scholarly journals Tangled String for Multi-Timescale Explanation of Changes in Stock Market

Information ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 118 ◽  
Author(s):  
Yukio Ohsawa ◽  
Teruaki Hayashi ◽  
Takaaki Yoshino
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Time Scale ◽  
Stock Exchange ◽  
Data Driven ◽  
Change Points ◽  
Sequential Data ◽  
Visualization Tool ◽  
Data Market ◽  
Innovation Platform

This work addresses the question of explaining changes in the desired timescales of the stock market. Tangled string is a sequence visualization tool wherein a sequence is compared to a string and trends in the sequence are compared to the appearance of tangled pills and wires bridging the pills in the string. Here, the tangled string is extended and applied to detecting stocks that trigger changes and explaining trend changes in the market. Sequential data for 11 years from the First Section of the Tokyo Stock Exchange regarding top-10 stocks with weekly increase rates are visualized using the tangled string. It was found that the change points obtained by the tangled string coincided well with changes in the average prices of listed stocks, and changes in the price of each stock are visualized on the string. Thus, changes in stock prices, which vary across a mixture of different timescales, could be explained in the time scale corresponding to interest in stock analysis. The tangled string was created using a data-driven innovation platform called Innovators Marketplace on Data Jackets, and is extended to satisfy data users here, so this study verifies the contribution of data market to data-driven innovation.

scholarly journals Interdependence and Risk Comparison of Slovak, Hungarian and Polish Stock Markets: Policy and Managerial Implications

2019 ◽  
Vol 69 (2) ◽  
pp. 273-287 ◽  
Author(s):  
Florin Aliu ◽  
Besnik Krasniqi ◽  
Adriana Knapkova ◽  
Fisnik Aliu
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Markets ◽  
Stock Exchange ◽  
Weighted Average ◽  
Stock Index ◽  
Risk Level ◽  
Average Return ◽  
Monetary System ◽  
Managerial Implications

Risk captured through the volatility of stock markets stands as the essential concern for financial investors. The financial crisis of 2008 demonstrated that stock markets are highly integrated. Slovakia, Hungary and Poland went through identical centralist economic arrangement, but nowadays operate under diverse stock markets, monetary system and tax structure. The study aims to measure the risk level of the Slovak Stock Market (SAX index), Budapest Stock Exchange (BUX index) and Poland Stock Market (WIG20 index) based on the portfolio diversification model. Results of the study provide information on the diversification benefits generated when SAX, BUX and WIG20 join their stock markets. The study considers that each stock index represents an independent portfolio. Portfolios are built to stand on the available companies that are listed on each stock index from 2007 till 2017. The results of the study show that BUX generates the lowest risk and highest weighted average return. In contrast, SAX is the riskiest portfolio but generates the lowest weighted average return. The results find that the stock prices of BUX have larger positive correlation than the stock prices of SAX. Moreover, the highest diversification benefits are realized when Portfolio SAX joins Portfolio BUX and the lowest diversification benefits are achieved when SAX joins WIG20.

scholarly journals Testing Weak-Form Market Efficiency of Dhaka Stock Exchange

2015 ◽  
Vol 4 (2) ◽  
pp. 79-90
Author(s):  
Md.‬ Abu Hasan‬‬‬‬‬‬‬‬
Keyword(s):  
Random Walk ◽  
Stock Market ◽  
Stock Prices ◽  
Stock Exchange ◽  
Weak Form ◽  
Jel Classification ◽  
Ratio Test ◽  
Daily Return ◽  
Classification Code ◽  
Augmented Dickey Fuller

Measuring the efficiency of the stock market is an important research topic as there are various implications for investors. This paper investigates the weak form efficiency in the framework of the random walk hypothesis for the stock market in Bangladesh, employing both Non Parametric tests (Runs test and Phillips-Perron test) and Parametric tests (Autocorrelation test, Augmented Dickey-fuller test, and Variance Ratio test). The study uses daily return data for the three stock indices of Dhaka Stock Exchange such as DSI (from 02 January 1993 to 27 January 2013) with a total of 4823 daily return observations, DGEN (from 01 January 2002 to 31 July 2013) with a total of 2903 daily return observations, and DSE-20 (from 01 January 2001 to 27 January 2013) with a total of 3047 daily return observations. The evidence suggests that all the return series do not follow the random walk model, and thus the Dhaka Stock Exchange is inefficient in weak form. Thus, historical stock prices can be used to achieve superior gains from the stock markets in Bangladesh. JEL Classification Code: C22, G10, G14

scholarly journals A Multifactor Fuzzy Time-Series Fitting Model for Forecasting the Stock Index

Symmetry ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 1474 ◽  
Author(s):  
Ming-Chi Tsai ◽  
Ching-Hsue Cheng ◽  
Meei-Ing Tsai
Keyword(s):  
Time Series ◽  
Stock Market ◽  
Trading Volume ◽  
Stock Exchange ◽  
Fuzzy Time Series ◽  
Stock Index ◽  
Sequential Data ◽  
Proposed Model ◽  
Market Indexes ◽  
Fitting Model

Fuzzy time series (FTS) models have gotten much scholarly attention for handling sequential data with incomplete and ambiguous patterns. Many conventional time series methods employ a single variable in forecasting without considering other variables that can impact stock volatility. Hence, this paper modified the multi-period adaptive expectation model to propose a novel multifactor FTS fitting model for forecasting the stock index. Furthermore, after a literature review, we selected three important factors (stock index, trading volume, and the daily difference of two stock market indexes) to build a multifactor FTS fitting model. To evaluate the performance of the proposed model, the three datasets were collected from the Nasdaq Stock Market (NASDAQ), Taiwan Stock Exchange Index (TAIEX), and Hang Seng Index (HSI), and the RMSE (root mean square error) was employed to evaluate the performance of the proposed model. The results show that the proposed model is better than the listing models, and these research findings could provide suggestions to the investors as references.

Performance and development of a thin stock market: the Stockholm Stock Exchange 1912–2017

2020 ◽  
pp. 1-19
Author(s):  
Kristian Rydqvist ◽  
Rong Guo
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Stock Selection ◽  
Data Set ◽  
Transaction Prices ◽  
Limit Orders ◽  
A Value

We estimate historical stock returns for Swedish listed companies in a newly constructed data set of daily stock prices that spans more than 100 years. Stock returns exhibit all the familiar characteristics. The growth of the public sector depressed the stock market, and the process of globalization revitalized it. Banks played an important role in the early development of the stock market. There was little trading in the past, and we examine the effects on return measurement from missing data. Stock selection and the replacement of missing transaction prices through search back procedures or limit orders make little difference to a value-weighted stock price index, while ignoring the price effects of capital operations makes a big difference.

scholarly journals The Behavior Patterns of Investors in Thailand Stock Market

2017 ◽  
Vol 9 (1) ◽  
pp. 155
Author(s):  
Quan Nhu Tran
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Exchange ◽  
Investment Decision ◽  
Behavior Patterns ◽  
Individual Investors ◽  
True Value ◽  
Investment Decision Making ◽  
Depth Interview ◽  
Decision Making Processes

The purpose of this paper is to investigate behavioral patterns expressed by investors in the Thailand stock market. The paper examines investment decision-making processes in the context of the current financial market in Thailand to shed some light on behavioral-induced pattern behind such investments. Data for this research was collated from 8 individual investors by semi-structured and in-depth interview. There are four behavioral factors of individual investors in Thailand Stock Exchange: Overconfidence, Excessive Optimism, Psychology of risk, and Herding Behavior. Securities Companies may also use the findings of this research for better understanding on investors’ decision to give better recommendations to them. Stock prices then reflect their true value and Thailand stock market becomes the yardstick of the economy’s wealth and helps enterprises to raise capital for business activities.

Impact on Stock Price by the Inclusion to and Exclusion from CNX Nifty Index

2012 ◽  
Vol 13 (1) ◽  
pp. 39-50 ◽  
Author(s):  
M. Selvam ◽  
G. Indhumathi ◽  
J. Lydia
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Research Study ◽  
Stock Exchange ◽  
Valuation Effect ◽  
Index Maintenance ◽  
Indian Stock Market ◽  
The Impact ◽  
Indian Perspective

Changes in an index are a regular phenomenon and they take place due to the inclusion and exclusion of stocks from the index. The inclusion or exclusion of stocks creates great impact on the value of the firm. However, these changes are simply a short-lived event with no permanent valuation effect. The present research study analyzed the impact of the inclusion into and exclusion of certain stocks from National Stock Exchange (NSE) S&P CNX Nifty index with Indian perspective. The study provides evidence on whether the announcements of Nifty index maintenance committee have any information content. This will also demonstrate the efficiency of Indian stock market with particular reference to NSE. The study revealed that on an average, no permanent effects were observed on stock prices. It is also found from the study that the NSE reacted unfavourably to the inclusion and exclusion of stocks and it is impossible to earn any excess returns where the particular stocks are included or excluded from the index.

scholarly journals Stock Market Prices Prediction using Random Forest and Extra Tree Regression

2019 ◽  
Vol 8 (3) ◽  
pp. 1224-1228
Keyword(s):  
Machine Learning ◽  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Research Area ◽  
Support Vector ◽  
Market Prices ◽  
Machine Learning Approach ◽  
Innovative Work

Prediction of Stock price is now a day’s an existing and interesting research area in financial and academic sectors to know the scale of economies. There did not exists any significant set of rules to estimate and predict the scale of share in the stock exchange. Many evolutionary technologies are existing such as technical, fundamental, time, statistical and series analysis which help us to attempt the prediction process, but none of the methods are proved as reliable and accurate tool to the society in the estimation of stock exchange or share market scales. Here in this paper we attempted to do innovative work through Machine Learning approach to predict or sense the behaviour tracking of the stock market sensex. Linear regression, Support Vector regression, Decision Tree, Ramdom Forest Regressor and Extra Tree Regressor are the Machine Learning models implemented effectively in predicting the stock prices and define the activity between the exchanges the securities between the buyers and sellers. We predicted the price of the stock based on the closing value and stock price. An algorithm with high accuracy we do the process of comparison for the accuracy of each of the model and finally is considered as better algorithm for predicting stock price. As share market is a vague domain we cannot predict the conditions occur, and also share market can never be predicted, this job can be done easily and technically through this work and the main aim of this paper is to apply algorithms in Machine Learning in predicting the stock prices.

scholarly journals FUNDAMENTAL AND TECHNICAL ANALYSIS OF THE STOCK PRICE

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Denis Spahija ◽  
Seadin Xhaferi
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Stock Exchanges ◽  
Full Time ◽  
Equal Opportunities ◽  
Factors Affecting ◽  
The Past ◽  
Real Value

Trading with stocks in developed market conditions for some is fun, for others it is a way to preserve the real value of the asset, while for the most is a challenge to gain bigger profits quickly and easily. Dreams on stock market alchemy rely on the development and upgrading of special systems whose ultimate goal is to uncover stock price secrets and their changes. What are the chances of this happening? Chances are minimal, according to experiences from the world’s leading stock exchanges in the past. The stock market complexity, the number and unpredictability of factors affecting stock prices and unexpected changes or stability do not give much hope to those who know what’s going to happen in the future. In such endeavors there are equal opportunities for both stock exchange experts and full-time amateurs. For all this, if the stock market cannot be defeated or deceived, then it is better to join it. So this means: to create a diversified portfolio of securities that provides a safe income, slightly higher than annual inflation, minimizing the risk.

scholarly journals Volatility at Karachi Stock Exchange

1995 ◽  
Vol 34 (4II) ◽  
pp. 651-657 ◽  
Author(s):  
Aslam Farid ◽  
Javed Ashraf
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Exchange ◽  
Efficient Market Hypothesis ◽  
Policy Implications ◽  
Positive Sign ◽  
Expected Returns ◽  
Portfolio Insurance ◽  
Almost All ◽  
Made In

Frequent “crashes” of the stock market reported during the year 1994 suggest that the Karachi bourse is rapidly converting into a volatile market. This cannot be viewed as a positive sign for this developing market of South Asia. Though heavy fluctuations in stock prices are not an unusual phenomena and it has been observed at almost all big and small exchanges of the world. Focusing on the reasons for such fluctuations is instructive and likely to have important policy implications. Proponents of the efficient market hypothesis argue that changes in stock prices are mainly dependent on the arrival of information regarding the expected returns from the stock. However, Fama (1965), French (1980), and French and Rolls (1986) observed that volatility is to some extent caused by trading itself. Portfolio insurance schemes also have the potential to increase volatility. Brady Commission’s Report provides useful insights into the effect of portfolio insurance schemes. It is interesting to note that many analysts consider the so-called “crashes” of Karachi stock market as a deliberate move to bring down prices. An attempt is made in this study to examine the effect of trading on the volatility of stock prices at Karachi Stock Exchange (KSE). Findings of the study will help understand the mechanism of the rise and fall of stock prices at the Karachi bourse.

scholarly journals Prediction model of stock market based on Chaos Theory

2021 ◽  
Vol 275 ◽  
pp. 01013
Author(s):  
Wenhan Qiao
Keyword(s):  
Stock Market ◽  
Dynamic Characteristics ◽  
Chaos Theory ◽  
Stock Prices ◽  
Stock Exchange ◽  
Development Trend ◽  
Exchange Market ◽  
Scale Modeling ◽  
Nonlinear Dynamic Characteristics ◽  
Modeling And Forecasting

After more than 30 years of development, China’s stock exchange market has already had a considerable scale. Modeling and forecasting stock prices is always a problem. Based on the data of three stocks given in the title, this paper analyzes the characteristics and development trend of each stock. Based on the foothold of chaos theory[1] this paper studies the nonlinear dynamic characteristics and predictability of China’s stock market, and finally tests it.

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