scholarly journals Technical analysis on select stocks of banking sector

2016 ◽  
Vol 6 (3) ◽  
pp. 231-242
Author(s):  
Sharmila R ◽  
Kavitha R ◽  
Ananthi S
Keyword(s):  
Banking Sector ◽  
Weather Forecasting ◽  
Stock Exchange ◽  
Moving Average ◽  
Technical Analysis ◽  
Relative Strength ◽  
Rate Of Change ◽  
Strength Index ◽  
Price Movements ◽  
Over Time

Technical Analysis is the forecasting of future financial price movements based on an examination of past price movements. Like weather forecasting, technical analysis does not result in absolute predictions about the future. Instead, technical analysis can help investors anticipate what is “likely” to happen to prices over time. Technical analysis uses a wide variety of charts that show price over time. This study is based on the analysis of four Nifty Bank Index stocks namely Axis Bank, Bank of Baroda, State Bank of India and ICICI bank listed in National Stock Exchange. Technical indicators such as Relative strength index (RSI), Rate of change (ROC) and Moving Average (MA) are used in the study. This paper aims at carrying out Technical Analysis of the securities of the selectedbanking stocks and to assist investment decisions in this Indian Market.

scholarly journals Analysis of Nifty Movement on Share Prices of Selected Construction Companies

2012 ◽  
Vol 1 (3) ◽  
pp. 59-65
Author(s):  
M. Gomathi ◽  
Dr.S. Nirmala
Keyword(s):  
Stock Prices ◽  
Moving Average ◽  
Technical Analysis ◽  
Relative Strength ◽  
Rate Of Change ◽  
Construction Sector ◽  
Strength Index ◽  
Share Prices ◽  
Construction Companies ◽  
Price Movements

This study aims at analyzing and predicting the price movements of construction companies stocks contributing to the NIFTY50 Index. To analyze the volatility of telecom stock and understand the behavior of stock prices in construction sector stocks i.e. (JP ASSOCIATES LIMITED, DLF LIMITED, GAMMON INDIA LIMITED, PUNJ LLOYD LIMITED, HCC LIMITED). The data for these stocks are collected from magazines, newspaper and websites. The stocks are analyzed by monitoring their respective price movements using technical tools. The technical tools used in this study are Exponential moving average, Relative strength index, Rate of change, MACD. Using these tools the trend over the recent past was deciphered. The expected trend in the immediate future was also predicted. Technical Analysis studies the price and volume movement in the market and predicts the future. It helps in identifying that the best time to buy and sell equity. Technical Analysis is a method of evaluating equities by analyzing the statistics generated by market activity, such as past prices and volume.

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 Effectiveness of Technical Analysis Signals Around the Earning Announcements in Malaysian Stock Market

2018 ◽  
Vol 7 (3.21) ◽  
pp. 109
Author(s):  
Kelvin Lee Yong Ming ◽  
Mohamad Jais
Keyword(s):  
Stock Market ◽  
Stock Exchange ◽  
Moving Average ◽  
Technical Analysis ◽  
Relative Strength ◽  
Kuala Lumpur ◽  
Earning Announcement ◽  
Strength Index ◽  
Corporate Announcements ◽  
Technical Indicator

Technical analysis is an analysis that widely applied by the investor in the stock market. However, various corporate announcements could cause the market to react, and the most significant corporate announcement is the earnings announcement (1). Thus, this study examines the effectiveness of technical analysis signals around the earning announcements dates in Malaysian stock market. In doing so, this study applied and tested four technical indicators, namely Simple Moving Average (SMA), Relative Strength Index (RSI), Stochastic (K line), and Moving Average Convergence/Divergence (MACD) in Malaysian stock market. The sample of this study consisted of 30 largest capitalization companies from the main market of Kuala Lumpur Stock Exchange (KLSE). Meanwhile, the sample period covered from 2nd January 2014 to 31st March 2016. This study found that Moving Average Convergence/Divergence (MACD) significantly produced higher returns as compared to the other technical indicator before the earning announcement dates in financial year 2014 and 2015. The combined indicator of MA-MACD also found to have higher return in financial year 2015. The findings conclude that the technical analysis signals can be used to generate returns before earning announcement dates.  

Candle charts for financial technical analysis

2019 ◽  
Vol 19 (1) ◽  
pp. 200-209 ◽  
Author(s):  
Mehmet F. Dicle
Keyword(s):  
Moving Average ◽  
Visual Representations ◽  
Technical Analysis ◽  
Relative Strength ◽  
Financial Industry ◽  
Strength Index ◽  
Research And Teaching ◽  
Industry Research ◽  
The Individual

Technical analysis is an important part of financial industry, research, and teaching. The methodology has two parts: i) calculation of the individual tools and ii) visual representations. In this article, I provide a community-contributed command, candlechart, to draw the most common technical analysis charts. My intent is to draw these charts similarly to industry examples. The popular candle price chart is combined with charts for volume, moving-average convergence divergence, relative strength index, and Bollinger bands.

scholarly journals Optimization of investment management in Warsaw stock market

2014 ◽  
Vol 15 (2) ◽  
pp. 143-156 ◽  
Author(s):  
Maciej Janowicz ◽  
Arkadiusz Orłowski ◽  
Franciszek Michał Warzyński
Keyword(s):  
Stock Market ◽  
Time Perspective ◽  
Moving Average ◽  
Technical Analysis ◽  
Relative Strength ◽  
Optimal Management ◽  
Brute Force ◽  
Exchange Market ◽  
Strength Index ◽  
Optimal Values

Abstract Application of simple prescriptions of technical analysis on the Warsaw Exchange Market (GPW) has been analyzed using several stocks belonging to WIG20 group as examples. Only long positions have been considered. Three well-known technical-analysis indicators of the market have been investigated: the Donchian channels, the Relative Strength Index, and Moving Average Convergence-Divergence indicator. Optimal values of parameters of those indicators have been found by „brute force“ evaluation of (linear) returns. It has been found that trading based on both Donchian channels and Relative Strength Index easily outperform the „buy and hold“ strategy if supplied with optimal values of parameters. However, those optimal values are by now means universal in the sense that they depend on particular stocks, and are functions of time. The optimal management of capital in the stock market strongly depends on the time perspective of trading. Finally, it has been argued that the criticism of technical analysis which is often delivered by academic quantitative financial science is unjustified as based of false premises.

scholarly journals Technical Financial Analysis Tools for Stata

2017 ◽  
Vol 17 (3) ◽  
pp. 736-747 ◽  
Author(s):  
Mehmet F. Dicle ◽  
John D. Levendis
Keyword(s):  
Financial Analysis ◽  
Moving Average ◽  
Technical Analysis ◽  
Relative Strength ◽  
Analysis Tool ◽  
Investment Strategies ◽  
Moving Averages ◽  
Strength Index ◽  
Analysis Tools

In this article, we provide four financial technical analysis tools: moving averages, Bollinger bands, moving-average convergence divergence, and the relative strength index. The tftools command is used with four subcommands, each referring to a technical analysis tool: bollingerbands, macd, movingaverage, and rsi. We provide examples for each tool. tftools allows researchers to backtest their own investment strategies and will be of interest to investors, researchers, and students of finance.

scholarly journals The Profitability of the Strategy Linking Fundamental, Portfolio and Technical Analysis on the Polish Capital Market

2016 ◽  
Vol 16 (1) ◽  
pp. 113-146 ◽  
Author(s):  
Marcin Flotyński
Keyword(s):  
Regression Model ◽  
Capital Market ◽  
Quantitative Methods ◽  
Financial Analysis ◽  
Stock Exchange ◽  
Moving Average ◽  
Technical Analysis ◽  
Relative Strength ◽  
Concurrent Use ◽  
Warsaw Stock Exchange

Abstract In the article, several methods of taking investment decisions are described: a fundamental, portfolio, and technical analysis. They constitute different approaches which are convenient for different types of investors with various expectations and time horizons of their investments. The simultaneous combination of these three analyses is not popular. The aim of this study is to test the effectiveness of simultaneous use of a fundamental analysis, portfolio analysis, and technical analysis for shares quoted on the Warsaw Stock Exchange (WSE) in 2000–2007. The research hypothesis is advanced that the concurrent-linked application of a fundamental, portfolio, and technical analysis brings better results than the separate use of these analyses. Models of capital market, such as CAPM and APT, have been used, as well as P/E ratio, Return on Equity (RoE), Relative Strength Index (RSI), and Exponential Moving Average (EMA). The combination of a financial analysis, technical indicators, and models of the capital market in order to invest on the stock exchange is author’s own method. In general, the survey has been carried out on the grounds of quantitative methods (financial analysis, regression model, and multi regression model) and a comparative analysis. The results of the research have been used to create diversified portfolios on the WSE. It occurs that the concurrent use of the three analyses brings the highest rate of return of a portfolio.

scholarly journals FUNDAMENTAL & TECHNICAL ANAYSIS OF CRUDE OIL PRICES

2021 ◽  
Vol 17 (1) ◽  
pp. 3-20
Author(s):  
Sumeet Gupta
Keyword(s):  
Crude Oil ◽  
Weather Forecasting ◽  
Price Volatility ◽  
Technical Analysis ◽  
Oil Price ◽  
Future Price ◽  
Human Beings ◽  
The Future ◽  
Price Movements ◽  
Over Time

The human mind is not as good at processing large amounts of information as we might like. Psychologists have shown that human beings are only able to juggle small numbers of related and often conflicting pieces of information without making judgment errors. As a result, individuals faced with the vast amounts of information available to support investment decisions often find themselves swamped by the enormity of the task; unable to see the wood from the trees. Technical analysis is a field of financial markets research that works to address the above problem by focusing on a single, commonly available, data source that reflects all known information and activity relating to all monetary securities- Price history. Technical analysts argue that as markets are efficient, prices reflect all known information and that they move over time as participants react to new information and changing needs. As a result, the technical analysis of these price changes can provide real insight into the market dynamics and be used to develop trade strategies that exhibit superior risk/reward characteristics. While technical analysis approaches have developed significantly over the past few decades, some techniques are far more ancient. While their real origins are anonymous, Japanese candlestick charts have been recorded as being employed in the rice markets as far back as the 1600s. What is particularly interesting is that various of these ancient approaches continue to provide highly effective trading signals when applied to modern markets and securities. Crude oil price volatility is in the midst of the largest business risk that oil and gas companies face. This is followed by unstable policy regime, managing costs and risks emerging from technological advancements. The high levels and rapid fluctuations of petroleum prices have become a great concern to individual consumers, firms, policy makers and society. Technical Analysis is the forecasting of future financial price movements based on an examination of past price movements. Like weather forecasting, technical analysis does not result in absolute predictions about the future. Instead, technical analysis can help investors anticipate what is "likely" to happen to prices over time. Technical analysis uses a wide variety of charts that show price over time. Hence, to mitigate the negative impacts of price volatility and to predict about the future price movement of crude oil and natural gas we can use technical analysis. Technical analysis is the study of market action, primarily through the use of charts, for the purpose of forecasting price trends. The term “market action” includes the three principal source of action available to the technician-price, volume and open interest. This research paper highlights  fundamental factor which affects the Brent price and analysed the factor which are highly correlated with Brent price and on the basis of the results forecasted the Brent price for next five years. Fundamental analysis of Brent oil, price pattern & movement of crude oil has also been carried out using candlestick technical tool.

scholarly journals Indian Stock Markets Data Analysis and Prediction using Macroeconomics Indictors in Machine Learning

2020 ◽  
Vol 9 (10) ◽  
pp. 484-486
Keyword(s):  
Machine Learning ◽  
Stock Market ◽  
Moving Average ◽  
Relative Strength ◽  
Rate Of Change ◽  
Random Forest Algorithm ◽  
Strength Index ◽  
Training Set ◽  
Trend Prediction ◽  
Unique Role

Machine Learning plays a unique role in the world of stock market when it comes to the trend prediction. Machine learning library MLIB helps in determining the future values of stocks. With the help of this research one can find the ups and downs of stock market by providing a signal for the same and done by analyzing the previous stock data. This study is based on analysis of stock data from 2000 to 2009 which includes top fifty companies of various sectors from all over India. Six stock data indicators known as, Bollinger Band, Relative Strength Index(RSI), Stochastic Oscillator, Williams % R, Moving Average Convergence Divergence (MACD), Rate of Change applied on the nineteen years of stock data then results of these indicators are compiled and finally with the use of machine learning libraries like Numpy, Pandas, Matplotlib, Sklearn a random forest algorithm is applied on the compiled result to predict the stock movement , these libraries which splits the results into two sets training set and testing set which also boost up the result and gives you the better prediction.

Trading rules and excess returns: evidence from Turkey

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Massoud Metghalchi ◽  
Nazif Durmaz ◽  
Peggy Cloninger ◽  
Kamvar Farahbod
Keyword(s):  
Moving Average ◽  
Relative Strength ◽  
Rate Of Change ◽  
Multiple Time ◽  
Excess Returns ◽  
Strength Index ◽  
Technical Trading Rules ◽  
Trading Rules ◽  
Content Type ◽  
Practical Implications

Purpose This paper aims to investigate popular technical trading rules (TTRs) applied to the FTSE Turkish all-cap and small-cap indexes from September 23, 2003 to August 9, 2019 to determine rules that produce net excess returns over the Buy-and-Hold strategy (B&H). Design/methodology/approach Five TTRs, namely, simple moving average, relative strength index, moving average convergence divergence, momentum, and rate of change, are applied, singly (one indicator) and in combination (two indicators) for multiple time periods. Findings For the small-cap index, some TTRs – including the famous Golden Cross, when the 50-day moving average rises above 200-day moving average – produced net annual excess returns (NAERs) over the B&H strategy, for the entire period and each sub-period, after accounting for risk and transaction costs. Results were mixed for the large-cap index. The results support Cakici and Topyan (2013). Research limitations/implications This study investigates several indicators, but future studies should examine others, especially based on volume and price. Practical implications Investors in the FTSE Turkish small-cap index may use some trading rules to earn NAERs over the B&H strategy. Originality/value This research is important because it addresses a gap in the research by examining numerous TTRs in the Turkish stock market. Studies of TTRs in Turkey are scarce.

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