scholarly journals Use of Technical Analysis Tools in Nepalese Stock Market

2018 ◽  
Vol 11 (1) ◽  
pp. 55-64
Author(s):  
Rashesh Vaidya
Keyword(s):  
Stock Market ◽  
Investment Decisions ◽  
Technical Analysis ◽  
Trade Volume ◽  
Market Participants ◽  
Support Level ◽  
Analysis Tools

This paper has attempted to find the interest of Nepalese investors, brokers and depository participants on the use the technical tools for the analysis of the stock market. The use of technical analysis in context to Nepal shows that the participants in the Nepalese stock market are highly interested on the use of new Hi-Lo price while making their investment decisions. Another interest was seen for trade volume indicators. The Nepalese stock market participants are not seen interested in using the resistance and support level followed by the pattern i.e. candlestick charts while analyzing the stock market trend.

Is Technical Analysis Profitable even for an Amateur Investor?

2015 ◽  
pp. 255-269
Author(s):  
Vasileiou Evangelos
Keyword(s):  
Stock Market ◽  
Transaction Costs ◽  
Behavioral Finance ◽  
Investment Decisions ◽  
Technical Analysis ◽  
Moving Averages ◽  
Trading Rules ◽  
Trading Decisions ◽  
Transaction Fees

The purpose of this chapter is to examine if even the simplest trading rules could take advantage of the market's inefficiency and lead to profitable trading decisions. For this reason, this study examined the profitability of the simplest trading rules, using only the simple moving averages (SMA) rules that even an amateur investor could apply. In order to examine the specific issue a data sample from the Greek stock market during the period 2002-12 was used. The results suggest that even if one takes into account the most expensive transaction fees, the trading rules signal profitable investment decisions; therefore, even an amateur trader and/or investor who does not have a significant amount of money to invest (which may lead to reduced transaction costs) could take advantage of the market's inefficiency. Behavioral finance theories may provide some useful and alternative explanations regarding some of the reasons that contribute to the Greek stock market's inefficient environment.

scholarly journals Don’t fight the tape! Technical Analysis Momentum and Contrarian Signals as Common Cognitive Biases

2020 ◽  
Vol 28 (2) ◽  
pp. 98-110
Author(s):  
Piotr Zielonka ◽  
◽  
Wojciech Białaszek ◽  
Paweł Biedrzycki ◽  
Bartłomiej Dzik ◽  
...  
Keyword(s):  
Stock Market ◽  
Natural Environment ◽  
Stock Price ◽  
Predictive Power ◽  
Cognitive Biases ◽  
Technical Analysis ◽  
Market Participants ◽  
Trend Reversal

Purpose: Stock market participants use technical analysis to seek trends in stock price charts despite its doubtful efficiency. We tested whether technical analysis signals represent typical and common cognitive biases associated with the continuation or reversal of the trend. Methodology: We compared investors’ opinions about the predictive power of technical analysis signals grouped into five conditions: real technical analysis signals associated with trend continuation (real momentum signals) or trend reversal (real contrarian signals), fake momentum or fake contrarian signals, and fluctuation signals. Findings: Investors assigned larger predictive power to real and fake signals associated with trend continuation than to signals associated with trend reversal. Fake signals, which represented cognitive biases, elicited similar predictions about trend continuation or reversal to real technical analysis signals. Originality: Market players assess momentum signals to have greater predictive power than contrarian signals and neutral signals to have the least predictive power. These results are independent of whether technical analysis signals were well-known to investors or made up by experimenters. The hardwired propensity of our brains to detect patterns combined with the non-natural environment of the stock market creates the illusion of expertise that is not easy to dispel.

scholarly journals Using E-GARCH to Analyze the Impact of Investor Sentiment on Stock Returns Near Stock Market Crashes

2021 ◽  
Vol 12 ◽  
Author(s):  
Sze Ting Chen ◽  
Kai Yin Allison Haga
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Policy Making ◽  
Composite Index ◽  
Investor Sentiment ◽  
Investment Decisions ◽  
Rate Of Return ◽  
Market Participants ◽  
Rational Investment ◽  
The Impact

Purpose: Investor sentiment, the willingness of market participants to invest, is a difficult concept to measure. Exploring the relationship between investor sentiment and stock returns can reveal how investor sentiment affects the operation of the stock market. Such an understanding can assist market participants in making more rational investment decisions based on market laws. Such an understanding can also assist regulators in their roles of supervision and policy making.Methodology: Although the E-GARCH model has the advantage of considering volatility clustering, it has not previously been used to investigate the impact of investor sentiment changes on the Shanghai Composite Index's market return. This research therefore applies the E-GARCH approach to data from 2015 to 2018, to explore the influence of investor sentiment on the return rate of the Shanghai Composite Index.Main Findings: There are three main findings. First, when the investor sentiment is increased by the same amount, the rate of return before a stock market crash will have a smaller increase than the rate of change after the crash, which is a new finding. Second, the rate of return on stocks is susceptible to emotional sentiment, rather than simply depending on stock price. Third, the tendency of retail investors to follow the crowd is less in periods of pessimism than it is in periods of optimism, which, in turn, can push up stock yields.Application: Based on these research results, this article can provide insights to understand how investors' subjective judgments on future earnings affect their investment behavior and how great the impact is on the market. At the same time, it can help investors make more rational investment decisions based on an understanding of market laws, and help regulators with guidance for their supervision and policy making.Originality/Value: This paper contributes to the theory of the investor sentiment index, improving the index construction method by adding two sentiment proxy indicators: investor activity ACT and stock market leverage level. After constructing the sentiment index and comparing it with the stock market index (Shanghai Composite Index), the fit is found to be improved.

scholarly journals Securities Analysis and Portfolio Management of Selected NSE Securities

2021 ◽  
pp. 540-543
Author(s):  
Prof. (Dr) Pramod Sharma
Keyword(s):  
Stock Market ◽  
Portfolio Management ◽  
Intrinsic Value ◽  
Technical Analysis ◽  
Future Price ◽  
Market Participants ◽  
Major Market ◽  
Price Trends ◽  
Indian Stock Market ◽  
A Company

“Technical Analysis is the study of data generated by the action of markets and by the behaviour and psychology of market participants and observers”: -Constitution of the market technicians Association Technical analysis is a completely different approach to stock market investing- it doesn’t try to find the intrinsic value of a company or try to find whether a share is mispriced or undervalued. "Technical analysis is the study of market action, primarily through the use of charts, for the purpose of forecasting future price trends. “A technical analyst is interested only in the price movements in the market. So, it is all about analysing the demand and supply or a price volume analysis. Technical analysis considers only the actual price behaviour of the market or instrument, based on the premise that price reflects all relevant factors before an investor becomes aware of them through other channels. These stock market indicators would help the investor to identify major market turning points. This paper examines the technical analysis of selected companies which helps to understand the price behaviour of the shares, the signals given by them and to assist investment decisions in the Indian stock Market.

scholarly journals Use of the Black and Scholes model in the pricing of purchasing options based on the index of the Iraq Stock Exchange for the period from 6/2 to 25/2/2019

2019 ◽  
Vol 5 (2) ◽  
pp. 68
Author(s):  
Ammar Shihab Ahmed
Keyword(s):  
Stock Market ◽  
Financial Markets ◽  
Stock Exchange ◽  
Investment Decisions ◽  
Technical Analysis ◽  
Relative Strength ◽  
Financial Indicators ◽  
Strength Index ◽  
The Future ◽  
The Impact

Due to the increasing number of interested investors in the rights of options, it is necessary to highlight this section of the financial markets, and that one of the main reasons for increasing the attractiveness of investors in this type of market is the reduction of capital required to invest in it, and contribute to maximize their profitability if true (Investors 'profits are unlimited) and reduce their losses to a certain extent (investors know in advance the amount of their losses before the turnout of investment) if their expectations are unhealthy. Investors' losses are determined by the amount of the bonus they pay to the contract editor, After the pricing of the contracts of the rights of the purchase choice, they will be certain of the size of the losses they will incur if their expectations for the future are incorrect, and many techniques of technical analysis help investors to predict the future prices of securities or financial indicators. In the research is the relative strength index, and through this indicator, investors can determine whether the prices in the stock market sold at high or low prices, contributing to the impact on the value of the index of the stock market, so the prospect of the future helps investors In making their investment decisions to buy buying rights in the event of higher prices in the future. Conversely, the expectation of lower prices in the future investors are selling purchase rights rights contracts, and thus achieve profits in both cases.Keywords: Black & Schulz model, RSI, financial choice, pricing of purchase choice.

Through the Lens of Recession 2.0: Diversification Dynamics Between the Leading Asian Stock Markets

2021 ◽  
pp. 097226292098395
Author(s):  
Manu K. S. ◽  
Surekha Nayak ◽  
Rameesha Kalra
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Market Integration ◽  
Developing Economies ◽  
Positive Impact ◽  
Global Market ◽  
Stock Market Integration ◽  
Developed Economies ◽  
Market Participants ◽  
Causality Tests

The focus of this article is to analyse the inter-linkages between eight leading stock markets in Asian continent from the period of July 2011 to February 2018. This period holds relevance as this was the time when Recession 2.0 set in, which adversely affected the developed economies; however, the developing economies withstood the crisis without much of an impact. Co-integration and Granger causality tests were conducted to probe the inter-linkages. Study revealed a positive impact on Asian stock market indices collectively on each of the indexes. The highest number of unidirectional causalities was to KOPSI and NIFTY from rest of the stock indices. Results confirmed that no co-integration relationship existed among the selected indices indicating favourable diversification opportunities. Thus, the study fosters global market participants and policymakers to consider the nitty-gritties of stock market integration so as to benefit from international stock market diversification in the Asian region.

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