Stock Price Variations Research Articles

Fractional Neuro-Sequential ARFIMA-LSTM for Financial Market Forecasting

Forecasting of fast fluctuated and high-frequency financial data is always a challenging problem in the field of economics and modelling. In this study, a novel hybrid model with the strength of fractional order derivative is presented with their dynamical features of deep learning, long-short term memory (LSTM) networks, to predict the abrupt stochastic variation of the financial market. Stock market prices are dynamic, highly sensitive, nonlinear and chaotic. There are different techniques for forecast prices in the time-variant domain and due to variability and uncertain behavior in stock prices, traditional methods, such as data mining, statistical approaches, and non-deep neural networks models are not suited for prediction and generalized forecasting stock prices. While autoregressive fractional integrated moving average (ARFIMA) model provides a flexible tool for classes of long-memory models. The advancement of machine learning-based deep non-linear modelling confirms that the hybrid model efficiently extracts profound features and model non-linear functions. LSTM networks are a special kind of recurrent neural network (RNN) that map sequences of input observations to output observations with capabilities of long-term dependencies. A novel ARFIMA-LSTM hybrid recurrent network is presented in which ARFIMA model-based filters having the linear tendencies better than ARIMA model in the data and passes the residual to the LSTM model that captures nonlinearity in the residual values with the help of exogenous dependent variables. The model not only minimizes the volatility problem but also overcome the over fitting problem of neural networks. The model is evaluated using PSX company data of the stock market based on RMSE, MSE and MAPE along with a comparison of ARIMA, LSTM model and generalized regression radial basis neural network (GRNN) ensemble method independently. The forecasting performance indicates the effectiveness of the proposed AFRIMA-LSTM hybrid model to improve around 80% accuracy on RMSE as compared to traditional forecasting counterparts.

Determinant of Bid - Ask Spread Share on LQ45 Index Emitents in Indonesia

The rapid development of capital market activities has brought profound changes to the demands of information quality. The issue surrounding stock prices is one indicator that investors consider to invest. So the difference between the selling price and the purchase price of a stock (spread) affects the level of liquidity of the stock. Factors also influence the Bid-Ask Spread, one of which is the stock price. When the stock price is high, it means that the shares are actively traded. Not only stock prices, stock price volatility is also considered to affect investment risk and uncertainty, as seen from fluctuations in stock price volatility. Another variable is the trading volume which describes the activity of the number of shares traded on the capital market, so that indirectly the trading volume of a security gives an influence on the Bid-Ask Spread. The study was conducted on Issuers listed in the LQ45 index for the period January 2016 - July 2019 on the Indonesia Stock Exchange. A sample of 31 companies with secondary data from the LQ45 report published by the Indonesia Stock Exchange. The study uses analysis techniques used to test the hypotheses in this study is the Panel Data Regression Method with the help of Eviews Application. The model chosen is the fixed effect model with the results of negative and significant stock price variables and other variables namely stock volatility, trading volume and positive and significant company size on the bid ask spread. All research variables together have a significant effect on Bid Ask Spread.

Dividend policy and stock price volatility in Indian capital market

As argued by Modigilani & Miller, the dividends are irrelevant only in perfect markets but in an emerging market like India, the dividends are expected to show its relevance. Indian capital market have surpassed a sea change in the recent past including demonetization, implementation of new tax regimes, political controversies and the like. Despite these facts, the Indian capital markets soars at many a times due to its active trading. Against this backdrop, this research paper seeks to examine the relationship between dividend policies and share price volatility. The motivation behind this research is to first time employ a powerful unbiased volatility estimator, created by Yang and Zhang that is 14 times as efficient as close to close estimate. A sample of 116 textiles companies, listed and actively traded in Bombay Stock Exchange of India (BSE) from 2008 to 2017 selected for the study. In examining the impact of dividend policy on share price volatility in Indian capital market, multiple least squares regressions is employed. Empirical results shows that dividends are affecting stock prices variations in India which fits in with the bird in hand and signaling theories of dividends. Due to the volatile nature of the market, Indian investors’ prefer demanding more dividends from firms rather keeping retained earnings on reinvestment. The outcomes of this study supports the fact that dividends policy influence stock price variations in Indian capital market. The results of this study provides an insight to the financial managers in developing their dividend policies to maximizing the shareholders wealth.

The Impact of International Oil Prices on the Stock Price Fluctuations of China’s Renewable Energy Enterprises

In order to address a series of issues, including energy security, global warming, and environmental protection, China has ranked first in global renewable investment for the seventh consecutive year. However, developing a renewable energy industry requires a significant capital investment. Also, the international oil price fluctuations have an important impact on the stock prices of renewable energy firms. Thus, in order to provide implications for market investment as well as policy recommendations, this paper studied the spillover effect of international oil prices on the stock prices of China’s renewable energy listed companies. We used a Vector Autoregressive (VAR) model with innovations using a Factor-GARCH (Generalized Autoregressive Conditional Heteroskedasticity) process to evaluate the impact of market co-movements and time-varying volatility and correlation between the international oil price and China’s renewable energy market. The results show that the international oil price has a significant price spillover effect on the stock prices of China’s renewable energy listed companies. Moreover, the fluctuations of international oil prices have an influence on the stock price variations of Chinese renewable energy listed companies.

Discovering Fundamental Value

Using machine learning methods we identify the fundamental value and noise components of quarterly stock prices. We show that 28% of stock price variation is attributable to noise, and that 40% of noise is attributable to mutual fund trading. We find spikes in noise around the dot-com bubble, the 2008 financial crisis, and the European sovereign-debt crisis. Noise is higher for small firms and firms with high R&D expenditures. In an application of our methodology, we show that corporate managers do not have private information about future changes in fundamental value nor can they identify noise in prices.

Present Value Models and the Behaviour of European Financial Markets

According to the efficient markets hypothesis stock returns should not be predictable on the basis of information available to economic agents in any given time period. We test the hypothesis using security market panel data for the top five Eurozone countries. In static return regressions there is a positive and significant relation between stock returns at horizons of 1–12 months and the dividend/price ratio. A dynamic vector autoregression model shows, that the cross-sectional variability of actual stock prices is significantly lower than predicted. In the time dimension actual stock prices are more volatile than predicted ones, although their movements anticipate future dividend changes. We provide an interpretation of these results from the point of view of the cognitive sciences. The regression to the mean between prices and stock returns might be explained by an excess smoothness of stock prices along the cross-sectional dimension, due to the process of expectations formation. The excess sensitivity along the time dimension supports the notion of capital markets efficiency as a fundamental factor for the determination of security prices.

Evidence of Fear in Fixed Income and Bourses: A Study on Certain G-7 Economies

The paper aimed to predict the Fear index for certain G7 countries (Canada, France, Germany and Japan) considering the two variables Stock Price (Close) and Bond Yield(LBY). Daily data were analyzed for the period from April 2013 to June 2017. The main purpose was to identify the degree in which fear affecting the stock market percolates to Fixed Income Instruments. Using Panel Data Regression (Fixed Effect Model) the two variables were able to predict the VIX index and the model was found to be robust in nature. The major finding is that Fixed Income and stocks share a negative relationship with VIX (Fear Index).

Earnings forecast revisions and securities prices evolution in the Tunisian stock market

PurposeThe purpose of this paper is to investigate the effect of forecast earnings’ revision on the evolution of securities prices in the Tunisian stock market.Design/methodology/approachA portfolio study of investor reaction and stock prices following revisions is first conducted to highlight the existence of abnormal return related to analysts’ earnings revisions. Analysis is then supplemented by a second empirical investigation based on the panel data to quantify the effect of revision on the abnormal profitability of securities.FindingsThe evidence found in this paper validates the fundamental theoretical hypothesis according to which the psychological bias resulting from the effect of the forecast earnings revision is related to the abnormal profitability of the securities. The authors conclude the importance of the revision impact on investors’ behavior on one hand, and the informational content of the analysts’ forecasts and the biases which they lead on the other hand.Originality/valueGlobally, the empirical illustrations largely validate the findings of behavioral models particularly that of Kormendi and Lippe (1987), Cornell and Letsman (1989), Beaver et al. (2008) which states that investors under psychological bias, react to the effect of forecast earnings revision by an abnormal variation in stock prices.

PENGARUH CURRENT RASIO DAN DEBT TO EQUITY RATIO TERHADAP HARGA SAHAM DI PERUSAHAAN FOOD AND BEVERAGE YANG TERDAFTAR DI BURSA EFEK INDONESIA PERIODE 2013 – 2017

This study aims to determine the effect of Current Ratio (CR) on Stock Prices, the effect of Debt to Equity Ratio (DER) on Stock Prices and to know the effect of Current Ratio ( CR) and simultaneous Debt to Equity Ratio (DER) to Stock Prices in Food and Beverage Companies for the 2013-2017 period. This study uses a descriptive type of statistical analysis with a quantitative approach. The population of this research are 16 companies. This study used financial report data with time series for the last 5 years. Sample selection through purposive sampling method There are 13 food and beverages companies that meet the criteria as a sample of research so that the research data amounted to 65 . The results of this research are Current Ratio has a significant effect on the Stock Price variable, the results of this research indicate that the increasing Current Ratio will increase the Stock Price. Debt to Equity Ratio has a significant effect on the Stock Price variable, the results of this research indicate that the low Debt to Equity Ratio will increase the Stock Price. independent variable Current Ratio and Debt to Equity Ratio simultaneously have a significant effect on the Stock Price variable.

Stock prices, exchange rates and portfolio equity flows

PurposeThe purpose of this paper is to develop a new framework to test the hypothesis that portfolio model predicts a negative correlation between stock prices and exchange rates in a trivariate transmission channel for foreign portfolio equity investment.Design/methodology/approachThis paper utilizes panel data for eight economies to extend the Dumitrescu and Hurlin (2012) Granger non-causality test of heterogeneous panels to a trivariate model by integrating the Toda and Yamamoto (1995) approach to Granger causality.FindingsThe evidence suggests that stock prices Granger-cause exchange rates and portfolio equity flows Granger-cause exchange rates. However, the overall panel evidence casts doubt on the explicit trivariate model of portfolio balance model. The study shows that Indonesia may be the only case where stock prices affect exchange rates through portfolio equity flows.Research limitations/implicationsThe proposed test does not account for potential asymmetries or structural shifts associated with the crisis period. To isolate the impact of the Asian Financial crisis, this paper rather splits the sample period into two sub-periods: pre- and post-crises. The sample period and countries are also limited due to the use of the balance of payment statistics.Practical implicationsThe study casts doubt on the maintained hypothesis of a trivariate transmission channel, as posited by the portfolio model. Policy makers of an economy may integrate capital market and fiscal policies in order to maintain stable exchange rate.Originality/valueThis paper integrates a portfolio equity inflow variable into a single framework with stock price and exchange rate variables. It extends the Dumitrescu and Hurlin’s (2012) bivariate stationary Granger non-causality test in heterogeneous panels to a trivariate setting in the framework of Toda and Yamamoto (1995).

Impact of Dividend Policy on Variation of Stock Prices: Empirical Study of Vietnam

This research is conducted to investigate the impact levels of dividend policy on stock prices variation in the case of the stock exchange of an emerging country − Vietnam. Data were collected from 248 listed firms on the Vietnamese stock market for the period from 2014 to 2017. By employing ordinary least squares (OLS) and quantile regression (QR), we found that there is a negative relationship between dividend policy and variation of stock prices. Some variables including income variation, long term liabilities and growth have positive relationships with stock price variation whereas firm size has no impact on it. We also found that firms using low dividend yields influence stock prices variation in a clearer way. The results of this study are important for management in emerging countries, and in this case Vietnam, to have a proper dividend policy because dividend policy is crucial information for stakeholders to make economic decisions.

Macroeconomic factors explaining stock volatility: multi-country empirical evidence from the auto industry

This paper aims to explore which macroeconomic factors affect the volatility of the automakers stock prices by employing a multifactor model. The study uses quarterly panel data of 39 automakers quoted on the stock exchanges in the 11 countries. It studies the effects of 19 macroeconomic variables from January 2000 to December 2017, and proposes the mixed-effect model constructed based on employing genetic algorithm and AIC criterion, and compares its explanatory power with the existing multifactor model (El Khoury, 2015). This paper suggests that the proposed model can shed more light on explaining the variability of stock prices of the quoted automakers. The findings show there are positive linkages between automaker's stock return volatility and explanatory variables such as stock market development, GDP and unemployment. Conversely, an inverse linkage between the dependent variable and money supply and IPI was found. The study demonstrates that selected macroeconomic factors can also be used as predictors.

Analisis Kausalitas Antara Harga Saham Konvensional Dengan Harga Saham Syariah Di Indonesia (pendekatan granger causality)

Stock Price that occur in the share market always fluctuate over time. Stock value fluctuations will be set by the strength of supply and demand. If the supply amount is greater than the amount of demand, generally the exchange stock value will decrease, and vice versa. Not only that, competition between companies in marketing their shares also affect the stock price changes. It is clear if there is a change in price increase on syariah stock price index, will affect other stock prices. The possibility may also occur otherwise, such as a decline in the price of shares listed in the syariah stock price index so in order to compete with healthy other companies will also lower the price on the issued shares. Therefore, this study was conducted with the aim to know whether there is a reciprocal relationship between the conventional stock price with the stock price of syariah. This study uses quantitative research method by using granger causality approach. The data used are secondary data sourced from publication data of Indonesia Stock Exchange with time series based on monthly statistic report, and other sources related to the research problem. The study model used is granger causality test. After the data used tested normality, stationarity, cointegration and has known the optimum lag value then do the granger causality test using the help of software EVIEWS 8. The results of this study indicate that the conventional stock price variables listed in the LQ45 index based on statistical analysis do not significantly affect the Syariah Stock Price listed in the Jakarta Islamic Index (JII) with the ratio F value of F statistic < F table, that is 1,01 < 2,59, with a significant value of 0,3677 > 0,05. On the contrary, Syariah Stock Price Variables registered in Jakarta Islamic Index (JII) based on statistical analysis have significant effect on Conventional Stock Price which is included in index LQ45 with F value of statistic > F table, that is 3,64 > 2,59, with value significant 0,0309 < 0,05. Therefore, the result of granger causality test that no granger causality occurs between JII and LQ45. This means that JII has a relationship with LQ45, but JII and LQ45 have no two-way relationship (causality). Keywords: Stock Price, Jakarta Islamic Index (JII), LQ45, Granger Causality Test.

When the Going Gets Tough, The Tweets Get Going! An Exploratory Analysis of Tweets Sentiments in the Stock Market

Information artifacts in social media can have significant impact on domains and subject matter opinions. Asset prices, stock prices and volumes, and metrics are influenced by turbulence in their information ecosystems. Analyses of digital information networks and social media information events have shown information artifacts to affect stock performance without consistent correlation to fundamentals. Thus it becomes important to dispel ambiguity and gain insights into how the sentiments associated with information artifacts in Twitter (due to its extensive usage in relevant signaling), are associated with equity movements. Using an exploratory analysis to study tweet sentiment, we link stock price variations, and explore associated metrics. Our tweets analytics deploying textual analytics, identifies forms in tweet behavior and sentiment shifts.

Pengaruh Net Profit Margin, Return on Asset, Return on Equity, Dan Earning Per Share Terhadap Harga Saham Pada Perusahaan Manufaktur Sektor Industri Barang Konsumsi Yang Terdaftar Di Bursa Efek Indonesia

This study aims to determine how much the effect of the company's financial performance focused on Net Profit Margin (NPM), Return on Assets (ROA), Return on Equity (ROE) and Earning Per Share (EPS) to Stock Price on Manufacturing Company of Consumer goods Industry Sector Listed in BEI as of 31 December 2016. The sampling technique used in this research is saturated sampling method and the sample used is 37 companies. The analysis technique used is Multiple Linear Regression, Correlation Coefficient, and Coefficient of Determination. Hypothesis Examination used F- test simultaneously and Hypothesis Examination used t-test partially. The Result of simultaneous test (F-test) indicate that independent variable that is NPM, ROA, ROE and EPS together have no significant effect on attached variable Stock Price on Manufacturing Company of Consumer goods Industry Sector Listed in BEI as of 31 December 2016. The partial test (t test) of NPM ROA ROE variable has no significant effect on the Stock Price on Manufacturing Company of Consumer goods Industry Sector Listed in BEI as of 31 December 2016. And the EPS variable has a significant effect on the Stock Price on Manufacturing Company of Consumer goods Industry Sector Listed in BEI as of 31 December 2016.

Determinants of Stock Price in Nepalese Market

The aim of this study is to determine the relationship between stock price and explanatory variables like: DPS, EPS, P-E ratio, BV, Market to BV for the period 2012 to 2017. Using simple and multiple regression analysis and descriptive statistics this study investigates the factor affecting the stock price. With the sample size of 11 financial and nonfinancial firms of Nepal, the result indicates that the variables Market to BV, P-E ratio are the significant determinants of stock price which directly affect the stock price. Likewise, DPS, BV also have significance positive influence on stock price whereas EPS has minimum influence on the stock price.

Effect Of Leverage, Inflation And GDP To Share Price Pt. Astra Otoparts Tbk.

The purpose of this study was to obtain empirical evidence about the effect of leverage, inflation and Gross Domestic Product (GDP) of the share price at PT. Astra Autopart, Tbk. companies in Indonesia Stock Exchange in 2011-2015. The sampling technique in this study using a purposive sampling. With the technique of purposive sampling, all the members of the research samples by criteria. Samples that meet the criteria are used research data. Then followed the classic assumption test and test hypotheses by linear regression. The results of this study demonstrate the regression results in regression equation that Y = 2605,424 + 1561,550 X1 + 2,338 X2 + 38,994X3. T test results showed that the leverage anda GDP (Gross Domestic Product) is positive and significant effect on stock prices, while inflation is not positive and significant effect on stock prices. F test results showed that jointly leverage variables, inflation and GDP variables affecting the stock price significantly. The test results R2 (coefficient of determination) found that the variable leverage, inflation and GDP able to explain 35,4% of the stock price variable, while the remaining 64,6% is explained by other variables.Keywords: leverage, inflation, GDP, and the share priceThe purpose of this study was to obtain empirical evidence about the effect of leverage, inflation and Gross Domestic Product (GDP) of the share price at PT. Astra Autopart, Tbk. companies in Indonesia Stock Exchange in 2011-2015.The sampling technique in this study using a purposive sampling. With the technique of purposive sampling, all the members of the research samples by criteria. Samples that meet the criteria are used research data. Then followed the classic assumption test and test hypotheses by linear regression.The results of this study demonstrate the regression results in regression equation that Y = 2605,424 + 1561,550 X1 + 2,338 X2 + 38,994X3. T test results showed that the leverage anda GDP (Gross Domestic Product) is positive and significant effect on stock prices, while inflation is not positive and significant effect on stock prices. F test results showed that jointly leverage variables, inflation and GDP variables affecting the stock price significantly. The test results R2 (coefficient of determination) found that the variable leverage, inflation and GDP able to explain 35,4% of the stock price variable, while the remaining 64,6% is explained by other variables.Keywords: leverage, inflation, GDP, and the share price

Value relevance of accounting information: an emerging country perspective

PurposeThis paper aims to examine the value relevance of accounting information from an emerging country perspective.Design/methodology/approachThe study adopts Ohlson (1995) Price model to examine the extent to which accounting information explain variation in stock prices of listed firms on the Ghana Stock Exchange.FindingsThe study reveals that earnings and book value of equity exhibit a positive and significant relationship in stock prices. Earnings explain higher variation in stock market values on the Ghana Stock Exchange compared to book value of equity. The study however finds that despite the introduction of the International Financial Reporting Standards in Ghana, the value relevance of book value and earnings have declined significantly over the period 2005-2014.Research limitations/implicationsA key implication is that regulators of capital markets, standards setters and accounting practitioners need to consistently improve upon the quality of financial reporting disclosures which will boost the confidence of users in their reliance on financial statements as the basis for choosing among alternative use of scarce resources. The authors adopted only the price model in testing the hypotheses. However, to provide comprehensive understanding of value relevance of accounting information, future studies can combine both the price and the return models.Originality/valueThe authors extend prior literature in the Ghanaian context with recent data. Finally, the study adds to the efficient market hypothesis by showing how share prices reflect accounting information produced by Ghanaian firms.

PENGARUH EARNING PER SHARE (EPS) DAN PRICE BOOK VALUE (PBV) TERHADAP HARGA SAHAM PADA INDUSTRI RETAIL YANG TERDAFTAR DI BEI PERIODE 2013-2016

The purpose of this studyis to find out how the influence of earnings per share (EPS) and price book value (PBV) simultaneously and parcial to stock prices in retail industry listed on the Stock Exchange Indonesia period 2013-2016. The ojek this analysis is the retail industry listed on the stock exchange indonesia period 2013-2016. Sampel used in this research is as many as 8 retail industry listed on the Stock Exchange Indonesia period 2013-2016. The method used is qualitative and quantitative method. . The analytical tool used in this research is multiple linear regression analysis, the classical assumption test (normality, multicolinearity, hetoroscedasicity, and autocorrelation) and coefficient of determination. Based on the results of multiple linear regression analysis showed the equation Log Y= 2.244 + Log 0,528EPS Log 0,018PBV + e , with F test value of 5,153. Value t test for earning per share (EPS) of 3,159 and the value of T test for price book value (PBV) of 0,113. Rated R Square 26,2%, while the remaining 73,8% explained other factors beyond the study models. And the R value of 0,512. The conclusion of this research indicates that simultaneously independent variable earnings per share (EPS) and price book value (PBV) have an effect on stock price variable. The parcial price (PBV) has no significant effect on stock price dependent and earnings per share (EPS) have a significant effect on stock price variables.

The Effect of Financial Performance and Financial Distress Indicators to the Stock Price of Bank Rakyat Indonesia

The bank’s financial report is the only lead for the public c to review, evaluate, and assess the soundness of a bank. By tinkering the available figures within the monthly financial reports, we have measured 52 variables comprised of the common indicators to calculate the effects of financial performance of the bank, its financial distress, to its stock price in the market. The common indicators used are the ratios of liquidity, rentability, and solvability. The bankruptcy prediction and financial distress indicators were considered to part ofthe solvability ratios. The data observed and collected was between January 2002 to 18 July 2017. The time lag and IPO as of 10 November 2003 reduced the eligibility of monthly financial reports, leaving the data usable for the period of November 2003 to April 2017. As 10 variables were excluded by the system, only 4 of42 variables were found to be significantly affecting the stock price variable. The 4 independent variables are market capitalization, the ratio of placement in BI to the third-party fund, debt to equity ratio, and debtto asset ratio.