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>

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 Downtrend of banking sectors using technical analysis

2021 ◽  
Vol 8 (1) ◽  
pp. 36-40
Author(s):  
Rahini M ◽  
Vivek Prabu M
Keyword(s):  
Significant Role ◽  
Stock Price ◽  
Banking Industry ◽  
Technical Analysis ◽  
Future Price ◽  
The Past ◽  
The Future ◽  
Price Movements ◽  
Past Price

The Banking industry plays a very significant role in the economy and the development of a country. It is important to our nation’s economy as it caters to the need of credit for all the section of the nation. In this paper, we are focusing on the stocks of Yes Bank Limited, Axis Bank Limited and ICICI Bank Limited and analyze them technically. Using technical analysis, we could predict the future price movements of stocks by examining the present and the past price movements of stocks.  It has many tools and indicators like SMA, EMA, RSI, MACD and P&L which are used for forecasting the future stock price and also identify the pattern, trend and it directs when to buy and sell stocks.

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 A Study on Stock Price Prediction using LSTM Model

2021 ◽  
Vol 9 (VI) ◽  
pp. 2618-2622
Author(s):  
Koushal Saini
Keyword(s):  
Stock Market ◽  
Stock Price ◽  
Time Series Data ◽  
Moving Average ◽  
Technical Analysis ◽  
Relative Strength ◽  
Trend Detection ◽  
Series Data ◽  
Future Price ◽  
Stock Price Prediction

Predicting stock price of any stock is a challenging task because the Volatility of stock market the nature of stock price is dynamic, chaotic, noisy and sometimes totally unexpected. The other most difficult task is to analyze and decide financial time series data that improves investment returns and help in minimizing losses. Technical analysis is a method that help in analyzing a stock and predict its future price via evaluating securities. There are already many Indicators and other tools for technical analysis in stock market. Some famous indicators such as SMA (Simple Moving Average), EMA (Exponential Moving Average), WMA (Weight Moving Average), VWMA (Volume Weight Moving Average), DEMA (moving averages), MACD (Moving Average Convergence/Divergence), ADX (Average Di- reactional Movement Index), TDI (Trend Detection Index), Arun, VHF (trend indicators), stochastic, RSI (Relative Strength Index), SMI(Stochastic Momentum Index, volume indicators are also available for technical analysis. Here, we have used the LSTM Model to predict future price of some big companies of stock market in NSE.

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 An analysis of equity share price movement of selected companies listed in nse

2012 ◽  
Vol 1 (3) ◽  
pp. 246-252
Author(s):  
CHITRA R ◽  
SATHYA M
Keyword(s):  
Average Rate ◽  
Moving Average ◽  
Secondary Data ◽  
Relative Strength ◽  
Rate Of Change ◽  
Share Price ◽  
Price Movement ◽  
Share Prices ◽  
The Past ◽  
Data Collections

The stock market has an important role in the allocation of resources, both directly as a source of funds and as a determinant of firm’s value and borrowing capacity. This study we made a study and analysis on Equity share price behaviour of selected companies listed in NSE India. The Purpose of the study is, attempted to test the equity price movements of IT,Pharmaceuticals, Banking and Automobiles sectors. These are taken as sample sectors. The objective of the study is to analyze the Equity share price movement of selected companies listed in NSE, India and to analyze the movements of the high pricedequity shares of four sectors for the past 3 years. Data collections are to be used in the study is secondary data. The study usestools such as Simple Moving Average, Rate of Change, Relative Strength Index, Stochastic oscillator and Trend analysis. TheMonthly share prices of above mentioned companies were taken for a period of three years from January 2009 to Dec 2011. Theclosing prices of share prices were taken. All four sectors registered tremendous growth in the past 3 years, and as per theanalysis all these sectors companies were predicted as best to invest for better rate of return for the investors.

PREDIKSI HARGA SAHAM PT. BRI, Tbk. MENGGUNAKAN METODE ARIMA (Autoregressive Integrated Moving Average)

2014 ◽  
Vol 14 (2) ◽  
pp. 60
Author(s):  
Greis S Lilipaly ◽  
Djoni Hatidja ◽  
John S Kekenusa
Keyword(s):  
Stock Price ◽  
Moving Average ◽  
Secondary Data ◽  
Research Use ◽  
Autoregressive Integrated Moving Average ◽  
Minimum Data ◽  
Research Show

PREDIKSI HARGA SAHAM PT. BRI, Tbk. MENGGUNAKAN METODE ARIMA (Autoregressive Integrated Moving Average) Greis S. Lilipaly1) , Djoni Hatidja1) , John S. Kekenusa1) ABSTRAK Metode ARIMA adalah salah satu metode yang dapat digunakan dalam memprediksi perubahan harga saham. Tujuan dari penelitian ini adalah untuk membuat model ARIMA dan memprediksi harga saham PT. BRI, Tbk. bulan November 2014. Penelitian menggunakan data harga saham  harian  maksimum dan minimum PT. BRI, Tbk. Data yang digunakan yaitu data sekunder yang diambil dari website perusahaan PT. BRI, Tbk. sejak 3 Januari 2011 sampai 20 Oktober 2014 untuk memprediksi harga saham bulan November 2014. Dari hasil penelitian menunjukkan bahwa data tahun 2011 sampai Oktober 2014 bisa digunakan untuk memprediksi harga saham bulan November 2014. Hasilnya model ARIMA untuk harga saham maksimum adalah ARIMA (2,1,3) dan harga saham minimum adalah model (2,1,3) yang dapat digunakan untuk memprediksi data bulan November 2014 dengan validasi prediksi yang diambil pada bulan Oktober 2014 untuk selanjutnya dilakukan prediksi bulan November 2014. Kata Kunci: Metode ARIMA, PT. BRI, Tbk., Saham THE PREDICTION STOCK PRICE OF PT. BRI, Tbk. USE ARIMA METHOD (Autoregressive Integrated Moving Average) ABSTRACT ARIMA method is one of the method that used to prediction the change of stock price. The purpose of this research is to make model of ARIMA and predict stock price of PT. BRI, Tbk. in November 2014. The research use maximum and minimum data of stock price daily of PT. BRI, Tbk. Data are used is secondary data that taking from website of PT. BRI, Tbk. since January 3rd 2011 until October 20th 2014 to predict stock price in November 2014. From this research show that data from 2011 until October 2014 can be used to predict the stock price in November 2014. The result of ARIMA’s model for the maximum stock price is ARIMA (2,1,3) and the minimum stock price is (2,1,3) can use to predict the data on November 2014 with predict validation that take on October 2014 and with that predict November 2014. Keywords: ARIMA method, PT. BRI, Tbk., Stock

scholarly journals Improving MACD Technical Analysis by Optimizing Parameters and Modifying Trading Rules: Evidence from the Japanese Nikkei 225 Futures Market

2021 ◽  
Vol 14 (1) ◽  
pp. 37
Author(s):  
Byung-Kook Kang
Keyword(s):  
Moving Average ◽  
Public Information ◽  
Technical Analysis ◽  
Weak Form ◽  
Futures Market ◽  
Traditional Model ◽  
Analysis Tool ◽  
Futures Prices ◽  
Improved Performance ◽  
Parameter Values

Much research has examined performance or market efficiency by using the moving average convergence divergence (MACD) technical analysis tool. However, most tests fail to verify efficiency with the traditional parameter settings of 12, 26, and 9 days. This study confirms that applying the traditional model to Japan’s Nikkei 225 futures prices produces negative performance over the period of 2011–2019. Yet, it also finds that the MACD tool can earn significant positive returns when it uses optimized parameter values. This suggests that the Japanese market is not weak-form efficient in the sense that futures prices do not reflect all public information. Hence, the three parameters values of the MACD tool should be optimized for each market and this should take precedence over finding other strategies to reduce false trade signals. This study also tests which models are able to improve profitability by applying additional criteria to avoid false trade signals. From simulations using 19,456 different MACD models, we find that the number of models with improved performance resulting from these strategies is far greater for models with optimized parameter values than for models with non-optimized values. This approach has not been discussed in the existing literature.

scholarly journals Predicting Stock Price Trend Using MACD Optimized by Historical Volatility

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Jian Wang ◽  
Junseok Kim
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Moving Average ◽  
Rapid Development ◽  
Price Trend ◽  
Technical Indicators ◽  
Volatility Index ◽  
Fixed Weight ◽  
The Stability

With the rapid development of the financial market, many professional traders use technical indicators to analyze the stock market. As one of these technical indicators, moving average convergence divergence (MACD) is widely applied by many investors. MACD is a momentum indicator derived from the exponential moving average (EMA) or exponentially weighted moving average (EWMA), which reacts more significantly to recent price changes than the simple moving average (SMA). Traders find the analysis of 12- and 26-day EMA very useful and insightful for determining buy-and-sell points. The purpose of this study is to develop an effective method for predicting the stock price trend. Typically, the traditional EMA is calculated using a fixed weight; however, in this study, we use a changing weight based on the historical volatility. We denote the historical volatility index as HVIX and the new MACD as MACD-HVIX. We test the stability of MACD-HVIX and compare it with that of MACD. Furthermore, the validity of the MACD-HVIX index is tested by using the trend recognition accuracy. We compare the accuracy between a MACD histogram and a MACD-HVIX histogram and find that the accuracy of using MACD-HVIX histogram is 55.55% higher than that of the MACD histogram when we use the buy-and-sell strategy. When we use the buy-and-hold strategy for 5 and 10 days, the prediction accuracy of MACD-HVIX is 33.33% and 12% higher than that of the traditional MACD strategy, respectively. We found that the new indicator is more stable. Therefore, the improved stock price forecasting model can predict the trend of stock prices and help investors augment their return in the stock market.

scholarly journals Impacts of bonus issue on stock price in Nepalese Equity Market

2017 ◽  
Vol 2 ◽  
pp. 106-117
Author(s):  
Raju Kumar Rai ◽  
Prem Silwal
Keyword(s):  
Commercial Banks ◽  
Stock Price ◽  
Equity Markets ◽  
Equity Market ◽  
Matched Pairs ◽  
Cross Sectional ◽  
Price Movement ◽  
Share Prices ◽  
Price Reactions ◽  
Made In

The aim of this study is to examine the effect of bonus issue on the price of equity share. The study is based on pooled cross-sectional data of 10 commercial banks whose stocks are listed in NEPSE and traded over the market. An attempt has been made in this study, to analyze the behaviour of the share prices in the Nepalese equity market towards the announcements of bonus issue, taking into account the price movements of the stocks listed in NEPSE. In order to assess the stock price reactions to bonus issue in the Nepalese equity market, Wilcoxon Matched Pairs Test has been applied in this study. The research has revealed that there is a significant impact on the price movement of shares in accordance with the bonus issue in the Nepalese equity market which is consistent to other foremost global equity markets.

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