scholarly journals Analisis Teknikal Harga Saham Waskita Karya Tahun 2017 dengan Metode ARIMA

2018 ◽  
Vol 7 (1) ◽  
pp. 80-84
Author(s):  
Wahyuni Windasari
Keyword(s):  
Key Words ◽  
Stock Prices ◽  
Stock Price ◽  
Historical Data ◽  
Arima Model ◽  
Security Analysis ◽  
Technical Analysis ◽  
Fundamental Analysis ◽  
Price Movement

As an investor needs to do an analysis before making a decision either in selling or buying shares. Security analysis consist of two types of analysis, namely tecnical analysis and fundamental analysis. Technical analysis to test wheater historical data will predict stock prices as a consideration to buy or sell an investment's instrument. One type of technical analysis is the ARIMA method. In this research uses daily stock price of WSKT Tbk during 1 Januari–10 Oktober 2017 to predict stock prices the few days. The best ARIMA model to describe WSKT stock price movement is MA(4), with MAE predict data is 480.25.Key words : forecasting, ARIMA, technical analysis, stock prices.

scholarly journals Analisis Teknikal Harga Saham Waskita Karya Tahun 2017 dengan Metode ARIMA

2018 ◽  
Vol 7 (1) ◽  
pp. 122-126
Author(s):  
Wahyuni Windasari
Keyword(s):  
Key Words ◽  
Stock Prices ◽  
Stock Price ◽  
Historical Data ◽  
Arima Model ◽  
Security Analysis ◽  
Technical Analysis ◽  
Price Movement

AbstractAs an investor needs to do an analysis before making a decision either in selling or buyingshares. Security analysis consist of two types of analysis, namely tecnical analysis andfundamental analysis. Technical analysis to test wheater historical data will predict stock pricesas a consideration to buy or sell an investment's instrument. One type of technical analysis isthe ARIMA method. In this research uses daily stock price of WSKT Tbk during 1 Januari–10Oktober 2017 to predict stock prices the few days. The best ARIMA model to describe WSKTstock price movement is MA(4), with MAE predict data is 480.25.Key words : forecasting, ARIMA, technical analysis, stock prices.

STOCK EVALUATION USING FUZZY LOGIC

2001 ◽  
Vol 04 (04) ◽  
pp. 585-602 ◽  
Author(s):  
HUSSEIN DOURRA ◽  
PEPE SIY
Keyword(s):  
Fuzzy Logic ◽  
Human Behavior ◽  
Stock Prices ◽  
Stock Price ◽  
Evaluation Method ◽  
Technical Analysis ◽  
Price Movement ◽  
Analysis Theory ◽  
System Output ◽  
Logic System

We use fuzzy logic engineering tools to detect human behavior in the finance arena, specifically in the technical analysis field. Since technical analysis theory consists of indicators used by experts to evaluate stock prices, the new proposed method maps these indicators into new inputs that can be fed into a fuzzy logic system. This system can create an optimum computerized model to evaluate stock price movement. This method relies on human psychology to predict human behavior when certain price movements or certain price formations occur. The success of the system is measured by comparing system output versus stock price movement. The new stock evaluation method is proven to exceed market performance and it can be an excellent tool in the technical analysis field. The flexibility of the system is also demonstrated.

scholarly journals Technical Analysis and Malaysian Banking Sector during COVID-19 Pandemic

2020 ◽  
Vol 4 (1) ◽  
pp. 41-46
Author(s):  
Kelvin Yong Ming Lee
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Banking Sector ◽  
Moving Average ◽  
Investment Decision ◽  
Movement Control ◽  
Technical Analysis ◽  
Price Movement ◽  
Technical Indicator ◽  
Control Order

The announcements of Movement Control Order and Loan Moratorium caused a significant impact on the stock prices of Malaysian banks during the COVID-19 pandemic. This study aims to investigate the effectiveness of technical analysis in predicting the stock price movement and the ability of the technical analysis in generating returns. In doing so, six moving average rules used as the proxy of technical analysis and tested in this study. Majority of the MA rules shown positive returns before the various announcements dates. Specifically, this study revealed that MA rules of (2,5) and (2,10) were among the best performing MA rules during the COVID-19 pandemic. This study also recommends the investors to use the signals emitted by the technical indicator as the reference for their investment decision in the banks’ stock.

scholarly journals PENGARUH TOTAL ASSET TURN OVER, RETURN ON ASSET DAN RETURN ON EQUITY TERHADAP ACCUMULATION DISTRIBUTION LINE

2017 ◽  
Vol 18 (3) ◽  
Author(s):  
Luna Haningsih ◽  
Zulkifli Zulkifli ◽  
Caturida Meiwanto Doktoralina
Keyword(s):  
Stock Price ◽  
Trading Volume ◽  
Technical Analysis ◽  
Total Asset ◽  
Fundamental Analysis ◽  
Return On Assets ◽  
Return On Equity ◽  
Asset Turnover ◽  
Distribution Line ◽  
Price Movements

Fundamental and technical analysis is used by analysis to predict the trend ofstock price and trading volume. Studies conducted aimed to determine the effect of fundamental analysis to technical analysis. Combining two forms of analysis can produce a more accurate prediction of the stock price movement of listed cement companies in Indonesia Stock Exchange. Research experts indicate that the fundamental and technical analysis can be used independently with the ability to predict stock price movements. This study combines both analysis in a model that can provide a more robust predictive capability in the Company's share price movements of cement. Fundamental analysis is the economy wide scope, one of the predictions of financial performance. In this study the total asset turnover, return on assets and return on equityto determine which stocks are pretty good. While technical analysis is usedaccumulation distribution line that has a better ability to predict future stock prices because the data contained technical stock price and trading volume to determine when to buy and sell momentum. These results indicate that the total asset turnover, return on assets and return on equity significantly influence the accumulation distribution line. While the individual that the return on equity has no significant effect. The results of this study are expected to improve knowledge for the readers, especially investors in order to obtain optimal benefits.

scholarly journals Comparison of ARIMA, ANN and LSTM for Stock Price Prediction

2020 ◽  
Vol 218 ◽  
pp. 01026
Author(s):  
Qihang Ma
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Short Term Memory ◽  
Moving Average ◽  
Arima Model ◽  
Predictive Ability ◽  
Research Direction ◽  
Ann Model ◽  
Advantages And Disadvantages ◽  
Stock Price Prediction

The prediction of stock prices has always been a hot topic of research. However, the autoregressive integrated moving average (ARIMA) model commonly used and artificial neural networks (ANN) still have their own advantages and disadvantages. The use of long short-term memory (LSTM) networks model for prediction also shows interesting possibilities. This article compares three models specifically through the analysis of the principles of the three models and the prediction results. In the end, it is believed that the LSTM model may have the best predictive ability, but it is greatly affected by the data processing. The ANN model performs better than that of the ARIMA model. The combination of time series and external factors may be a worthy research direction.

scholarly journals FORECASTING OF THE STOCK RATE OF LEADING WORLD COMPANIES USING ECONOMETRIC METHODS AND DCF ANALYSIS

2020 ◽  
pp. 33-41
Author(s):  
Olena Nikolaieva ◽  
Anzhela Petrova ◽  
Rostyslav Lutsenko
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Financial Analysis ◽  
Moving Average ◽  
Arima Model ◽  
Financial Indicators ◽  
Econometric Methods ◽  
Global Companies ◽  
The Moment ◽  
Data Analysis Methods

In this article, we will cover various models for forecasting the stock price of global companies, namely the DCF model, with well-reasoned financial analysis and the ARIMA model, an integrated model of autoregression − moving average, as an econometric mechanism for point and interval forecasting. The main goal is to compare the obtained forecasting results and evaluate their real accuracy. The article is based on forecasting stock prices of two companies: Coca-Cola HBC AG (CCHGY) and Nestle S.A. (NSRGF). At the moment, it is not determined which approach is better for predicting the stock price − the analysis of financial indicators or the use of econometric data analysis methods.

scholarly journals Pengaruh NPM, ROA, ROE terhadap Harga Saham pada Perusahaan LQ45

2020 ◽  
Vol 30 (5) ◽  
pp. 1258
Author(s):  
Kannia Aulia Sahari ◽  
I Wayan Suartana
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Linear Regression Analysis ◽  
Sampling Technique ◽  
Multiple Linear Regression Analysis ◽  
Fundamental Analysis ◽  
Share Prices ◽  
Research Population ◽  
Profitability Ratios

The purpose of this study is to determine the movement of stock prices, namely fundamental analysis where profitability ratios are often used in fundamental analysis, namely NPM, ROA and ROE This research was conducted on companies incorporated in the 2014-2018 LQ45 index on the Indonesia Stock Exchange. The research population is 68 companies. Samples were selected using a purposive sampling technique so that the number of samples obtained was 26 companies and the number of observations over 5 years was 130 observations. Data analysis techniques using multiple linear regression analysis. Based on the results of this analysis show that NPM and ROA have no effect on stock prices so that they are unable to increase share prices in companies incorporated in the LQ45 index, while ROE affects stock prices so the higher the ROE level the higher the stock prices at companies incorporated in the LQ45 index. Keywords: NPM; ROA; ROE; Stock Price.

scholarly journals FORECASTING HARGA SAHAM MENGGUNAKAN METODE SIMPLE MOVING AVERAGE DAN WEB SCRAPPING

2019 ◽  
Vol 21 (3) ◽  
pp. 234-241
Author(s):  
Dessy Tri Anggraeni
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Moving Average ◽  
Technical Analysis ◽  
Secondary Market ◽  
A Value ◽  
Price History ◽  
The Difference ◽  
Absolute Percent Error ◽  
Error Method

Abstract:  The fluctuative of stock prices in a secondary market provide the possibility for investors/traders to gain profits through the difference in stock prices (capital gain). In order to obtain these benefits, it is necessary to analyze before buying shares, through fundamental and technical analysis. One of several methods in Technical Analysis is Simple Moving Average Method. This method can be used to predict (forecast) stock prices by calculating moving average of the stock price history. Historical stock prices can be obtained in real time using the Web Scrapper technique, so the results is more quickly and accurately. Using the MAPE (Mean Absolute Percent Error) method, the level of accuracy of forecasting can be calculated. As a result, the program was able to run successfully and was able to display the value of forecasting and the level of accuracy for the entire data tested in LQ45. Besides forecasting with a value of N = 5 has the highest level of accuracy that reaches 97,6 % while the lowest one is using the value of N = 30 which is 95,0 %.

scholarly journals Analisis Fundamental dan Teknikal terhadap Harga Saham pada Perusahaan Utilitas dan Transportasi

2021 ◽  
Vol 31 (2) ◽  
pp. 499
Author(s):  
Christina Christina ◽  
Sulastri Halim ◽  
Valentina Angrensia ◽  
Arie Pratania Putri
Keyword(s):  
Stock Price ◽  
Trading Volume ◽  
Technical Analysis ◽  
Fundamental Analysis ◽  
Current Ratio ◽  
Book Value ◽  
Asset Turnover ◽  
Equity Ratio

The purpose of this research is to known if fundamental and technical analysis could affect the price of stock. Furthermore each of analysis have several factor to determine the stock price, as for fundamental analysis we will use current ratio, DER, and ROA while for the technical analysis we will use IHSG and trading volume. From the population of 69 company we pick 18 sample that suit the analysis, for the regression it will use multiply 5 because of the independent variabel. According to the partial research, there are only two factor that have significant impact to the price of stock, it is DER And ROA, as for the rest of the factor it don’t really affect the price. Simultaneously the five variabel shown the effect to the stock price according to result of adjused r square amount of 29.1% . From the variation of stock price according to the variabel such as CR, DER , ROA. IHSG and trading volume, while the rest 70.9% affected by other factor such as company asset turnover, price earning ratio and price book value. Keywords: Current Ratio; Debt to Equity Ratio; IDX Composite; Return On Asset; Stock Price; Trading Volume.

scholarly journals A study on technical analysis of s&p cnx nifty index

2013 ◽  
Vol 1 (1) ◽  
pp. 171-181
Author(s):  
Ragupathi M ◽  
Arthi B
Keyword(s):  
Intrinsic Value ◽  
Technical Analysis ◽  
Fundamental Analysis ◽  
Past Performance ◽  
Price Movement ◽  
Factors Affecting ◽  
The Past ◽  
Future Performance ◽  
The Difference ◽  
Future Growth

Technical analysts do not attempt to measure a security's intrinsic value; instead they look at stock charts for patterns and indicators that will determine a stock's future performance. The use of past performance should come as no surprise. People using fundamental analysis have always looked at the past performance of companies by comparing fiscal data from previous quarters and years to determine future growth. The difference lies in the technical analyst's belief thatsecurities move according to very predictable trends and patterns. These trends continue until something happens to change the trend, and until this change occurs, price levels are predictable. There are many instances of investors successfully trading a security using only their knowledge of the security's chart, without even understanding what the company does. However, although technical analysis is a terrific tool, most agree it is much more effective when used in combination with fundamental analysis. The technical analysis reveals the peaks, bottoms, trends, patterns and other factors affecting a stock‘s price movement and then makes buy/sell decisions based on those factors. The tools namely RSI and EMA have been used to predict the index price movement of S&P CNX Nifty.

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