scholarly journals Forecasting stock market prices using mixed ARIMA model: a case study of Indian pharmaceutical companies

2021 ◽  
Vol 18 (1) ◽  
pp. 42-54
Author(s):  
Bharat Kumar Meher ◽  
Iqbal Thonse Hawaldar ◽  
Cristi Spulbar ◽  
Ramona Birau
Keyword(s):  
Time Series ◽  
Stock Market ◽  
Stock Prices ◽  
Arima Model ◽  
Information Criterion ◽  
Future Research ◽  
Pharmaceutical Companies ◽  
Market Prices ◽  
Share Prices ◽  
Adf Test

Many investors in order to predict stock prices use various techniques like fundamental analysis and technical analysis and sometimes rely on the discussions provided by various stock market analysts. ARIMA is a part of time-series analysis under prediction algorithms, and this paper attempts to predict the share prices of selected pharmaceutical companies in India, listed under NIFTY100, using the ARIMA model. A sample size of 782 time-series observations from January 1, 2017 to December 31, 2019 for each selected pharmaceutical firm has been considered to frame the ARIMA model. ADF test is used to verify whether the data are stationary or not. For ARIMA model estimation, significant spikes in the correlogram of ACF and PACF have been observed, and many models have been framed taking different AR and MA terms for each selected company. After that, 5 best models have been selected, and necessary inculcation of various AR and MA terms has been made to adjust the models and choose the best adjusted ARIMA model for each firm based on Volatility, adjusted R-squared, and Akaike Information Criterion. The results could be used to analyze the stock prices and their prediction in-depth in future research efforts.

scholarly journals Comparing classic time series models and the LSTM recurrent neural network: An application to S&P 500 stocks

2020 ◽  
Vol 6 (2) ◽  
pp. 137-148
Author(s):  
J. Oliver Muncharaz
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Time Series ◽  
Stock Market ◽  
Recurrent Neural Network ◽  
Stock Prices ◽  
Arima Model ◽  
Time Series Models ◽  
Prediction Errors ◽  
The Creation

In the financial literature, there is great interest in the prediction of stock prices. Stock prediction is necessary for the creation of different investment strategies, both speculative and hedging ones. The application of neural networks has involved a change in the creation of predictive models. In this paper, we analyze the capacity of recurrent neural networks, in particular the long short-term recurrent neural network (LSTM) as opposed to classic time series models such as the Exponential Smooth Time Series (ETS) and the Arima model (ARIMA). These models have been estimated for 284 stocks from the S&P 500 stock market index, comparing the MAE obtained from their predictions. The results obtained confirm a significant reduction in prediction errors when LSTM is applied. These results are consistent with other similar studies applied to stocks included in other stock market indices, as well as other financial assets such as exchange rates.

scholarly journals EFFECT OF DIVIDEND POLICY ON STOCK PRICES

2015 ◽  
Vol 3 (1) ◽  
Author(s):  
Adnan ALİ ◽  
Farzand Ali Jan ◽  
Ilyas Sharif
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Dividend Policy ◽  
Random Effect ◽  
Capital Gains ◽  
Upward Movement ◽  
Significant Relation ◽  
Market Prices ◽  
Return On Equity ◽  
Share Prices

This investigates the effect of dividend policy on stock prices. Objective of the study is to see if there exists any relationship between dividend policy and stock prices. We analyzed 45 non-financial companies listed on KSE-100 index that have earned profits and paid dividend for a period of twelve year w.e.f. 2001. Technique adopted for sampling adopted is convenience sampling. As the nature of data is panel therefore, pooled regression, fixed and random effect tests are run. Random effect results are focused after applying Hausman’s test.Regression Results witness that Dividend per Share andRetention Ratio havean insignificant relationship with Share Market Prices.Dividend Payout Ratio has a significant positive relationship with Share Prices as supported by the Bird in hand theory suggested that owners give preference to a dollar of estimated dividends over a likely dollar of capital gains. Profit after tax, Earning per share and Return on Equity are the three control variables. Profit after Tax has insignificant relation to Stock Prices. Earnings per Share have positive significant relation to Stock Prices. There is negative significant relation between Return on Equity and Share Prices. It is recommended that firms in the sample should regularly pay dividend as it will cause an upward movement in the stock market prices. Whereas profit retention by firms will result in a decrease in the value of the stock market prices.

Forecasting Stock Market Prices Using Mixed ARIMA Model: A Case Study of Indian Pharmaceutical Companies

2021 ◽  
Author(s):  
Bharat Kumar Meher ◽  
Iqbal Thonse Hawaldar ◽  
Cristi Marcel Spulbar ◽  
Felicia Ramona Birau
Keyword(s):  
Stock Market ◽  
Arima Model ◽  
Pharmaceutical Companies ◽  
Market Prices

COVID-19 Sentiments and Impact on Stock Market Prices

2021 ◽  
Vol 2 (2) ◽  
pp. 40-58
Author(s):  
Chandra Prayaga ◽  
Krishna Devulapalli ◽  
Lakshmi Prayaga ◽  
Aaron Wade
Keyword(s):  
Time Series ◽  
Stock Market ◽  
Stock Prices ◽  
Multivariate Time Series ◽  
Market Prices ◽  
Vector Error Correction ◽  
Jones Index ◽  
Vector Error ◽  
The Impact ◽  
Stock Values

This paper studies the impact of sentiments expressed by tweets from Twitter on the stock market associated with COVID-19 during the critical period from December 1, 2019 to May 31, 2020. The stock prices of 30 companies on the Dow Jones Index were collected for this period. Twitter tweets were also collected, using the search phrases “COVID-19” and “Corona Virus” for the same period, and their sentiment scores were calculated. The three time series, open and close stock values, and the corresponding sentiment scores from tweets were sorted by date and combined. Multivariate time series models based on vector error correction (VEC) models were applied to this data. Forecasts for these 30 companies were made for the time series open, for the 30 days of June 2020, following the data collection period. Stock market data for the month of June was for all the companies was compared with the forecast from the model. These were found to be in excellent agreement, implying that sentiment had a significant impact or was significantly impacted by the stock market prices.

scholarly journals DAILY VARIATION AND PREDICTING STOCK MARKET RETURNS FOR THE FRANKFURTER BÖRSE (STOCK MARKET)

2008 ◽  
Vol 9 (3) ◽  
pp. 189-198 ◽  
Author(s):  
Jeffrey E. Jarrett ◽  
Janne Schilling
Keyword(s):  
Time Series ◽  
Stock Market ◽  
Stock Returns ◽  
Stock Prices ◽  
Stock Exchange ◽  
Arima Model ◽  
Unit Root Test ◽  
Unit Roots ◽  
Stock Market Returns ◽  
Daily Stock Returns

In this article we test the random walk hypothesis in the German daily stock prices by means of a unit root test and the development of an ARIMA model for prediction. The results show that the time series of daily stock returns for a stratified random sample of German firms listed on the stock exchange of Frankfurt exhibit unit roots. Also, we find that one may predict changes in the returns to these listed stocks. These time series exhibit properties which are forecast able and provide the intelligent data analysts’ methods to better predict the directive of individual stock returns for listed German firms. The results of this study, though different from most other studies of other stock markets, indicate the Frankfurt stock market behaves in similar ways to North American, other European and Asian markets previously studied in the same manner.

scholarly journals Effect of Dividend Policy on Stock Prices

2017 ◽  
Vol 4 (1) ◽  
pp. 19-28
Author(s):  
Adnan Ali ◽  
Ilyas Sharif ◽  
Farzand Ali Jan
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Dividend Policy ◽  
Random Effect ◽  
Capital Gains ◽  
Upward Movement ◽  
Significant Relation ◽  
Market Prices ◽  
Return On Equity ◽  
Share Prices

This investigates the effect of dividend policy on stock prices. Objective of the study is to see if there exists any relationship between dividend policy and stock prices. We analyzed 45 non-financial companies listed on KSE-100 index that have earned profits and paid dividend for a period of twelve-year w.e.f. 2001. Technique adopted for sampling adopted is convenience sampling. As the nature of data is panel therefore, pooled regression, fixed and random effect tests are run. Random effect results are focused after applying Hausman’s test. Regression Results witness that Dividend per Share and Retention Ratio have an insignificant relationship with Share Market Prices. Dividend Payout Ratio has a significant positive relationship with Share Prices as supported by the Bird in hand theory suggested that owners give preference to a dollar of estimated dividends over a likely dollar of capital gains. Profit after tax, Earning per share and Return on Equity are the three control variables. Profit after Tax has insignificant relation to Stock Prices. Earnings per Share have positive significant relation to Stock Prices. There is negative significant relation between Return on Equity and Share Prices. It is recommended that firms in the sample should regularly pay dividend as it will cause an upward movement in the stock market prices, whereas profit retention by firms will result in a decrease in the value of the stock market prices.

scholarly journals Market Efficiency of Indian Capital Market: An Event Study Around the Announcement of Results of Lok Sabha Election 2019

2020 ◽  
Vol 12 (1) ◽  
pp. 60
Author(s):  
Nazreen Parveen Ali ◽  
Ashit Saha
Keyword(s):  
Stock Market ◽  
Market Efficiency ◽  
Stock Prices ◽  
Public Information ◽  
Market Model ◽  
Event Window ◽  
Share Prices ◽  
Indian Stock Market ◽  
The Impact ◽  
Adf Test

Market efficiency categorizes a stock market into three sections based on the reaction of share prices to private and public information. This paper mainly deals with reactions of stock market dynamics to information in political events considering the impact of result announcement of the Lok Sabha Elections 2019 on the Indian Stock market as reflected in the behaviour of share prices. Taking BSE 100 as the proxy market, daily closing stock prices of the 30 companies listed in BSE SENSEX was used. An estimation window of 120 trading days was taken prior to the event window. The standard Market model was applied to calculate the AAR and CAAR during the event window of 21 days. Further the Augmented Dickey Fuller (ADF) Test for unit root is applied to measure the stationary of the variables and the presence of ARCH/GARCH effect is tested to understand the volatility during the study period. The Runs Test was used to test the randomness of AAR and the paired sample t test was applied to check the impact of the event on the volume of trading. Consistent negative returns were observed following the event. But the absence of volatility and the insignificant results indicated that market efficiency Indian Stock Market is in a semi strong form.

scholarly journals EFFECT OF DIVIDEND POLICY ON STOCK PRICES

2015 ◽  
Vol 3 (1) ◽  
pp. 56-87
Author(s):  
Ilyas SHARIF ◽  
Adnan ALİ ◽  
Farzand Ali JAN
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Dividend Policy ◽  
Random Effect ◽  
Capital Gains ◽  
Upward Movement ◽  
Significant Relation ◽  
Market Prices ◽  
Return On Equity ◽  
Share Prices

This investigates the effect of dividend policy on stock prices. Objective of the study is to see if there exists any relationship between dividend policy and stock prices. We analyzed 45 non-financial companies listed on KSE-100 index that have earned profits and paid dividend for a period of twelve year w.e.f. 2001. Technique adopted for sampling adopted is convenience sampling. As the nature of data is panel therefore, pooled regression, fixed and random effect tests are run. Random effect results are focused after applying Hausman’s test.Regression Results witness that Dividend per Share andRetention Ratio havean insignificant relationship with Share Market Prices.Dividend Payout Ratio has a significant positive relationship with Share Prices as supported by the Bird in hand theory suggested that owners give preference to a dollar of estimated dividends over a likely dollar of capital gains. Profit after tax, Earning per share and Return on Equity are the three control variables. Profit after Tax has insignificant relation to Stock Prices. Earnings per Share have positive significant relation to Stock Prices. There is negative significant relation between Return on Equity and Share Prices. It is recommended that firms in the sample should regularly pay dividend as it will cause an upward movement in the stock market prices. Whereas profit retention by firms will result in a decrease in the value of the stock market prices.

scholarly journals Fractional differencing in stock market price and online presence of global tourist corporations

2019 ◽  
Vol 24 (48) ◽  
pp. 194-204 ◽  
Author(s):  
Francisco Flores-Muñoz ◽  
Alberto Javier Báez-García ◽  
Josué Gutiérrez-Barroso
Keyword(s):  
Time Series ◽  
Stock Market ◽  
Market Price ◽  
Google Trends ◽  
Data Sets ◽  
Market Prices ◽  
Content Type ◽  
Search Results ◽  
Online Presence ◽  
Fractional Differencing

Purpose This work aims to explore the behavior of stock market prices according to the autoregressive fractional differencing integrated moving average model. This behavior will be compared with a measure of online presence, search engine results as measured by Google Trends. Design/methodology/approach The study sample is comprised by the companies listed at the STOXX® Global 3000 Travel and Leisure. Google Finance and Yahoo Finance, along with Google Trends, were used, respectively, to obtain the data of stock prices and search results, for a period of five years (October 2012 to October 2017). To guarantee certain comparability between the two data sets, weekly observations were collected, with a total figure of 118 firms, two time series each (price and search results), around 61,000 observations. Findings Relationships between the two data sets are explored, with theoretical implications for the fields of economics, finance and management. Tourist corporations were analyzed owing to their growing economic impact. The estimations are initially consistent with long memory; so, they suggest that both stock market prices and online search trends deserve further exploration for modeling and forecasting. Significant differences owing to country and sector effects are also shown. Originality/value This research contributes in two different ways: it demonstrate the potential of a new tool for the analysis of relevant time series to monitor the behavior of firms and markets, and it suggests several theoretical pathways for further research in the specific topics of asymmetry of information and corporate transparency, proposing pertinent bridges between the two fields.

scholarly journals The Dynamics of Gold Prices, Gold Mining Stock Prices and Stock Market Prices Comovements

2009 ◽  
Vol 1 (1) ◽  
Author(s):  
Claire G. Gilmore ◽  
Ginette M. McManus ◽  
Rajneesh Sharma ◽  
Ahmet Tezel
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Gold Mining ◽  
Market Prices
Sign in / Sign up

Export Citation Format

Share Document