Maximizing Short-Term Stock Prices through Advertising

2010 ◽  
Author(s):  
Dong Lou
Keyword(s):  
Stock Prices ◽  
Short Term

Prior Return Effect in Indian Stock Market: An Intra-day Analysis

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Vanita Tripathi ◽  
Shalini Aggarwal
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
High Frequency ◽  
Good News ◽  
High Frequency Data ◽  
Short Term ◽  
Fund Managers ◽  
News Events ◽  
Return Effect ◽  
Indian Stock Market

In a first of this kind, this paper examines the issue of prior return effect in Indian stock market in intra-day analysis using high frequency data. We document that in Indian stock market, security returns exhibit a reversal in their direction within few minutes of extreme price rises as well as price falls. However the speed with which the correction takes place is slightly different for good news events and bad news events. Indian investors tend to be optimistic as they immediately bring stock prices up following unjustified price falls but take time to bring stock prices down following unjustified price rises. These findings lend a further support to short-term overreaction literature. More importantly, these findings serve as a proof of predictability of the direction of future stock prices and consequent returns on an intra-day basis. It forwards important investment implications for traders, fund managers, and investors at large.

العلاقة التبادلية بين سعر الصرف وأسعار الأسهم دراسة تطبيقية في سوق اسطنبول للأوراق المالية للمدة 2005-2020

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
سعدالله ألنعيمي
Keyword(s):  
Exchange Rate ◽  
Stock Prices ◽  
Negative Impact ◽  
Reciprocal Relationship ◽  
Nominal Exchange Rate ◽  
Share Price ◽  
Theoretical Interpretation ◽  
Short Term ◽  
The Exchange Rate

The study aims to analyzing the reciprocal relationship between the nominal exchange rate of the Turkish lira versus the U.S. dollar and the stock prices of the companies listed on the Istanbul Stock Exchange (ISE) expressed in the general market index for the period from 2005 to 2020 with 192 monthly observations, based on the traditional theory and the theory of portfolio balance model in theoretical interpretation for that relationship, aiming to identify the effect of the exchange rate on stock prices, as well as to analyze the causal relationship between those variables and to identify which of them is the cause or which is the result, using the Autoregressive Distributed Lag (ARDL) model. The research found that the exchange rate has a positive effect on stock prices in the long term, despite the emergence of the negative impact in the short term, but the long-term relationship has corrected the course of the short-term relationship with a time period not exceeding one month, in addition to proving that this relationship takes one direction. From the exchange rate towards stock prices, that is, the exchange rate is the reason and stock prices are the result, therefore the results of this research helps investors to predict future trends of stock prices depending on the exchange rate changes, and it also enables the companies, especially those with foreign transactions, to manage price risks the exchange rate in order to avoid its negative impact on its share price, as it represents an obstacle to achieving its main goal of maximizing the share price

Testing the weak form of efficient market hypothesis for socially responsible and Shariah indexes in the USA

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abbas Khan ◽  
Muhammad Yar Khan ◽  
Abdul Qayyum Khan ◽  
Majid Jamal Khan ◽  
Zia Ur Rahman
Keyword(s):  
Stock Prices ◽  
Arima Model ◽  
Weak Form ◽  
Efficient Market Hypothesis ◽  
Future Price ◽  
Short Term ◽  
Socially Responsible ◽  
Efficient Market ◽  
Content Type ◽  
The Us

Purpose By testing the weak form of efficient market hypothesis (EMH) this study aims to forecast the short-term stock prices of the US Dow and Jones environmental socially responsible index (SRI) and Shariah compliance index (SCI). Design/methodology/approach This study checks the validity of the weak form of EMH for both SCI and SRI prices by using different parametric and non-parametric tests, i.e. augmented Dickey-Fuller test, Philip-Perron test, runs test and variance ratio test. If the EMH is invalid, the research further forecasts short-term stock prices by applying autoregressive integrated moving average (ARIMA) model using daily price data from 2010 to 2018. Findings The research confirms that a weak form of EMH is not valid in the US SRI and SCI. The historical data can predict short-term future price movements by using technical ARIMA model. Research limitations/implications This study provides better guidance to risk-averse national and international investors to earn higher returns in the US SRI and SCI. This study can be extended to test the EMH of Islamic equity in the Middle East and North Africa region and other top Islamic indexes in the world. Originality/value This study is a new addition to the existing literature of equity investment and price forecasting by comparing and investigating the market efficiency of two interrelated US SRI and SCI.

scholarly journals ANALISIS HARGA SAHAM INDEX KOMPAS 100 DENGAN PENDEKATAN ERROR CORRECTION MODEL

2021 ◽  
Vol 4 (1) ◽  
pp. 406-414
Author(s):  
Amir Hamzah
Keyword(s):  
Error Correction ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Financial Statements ◽  
Error Correction Model ◽  
Short Term ◽  
Correction Model ◽  
Positive Effect

The purpose of this research is to analyze the short term and long term relationship between ROI, EPS, PER ,inflation, SBI, exchange rate,and GDP on Stock Price. The data in this research is company financial statements which included Compas 100 Index on the Indonesia Stock Exchange. statistical analysis in this research used stasionarity test, The Classical Assumptions Test, Cointegration Test, Error Correction Model Test. This research found that partially ROI, EPS, PER variables a positive effect on stock prices in the short term and long term, KURS and SBI a positive effect on stock prices in the short term, but there is no effect in the long term, inflation and GDP do not affect the stock price both in the short term and long term. Simultaneously affected the stock prices significantly affect on stock price both in the short term and long term.

scholarly journals Impact of COVID-19 on Forecasting Stock Prices: An Integration of Stationary Wavelet Transform and Bidirectional Long Short-Term Memory

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Daniel Štifanić ◽  
Jelena Musulin ◽  
Adrijana Miočević ◽  
Sandi Baressi Šegota ◽  
Roman Šubić ◽  
...  
Keyword(s):  
Crude Oil ◽  
Stock Prices ◽  
Short Term Memory ◽  
Oil Price ◽  
Stationary Wavelet Transform ◽  
Crude Oil Price ◽  
Short Term ◽  
Term Memory ◽  
Long Short Term Memory ◽  
The Impact

COVID-19 is an infectious disease that mostly affects the respiratory system. At the time of this research being performed, there were more than 1.4 million cases of COVID-19, and one of the biggest anxieties is not just our health, but our livelihoods, too. In this research, authors investigate the impact of COVID-19 on the global economy, more specifically, the impact of COVID-19 on the financial movement of Crude Oil price and three US stock indexes: DJI, S&P 500, and NASDAQ Composite. The proposed system for predicting commodity and stock prices integrates the stationary wavelet transform (SWT) and bidirectional long short-term memory (BDLSTM) networks. Firstly, SWT is used to decompose the data into approximation and detail coefficients. After decomposition, data of Crude Oil price and stock market indexes along with COVID-19 confirmed cases were used as input variables for future price movement forecasting. As a result, the proposed system BDLSTM + WT-ADA achieved satisfactory results in terms of five-day Crude Oil price forecast.

scholarly journals The Relationship between Stock Prices and Exchange Rates: The Focus on Dar Es Salaam Stock Exchange (DSE)

2017 ◽  
Vol 8 (1) ◽  
pp. 1
Author(s):  
Fredynandy M John ◽  
Zakayo S Kisava
Keyword(s):  
Exchange Rates ◽  
Granger Causality ◽  
Stock Prices ◽  
Stock Exchange ◽  
Dar Es Salaam ◽  
Data Sets ◽  
Short Term ◽  
Vector Autoregressive ◽  
United States Dollar ◽  
Daily Data

This paper aims to examine the existing relationship between the prices of different stocks traded in the Dar es Salaam Stock Exchange (DSE) and the Tanzanian Shillings – United States dollar exchange rates (TZS/USD). In this study, we use the daily data sets covering a period of six years from August 15, 2011 through July 28, 2017 making 1455 observations. Vector Autoregressive (VAR) – Granger Causality model is employed accompanied with several tests conducted on the variables and the model itself. The findings conclude that, there is a short-term association between Stock Prices (SP) and Exchange Rates (ExR). Additionally, Stock Prices Granger Causes Exchange Rates as evidenced by Granger Causality and the Impulse test. These findings are supported by the fact that shocks in the Exchange Rates have no effect in the Stock Prices. This could mean that an investor can invest in short term at the DSE.

scholarly journals With a Bang, not a Whimper: Pricking Germany's “Stock Market Bubble” in 1927 and the Slide into Depression

2003 ◽  
Vol 63 (1) ◽  
pp. 65-99 ◽  
Author(s):  
Hans-Joachim Voth
Keyword(s):  
Stock Market ◽  
Central Bank ◽  
Stock Prices ◽  
Money Market ◽  
Short Term ◽  
Real Effects ◽  
Foreign Borrowing ◽  
Relative Stabilization

In May 1927, the German central bank intervened indirectly to reduce lending to equity investors. The crash that followed ended the only stock market boom during Germany's relative stabilization 1924–1928. The evidence strongly suggests that the German central bank under Hjalmar Schacht was wrong to be concerned about stock prices—there was no bubble. Also, the Reichsbank was mistaken in its belief that a fall in the market would reduce the importance of short-term foreign borrowing and improve conditions in the money market. The misguided intervention had important real effects. Investment suffered, helping to tip Germany into depression.

scholarly journals Stock Prediction Using Sentiment Analysis and LSTM

2021 ◽  
Vol 9 (9) ◽  
pp. 1752-1756
Author(s):  
Ms. Anjima K. S
Keyword(s):  
Stock Market ◽  
Sentiment Analysis ◽  
Programming Language ◽  
Stock Prices ◽  
Short Term Memory ◽  
Short Term ◽  
Term Memory ◽  
Python Programming Language ◽  
Long Short Term Memory ◽  
Python Programming

Abstract: The stock market is a difficult area to anticipate since it is influenced by a variety of variables at the same time. The stock exchange is where equities are exchanged, transferred, and circulated. This research proposes a hybrid algorithm that predicts a stock's next day closing prices using sentiment analysis and Long Short Term Memory. The LSTM model seems to be quite popular in time-series forecasting, which is why it was selected for this project. Our proposed methodology makes use of the temporal association between public opinion and stock prices. Part-of-speech tagging is used to do sentiment analysis, and Long Short Term Memory is utilized to predict the stock's next day closing price. When these two factors are combined, we get a good picture of the stock's future. In this project, two main datasets have been used: HCLTECH company stock data and the news related to each stock of the HCL company for each day. The project is implemented by using the python programming language. The python programming language has been used to execute the project. This also incorporates machine learning along with public feedback. Sentiment analysis enables us to evaluate a diversity of political and economic factors, which have a significant impact on the stock market. Keywords: LSTM, sentiment analysis, RNN, Back propagation neural network.

Sign in / Sign up

Export Citation Format

Share Document