Hence modelling volatility in financial markets is one of the factors that have direct role and effect on pricing, risk and portfolio management. Therefore, this study aims to examine the volatility characteristics on Jordan’s capital market that include; clustering volatility, leptokurtosis, and leverage effect. This objective can be accomplished by selecting symmetric and asymmetric models from GARCH family models. This study applies; ARCH, GARCH, and EGARCH to investigate the behavior of stock return volatility for Amman Stock Exchange (ASE) covering the period from Jan. 1 2005 through Dec.31 2014. The main findings suggest that the symmetric ARCH /GARCH models can capture characteristics of ASE, and provide more evidence for both volatility clustering and leptokurtic, whereas EGARCH output reveals no support for the existence of leverage effect in the stock returns at Amman Stock Exchange.</p>

Macroeconomic Sensitivity, Risk-Return Trade-Off and Volatility Dynamics Evidence From Developed and Developing Markets

2019 ◽  
Vol 6 (1) ◽  
pp. 1-16
Author(s):  
Faisal Khan ◽  
Hashim Khan ◽  
Saif Ur-Rehman Khan ◽  
Muhammad Jumaa ◽  
Sharif Ullah Jan
Keyword(s):  
Stock Returns ◽  
Stock Return ◽  
Stock Exchange ◽  
Three Dimensions ◽  
Leverage Effect ◽  
Return Volatility ◽  
Macroeconomic Factors ◽  
Stock Return Volatility ◽  
Risk Return ◽  
The Impact

This study aims to examine the impact of macroeconomic factors on the stock return volatility along with the pricing of risk, and asymmetry and leverage effect on a comparative basis for the USA and UAE markets. Further, these three dimensions are also investigated with regard to various firm's features (such as firm's size and age). The daily data for the period 4th January 2010 to 29th December 2017 of firm stock returns from the New York Stock Exchange (NYSE), the Abu Dhabi Securities Exchange (ADSE), and the Dubai Financial Market (DFM) is considered and three time-series models were applied. The results from GARCH (1. 1) indicated that all the economic factors have significant impact on the stock return volatility in both the markets. Similarly, the study also found evidence of asymmetry & leverage effect using EGARCH in the NYSE (for all firms) and the UAE (partially). Finally, for a majority of the firms, a positive risk-return relationship is found in the UAE and a negative risk-return relationship is found in the NYSE using GARCH-in the mean. Interestingly, these results in context of both markets were different with respect to various firm features such as firm size and age. In light of these results, it is concluded that both the markets have different dynamics with regard to all three dimensions. Hence, the investors have a clear opportunity to diversify their risk and investments across developed and emerging markets.

scholarly journals Modelling volatility of Kuala Lumpur composite index (KLCI) using SV and garch models

2019 ◽  
Vol 13 (3) ◽  
pp. 1087
Author(s):  
Ezatul Akma Abdullah ◽  
Siti Meriam Zahari ◽  
S.Sarifah Radiah Shariff ◽  
Muhammad Asmu’i Abdul Rahim
Keyword(s):  
Stock Returns ◽  
Price Index ◽  
Financial Time Series ◽  
Composite Index ◽  
Garch Models ◽  
Financial Assets ◽  
Kuala Lumpur ◽  
Financial Decisions ◽  
Auto Regressive ◽  
Public Holidays

It is well-known that financial time series exhibits changing variance and this can have important consequences in formulating economic or financial decisions. In much recent evidence shows that volatility of financial assets is not constant, but rather that relatively volatile periods alternate with more tranquil ones. Thus, there are many opportunities to obtain forecasts of this time-varying risk. The paper presents the modelling volatility of the Kuala Lumpur Composite Index (KLCI) using SV and GARCH models.  Thus, the aim of this study is to model the KLCI stock market using two models; Stochastic Volatility (SV) and Generalized Auto-Regressive Conditional Heteroscedasticity (GARCH). This study employs an SV model with Bayesian approach and Markov Chain Monte Carlo (MCMC) sampler; and GARCH model with MLE estimator. The best model will be used to forecast the future volatility of stock returns. The study involves 971 daily observations of KLCI Closing price index, from 2 January 2008 to 10 November 2016, excluding public holidays. SV model is found to be the best based on the lowest RMSE and MAE values.

scholarly journals The Impact of Earnings Management on Stock Returns for Listed Industrial Firms on the Amman Stock Exchange

2019 ◽  
Vol 9 (3) ◽  
pp. 1
Author(s):  
Ahmed M. Al Omush ◽  
Walid M Masadeh ◽  
Rasha M. Zahran
Keyword(s):  
Earnings Management ◽  
Stock Returns ◽  
Management Practices ◽  
Stock Exchange ◽  
Financial Statements ◽  
Industrial Firms ◽  
Significance Level ◽  
Amman Stock Exchange ◽  
Study Population ◽  
Operating Cash Flow

This study aims to investigate the impacts of earning management on the stock returns of listed industrial firms on the Amman Stock Exchange, with the observance of (firm size and operating cash flow) as control variables for the study. In order to fulfill the purposes of this study, the researcher utilized (Jones model) and (Modified Jones model) to measure earning management through reliance on discretionary accruals as evidence of earnings management practices, and utilize (Market Return On the Stock model) to measure stock returns, and the study population was Mining and Extraction Industries firms also Food and Beverages firms listed in Amman Stock Exchange, the study was conducted on a sample of 18 firms which represents 75% of the study population for the period from 2014 to 2018, In addition to using descriptive and analytical approach to data collection, analysis, and testing hypotheses through financial statements of the firms in the study, the researcher has used the Statistical Package for Social Sciences (SPSS) program to test the hypotheses. This study creates many results some of which are: there is an insignificant relationship between earnings management practices and stock returns for listed industrial firms in Amman Stock Exchange during the study period at the significance level of 5%, Which reflects the poor efficiency in Amman Stock Exchange and not the information contained in the financial statements issued and therefore not impact stock prices, which in turn affects the stock returns, and there is an insignificant relationship between stock returns and operating cash flow at the level of significance of 5%, In addition found significant correlation between firm size and stock returns at the significance level of 1%. The researcher presented a set of recommendations; the following are most valuable: the importance of increasing the awareness of the relevant parties about the unreliability of financial statements issued by industrial companies listed on the Amman Stock Exchange in existence of the earnings management practice and not reflecting the information contained in the financial statements on prices and stock returns by holding seminars, conferences and meetings also Activating the role of audit committees further to be able to detect the practice of earnings management and decrease it.

scholarly journals Does Sustainability Engagement Affect Stock Return Volatility? Evidence from the Chinese Financial Market

2018 ◽  
Vol 10 (10) ◽  
pp. 3361 ◽  
Author(s):  
Junru Zhang ◽  
Hadrian Djajadikerta ◽  
Zhaoyong Zhang
Keyword(s):  
Stock Returns ◽  
Portfolio Management ◽  
Stock Return ◽  
Return Volatility ◽  
Chinese Stock Market ◽  
Stock Return Volatility ◽  
News Release ◽  
Volatility Persistence ◽  
Google Search ◽  
The Impact

This paper examines the impact of firms’ sustainability engagement on their stock returns and volatility by employing the EGARCH and FIGARCH models using data from the major financial firms listed in the Chinese stock market. We find evidence of a positive association between sustainability engagement and stock returns, suggesting firms’ sustainability news release in favour of the market. Although volatility persistence can largely be explained by news flows, the results show that sustainability news release has the significant and largest drop in volatility persistence, followed by popularity in Google search engine and the general news. Sustainability news release is found to affect positively stock return volatility. We also find evidence that market expectation can be driven by the dominant social paradigm when sustainability is included. These findings have important implications for market efficiency and effective portfolio management decisions.

scholarly journals The Relationship between Stock Returns and Trading Hours: Evidence from Amman Stock Exchange

2018 ◽  
Vol 7 (3.21) ◽  
pp. 89
Author(s):  
Buthiena Kharabsheh ◽  
Mahera Hani Megdadi ◽  
Waheeb Abu-ulbeh
Keyword(s):  
Stock Returns ◽  
Stock Exchange ◽  
Garch Model ◽  
Conditional Heteroscedasticity ◽  
Amman Stock Exchange ◽  
The Relationship ◽  
Autoregressive Conditional Heteroscedasticity

This study investigates the relationship between stock returns and trading hours for 22 shares listed on Amman Stock Exchange (ASE). We analyze the hourly trading data for the period Dec.2005 to Dec.2006. The two trading hours in ASE were split into four periods; first half of the first hour (10:00-10:30), second half of the first hour (10:30-11:00), first half of the second hour (11:00-11:30), and second half of the second hour (11:30-12:00). Using the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model, our results reveal that the hourly trading time significantly affects stock returns.  

scholarly journals Dynamic value at risk estimation for BELEX15

2011 ◽  
Vol 8 (1) ◽  
Author(s):  
Emilija Nikolić-Đorić ◽  
Dragan Đorić
Keyword(s):  
At Risk ◽  
Stock Returns ◽  
Long Memory ◽  
Value At Risk ◽  
Stock Exchange ◽  
Risk Estimation ◽  
Value Theory ◽  
Garch Models ◽  
Measurement Models ◽  
Standardized Residuals

This paper uses RiskMetrics, GARCH and IGARCH models to calculate daily VaR for Belgrade Stock Exchange index BELEX15 returns based on the normal and Student t innovation distribution. In the case of GARCH and IGARCH models VaR values are obtained applying Extreme Value Theory on the standardized residuals. The Kupiec's LR statistics was used to test the accuracy of risk measurement models. The main conclusions are: (1) when modelling value-at-risk it is very important to have a good model for volatility of stock returns; (2) both stationary and integrated GARCH models outperform RiskMetrics in estimating VaR; (3) although long memory volatility is present in the BELEX15 index, IGARCH models cannot outperform GARCH type models in VaR evaluations for this index.

scholarly journals Weak Form Efficiency of the Amman Stock Exchange: An Empirical Analysis (2000-2013)

2015 ◽  
Vol 11 (1) ◽  
pp. 173 ◽  
Author(s):  
Izz eddien N. Ananzeh
Keyword(s):  
Financial Markets ◽  
Stock Returns ◽  
Stock Prices ◽  
Stock Exchange ◽  
Weak Form ◽  
Efficient Market Hypothesis ◽  
Final Conclusion ◽  
Clear Cut ◽  
Amman Stock Exchange ◽  
Daily Returns

<p>The Efficient Market Hypothesis (EMH) has been a lot of debates in the literature of finance because of its important implication, and there is no clear-cut case regarding the efficiency of the financial markets for both developed and emerging markets. This empirical study conducted to examine EMH at the weak form level of Amman stock Exchange (ASE) by using daily observations for the period span from 2000 to 2013. Recent econometric procedures utilized for testing the randomness of stock prices for ASE. The results of serial correlation reject the existence of random walks in daily returns of the ASE, and the unit root tests also conclude the return series of ASE are stationary and inefficient at the weak-level. Also the runs tests verify that the stock returns series on ASE are not random, and our final conclusion reports that the ASE is inefficient at the weak form level. </p>

Volatility in the Indian Stock Market: Evidence from S&P CNX 500

2020 ◽  
Vol 17 (4) ◽  
pp. 1826-1830
Author(s):  
V. Shanthaamani ◽  
V. B. Usha
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Risk Premium ◽  
Conditional Variance ◽  
Leverage Effect ◽  
Volatility Clustering ◽  
Expected Stock Returns ◽  
High Volatility ◽  
Indian Stock Market ◽  
Daily Returns

This paper uses the Generalized Autoregressive Conditional Heteroskedastic models to estimate volatility (conditional variance) in the daily returns of the S&P CNX 500 index over the period from April 2007 to March 2018. The models include both symmetric and asymmetric models that capture the most common stylized facts about index returns such as volatility clustering and leverage effect. The empirical results show that the conditional variance process is highly persistent and provide evidence on the existence of risk premium for the S&P CNX 500 index return series which support the positive correlation hypothesis between volatility and the expected stock returns. Our findings also show that the asymmetric models provide better fit than the symmetric models, which confirms the presence of leverage effect. These results, in general, explain that high volatility of index return series is present in Indian stock market over the sample period.

scholarly journals Stock Return Volatility And Trading Volume Relationships Captured With Stable Paretian GARCH And Threshold GARCH Models

2012 ◽  
Vol 11 (1) ◽  
pp. 47 ◽  
Author(s):  
Atsuyuki Naka ◽  
Ece Oral
Keyword(s):  
Stock Returns ◽  
Trading Volume ◽  
Stock Return ◽  
Goodness Of Fit ◽  
Garch Models ◽  
Return Volatility ◽  
Font Size ◽  
Gaussian Models ◽  
Stock Return Volatility ◽  
Dow Jones Industrial Average

<span style="font-family: Times New Roman; font-size: small;"> </span><p style="margin: 0in 0.5in 0pt; text-align: justify;" class="MsoNormal"><span style="font-size: 10pt; mso-fareast-language: JA;"><span style="font-family: Times New Roman;">This paper examines the volatility of Dow Jones Industrial Average stock returns and the trading volume by employing stable Paretian GARCH and Threshold GARCH (TGARCH) models. Our results indicate that the trading volume significantly contributes to the volatility of stock returns. Additionally, strong leverage effects exist with negative shocks having a larger impact on volatility than positive shocks. The likelihood ratio tests and goodness of fit support the use of stable Paretian GARCH and TGARCH models over Gaussian models.</span></span></p><span style="font-family: Times New Roman; font-size: small;"> </span>

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