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).

scholarly journals CHALLENGES TO CHINA'S NEW STOCK MARKET FOR SMALL AND MEDIUM-SIZE ENTERPRISES: TRADING PRICE FALLS BELOW THE IPO PRICE

2014 ◽  
Vol 19 (Supplement_1) ◽  
pp. S409-S424 ◽  
Author(s):  
Haifeng Guo ◽  
Tienan Wang ◽  
Yijun Li ◽  
Hung-Gay Fung
Keyword(s):  
Stock Market ◽  
Initial Public Offerings ◽  
Stock Exchange ◽  
Medium Size ◽  
Probability Models ◽  
Market Returns ◽  
Stock Market Returns ◽  
Public Offerings ◽  
Turnover Ratio ◽  
Non Linear

This study discusses the development of the Growth Enterprise Board (GEB), a part of the Shenzhen Stock Exchange (SZSE), which allows small and medium-size enterprises (SMEs) to raise capital on favourable terms by issuing shares in China. We use all initial public offerings (IPOs) in the GEB market to model the probability of the trading price for new issues that will fall below their IPO price from October 2009 to December 31, 2011. Three probability models (logit, probit and scobit models) are used. The results show that four important factors explain the probability of trading price falling below their IPO price. A high first-day turnover ratio, a small price update, an optimistic stock market, and high average initial returns of other firms prior to an IPO issue all reduce the risk that the trading price will fall below the IPO price. The stock market returns have a non-linear significant effect on that probability. Our results are useful for regulators, underwriters, and issuers in the development of the GEB market.

scholarly journals Stock Market Returns and Shareholders’ Wealth Sustainability of Companies Listed on the Nigerian Stock Exchange

2020 ◽  
pp. 27-45
Author(s):  
Adekunle Orelope Koleosho ◽  
Folajimi Festus Adegbie ◽  
Ayooluwa Olotu Ajayi- Owoeye
Keyword(s):  
Stock Market ◽  
Stock Exchange ◽  
Market Price ◽  
Secondary Data ◽  
Target Population ◽  
Validity And Reliability ◽  
Market Returns ◽  
Stock Market Returns ◽  
Ex Post ◽  
Negative Effect

Sustainability of shareholder’s wealth has been a subject of discussion globally due to various decisions of the managers and the effect it has on company’s performance. Various corporate actions and information about the companies are disseminated over time and studies have shown the effect on shareholder's wealth. This study examined the effect of capital market returns on sustainability of shareholder's wealth in Nigeria Listed Companies. The study adopted ex-post facto research design. A sample of 57 companies from a target population of 168 companies listed on the Nigerian Stock Exchange (NSE) as December 2018 was randomly drawn across the various market sectors for the panel data. The study used secondary data from the NSE, CBN and companies’ data on the Bloomberg Terminals. Validity and reliability were premised on the statutory audit of the financial statement. The study adopted descriptive and inferential (Regression and Correlation) statistics to analyze the data. The study found that the stock market returns indicators (dividend per share, earnings and Leverage) have joint and statistically significant relationship with market price per share: DPS, EPS and LEV with Adjusted R2 = 0.738, F(3, 796) = 54.74, p = 0.108 > 0.05. The study concluded that stock market returns measured by dividend and earnings have a significant effect on the shareholders' wealth while leverage exerts a negative effect on Market Price per share. The study recommended that the management of the companies should embrace the payment of dividend to shareholders while ensuring the growth of earnings over the period to sustain shareholder's wealth.

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.

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 Stock Market Returns and Weather Anomaly: Evidence from an Emerging Economy

2012 ◽  
Vol 4 (5) ◽  
pp. 239-244 ◽  
Author(s):  
Hammad Hassan Mirza ◽  
Naveed Mushtaq .
Keyword(s):  
Stock Market ◽  
Stock Exchange ◽  
Weather Condition ◽  
Efficient Market Hypothesis ◽  
Emerging Economy ◽  
Market Returns ◽  
Stock Market Returns ◽  
Factors Affecting ◽  
Temperature Records ◽  
The Impact

Financial economists believe that the arbitrage forces in the market are the main reason of market efficiency and these forces are the fundamental concept of efficient market hypothesis (EMH). During last few years, various theoretical and empirical evidences have been presented to support the work of financial modeling for the markets with less than rational investors whose trading strategies are based on psychological factors like mood and emotions. Weather condition is among the substantial factors affecting investors’ mood and emotions. Present study investigates the impact of temperature on stock market returns in emerging economy of Pakistan. Using the daily temperature records and stock market indices of Karachi and Islamabad, the study has employed auto regressive (AR) – generalized autoregressive conditional heteroscedasticity (GARCH) model from 2006 to 2010. Based on AR (1)-GARCH (1, 1) estimation the study has found that weather temperatures of both Karachi and Islamabad are negatively related with Karachi Stock Exchange (KSE) and Islamabad Stock Exchange (ISE) index returns, respectively.

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.

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