Long-term and short-term price memory in the stock market

1995 ◽  
Vol 49 (3) ◽  
pp. 287-293 ◽  
Author(s):  
K. Victor Chow ◽  
Karen C. Denning ◽  
Stephen Ferris ◽  
Gregory Noronha
Keyword(s):  
Stock Market ◽  
Short Term ◽  
Price Memory

Impact of FII’s and FDI’s on Indian Stock Market

2016 ◽  
Vol 1 (1) ◽  
Author(s):  
Dr. Kamlesh Kumar Shukla
Keyword(s):  
Stock Market ◽  
Financial Markets ◽  
Global Economy ◽  
Short Term ◽  
Earnings Growth ◽  
The Past ◽  
Bull Market ◽  
Indian Stock Market

FIIs are companies registered outside India. In the past four years there has been more than $41 trillion worth of FII funds invested in India. This has been one of the major reasons on the bull market witnessing unprecedented growth with the BSE Sensex rising 221% in absolute terms in this span. The present downfall of the market too is influenced as these FIIs are taking out some of their invested money. Though there is a lot of value in this market and fundamentally there is a lot of upside in it. For long-term value investors, there’s little because for worry but short term traders are adversely getting affected by the role of FIIs are playing at the present. Investors should not panic and should remain invested in sectors where underlying earnings growth has little to do with financial markets or global economy.

scholarly journals The Effect of Macroeconomic Variables On the Saudi Stock Market

2019 ◽  
Vol 7 (12) ◽  
pp. 126-152
Author(s):  
Amani Mohammed Aldukhail
Keyword(s):  
Stock Market ◽  
Performance Indicators ◽  
Stock Price ◽  
Price Index ◽  
Inflation Rate ◽  
Market Value ◽  
Short Term ◽  
Macroeconomic Variables ◽  
Time Deposits

This study aimed at exploring the effect of macroeconomic variables on the activity of the Saudi stock market for the period 1997-2017. Macroeconomic variables were: GDP, interest rate on time deposits, inflation rate. The variables of the Saudi stock market activity were: stock price index, market value of shares, value of traded shares. To achieve this objective, the researcher used the ARDL model for the self-regression of the lagged distributed time gaps. The most important results of the research are: The effect of macroeconomic variables on the performance indicators in the Saudi stock market is not important in the short term and is statistically significant in the long term according to the proposed models, so investors in this market can rely on macroeconomic variables in Predict the movement of the stock market and predict long-term profits and losses.

scholarly journals Stochastic and Momentum Analysis of Nepalese Stock Market

2018 ◽  
Vol 11 (1) ◽  
pp. 14-22
Author(s):  
Rashesh Vaidya
Keyword(s):  
Stock Market ◽  
Basic Concept ◽  
Moving Average ◽  
Fiscal Year ◽  
Short Term ◽  
Stochastic Oscillator ◽  
Zero Line ◽  
June July

The stochastic oscillator is one of the popular tools used by technical analysts. The tools are used mainly to find the overbought and oversold position in the stock market. The stochastic values are between 0-100 which helps to determine the market scenario. The two stochastic indicators are comprised of two lines namely; %K and %D. The investors using the short-term moving average follows %K and for long-term moving average for %D. Though, both are used for buy signal or sell signal by the investors. The basic concept is if, the value of %K is seen above %D, which reflects to sell position, which in context to Nepalese stock market, the scenario is seen during the month of June-July of every fiscal year. At the same time, momentum uses transaction signal or trade signal or the zero ‘0’ line to find the bearish or bullish trend of the market. The momentum of NEPSE index clearly pictures out the bullish and the bearish trend for a specific duration. If the momentum line touches the ‘zero line’, the NEPSE has changed its trend.

scholarly journals THE ISLAMIC CAPITAL MARKET VOLATILITY: A COMPARATIVE STUDY BETWEEN IN INDONESIA AND MALAYSIA

2013 ◽  
Vol 15 (4) ◽  
pp. 391-415
Author(s):  
Muhammad Syafii Antonio ◽  
Hafidhoh Hafidhoh ◽  
Hilman Fauzi
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Crude Oil ◽  
Capital Market ◽  
Oil Price ◽  
Crude Oil Price ◽  
Short Term ◽  
Macroeconomic Variables ◽  
Jones Index

This study attempts to examine the short-term and long-term relationship among selected global anddomestic macroeconomic variables fromeach country (Fed rate, crude oil price, Dow Jones Index, interest rate, exchange rate and inflation) for Indonesia and Malaysia Islamic capital market (Jakarta Islamic Index (JII) and FTSE Bursa Malaysia Hijrah Shariah Index (FHSI). The methodology used in this study is vector error correction model (VECM) for the monthly data starting from January 2006 to December 2010. The result shows that in the long-term, all selectedmacroeconomic variables except Dow Jones Index variable have significantly affect in both Islamic stock market FHSI and JII, while in the short-term there is no any selected macroeconomic variables that significantly affect FHSI and only inflation, exchange rate and crude oil price variables seem to significantly affect JII. Keywords : Islamic Stock Market, Jakarta Islamic Index, FTSE Hijrah Shariah Index, VAR/VECMJEL Classification: E52, E44

scholarly journals Price Discovery on Stock Index Futures markets under Extreme Events: Evidence from China

2018 ◽  
Vol 14 (25) ◽  
pp. 190 ◽  
Author(s):  
Qian Zhang
Keyword(s):  
Stock Market ◽  
Futures Markets ◽  
Price Discovery ◽  
Stock Index ◽  
Stock Index Futures ◽  
Chinese Stock Market ◽  
Short Term ◽  
Index Futures ◽  
Stable Period

In this paper, the price discovery function of stock index futures for spot stock index is studied in view of the soaring and plunging periods of Chinese stock market in recent years. We use the VECM model to do empirical research under periods of stationary, boom and slump. The results show that there is a long-term relationship between CSI 300 index and CSI 300 index futures. During the stable period of Chinese stock market, the CSI 300 stock index futures are sensitive to the short-term impact, and its ability of price discovery is obviously. However, during the period of boom and collapse, the price discovery function of CSI 300 index futures is weak.

scholarly journals The Economics of the Name Change: Long-term Adjustments towards EU/NATO or Short-term Resolution of Political Uncertainty?

2021 ◽  
Vol 12 (1) ◽  
pp. 86-105
Author(s):  
Bojan Srbinoski ◽  
Klime Poposki ◽  
Ksenija Dencic-Mihajlov ◽  
Milica Pavlovic
Keyword(s):  
Stock Market ◽  
Stock Price ◽  
Eu Enlargement ◽  
Political Uncertainty ◽  
Short Term ◽  
Market Reactions ◽  
Name Change ◽  
Stock Market Reactions ◽  
The Eu

North Macedonia and Greece resolved the 27-year country name dispute and removed the main hurdle for North Macedonia to start the accession processes towards the EU and NATO. The paper analyzes the stock market movements around several events related to the name issue resolution to uncover whether Macedonian companies experienced stock price adjustments according to the long-term benefits/costs of joining the EU/NATO. The dynamics of the market reactions suggest that the investors reacted systematically to the short-term political uncertainty created around the referendum rather than to the long-term perspectives of the EU/NATO integration. We integrate the knowledge from the literature which explores stock market reactions to EU enlargement/exit and political elections and provide contributions for researchers and policymakers.

scholarly journals A Novel Stock Index Intelligent Prediction Algorithm Based on Attention-Guided Deep Neural Network

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yangzi Zhao
Keyword(s):  
Neural Network ◽  
Stock Market ◽  
Deep Neural Network ◽  
Short Term Memory ◽  
Stock Index ◽  
Prediction Algorithm ◽  
Short Term ◽  
Term Memory ◽  
Model Based

The stock market is affected by economic market, policy, and other factors, and its internal change law is extremely complex. With the rapid development of the stock market and the expansion of the scale of investors, the stock market has produced a large number of transaction data, which makes it more difficult to obtain valuable information. Because deep neural network is good at dealing with the prediction problems with large amount of data and complex nonlinear mapping relationship, this paper proposes an attention-guided deep neural network stock prediction algorithm. This paper synthesizes the daily stock social media text emotion index and stock technology index as the data source and applies them to the long-term and short-term memory neural network (LSTM) model to predict the stock market. The stock emotion index is extracted by constructing a social text classification emotion model of bidirectional long-term and short-term memory neural network (Bi-LSTM) based on attention mechanism and glove word vector representation algorithm. In addition, a dimensionality reduction model based on decision tree (DT) and principal component analysis (PCA) is constructed to reduce the dimensionality of stock technical indicators and extract the main data information. Furthermore, this paper proposes a model based on nasNet for pattern recognition. The recognition results can be used to automatically identify short-term K-line patterns, predict reliable trading signals, and help investors customize short-term high-efficiency investment strategies. The experimental results show that the prediction accuracy of the proposed algorithm can reach 98.6%, which has high application value.

scholarly journals Role of Framing towards Islamic Business Engagement in Asia: A Case of Pakistan

2020 ◽  
Vol V (III) ◽  
pp. 23-31
Author(s):  
Muhammad Awais ◽  
Waqar Haider Hashmi ◽  
Adeel Mustafa
Keyword(s):  
Stock Market ◽  
Primary Data ◽  
Research Paradigm ◽  
Short Term ◽  
Word Cloud ◽  
Short Term Investment ◽  
The Way

The aim of this study is to examine the phenomenon of framing as a cause of making wrong decisions while investing in Islamic stocks. Framing refers to the bias of people that describes the way they respond to a specific option as per its offer. After collecting primary data through interviews, including open-ended questions from the Pakistani stock market under the subjective or constructivist research paradigm, NVivo it is applied to get word cloud for appropriate analysis. The study finds that there are so many complexities and impurities that blindfold brokers and investors to differentiate between Shariah-compliant versus conventional stocks. This research can be further extended by differentiating between long-term and short-term investment horizons.

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