scholarly journals Application of Genetic Algorithm and Personal Informatics in Stock Market

2018 ◽  
Vol 2 (2) ◽  
pp. 68 ◽  
Author(s):  
Khulood Albeladi ◽  
Salha Abdullah
Keyword(s):  
Genetic Algorithms ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Stock Index ◽  
Target Market ◽  
Technical Data ◽  
Personal Informatics ◽  
Informatics System ◽  
Input Variables

The financial market is extremely attractive since it moves trillion dollars per year. Many investors have been exploring ways to predict future prices by using different types of algorithms that use fundamental analysis and technical analysis. Many professional speculators or amateurs had been analysing the price movement of some financial assets using these algorithms. The use of genetic algorithms, neural networks, genetic programming combined with these tools in an attempt to find a profitable solution is very common. This study presents a prototype that utilizes genetic algorithms (GAs) and personal informatics system (PI) for short-term stock index forecast. The prototype works according to the following steps. Firstly, a collection of input variables is defined through technical data analysis. Secondly, GA is applied to determine an optimal set of input variables for a one-day forecast.  The data is gathered from the Saudi Stock Exchange as being the target market. Thirdly, PI is utilised to create a smart environment, which enables visualisation of stock prices. The outcome indicates that this approach of forecasting the stock price is positive. The highest accuracy obtained is 64.67% and the lowest one is 48.06%.

scholarly journals The Impact of Corona Virus Disease 2019 (COVID-19) on Indonesia Property Stock Index

2021 ◽  
Vol 4 (2) ◽  
pp. 85-96
Author(s):  
Kevin Ronaldo Gotama ◽  
Njo Anastasia
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Virus Disease ◽  
Sampling Technique ◽  
Stock Index ◽  
Event Analysis ◽  
Corona Virus ◽  
Before And After ◽  
The Impact

A promising investment in the property sector is due to appreciation in property value. As an economic instrument, the stock market, inseparable from different environmental factors, was triggered by incident in Wuhan, Hubei Province, China, an outbreak of acute respiratory tract infection 2 (SARS-CoV-2) in December 2019 and then spread across China. This study is a comparative study on the stock index of the property sector on the stock exchange of countries affected by the Corona Virus Disease 2019 (COVID-19) case, with a purposive sampling technique according to certain criteria for sample selection. The event analysis was performed by analyzing market reaction; with COVID-19 incident effect as one of the event tests, the stock price index. The findings of the study indicate that there is an index response to the incident of COVID-19. The reflected reaction shows in the abnormal return and trade volume activity before and after the incident. Thus, this study is expected to be taken into consideration for stock investors regarding the impact of the Corona Virus Disease 2019 (COVID-19) pandemic on stock prices, by providing an overview of changes in stock prices during the monitoring period, so that they can make investment decisions in the period before and after incident.

scholarly journals LQ45 Stock Index Prediction using k-Nearest Neighbors Regression

2019 ◽  
Vol 8 (3) ◽  
pp. 2388-2391 ◽  
Keyword(s):  
Capital Market ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Numerical Data ◽  
Nearest Neighbors ◽  
Stock Index ◽  
K Nearest Neighbors ◽  
Stock Price Prediction ◽  
The Capital Market

The capital market is an organized financial system consisting of commercial banks, intermediary institutions in the financial sector and all outstanding securities. One of the benefits of the capital market is creating opportunities for the community to participate in economic activities, especially in investing. In daily stock trading activities, stock prices tend to have fluctuated. Therefore, stock price prediction is needed to help investors make decisions when they want to buy or sell their shares. One asset for investment is shares. One of the stock price indices that attracts many investors is the LQ45 stock index on the Indonesian stock exchange. One of the algorithms that can be used to predict is the k-Nearest Neighbors (kNN) algorithm. In the previous study, kNN had a higher accuracy than the moving average method of 14.7%. This study uses kNN regression method because it predicts numerical data. The results of the research in making the LQ45 stock index prediction application have been successfully built. The highest accuracy achieved reaches 91.81% by WSKT share.

Estimating Spillover Effect and Leverage Effect Using EGARCH-ARMA Approach in Mongolian Stock Exchange

Jurnal METRIS ◽  
2019 ◽  
Vol 20 (2) ◽  
pp. 71-76
Author(s):  
Cheng-Wen Lee ◽  
Dolgion Gankhuyag
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Spillover Effect ◽  
Time Frame ◽  
Stock Index ◽  
Leverage Effect ◽  
Financial Instruments ◽  
Stock Volatility ◽  
Market Index

This study checked the spillover effect and leverage effect from 2 January 2012 to 27 December 2017 in the Mongolian Stock Index MSE20 time frame. We found spillover effect on individual stock prices from the market index, but our analysis did not support individual stock has a spillover effect on stock index. In terms of volatility, only market and stock volatility have a bilateral spillover effect. Stock index in particular has a much stronger influence on stock price. Our research did not support previous studies for the leverage effect of the EGARCH-ARMA method, suggesting negative asymmetric influence of volatility such that two financial instruments overlap in their value.

scholarly journals The Effects of Earnings Per Share and Firm Size to Stock Price LQ45 Company Listed in Indonesian Securities

2018 ◽  
Vol 7 (4.9) ◽  
pp. 247
Author(s):  
Arma Yuliza
Keyword(s):  
Regression Analysis ◽  
Firm Size ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Stock Index ◽  
Earnings Per Share ◽  
The Relationship

This study was conducted by the firm that included the stock index of IDX (Indonesian stock exchange) consist of the 45 best stocks (LQ45 index companies) that are listed on the Indonesian Securities. This study aims to assess the effect of earnings per share and the firm size on stock prices. The purpose of this study is also to prove that the size of the firm can moderate the relationship between earnings per share and stock prices. By conducting a regression analysis, this study gives evidence that earnings per share and firm size have a significant effect on stock prices. The size of the firm is also able to moderate the relationship between earnings per share and stock prices. The results of this study gave evidence that profit and the size of the company can provide important information for investors in making decisions. 

Forecasting of Stock Price Using Autoregressive Integrated Moving Average Model

2019 ◽  
Vol 16 (8) ◽  
pp. 3519-3524
Author(s):  
Loh Chi Jiang ◽  
Preethi Subramanian
Keyword(s):  
New York ◽  
Stock Prices ◽  
Stock Price ◽  
Time Series Data ◽  
Stock Exchange ◽  
Moving Average ◽  
Arima Model ◽  
Stock Index ◽  
Series Data ◽  
Autoregressive Integrated Moving Average

Finance sector is highly volatile where the stock prices fluctuate rapidly and it is usually challenging to forecast. The unstable conditions and rapid changes can drastically modify the monetary value of an organization or an individual. Hence, the prediction of stock prices continues to remain as one of the sizzling and vital topics in the applications of data mining in the finance sector. This forecasting is significant as it has the potential to reduce the losses that happen mainly due to erroneous intuitions and blind investment. Moreover, the prediction of stock prices endure to increase in complexity with accumulation of more and more historical data. This paper focuses on American Stock Market (New York Stock Exchange and NASDAQ Stock Exchange). Taking into account the complexity of the prediction, this research proposes Autoregressive Integrated Moving Average (ARIMA) model for estimating the value of future stock prices. ARIMA demonstrated better results for prediction as it can handle the time series data very well which is suitable for forecasting the future stock index.

scholarly journals Rogalsky Effect pada Bursa Efek Indonesia Tahun 2013–2017 (Studi Kasus Indeks Saham Bisnis-27)

2019 ◽  
Vol 4 (2) ◽  
pp. 146
Author(s):  
Muhammad Yusril Laksana Amrullah ◽  
Khairunnisa Khairunnisa
Keyword(s):  
Capital Market ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Research Data ◽  
Stock Index ◽  
Distributed Data ◽  
Market Anomalies ◽  
Smirnov Test ◽  
The Capital Market

Market anomalies described the price of shares outstanding in the market show that performance in contravention of the concept of the capital market efficient in other words the stock price does not reflect all the information is in the capital market efficient. The purpose of this research is to see if is going on the phenomenon of market anomalies seasonal in nature namely rogalsky effect in the index bisnis-27 indonesia stock exchange a period of 2013 - 2017. A method of testing using Kolmogrov-Smirnov test to see normally distributed data, Independent Sample T-Test to hypothesis. The research data the stock price is secondary. Testing of statictic using SPSS 25 version software. The result of this research suggests that not happened Rogalsly Effect on stock index bisnis-27 period 2013 - 2017. The implications of this research indicates that appear new phenomenon but rogalsky effect that occurs on Wednesday.The results that not found Rogalsky Effect, investors can buy stock prices than on Wednesday for a cheap price and sell back in the Wednesday with higher prices especially for January to get maximum return.

scholarly journals The Index and Stock Price Synchronicity: Evidence from Taiwan

2020 ◽  
Vol 198 ◽  
pp. 04029
Author(s):  
Chung-Lien Pan ◽  
Yu-Chun Pan
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Audit Quality ◽  
Stock Exchange ◽  
Small Sample ◽  
Stock Index ◽  
Stock Price Synchronicity ◽  
Taiwan Stock Exchange ◽  
Gray System ◽  
Technical Theory

Research on stock synchronization has always been a topic of concern to scholars and investors. In the past, the focus was mainly on equity concentration, foreign shareholding, audit quality, and other issues, not including indexes. This article uses the monthly data of the Taiwan Stock Exchange Capital Weighted Stock Index (TAIEX) to solve the problem of the index and stock synchronization. And use the technical theory of the gray system to solve the small sample and uncertain problem. The discovery of the synchronization between these indexes and stock prices may provide investors with sufficient reference to make investment decisions.

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

ProBank ◽  
2018 ◽  
Vol 3 (2) ◽  
pp. 17-21
Author(s):  
Heriyanta Budi Utama ◽  
Florianus Dimas Gunurdya Putra Wardana
Keyword(s):  
Gross Domestic Product ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Sampling Technique ◽  
Share Price ◽  
Domestic Product ◽  
Coefficient Of Determination ◽  
Test Results ◽  
Purposive Sampling

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

scholarly journals PENGARUH INFLASI, PROFITABILITAS, STRUKTUR MODAL, DAN EARNING PER SHARE TERHADAP HARGA SAHAM PERUSAHAAN CONSUMER GOODS

2019 ◽  
Vol 8 (6) ◽  
pp. 3930
Author(s):  
Septia Wulandari Suarka ◽  
Ni Luh Putu Wiagustini
Keyword(s):  
Data Collection ◽  
Consumer Goods ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Participant Observation ◽  
Share Price ◽  
Significant Positive Effect ◽  
Positive Effect

The purpose of this study is to analyze the significance of the influence of inflation, ROE, DER, and EPS on stock prices. This research was conducted at Concern Goods Companies that are listed on the Indonesia Stock Exchange (IDX) for the 2015-2017 period. The number of samples of this study were 31 companies. Data collection is done by the method of non-participant observation. Based on the results of the analysis found that inflation, ROE. DER, and EPS simultaneously have a significant effect on stock prices. Partially Inflation and DER have no significant effect on stock prices, this indicates that investors do not see Inflation and DER as a decision to buy shares. While partially ROE and EPS have a significant positive effect on stock prices, this shows that investors pay attention to ROE and EPS in deciding to invest. The higher the ROE and EPS, the higher the investor's interest in investing in the company's capital, so that the share price will go up. Keywords: Inflation, ROE, DER, EPS, stock price    

scholarly journals FACTORS AFFECTING OPERATING CASH FLOW TO STOCK RETURN THROUGH STOCK PRICE

2018 ◽  
Vol 5 (2) ◽  
Author(s):  
Aprih . Santoso
Keyword(s):  
Stock Returns ◽  
Cash Flow ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Return ◽  
Stock Exchange ◽  
Sampling Technique ◽  
Financial Statements ◽  
Manufacturing Companies ◽  
Operating Cash Flow

Abstract : Companies need funds in order to carry out operations such as the financing of production activities, pay employees, pay other expenses related to the operation of the company. One way to obtain these funds is to attract investors to invest in companies in the form of stock, but in making this investment is certainly not easy for investors, because investors need consideration beforehand to find out how the company's performance. The purpose of this study was to examine and analyze the effect of operating cash flow to stock return through stock price at companies listed on the Stock Exchange Year 2012-2015. The data used in this study dala are secondary data from the financial statements of companies listed on the Indonesia Stock Exchange period 2012 - 2015. The data are in the form of financial statements can be obtained from the Indonesian Capital Market Directory (ICMD), the IDX website www.idx.co. id as well as from various other sources to support this research. The population in this research is manufacturing companies listed on the Stock Exchange the period 2012 - 2015. The samples taken by the sampling technique used purposive sampling.From the test results and analysis of the data it can be concluded that operating cash flow directly and indirectly has no effect on stock returns through stock prices showed no significant results. Keywords :  Operating Cash Flow, Stock Price, Stocks Return

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