The Establishment of the Forecasting Model for Regime Switching in Time Series

2003 ◽  
Vol 11 (1) ◽  
pp. 57-99
Author(s):  
Geun Gwan Lyu ◽  
Gi Beom Bin ◽  
Yeong Jo Lee ◽  
Seong Jun Jo
Keyword(s):  
Regime Switching ◽  
Trading Volume ◽  
Efficient Market Hypothesis ◽  
Future Price ◽  
Forecasting Model ◽  
Investment Performance ◽  
The Past ◽  
Elapsed Time ◽  
Analysis Technique ◽  
Price Movements

Efficient market hypothesis implies that the past price movements do not help forecast future price movements. Thus, it is impossible to consistently benefit by a technical trading strategy. On the other hand, technical analysts claim that the historical price movements are useful in predicting future price movements. These two lines of arguments are mutually contradictory. This paper reasonably assumes that the more efficient markets are, the worse will be the investment performance of technical analysis, and that as financial market‘s trading volume grows and with the elapse of time, the efficiency of markets should improve. This implies that after the launch of a new financial asset, market efficiency would improve with increased trading and elapsed time. In this paper, the duration analysis technique is used as a forecasting model and applied to measure the efficiency of Korean futures market and the won/dollar exchange rate market.

scholarly journals Analysis of trading volume and its use in prediction future price movements in the process of maximizing trading earnings

2021 ◽  
Vol 92 ◽  
pp. 02010
Author(s):  
Jan Chutka ◽  
Filip Rebetak
Keyword(s):  
Trading Volume ◽  
Value Added ◽  
Theoretical Data ◽  
Future Price ◽  
Financial Instruments ◽  
Valuable Contribution ◽  
Innovative Method ◽  
Analysis And Synthesis ◽  
Price Movements ◽  
Trading Volumes

Research background: When we start looking for tools that could give a trader a certain trading advantage, we will certainly come across the problem of analysing the trading volume. This is an advanced type of analysis where the primary price chart of the underlying asset is not analysed, but traders focus on the volume of trades that have been executed at certain price levels. Although it may seem like an innovative method, this type of analysis has been used for several decades. In our article, we elaborated the theoretical basis of the analysis of trading volume as a tool for predicting the movement of prices of financial instruments. Purpose of the article: The aim of our article is to explore the possibilities, methods and procedures of analysis of trading volumes and the possibilities of their use in maximizing earnings from trading of financial instruments. Methods: We used formal methods such as analysis and synthesis of theoretical findings and others. Findings & Value added: Based on the study of the analysis and synthesis of theoretical data, we identified and described the possibilities of using the analysis of trading volume in the process of predicting the price movements of financial instruments. We consider the aim of the article to be fulfilled and we believe that it will be a valuable contribution in the field of research on this issue.

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 Stock market prediction using technical analysis

2006 ◽  
Vol 51 (170) ◽  
pp. 125-146 ◽  
Author(s):  
Aleksandra Bradic-Martinovic
Keyword(s):  
Stock Market ◽  
Trading Volume ◽  
Moving Average ◽  
Supply And Demand ◽  
Wave Theory ◽  
Technical Analysis ◽  
Ease Of Use ◽  
Future Price ◽  
Mathematical Methods ◽  
Price Movements

Technical analysis (TA) is a form of analyzing market encompassing supply and demand of securities according to the study of their prices and trading volume. Using the appropriate methods, TA aims to identify price movements in the stock market, futures or currencies. In short, TA analysis is the process by which "future price movements are formulated according to the price history". TA originates from the work of Charles Dow and his conclusions about the global behavior of the market, as well as from Elliot Wave Theory. Dow did not regard its theory as a tool for stock market movement prediction, nor as a guide for investors, but as a kind of barometer of general market movements. The term TA methods encompasses all the methods used in tracking prices aiming to clearly predict future events. Many different methods, mainly statistical, are used in technical analysis, the most popular ones being: establishing and following trends using moving average, recognizing price momentum, calculating indicators and oscillators, as well as cycle analysis (structure indicators). It is also necessary to point out that TA is not a science in the true meaning of the term, and that methods it uses frequently deviate from the conventional manner of their use. The main advantage of these methods is their relative ease of use, aiming to give as clear picture as possible of price movements, while at the same time avoiding the use of complicated and complex mathematical methods. The reason for this is simple and is reflected in the dynamics of financial markets, where changes occur during short periods of time and where prompt decision-making is of vital importance.

An Empirical Study on Efficient Market Hypothesis with reference to FMCG Sector

GIS Business ◽  
2020 ◽  
Vol 15 (1) ◽  
pp. 109-126
Author(s):  
Nitin Tanted ◽  
Prashant Mistry
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Abnormal Returns ◽  
Weak Form ◽  
Efficient Market Hypothesis ◽  
Controversial Issues ◽  
Efficient Market ◽  
Price Movements ◽  
Run Test ◽  
Stock Price Movements

One of the highly controversial issues in the area of finance is “Efficient Market Hypothesis”. Efficient Market Hypothesis states that, “In an efficient market, all available price information is reflected in the stock prices and it is not possible to generate abnormal returns compared to other investors.” A lot of studies conducted previouslyto test the Efficient Market Hypothesis, confirmed the theory until recent years, when some academicians found it to be non-applicable in financial markets. According to them, it is possible to forecast the stock price movements using Technical Analysis. The results of various studies have been inconclusive and indefinite about the issue. This study attempted to test the efficiency of FMCG Sector stocks in India in its weak form. For the study, closing prices of top 10 stocks from Nifty FMCG index has been taken for the 5-year period ranging from 1st October 2014 to 30th September 2019. Wald-Wolfowitz Run test has been used to test the haphazard movements in the stock price movements. The results indicated that FMCG sector stocks does support the Efficient Market Hypothesis and exhibit efficiency in its weak form. Hence, it is not possible to accurately predict the price movements of these stocks.

Uji Komparasi Abnormal Return, Trading Volume, Trading Frequency, Dan Bid-Ask Spread Sebelum Dan Sesudah Share Split

2016 ◽  
Vol 8 (2) ◽  
pp. 24-45
Author(s):  
Tania Hayu Safira ◽  
Febryanti Simon
Keyword(s):  
Abnormal Return ◽  
Trading Volume ◽  
Stock Exchange ◽  
Distributed Data ◽  
Trading Frequency ◽  
Bid Ask Spread ◽  
Analysis Technique ◽  
Before And After ◽  
Test Of Hypothesis ◽  
Kolmogorov Smirnov

This study is event study that was conduct to examine the differences of abnormal return, trading volume, trading frequency and bid-ask spread before and after the events of share split. The object of this research is the companies that did share split and listed in Indonesia Stock Exchange in 2008 - 2015. The samples are 30 companies chosen by purposive sampling method. The criteria are the company did not do corporate action right issue, pre-emptive rights, a share dividend and bonus shares in the same year with share split. Event window used in this study was 30 days consisting of 15 days before and 15 days after the share split. Data analysis technique begins with a test of normality using Kolmogorov – Smirnov and transform for unnormally distributed data. Then, test of hypothesis using Paired t – test to compare the differences before and after share split. The results of this study showed that volume trading activity and trading frequency had significant differences before and after the share split. While, variable abnormal return and bid-ask spread had not significant differences before and after the share split. Keywords: Abnormal return, bid-ask spread, share split, trading frequency, trading 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.

Testing the weak form of efficient market hypothesis for socially responsible and Shariah indexes in the USA

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abbas Khan ◽  
Muhammad Yar Khan ◽  
Abdul Qayyum Khan ◽  
Majid Jamal Khan ◽  
Zia Ur Rahman
Keyword(s):  
Stock Prices ◽  
Arima Model ◽  
Weak Form ◽  
Efficient Market Hypothesis ◽  
Future Price ◽  
Short Term ◽  
Socially Responsible ◽  
Efficient Market ◽  
Content Type ◽  
The Us

Purpose By testing the weak form of efficient market hypothesis (EMH) this study aims to forecast the short-term stock prices of the US Dow and Jones environmental socially responsible index (SRI) and Shariah compliance index (SCI). Design/methodology/approach This study checks the validity of the weak form of EMH for both SCI and SRI prices by using different parametric and non-parametric tests, i.e. augmented Dickey-Fuller test, Philip-Perron test, runs test and variance ratio test. If the EMH is invalid, the research further forecasts short-term stock prices by applying autoregressive integrated moving average (ARIMA) model using daily price data from 2010 to 2018. Findings The research confirms that a weak form of EMH is not valid in the US SRI and SCI. The historical data can predict short-term future price movements by using technical ARIMA model. Research limitations/implications This study provides better guidance to risk-averse national and international investors to earn higher returns in the US SRI and SCI. This study can be extended to test the EMH of Islamic equity in the Middle East and North Africa region and other top Islamic indexes in the world. Originality/value This study is a new addition to the existing literature of equity investment and price forecasting by comparing and investigating the market efficiency of two interrelated US SRI and SCI.

scholarly journals Analisis Reaksi Pasar Terhadap Pengumuman Merger dan Akuisisi Pada Perusahaan Akuisitor yang Terdaftar di BEI

2018 ◽  
pp. 1870
Author(s):  
Ika Putri Adnyani ◽  
Gayatri Gayatri
Keyword(s):  
Abnormal Return ◽  
Trading Volume ◽  
Sampling Method ◽  
Stock Exchange ◽  
Cumulative Abnormal Return ◽  
Test Results ◽  
Volume Activity ◽  
Paired Sample ◽  
Analysis Technique ◽  
Before And After

This research is conducted on all acquisition companies that conduct acquisitions listed on Indonesia Stock Exchange 2011-2016 period. Sampling method using purposive sampling. The number of samples of this research is 50 companies. The market reaction in this study used abnormal return and trading volume activity. The testing of information content will be done by looking at differences in cumulative abnormal return and the average trading volume of shares five days before and five days after the announcement of the acquisition. Data analysis technique used is paired sample t-test. Based on the test results, found there are significant differences in the abnormal return of the acquirer company before and after the announcement of the acquisition. However, there is no difference in trading volume activity of the acquirer's stock before and after the acquisition announcement   Keywords: acquisitions, stock market, abnormal return, trading volume activity

scholarly journals Exchange Listing Changes: Volatility and Liquidity Effects in Taiwan

2003 ◽  
Author(s):  
Lloyd P. Blenman ◽  
Dar-Hsin Chen ◽  
Chang-Wen Duan
Keyword(s):  
Trading Volume ◽  
Abnormal Returns ◽  
Relative Volatility ◽  
The Past ◽  
Listing Change ◽  
The Rose

We examine the volatility, liquidity and returns effects on stocks that switch exchange listings from the ROSE to the TSE in Taiwan from 1992 to 2000. Switching firms earn statistically positive returns before the transfer day and earn statistically negative returns after that day. We find evidence of improved liquidity, ownership dispersion and actual trading volume for such firms. The relative volatility of trading volume, compared against the firms’ own histories, and volatility of returns also increase after a listing change. We show that increased trading volume and liquidity are associated with the abnormal returns around the transfer date. We find no evidence that the past earnings of firms significantly affect the abnormal returns realized in the post-listing period.  

scholarly journals Modeling of Returns and Trading Volume by Regime Switching Copulas

2013 ◽  
pp. 45
Author(s):  
Henryk Gurgul ◽  
Artur Machno ◽  
Roland Mestel
Keyword(s):  
Regime Switching ◽  
Trading Volume
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