scholarly journals Neural Network Backpropagation Identification of Jakarta Islamic Index (JII) Stock Price Patterns

2020 ◽  
Vol 4 (1) ◽  
pp. 90-94
Author(s):  
Musli Yanto ◽  
Liga Mayola ◽  
M. Hafizh
Keyword(s):  
Interest Rates ◽  
Stock Prices ◽  
Stock Price ◽  
Share Prices ◽  
Inflation Rates ◽  
Price Patterns ◽  
Price Movements ◽  
Pattern Determination ◽  
Network Patterns ◽  
Stock Price Movements

Jakarta Islamic Index (JII) is an organization engaged in the economy with the aim to pay attention to stock movements every day. With the JII, people who do not understand about shares and their movements, will be easy to know and understand the movement of shares that occur at certain times. The problem in this research is that many investors are unable to predict the rise and fall of stock prices. The prediction process can be done with a backpropagation algorithm. The algorithm is a concept of computer science which is widely used in the case of analysis, prediction and pattern determination. The process starts from the analysis of the variables used namely interest rates, exchange rates, inflation rates and stock prices that occurred in the previous period. The variables used are continued in the formation of network patterns and continued in the process of training and testing in order to produce the best network patterns so that they are used as a process of identifying JII stock price movements. The results obtained in the form of the value of stock price movements with an error rate based on the MSE value of 11.85% so that this study provides information in the form of knowledge for making a decision. The purpose of the research is used as input for investors in identifying share prices. In the end, the benefits felt from the results of this study, investors can make an initial estimate before investing in JII.

An Empirical Study on Efficient Market Hypothesis with reference to FMCG Sector

GIS Business ◽  
2020 ◽  
Vol 15 (1) ◽  
pp. 109-126
Author(s):  
Nitin Tanted ◽  
Prashant Mistry
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Abnormal Returns ◽  
Weak Form ◽  
Efficient Market Hypothesis ◽  
Controversial Issues ◽  
Efficient Market ◽  
Price Movements ◽  
Run Test ◽  
Stock Price Movements

One of the highly controversial issues in the area of finance is “Efficient Market Hypothesis”. Efficient Market Hypothesis states that, “In an efficient market, all available price information is reflected in the stock prices and it is not possible to generate abnormal returns compared to other investors.” A lot of studies conducted previouslyto test the Efficient Market Hypothesis, confirmed the theory until recent years, when some academicians found it to be non-applicable in financial markets. According to them, it is possible to forecast the stock price movements using Technical Analysis. The results of various studies have been inconclusive and indefinite about the issue. This study attempted to test the efficiency of FMCG Sector stocks in India in its weak form. For the study, closing prices of top 10 stocks from Nifty FMCG index has been taken for the 5-year period ranging from 1st October 2014 to 30th September 2019. Wald-Wolfowitz Run test has been used to test the haphazard movements in the stock price movements. The results indicated that FMCG sector stocks does support the Efficient Market Hypothesis and exhibit efficiency in its weak form. Hence, it is not possible to accurately predict the price movements of these stocks.

scholarly journals The Effect of The Match Results on Bali United’s Stock Price Movements

2020 ◽  
Vol 3 (1) ◽  
pp. 26
Author(s):  
Agung Novianto Margarena ◽  
Arian Agung Prasetiyawan
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
European Countries ◽  
Football Club ◽  
Study Results ◽  
Price Movements ◽  
Positive Effect ◽  
Stock Price Movements

This study was conducted due to differences in the study results inseveral countries related to the effect of the match results on stockmovements. Dimic et. al (2019) stated the match results effect themovement of stock prices, while Mishra & Smyth (2010) stated thevice versa. Then, Floros (2014) put forward different results throughthe study of four clubs in four European countries. Thus, this studyreexamines the effect of the match results on the stock pricemovement of Bali United. Moreover, Bali United is the first SoutheastAsian football club to be listed on the stock market. This study uses aquantitative method with a sample of 31 Bali United’s matches afterlisted on the stock market. The data were analyzed using simple linearregression with SPSS 21 with either won, drawn or lost match resultsrepresented by goal margins. The stock price movements arerepresented by stock prices after the results of the match. It was foundthat the results of the match had a positive effect on the stockmovement of Bali United

Anomalous Market Movements and the Rolling Settlement: Empirical Evidence from Indian Stock Markets

2007 ◽  
Vol 11 (4) ◽  
pp. 31-44 ◽  
Author(s):  
Ramesh Chander ◽  
Kiran Mehta
Keyword(s):  
Stock Prices ◽  
Stock Markets ◽  
Stock Price ◽  
Structural Changes ◽  
Abnormal Returns ◽  
Weekend Effect ◽  
Settlement Period ◽  
Price Movements ◽  
Anomalous Pattern ◽  
Stock Price Movements

Investors and analysts are unable to predict stock price movements consistently so as to beat the market in informationally efficient markets. Still, concerted efforts are being made to earn abnormal returns discerning some anomalous pattern in the stock price movements. Also, the study of some structural changes in the market leading to, or removing some anomalous pattern in the stock prices, are of interest to investors and analysts. The present study was conceptualised to scrutinise whether anomalous patterns yield abnormal return consistently for any specific day of the week even after introduction of the compulsory rolling settlement on Indian bourses. Three market series viz., BSE Sensex, S and P CNX Nifty and S and P CNX 500 were observed on daily basis for ten years viz., i) Pre-rolling settlement period, April 1997 - December, 2001 and ii) Post-rolling settlement period, January 2002 - March 2007 to discern evidences in this regard. Contrary to developed capital markets, the results reported in this study documented lowest (significant) Friday returns in the pre-rolling settlement period as credible evidence for the weekend effect. The findings recorded for post-rolling settlement period were in harmony with those obtained elsewhere in the sense that Friday returns were highest and those on Monday were the lowest. It implied that arbitrage opportunities existed (for different trade settlement cycle on two exchanges, BSE and NSE) have disappeared consequent to the rolling settlement. On the whole, the study noted stock markets moved more rationally and anomalous return pattern noticed earlier could not sustain, in the post rolling settlement period.

scholarly journals Company fundamentals and stock price movements: The role of crude oil prices – Evidence from Nigerian Stock Exchange (NSE)

2020 ◽  
Vol 3 (1) ◽  
pp. 1-13
Author(s):  
Tijjani Bashir Musa
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Panel Study ◽  
Oil Prices ◽  
Secondary Source ◽  
Linear Regression Models ◽  
Price Movements ◽  
Stock Price Movements

This study analyzed company fundamentals on how it relates and predict stock price movements and the extent of the role of oil prices in moderating the influence of these company fundamentals in stock price movements. The study covered the period of 2014 to 2018. The study is a panel study. A total of 132 companies were sampled from 196 companies listed on the Nigerian Stock Exchange (NSE) as of December 2018. Data were collected from a secondary source. Multiple linear regression models were used to analyze the data. The study found that a relationship exists between selected companies' fundamentals and stock prices, and oil prices moderate the relationship. But EPS and Working Capital have high predictive power on stock price movements but moderating with oil prices the influence reduces significantly. The study recommends among others that Managers of companies in Nigeria should formulate policies and exert effort geared towards improving company fundamentals in the event of oil prices increases.

scholarly journals Do Blockchain Stocks Exhibit More Herding Behaviour than Traditional Stocks?

2021 ◽  
Vol 10 (4) ◽  
Author(s):  
Prakhar Goel ◽  
Abhishek Dev
Keyword(s):  
Social Media ◽  
Stock Returns ◽  
Automotive Industry ◽  
Stock Prices ◽  
Stock Price ◽  
Absolute Deviation ◽  
Cross Sectional ◽  
Price Movements ◽  
The Impact ◽  
Stock Price Movements

While the volatile behaviour of cryptocurrency is extensively studied, the stock market’s blockchain sector, which has not been given much attention in the academic world, operates very differently from traditional stock industries. The paper hypothesizes that blockchain stocks exhibit more herding behaviour than traditional stocks and uses quantitative data analysis techniques to study it. The automotive industry is taken as a representative of traditional stocks. Cross-Sectional Absolute Deviation, the academic standard for herding behaviour, is used as the primary comparative measure between blockchain and automotive stocks. It reveals that blockchain industry has significant herding, while rational pricing mechanisms prevail in the automotive industry. Supporting this conclusion, a correlation matrix of stock prices of small market capitalisation firms in each industry is constructed, analysing how closely stock price movements in an industry are related. The correlation coefficient for blockchain stocks is 20% higher than the coefficient for automotive stocks. This indicates that blockchain stocks likely exhibit higher levels of herding. The impact of social media on stock price movements in the two industries is analysed by conducting a correlation study between Google Trends data for industry-related keywords and individual stock returns. The blockchain industry saw a significantly higher correlation, likely suggesting that social media has a stronger influence on blockchain stock price movements. Finally, the paper provides possible explanations for why herding behaviour is more prominent in the blockchain stocks compared to traditional stocks. These include absence of traditional stock valuation metrics, lack of financial knowledge and role of social media.

ENDOGENOUS SHORT-SALE CONSTRAINT, STOCK PRICES AND OUTPUT CYCLES

1997 ◽  
Vol 1 (1) ◽  
pp. 228-254 ◽  
Author(s):  
HAROLD H. ZHANG
Keyword(s):  
Risk Aversion ◽  
Stock Prices ◽  
Stock Price ◽  
Trading Volume ◽  
Time Preference ◽  
Short Sale Constraints ◽  
Short Sale ◽  
Price Movements ◽  
Negative Shock ◽  
Stock Price Movements

This study examines the effect of short-sale constraints on a stock market, in particular, on stock prices, trading volume, and the relationship between stock price movements and output cycles. The economic model features incomplete markets and heterogeneous agents. The short-sale constraint is endogenously determined in the economy and is a function of agents' risk aversion, time preference, and exogenous driving forces. The dynamic model is solved using a policy function iteration algorithm. We find that, for an array of reasonable time-preference parameters and risk-aversion coefficients, the short sale limits range from 27 to 45% of total outstanding shares. Imposing short-sale constraints causes stock prices to move upward. Trading volume is high when some agents have a large amount of stock holdings but incur a negative shock on their nonfinancial income and is low when some agents have few stock holdings and also incur a negative shock to their nonfinancial income. Stock prices are found to be countercyclical and the expected stock returns are procyclical. These countercyclical stock-price movements are shown to be related to the imposition of a short-sale constraint.

scholarly journals Machine Learning-Based Analysis of the Association Between Online Texts and Stock Price Movements

2018 ◽  
Vol 21 (61) ◽  
pp. 95 ◽  
Author(s):  
František Dařena ◽  
Jonáš Petrovský ◽  
Jan Žižka ◽  
Jan Přichystal
Keyword(s):  
Machine Learning ◽  
Stock Prices ◽  
Stock Price ◽  
Price Change ◽  
Processing Parameters ◽  
Substantial Impact ◽  
Price Movements ◽  
Online Texts ◽  
Textual Content ◽  
Stock Price Movements

The paper presents the result of experiments that were designed with the goal of revealing the association between texts published in online environments (Yahoo! Finance, Facebook, and Twitter) and changes in stock prices of the corresponding companies at a micro level. The association between lexicon detected sentiment and stock price movements was not confirmed. It was, however, possible to reveal and quantify such association with the application of machine learning-based classification. From the experiments it was obvious that the data preparation procedure had a substantial impact on the results. Thus, different stock price smoothing, lags between the release of documents and related stock price changes, five levels of a minimal stock price change, three different weighting schemes for structured document representation, and six classifiers were studied. It has been shown that at least part of the movement of stock prices is associated with the textual content if a proper combination of processing parameters is selected.

scholarly journals Effect of Corporate Fundamental and Macro Economic Factors on Share Prices in Indonesia Stock Exchange Market

2020 ◽  
Vol 1 (2) ◽  
pp. 117-127
Author(s):  
Mulyanto Mulyanto ◽  
◽  
Riyanti Riyanti ◽  
Keyword(s):  
Interest Rates ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Secondary Data ◽  
Sampling Technique ◽  
Least Square ◽  
Research Subjects ◽  
Macroeconomic Factors ◽  
Share Prices

This paper aims to examine and analyze the influence of fundamental and macroeconomic factors on stock prices either partially or simultaneously. The research subjects focused on LQ45 Index companies listed on the Indonesia Stock Exchange. Secondary data of Indonesian stock market share prices covering between 2013-2019 were used. One Least Square was used to analyze the data. The sampling technique used is the purposive sampling method, the sample used is the LQ45 Index Company. The results shows fundamental factors include ROA, ROE, DER, EPS, and PER have a positive and significant effect on stock prices. and Inflation and interest rates have a negative and significant effect on stock prices. And simultaneously these variables have a significant and significant effect on stock prices. The study can provide a picture that stock price movements have a strong and clear influence on the company's fundamentals and are reflected in some of the ratios contained in the financial statements, as well as macroeconomic conditions.

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