scholarly journals The effect of ambiguity on the UK stock market: evidence from a new empirical approach

2017 ◽  
Vol 14 (4) ◽  
pp. 133-147
Author(s):  
Run Qing Tan ◽  
Viktor Manahov ◽  
Jacco Thijssen
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Prices ◽  
Linear Models ◽  
The Other ◽  
Var Model ◽  
Market Returns ◽  
Stock Market Returns ◽  
Bid Ask Spread ◽  
The Uk

This study developed a new ambiguity measure using the bid-ask spread. The results suggest that the degree of ambiguity has an impact on the daily UK stock market returns, but ambiguity does not cause changes in the returns. This implies that UK stock prices or returns cannot be predicted using variation in the degree of ambiguity through linear models, such as the VAR model, which was used in the study. The two sets of results in the study show that the degree of ambiguity from the previous two days might affect stock market returns. The authors observe that an increase in the degree of ambiguity two days ago is associated with a positive premium required by the investors. On the other hand, the degree of ambiguity tends to be affected by its past five-day values. Thus, the degree of ambiguity seems to persist for five days until investors update their priors. The intuition behind the result is that the degree of ambiguity can affect the returns of the UK stock market and UK stock market returns can in turn have an impact on the degree of ambiguity. The authors also observe that the degree of ambiguity does not seem to predict stock market returns in the UK when one applies linear models. However, this does not mean that there is no non-linear relationship between the degree of ambiguity and stock market returns or stock returns.

Volatility and cross correlations of stock markets in SAARC nations

2014 ◽  
Vol 3 (2) ◽  
pp. 154-169 ◽  
Author(s):  
Monica Singhania ◽  
Shachi Prakash
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Prices ◽  
Stock Markets ◽  
Cross Correlation ◽  
Global Market ◽  
Market Returns ◽  
Stock Market Returns ◽  
Content Type ◽  
Stock Indices

Purpose – The purpose of this paper is to examine cross-correlation in stock returns of SAARC countries, conditional and unconditional volatility of stock markets and to test efficient market hypothesis (EMH). Design/methodology/approach – Stock indices of India, Bangladesh, Sri Lanka and Pakistan are considered to serve as proxy for stock markets in SAARC countries. Data consist of daily closing price of stock indices from 2000 to 2011. Since preliminary testing indicated presence of serial autocorrelation and volatility clustering, family of GARCH models is selected. Findings – Results indicate presence of serial autocorrelation in stock market returns, implying dependence of current stock prices on stock prices of previous times and leads to rejection of EMH. Significant relationship between stock market returns and unconditional volatility indicates investors’ expectation of extra risk premium for exposing their portfolios to unexpected variations in stock markets. Cross-correlation revealed level of integration of South Asian economies with global market to be high. Research limitations/implications – Business cycles and other macroeconomic developments affect most companies and lead to unexplained relationships. The paper finds stock markets to exist at different levels of development as economic liberalization started at different points of time in SAARC countries. Practical implications – Correlation between stock indices of SAARC economies are found to be low which is in line with intra-regional trade being one of lowest as compared to other regional groups. Results point towards greater need for economic cooperation and integration between SAARC countries. Greater financial integration leads to development of markets and institutions, effective price discovery, higher savings and greater economic progress. Originality/value – The paper focuses on EMH and risk return relation for SAARC nations.

A quantile regression approach to evaluate the relative impact of global and local factors on the MENA stock markets

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Slah Bahloul ◽  
Nawel Ben Amor
Keyword(s):  
Stock Market ◽  
Quantile Regression ◽  
Stock Returns ◽  
Stock Markets ◽  
Financial Integration ◽  
Ordinary Least Squares ◽  
Market Returns ◽  
Stock Market Returns ◽  
Content Type ◽  
The Impact

PurposeThis paper investigates the relative importance of local macroeconomic and global factors in the explanation of twelve MENA (Middle East and North Africa) stock market returns across the different quantiles in order to determine their degree of international financial integration.Design/methodology/approachThe authors use both ordinary least squares and quantile regressions from January 2007 to January 2018. Quantile regression permits to know how the effects of explanatory variables vary across the different states of the market.FindingsThe results of this paper indicate that the impact of local macroeconomic and global factors differs across the quantiles and markets. Generally, there are wide ranges in degree of international integration and most of MENA stock markets appear to be weakly integrated. This reveals that the portfolio diversification within the stock markets in this region is still beneficial.Originality/valueThis paper is original for two reasons. First, it emphasizes, over a fairly long period, the impact of a large number of macroeconomic and global variables on the MENA stock market returns. Second, it examines if the relative effects of these factors on MENA stock returns vary or not across the market states and MENA countries.

Weather, investor psychology and stock returns: evidence from Fiji's stock market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Janesh Sami
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Sunshine Duration ◽  
Market Returns ◽  
Modeling Framework ◽  
Stock Market Returns ◽  
Content Type ◽  
Asset Pricing Models ◽  
Weather Changes ◽  
Practical Implications

PurposeThis paper investigates whether weather affects stock market returns in Fiji's stock market.Design/methodology/approachThe author employed an exponential general autoregressive conditional heteroskedastic (EGARCH) modeling framework to examine the effect of weather changes on stock market returns over the sample period 9/02/2000–31/12/2020.FindingsThe results show that weather (temperature, rain, humidity and sunshine duration) have robust but heterogenous effects on stock market returns in Fiji.Research limitations/implicationsIt is useful for scholars to modify asset pricing models to include weather-related variables (temperature, rain, humidity and sunshine duration) to better understand Fiji's stock market dynamics (even though they are often viewed as economically neutral variables).Practical implicationsInvestors and traders should consider their mood while making stock market decisions to lessen mood-induced errors.Originality/valueThis is the first attempt to examine the effect of weather (temperature, rain, humidity and sunshine duration) on stock market returns in Fiji's stock market.

scholarly journals Forecasting stock returns on the Amman Stock Exchange: Do neural networks outperform linear regressions?

2021 ◽  
Vol 18 (4) ◽  
pp. 280-296
Author(s):  
Abdel Razzaq Al Rababa’a ◽  
Zaid Saidat ◽  
Raed Hendawi
Keyword(s):  
Stock Market ◽  
Regression Models ◽  
Linear Models ◽  
Stock Exchange ◽  
Market Returns ◽  
Stock Market Returns ◽  
Statistical Measures ◽  
Amman Stock Exchange ◽  
Non Linear ◽  
Ann Models

Different models have been used in the finance literature to predict the stock market returns. However, it remains an open question whether non-linear models can outperform linear models while providing accurate predictions for future returns. This study examines the prediction of the non-linear artificial neural network (ANN) models against the baseline linear regression models. This study aims specifically to compare the prediction performance of regression models with different specifications and static and dynamic ANN models. Thus, the analysis was conducted on a growing market, namely the Amman Stock Exchange. The results show that the trading volume and interest rates on loans tend to explain the monthly returns the most, compared to other predictors in the regressions. Moreover, incorporating more variables is not found to help in explaining the fluctuations in the stock market returns. More importantly, using the root mean square error (RMSE), as well as the mean absolute error statistical measures, the static ANN becomes the most preferred model for forecasting. The associated forecasting errors from these metrics become equal to 0.0021 and 0.0005, respectively. Lastly, the analysis conducted with the dynamic ANN model produced the highest RMSE value of 0.0067 since November 2018 following the amendment to the Jordanian income tax law. The same observation is also seen since the emerging of the COVID-19 outbreak (RMSE = 0.0042).

Do global sentiment shocks spillover towards emerging and frontier markets?

2020 ◽  
Vol 47 (3) ◽  
pp. 433-465 ◽  
Author(s):  
Mobeen Ur Rehman ◽  
Nicholas Apergis
Keyword(s):  
Stock Market ◽  
Regime Switching ◽  
Linear Models ◽  
Market Returns ◽  
Markov Regime Switching ◽  
Stock Market Returns ◽  
Content Type ◽  
Regime Switching Model ◽  
Switching Model ◽  
Investor Sentiments

PurposeThis study aims to investigate the impact of sentiment shocks based on US investor sentiments, bearish and bullish market conditions. Earlier studies, though very few, only consider the effect of investor sentiments on stock returns of emerging frontier Asian (EFA) markets.Design/methodology/approachThis study uses the application of regime switching model because of its capability to explore time-varying causality across different regimes unlike traditional linear models. The Markov regime switching model uses regime switching probabilities for capturing the potential asymmetries or non-linearity in a model, in this study’s case, thereby adjusting investor sentiments shocks to stock market returns.FindingsThe results of the Markov regime switching method suggests that US sentiment, bullish and bearish market shocks act as a main contributors for inducing variation in EFA stock market returns. The study’s non-parametric robustness results highlight an asymmetric relationship across the mean series, whereas a symmetric relationship across variance series. The study also reports Thailand as the most sensitive market to global sentiment shocks.Research limitations/implicationsThe sensitivity of the EFA markets to these global sentiment shocks highlights their sensitivity and implications for investors relying merely on returns correlation and spillover. These findings also suggest that spillover from developed to emerging and frontier equity markets only in the form of returns following traditional linear models may not be appropriate.Practical implicationsThis paper supports the behavioral aspect of investors and resultant spillover from developed market sentiments to emerging and frontier market returns across international equity markets offering more rational justification for an irrational behavior.Originality/valueThe study’s motivation to use the application of regime switching models is because of its capability to explore time-varying causality across different regimes unlike traditional linear models. The Markov regime switching model uses regime switching probabilities for capturing the potential asymmetries or non-linearity in a model, in the study’s case, thereby adjusting investor sentiments shocks to stock market returns. It is also useful of the adjustment attributable to exogenous events.

Effects of Daylight-Saving Time Changes on Stock Market Returns and Stock Market Volatility: Rebuttal

2013 ◽  
Vol 112 (1) ◽  
pp. 89-99 ◽  
Author(s):  
Mark J. Kamstra ◽  
Lisa A. Kramer ◽  
Maurice D. Levi
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Market Volatility ◽  
Stock Market Volatility ◽  
Market Returns ◽  
Stock Market Returns ◽  
Daylight Saving Time ◽  
Daylight Saving ◽  
Time Changes ◽  
Saving Effect

In a 2011 reply to our 2010 comment in this journal, Berument and Dogen maintained their challenge to the existence of the negative daylight-saving effect in stock returns reported by Kamstra, Kramer, and Levi in 2000. Unfortunately, in their reply, Berument and Dogen ignored all of the points raised in the comment, failing even to cite the Kamstra, et al. comment. Berument and Dogen continued to use inappropriate estimation techniques, over-parameterized models, and low-power tests and perhaps most surprisingly even failed to replicate results they themselves reported in their previous paper, written by Berument, Dogen, and Onar in 2010. The findings reported by Berument and Dogen, as well as by Berument, Dogen, and Onar, are neither well-supported nor well-reasoned. We maintain our original objections to their analysis, highlight new serious empirical and theoretical problems, and emphasize that there remains statistically significant evidence of an economically large negative daylight-saving effect in U.S. stock returns. The issues raised in this rebuttal extend beyond the daylight-saving effect itself, touching on methodological points that arise more generally when deciding how to model financial returns data.

scholarly journals Reaction of stock market returns to COVID-19 pandemic and lockdown policy: evidence from Nigerian firms stock returns

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Isiaka Akande Raifu ◽  
Terver Theophilus Kumeka ◽  
Alarudeen Aminu
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Exchange ◽  
Estimation Methods ◽  
Panel Var ◽  
Impulse Response Functions ◽  
Market Returns ◽  
Stock Market Returns ◽  
Long Run ◽  
Policy Shocks

AbstractGiven the effects COVID-19 pandemic on the financial sectors across the world, this study examined the reaction of stock returns of 201 firms listed in the Nigerian Stock Exchange to the COVID-19 pandemic and lockdown policy. We deployed both Pooled OLS and Panel VAR as estimation methods. Generally, the results from POLS show the stock market returns of the Nigerian firms reacted negatively more to the global COVID-19 confirmed cases and deaths than the domestic COVID-19 confirmed cases and deaths and lockdown policy. The results of the impulse response functions revealed that the effects of COVID-19 confirmed cases and deaths and lockdown policy shocks on stock returns oscillate between negative and positive before the stock market returns converge to the equilibrium in the long run. The FEVD results showed that growth in the COVID-19 confirmed cases, deaths and lockdown policy shocks explained little variations in stock market returns. Given our finding, we advocate for the relaxation of policy of lockdown and the combine use of monetary and fiscal policies to mitigate the negative effect of COVID-19 pandemic on stock market returns in Nigeria.

scholarly journals Measuring Stock Market Predictability with Implications of Financial Ratios: An Empirical Investigation of Pakistan Stock Market

2020 ◽  
Vol 12 (2) ◽  
Author(s):  
Abdul Samad Shaikh ◽  
Muhammad Kashif ◽  
Sadia Shaikh
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Exchange ◽  
Strong Predictor ◽  
Generalized Least Squares ◽  
Financial Ratios ◽  
Arbitrage Pricing Theory ◽  
Market Returns ◽  
Stock Market Returns ◽  
Study Results

This paper investigates the financial ratios prediction on Stock Market Returns for Pakistan Stock Exchange. The research includes three financial ratios; Dividend Yield (DY), Earning Yield Ratio (EYR) and Book-to-Market Ratio (B/M); that have been observed through past researchers as predictors of Stock Market Returns. The theoretical framework is based on Arbitrage Pricing Theory and Capital Asset Pricing Model CAPM by Roll and Ross (1977) and Fama-French 3 factor (1992). Generalized Least Squares (GLS) is applied to estimate the predictive regressions, Cointegration runs are applied to evaluate the long-term relationship, and Generalized Methods of Moments (GMM) to measure the moments over the years and fluctuations in stock returns. The study results show financial ratios as strong predictor of stock return in Pakistan Stock Exchange, the GMM analyses reveal that the EYR has the higher predictive power than DY and B/M respectively. Furthermore, it is found that the financial ratios predictability is enhanced when ratios are combined in the multiple predictive regression models. The research findings are useful for the stock market investors to evaluate their decisions and for academic researchers to evaluate the stock market and investment predictability.

scholarly journals FACTORS DETERMINING STOCK MARKET RETURNS: CASE OF NAIROBI STOCK EXCHANGE

2016 ◽  
Vol 1 (1) ◽  
pp. 108
Author(s):  
Samson Okoth Ondiek ◽  
Dr. Ongoro
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Significant Relationship ◽  
Unique Contribution ◽  
Market Returns ◽  
Macroeconomic Factors ◽  
Stock Market Returns ◽  
Book Value ◽  
Company Stock ◽  
The Government

AbstractPurpose: The study attempts to establish if the changing macroeconomic factors and the industry variables can predict the variation on the Nairobi Security Exchange stocks return Methodology: It adopted a regression model that related stock returns to various selected macro and micro economic factors and used data of 20 companies that constitute the NSE index. The study used monthly data spanning the year 2006 to 2010.Results: The regression results indicate that, four of the variables i.e. market return (NSEI), exchange rate for US/KSH, market to book value ratio have a positive and significant relationship with an individual company stock market returns. Risk Free rate (91 Treasury bill rate) also had a positive and significant relationship while industrial growth opportunity and inflation were found to be negative and significant. leverage on the other hand was found to be insignificant and therefore does not influence individual company stock market returns. Unique contribution to theory, practice and policy: These findings will have significant effects on investors’ investment decisions making as well as the Government and the capital markets authority (CMA) in the formulation of polices and guidelines. Once factor betas are estimated, we can describe the expected change in security returns with respect to changes in a given factor and thus giving the investors, CMA and the Government a better understanding on the effect of a change in the fiscal and monetary policies in the stock market. This is crucial to the Government as it seeks to promote the capital market as a source of alternative funding for economic growth. Investors wishing to construct portfolios should also consider the trends of the inflation rates, exchange rates, market to book value ratio, industrial production and the stock market.  The rise of either of this micro and macroeconomic indicators may influence the returns positively or negatively and hence the investor may choose the best time to either buy or sell their securities

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