scholarly journals Predictive Power of Output Growth, Inflation, and Interest Rate on Stock Return and Volatility: A Comparison

2010 ◽  
Author(s):  
Wai Ching Poon ◽  
Gee Kok Tong
Keyword(s):  
Interest Rate ◽  
Emerging Markets ◽  
Stock Returns ◽  
Stock Return ◽  
Predictive Power ◽  
Output Growth ◽  
Stock Market Volatility ◽  
Monthly Data ◽  
Stock Return Volatility ◽  
Economic Volatility

Using monthly data from seven mature and emerging markets and a battery of GARCH and EGARCH models, the study of Davis and Kutan (2003) on inflation and output on stock returns and volatility is extended by including interest rate to compare the effect between three mature markets (US, Japan, and Singapore) and four emerging markets who experienced a crisis before (Malaysia, India, Korea, and Philippines). It is found that economic volatility, as measured by movement in inflation, output growth, and interest rate, have a weak predictor power for stock market volatility and returns. In line with the evidence reported in Davis and Kutan (2003), the findings suggest that there is no support for the Fisher effect in stock returns among the seven mature and emerging markets.   Keywords: Predictive power; output; inflation; interest rate; stock return volatility.  

scholarly journals Prediction of Stock Returns: A New Way to Look at It

2003 ◽  
Vol 33 (02) ◽  
pp. 399-417 ◽  
Author(s):  
Jens Perch Nielsen ◽  
Stefan Sperlich
Keyword(s):  
Interest Rate ◽  
Stock Market ◽  
Stock Returns ◽  
Stock Return ◽  
Predictive Power ◽  
Financial Models ◽  
Price Ratio ◽  
Finite Samples ◽  
One Year

While the traditional R 2 value is useful to evaluate the quality of a fit, it does not work when it comes to evaluating the predictive power of estimated financial models in finite samples. In this paper we introduce a validated value useful for prediction. Based on data from the Danish stock market, using this measure we find that the dividend-price ratio has predictive power. The best horizon for prediction seems to be four years. On a one year horizon, we find that while inflation and interest rate do not add to the predictive power of the dividend-price ratio then last years excess stock return does.

Stock Returns and Volatility: Evidence from Select Emerging Markets

2009 ◽  
Vol 12 (04) ◽  
pp. 567-592 ◽  
Author(s):  
Ravinder Kumar Arora ◽  
Himadri Das ◽  
Pramod Kumar Jain
Keyword(s):  
Emerging Markets ◽  
Stock Returns ◽  
Stock Return ◽  
Leverage Effect ◽  
Return Volatility ◽  
Stock Return Volatility ◽  
Developed Markets ◽  
Return Distributions ◽  
The Mean ◽  
Return Data

This paper investigates the behavior of stock returns and volatility in 10 emerging markets and compares them with those of developed markets under different measures of frequency (daily, weekly, monthly and annual) over the period January 1, 2002 to December 31, 2006. The ratios of mean return to volatility for emerging markets are found to be higher than those of developed markets. Sample statistics for stock returns of all emerging and developed markets indicate that return distributions are not normal and return volatility shows clustering. In most cases, GARCH (1, 1) specification is adequate to describe the stock return volatility. The significant lag terms in the mean equation of GARCH specification depend on the frequency of the return data. The presence of leverage effect in volatility behavior is examined using the TAR-GARCH model and the evidence indicates that is not present across all markets under all measures of frequency. Its presence in different markets depends on the measure of frequency of stock return data.

scholarly journals Contemporaneous Relationship between Trading Volume and Stock Returns Volatility : Evidence from Nepalese Stock Market

2017 ◽  
Vol 10 (1) ◽  
pp. 40-63
Author(s):  
Shivaram Shrestha
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Trading Volume ◽  
Stock Return ◽  
Efficient Market Hypothesis ◽  
Least Square ◽  
Return Volatility ◽  
Monthly Data ◽  
Stock Return Volatility ◽  
Mixture Of Distribution Hypothesis

This paper examines the contemporaneous relation between trading volume and stock returns volatility for Nepalese stock market using monthly data for the period 2005 mid-July to 2017 mid-April. The study uses ordinary least square method and analyzes whether rising price leads to higher volume or vice versa. The study also investigates the association between trading volume and stock returns volatility based on monthly data of NEPSE index and examines the effects of trading volume on stock returns volatility using GARCH (1, 1) model. The study finds positive contemporaneous relationship between trading volume and stock return volatility. The study result indicates that the relationship between trading volume and return volatility is asymmetric. The findings strongly support the hypothesis that higher trading volume is associated with an increase in stock return volatility, but offers little support to the sequential arrival hypothesis and the mixture of distribution hypothesis. Finally, the findings support the weak-form efficient market hypothesis in Nepalese stock market.

Investor sentiment and stock return volatility: evidence from the Indian Stock Exchange

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sreenu N ◽  
Suresh Naik
Keyword(s):  
Asset Pricing ◽  
Stock Market ◽  
Stock Returns ◽  
Stock Return ◽  
Stock Exchange ◽  
Investor Sentiment ◽  
Return Volatility ◽  
Stock Market Volatility ◽  
Content Type ◽  
Stock Return Volatility

PurposeIn any stock market, volatility is a significant factor in strengthening their asset pricing. The upsurge in volatility in the stock market can activate and bring changes in the financial risk. According to financial conventional theory, the stakeholders (investors) are selected to be balanced and variations in pertinent risk are also to be anticipated due to the outcome of the drive-in basic factors in Indian stock markets. The hypothesis shows that there are actions in systematic and unsystematic risks that are determined by volatility. It is allied to sentiment-driven in the trader movement.Design/methodology/approachThe paper used the methodology of generalized autoregressive conditional heteroskedasticity-in mean GARCH-M and exponential GARCH-M (E-GARCH-M) methods on the Indian stock market. The data have been covered from 2000 to 2019.FindingsFinally, the study suggests that due to the unfitness of the capital asset pricing model (CAPM), the selection has enhanced with sentiment is an important risk factor.Practical implicationsThe investor sentiment and stock return volatility statement are established by using the investor sentiment amalgamated stock market index built.Originality/valueThe outcome of the study shows that there is an important association between stakeholder (investor) sentiment and stock return, in case of volatility behavioural finance can significantly explain the behaviour of stock returns on the Indian Stock Exchange.

scholarly journals Prediction of Stock Returns: A New Way to Look at It

2003 ◽  
Vol 33 (2) ◽  
pp. 399-417 ◽  
Author(s):  
Jens Perch Nielsen ◽  
Stefan Sperlich
Keyword(s):  
Interest Rate ◽  
Stock Market ◽  
Stock Returns ◽  
Stock Return ◽  
Predictive Power ◽  
Financial Models ◽  
Price Ratio ◽  
Finite Samples ◽  
One Year

While the traditionalR2value is useful to evaluate the quality of a fit, it does not work when it comes to evaluating the predictive power of estimated financial models in finite samples. In this paper we introduce a validatedvalue useful for prediction. Based on data from the Danish stock market, using this measure we find that the dividend-price ratio has predictive power. The best horizon for prediction seems to be four years. On a one year horizon, we find that while inflation and interest rate do not add to the predictive power of the dividend-price ratio then last years excess stock return does.

scholarly journals The Impact of Interest Rate Volatility on Stock Returns Volatility: Empirical Evidence from Pakistan Stock Exchange

2021 ◽  
Vol 3 (2) ◽  
pp. 53-58
Author(s):  
ARIF HUSSAIN ◽  
AHMAD BILAL HUSSAIN ◽  
SHAHID ALI
Keyword(s):  
Interest Rate ◽  
Stock Returns ◽  
Stock Return ◽  
Stock Exchange ◽  
Stock Volatility ◽  
Stock Return Volatility ◽  
Interest Rate Volatility ◽  
Volatility Models ◽  
Short Run ◽  
Auto Regressive

Apprehension pertaining to Stock return volatility always has been producing the appreciable significance in the various current research works and it has been lucrative to many researchers for forecasting stock market volatility. This study is about the forecasting of stock returns volatility on the basis of interest rate volatility in the well established Pakistan Stock Exchange (PSX). The stock returns are calculated on the basis of KSE 100 index and interest rate volatility is calculated on the basis of monthly treasury bills rate during a period of 1994 to 2016. Various volatility models like Auto Regressive Conditional Heteroscedasticity (ARCH) and Generalized Auto Regressive Conditional Heteroscedasticity (GARCH) were used to predict stock return volatility on the basis of interest rate volatility in Pakistan. ARCH model is one of the well known methods to forecast the error term in the data and which will certain our forecast regarding stock prices. In the Pakistan Stock Exchange the ARCH (1, 1) has been statistically significantly proved. The GARCH (1, 1) model is also used to estimate the stock volatility. This model shows the short run volatility affect the lagged stock returns and is contributing to the overall volatility. The sum of α and β is less than 1 so the short run volatility is positively related to the overall stock volatility. The GARCH (1, 1) model has outperformed the other volatility models in the case of Pakistan Stock Exchange.

scholarly journals PENGARUH LOAN TO DEPOSITE RATIO, RETURN ON ASSETS, CAPITAL ADEQUACY RATIO, EXCHANGE RATE DAN INTEREST RATE TERHADAP RETURN SAHAM

2017 ◽  
Vol 19 (3) ◽  
pp. 340
Author(s):  
Ketut Asmara Jaya
Keyword(s):  
Exchange Rate ◽  
Interest Rate ◽  
Stock Returns ◽  
Significant Influence ◽  
Stock Return ◽  
Random Effect ◽  
Capital Adequacy ◽  
Return On Assets ◽  
Capital Adequacy Ratio ◽  
Lm Test

Pertumbuhan pasar modal pada akhir tahun 2010 menunjukkan kinerja yang luar biasa dengan meningkatnya kembali nilai saham dengan dipengaruhi oleh berbagai faktor, baik faktor internal ataupun faktor eksternal dari setiap perusahaan. Studi ini menganalisis untuk pinjaman deposit rasio (LDR), pengembalian asset (ROA), rasio kecukupan modal (CAR), nilai tukar dan suku bunga yang berdampak pada keuntungan saham di perusahaan perbankan. Studi panel ini menggunakan data LM test statistik yang menunjukkan perhitungan metode random effect adalah cara yang lebih tepat digunakan untuk mengestimasi model dalam penelitian ini. Hasil studi menunjukkan bahwa variabel ROA memberikan pengaruh positif dan signifikan dalam return saham. Sedangkan variabel LDR, CAR dan Kurs tidak ada pengaruh yang signifikan terhadap return saham, dan hanya kecenderungan jika LDR, CAR dan Kurs meningkat maka return saham dapat meningkat pula Suku bunga variabel tidak memberikan pengaruh positif dan pengaruh signifikan karena tidak memiliki hubungan dengan return saham.Growth of Capital market in late 2010 showed outstanding performance with rising of stock return which is influenced by various factors, both internal factors and external factors of each company it self. This study analyzes the Loan To Deposite Ratio (LDR), Return On Assets (ROA), Capital Adequacy Ratio (CAR), Exchange Rate and Interest Rate impact on stock returns in corporate banking. This study uses panel data with LM Test statistical calculation it is shown that Random Effect method is more precise to be used in this study. The result of the study shown that ROA variable gives positive and significant influence in stock return. While LDR, variables CAR and exchange rate of no influence and significantly to return stock, and only tendency if LDR, CAR and exchange rate increase then return shares can be increased as well. The Interest Rate variable did not give positive and significant influence because of not having relationship with stock return.

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.

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