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 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 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.

scholarly journals Stock Price Movement through Technical Analysis: Empirical Evidence from the Information Technology (IT) Sector

2016 ◽  
Vol 3 (1) ◽  
Author(s):  
Shalini Singh ◽  
Anindita Chakraborty
Keyword(s):  
Stock Price ◽  
Moving Average ◽  
Secondary Data ◽  
Technical Analysis ◽  
Future Price ◽  
Analysis Tool ◽  
Price Movement ◽  
Technical Indicators ◽  
Share Prices ◽  
The Future

<em>Technical analysis forecasts the future asset prices with the use of their historical prices, trading volumes, market action and primarily through the uses of charts that predicts the future price trends. Technical analysis guides the investor to track the market with different indicators which is convenient for their study. Technical indicators aids to analyse the short-term price movement of the shares, most importantly it indicates the turning point and helps in projecting the price movement. This paper is prepared to employ the technical analysis tool to IT index companies. Indicators have been analysed using share prices of companies for 1 years, i.e., from January 2015- December 2015. Study is performed using secondary data, which has been collected from NSE website. The Technical Indicators used for the study are Bollinger Bands and MACD (Moving Average Convergence and Divergence). The purpose of the study is to find the best technical indicator to analyse the share prices.</em>

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 BULL VS BEAR MARKET- AN INVESTMENT GAME ANALYSIS USING MOVING AVERAGE METHOD

2017 ◽  
Vol 5 (11) ◽  
pp. 425-443
Author(s):  
Biswajit Rout ◽  
Ayesha Mohanty ◽  
Akash Kumar Kacharia
Keyword(s):  
Stock Prices ◽  
Banking Sector ◽  
Moving Average ◽  
Technical Analysis ◽  
Two Phase ◽  
Game Analysis ◽  
Financial Decisions ◽  
Bear Market ◽  
Oil And Natural Gas ◽  
Official Site

This paper aims to analyse and interpret the investor perception about investing in stock market. The market is often referred as to bull or bear market. This is key importance for financial decisions and economic analysis. The market behaves differently in these two phase. The bull market is identified when there is constant rise of stock prices whereas bear market is referred when there is fall in stock prices. These phases occur due to different trends of market or economy. Investor sentiments get affected by this. The paper tries to identify and provides understanding about the factors that causes and how it affects the psychology of investors. There are different analysis techniques used by analysts. The popular and common analysis theories are Fundamental Analysis and Technical Analysis. This paper is based on technical analysis of different category of stock with respect to wide spread industry like FMCG sector, Banking sector, Oil and Natural Gas sector, Automobiles sector and Pharmaceutical Sector etc. The paper also tries to establish whether the market is having a Bull Run or bear. The movement of stock prices is analysed in technical analysis. The data of stock prices are collected from NSE official site. The analysis in done for 5 years span starting from April 2012 to Mar 2017. Even to understand better, analysis of the stock is done on 100days moving average. Prevailing news during those times are also considered to interpret the behaviour of the investors.

scholarly journals ANALISIS TEKNIKAL PERGERAKAN HARGA SAHAM DENGAN MENGGUNAKAN INDIKATOR STOCHASTIC OSCILLATOR DAN WEIGHTED MOVING AVERAGE

KEUNIS ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 36
Author(s):  
Nur Alviyanil 'Izzah ◽  
Dina Yeni Martia ◽  
Maria Imaculata ◽  
Moh Iqbal Hidayatullah ◽  
Andhika Bagus Pradana ◽  
...  
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Moving Average ◽  
Technical Analysis ◽  
First Semester ◽  
Share Prices ◽  
Stochastic Oscillator ◽  
Industrial Sectors ◽  
The Right ◽  
Weighted Moving Average

<p><em>Investments in the stock market are closely related to the price movement risk. Investors used technical analysis to minimize the risk caused by changes in stock prices. Hence, investors get the right decision to buy or sell the stocks. Weighted Moving Average and Stochastic Oscillator are technical analysis indicators that investors often use due to their ease and accuracy predictions. This study combines the Stochastic Oscillator and Weight Moving Average (WMA) indicators to predict stock price movements in various industrial sectors during the 2015 to 2019 period and the first semester of the 2020 covid-19 pandemic outbreak in Indonesia. This combination aims to provide better predictive results by completing the weaknesses of each indicator. To provide recommendations for the right investment decisions for investors interested in investing their funds, especially in various industrial sectors. Using the combination of WMA and SI indicator charts from the investing.com website resulting in a better prediction of the right time to buy or sell stocks in various industry sectors. While the shares of SCCO, INDR, INDS appear stable during 2020, the movement of KLBM and KLBI's share prices seems to be affected by the Covid-19 pandemic in Indonesia.</em></p>

scholarly journals Random Regression Forest Model using Technical Analysis Variables

2016 ◽  
Vol 5 (3) ◽  
pp. 85-102 ◽  
Author(s):  
Senol Emir ◽  
Hasan Dincer ◽  
Umit Hacioglu ◽  
Serhat Yuksel
Keyword(s):  
Random Forest ◽  
Banking Sector ◽  
Mean Absolute Error ◽  
Moving Average ◽  
Technical Analysis ◽  
Absolute Error ◽  
Important Variable ◽  
Random Regression ◽  
Random Forest Method ◽  
Technical Indicator

The purpose of this study is to explore the importance and ranking of technical analysis variables in Turkish banking sector. Random Forest method is used for determining importance scores of inputs for eight banks in Borsa Istanbul. Then two predictive models utilizing Random Forest (RF) and Artificial Neural Networks (ANN) are built for predicting BIST-100 index and bank closing prices. Results of the models are compared by three metrics namely Mean Absolute Error (MAE), Mean Square Error (MSE), Median Absolute Error (MedAE). Findings show that moving average (MAV-100) is the most important variable for both BIST -100 index and bank closing prices. Therefore, investors should follow this technical indicator with respect to Turkish banks. In addition ANN shows better performance for all metrics.

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.

MOMENTUM OSCILLATORS - A TOOL TO PREDICT STOCK PRICE BEHAVIOUR

2016 ◽  
Vol 12 (1) ◽  
Author(s):  
Shishir Kumar Gujrati
Keyword(s):  
Stock Price ◽  
Moving Average ◽  
Technical Analysis ◽  
Relative Strength ◽  
Future Price ◽  
Range Data ◽  
Strength Index ◽  
Price Trends ◽  
Past Data ◽  
Price Movements

Stock markets are always taken as the barometer of the economy. The price movement of their indices reflects every ups and downs of the economy. Although seem to be random, these price movements do follow a certain track which can be identified using appropriate tool over long range data. One such method is of Technical Analysis wherein future price trends are forecasted using past data. Momentum Oscillators are the important tools of technical analysis. The current paper aims to identify the previous price movements of sensex by using Relative Strength Index (RSI) and Moving Average Convergence Divergence (MACD) tools and also aims to check whether these tools are appropriate in forecasting the price trends or not.

scholarly journals Impact of Financial Ratios on Stock Price: Evidence from Indian Listed Banks on NSE

2021 ◽  
Vol 11 (4) ◽  
pp. 5132-5144
Author(s):  
Nitish Rane ◽  
Pooja Gupta
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Banking Sector ◽  
Study Data ◽  
Capital Adequacy ◽  
Financial Ratios ◽  
Annual Reports ◽  
Earnings Per Share ◽  
Net Interest Margin ◽  
The Impact

This study aims to examine the impact of financial ratios on the stock prices of companies listed on NIFTY Bank. Nifty Bank is a sub-index of NIFTY 50 and has various listed banks included based on the criteria given by NSE. This study data has been taken from the period 2010-2019 and taken from the company annual reports. The analysis is done using panel data regression and other tests to verify the best model for the dataset. The results obtained from this study show that the capital adequacy ratio and the dividend payout ratio do not impact the stock price. In contrast, earnings per share, net NPA ratio, and basic earnings per share, net profit margin, and net interest margin exhibited a relationship with the stock price. In the Indian context, there is less research available on this topic, and the idea chosen for the study is original. Along with this, the data collected for the study and the code used for analysis is original work. New investors can use the results of this study in the Indian stock market to analyze a stock and take proper investment decisions. Another practical usage of this study is that banking sector companies can improve their ratios to attract new investors.

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