An ARIMA-LSTM Correlation Coefficient Based Hybrid Model for Portfolio Management of Dhaka Stock Exchange

2020 ◽  
pp. 214-226
Author(s):  
Rafatul Alam ◽  
Raisul Islam Arnob ◽  
Alvi Ebne Alam
Keyword(s):  
Correlation Coefficient ◽  
Hybrid Model ◽  
Portfolio Management ◽  
Stock Exchange

scholarly journals Optimizing Return on Assets through Investment in Property, Plant and Equipment: Evidence from Listed Nigerian Manufacturing Companies

2020 ◽  
Vol 4 (10) ◽  
pp. 50-57
Keyword(s):  
Portfolio Management ◽  
Stock Exchange ◽  
Secondary Data ◽  
Growth Options ◽  
Manufacturing Companies ◽  
Return On Assets ◽  
Correlational Research ◽  
Ex Post ◽  
Ex Post Facto ◽  
Level Of Significance

This study examined the extent to which investment in property, plant & equipment (PPE) made by listed manufacturing companies in Nigeria relate with the return on assets (ROA). The non-usage of composite appraisal techniques, other than traditional budgeting techniques was seen as a major problem of investment decisions on PPE. The study adopted the quantitative panel methodology of the ex post facto and correlational research design. Secondary data were extracted from the fact books of the Nigerian Stock Exchange for the period, 2013 – 2018. The number of manufacturing companies listed in the Stock Exchange during this period was 83, which was also taken as the population of the study. The sample used in the study was 69. Three hypotheses were tested at 0.05 level of significance. Multiple and simple regression analyses were used on the data collected, to find the relationship between the independent and dependent variables. The hypotheses tested indicated in the findings that property, plant and equipment had a significant relationship with return on assets of listed manufacturing firms in Nigeria when there is a joint relationship between variables of property, plant & equipment (PPE) and return on asset (ROA). Based on the findings and conclusion, it was recommended that management of manufacturing companies should ensure a holistic use of all techniques, exploring the real and growth options analyses as well as portfolio management techniques involving productive non-current assets, to earn the benefit of return on assets invested.

A selection of remarks on the measurement of correlations between variables of a panel data structure

2021 ◽  
Vol 66 (5) ◽  
pp. 7-25
Author(s):  
Mieczysław Kowerski ◽  
Jarosław Bielak
Keyword(s):  
Panel Data ◽  
Correlation Coefficient ◽  
Linear Correlation ◽  
Stock Exchange ◽  
Panel Data Analysis ◽  
Correlation Coefficients ◽  
Data Dependencies ◽  
Construction Companies ◽  
Advantages And Disadvantages ◽  
Warsaw Stock Exchange

Many articles featuring panel data modelling tend to begin their considerations with an introduction of the Pearson linear correlation coefficients matrix between the analysed variables. The aim of the article is to prove such an approach unsuitable in the analysis of panel data dependencies. Instead, an attempt has been made to propose a more appropriate measure – a correlation coefficient between the empirical and fitted values of the dependent variable of the estimated panel model (with fixed or random effects) in relation to the variable whose dependency towards the dependent variable is being studied. Pearson’s linear correlation coefficient does not reflect the basic advantage of panel data, which is the ability to provide information about the dependencies of the studied phenomena simultaneously in time and space. The fact that one observation relates to object i during period t and another to object j during period t + 1 is irrelevant for the calculation of the coefficient. Pearson’s coefficient, however, can be used when conducting sub-calculations in panel data analysis. The presented considerations have been illustrated by the calculations of the relationships between the structure of capital and the profitability and size of 17 construction companies listed on the Warsaw Stock Exchange in the years 2009–2018 (170 observations) which created a balanced panel. A specification of the advantages and disadvantages of the proposed solution was formulated on the basis of the calculations.

scholarly journals Applying Least Squares Support Vector Machines to Mean-Variance Portfolio Analysis

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Jian Wang ◽  
Junseok Kim
Keyword(s):  
Support Vector Machines ◽  
Least Squares ◽  
Portfolio Management ◽  
Stock Exchange ◽  
Efficient Frontier ◽  
Support Vector ◽  
Research Fields ◽  
Vector Machines ◽  
Mean Variance Portfolio ◽  
Mean Variance

Portfolio selection problem introduced by Markowitz has been one of the most important research fields in modern finance. In this paper, we propose a model (least squares support vector machines (LSSVM)-mean-variance) for the portfolio management based on LSSVM. To verify the reliability of LSSVM-mean-variance model, we conduct an empirical research and design an algorithm to illustrate the performance of the model by using the historical data from Shanghai stock exchange. The numerical results show that the proposed model is useful when compared with the traditional Markowitz model. Comparing the efficient frontier and total wealth of both models, our model can provide a more measurable standard of judgment when investors do their investment.

scholarly journals Hybrid Models Combining Technical and Fractal Analysis with ANN for Short-Term Prediction of Close Values on the Warsaw Stock Exchange

2018 ◽  
Vol 8 (12) ◽  
pp. 2473 ◽  
Author(s):  
Michał Paluch ◽  
Lidia Jackowska-Strumiłło
Keyword(s):  
Hybrid Model ◽  
Fractal Analysis ◽  
Stock Prices ◽  
Stock Exchange ◽  
Hybrid Models ◽  
Fractal Modeling ◽  
Fractal Analyses ◽  
Warsaw Stock Exchange ◽  
Artificial Neural Network Ann ◽  
Short Term Prediction

This paper presents new methods and models for forecasting stock prices and computing hybrid models, combining analytical and neural approaches. First, technical and fractal analyses are conducted and selected stock market indices calculated, such as moving averages and oscillators. Next, on the basis of these indices, an artificial neural network (ANN) provides predictions one day ahead of the closing prices of the assets. New technical analysis indicators using fractal modeling are also proposed. Three kinds of hybrid model with different degrees of fractal analysis were considered. The new hybrid modeling approach was compared to previous ANN-based prediction methods. The results showed that the hybrid model with fractal analysis outperforms other models and is more robust over longer periods of time.

scholarly journals O SETOR DE CONSUMO CÍCLICO SEGUNDO AÇÕES NEGOCIADAS NA B3: O SEGMENTO DE ELETRODOMÉSTICOS, PRODUTOS DIVERSOS,TECIDOS,VESTUÁRIOE CALÇADOS

2020 ◽  
Vol 3 (4) ◽  
pp. 37-46
Author(s):  
Rafael Gutierres Castanha ◽  
Andreia de Fatima Costa Miranda ◽  
Lucas Alves de Pontes
Keyword(s):  
Stock Market ◽  
Correlation Coefficient ◽  
Financial Market ◽  
Stock Price ◽  
Stock Exchange ◽  
Methodological Approach ◽  
Price Variability ◽  
Pearson’S Correlation Coefficient ◽  
Home Appliances ◽  
The Stability

By analyzing a portion of the Brazilian financial market, according to the daily value of its shares traded on the largest stock exchange in the country, the B3 stock exchange, offering possibilities to understand more clearly the behavior of the stock market according to growth, decrease, and even the stability of the values traded on the stock market in question. Thus, this research presents an analysis using Pearson's correlation coefficient and offers elements to affirm or refute the idea of proximity between companies in the same sector or not. By proposing the application of this methodology in the segment of home appliances, miscellaneous products, and fabrics, clothing and footwear, it is possible to point out how closely these companies are interconnected in terms of stock price variability. Thus, the objective was to observe not only the behavior of the stock price of the companies of the sector in question during a given period, as well as the intensity of variation between the same measures by the correlation coefficient, but also to evaluate the use of this coefficient as a proposal. methodological approach to assess the proximity between the companies. As a result, it was concluded that the largest proximityis between companies of the same segment.

scholarly journals Pengembangan Aplikasi Simulasi Perdagangan Saham dengan Sector Rotation dan Linear Programming

2014 ◽  
Vol 5 (1) ◽  
pp. 418
Author(s):  
Tomy G. Soemapradja ◽  
Jerry Marcellinus Logahan ◽  
Hengky Ongowarsito
Keyword(s):  
Linear Programming ◽  
Portfolio Management ◽  
Capital Market ◽  
Research University ◽  
Stock Exchange ◽  
Selection Strategy ◽  
Strategic Development ◽  
Management Measures ◽  
Market Needs ◽  
Sector Rotation

In strategic development a university will shift from teaching university to research university. It is because academic outcomes will be more useful if they can be commercialized by industries, which help improve the ranking of a university. The development of capital market and management measures of Indonesia Stock Exchange during the last 8 years aiming at academicians in order to identify and be interested in investing in the stock market needs to be observed. That is by providing a simulation so that more students can improve the competition at their graduation. The involvement of industry selection strategy and portfolio management will be required so that the expertise and ability to manage investments in the capital market can be better. So, it necessarily requires a development of simulation application of stock trading with business rotation and linear programming.

scholarly journals STOCK PRICE SEASONALITY EFFECT AND TRADING STRATEGY – AN EMPIRICAL STUDY OF SELECTED IT COMPANIES IN INDIA

2012 ◽  
Vol 10 (2) ◽  
pp. 264-288 ◽  
Author(s):  
Sathya Swaroop Debasish
Keyword(s):  
Portfolio Management ◽  
Stock Price ◽  
Stock Exchange ◽  
Trading Strategy ◽  
Primary Objective ◽  
Price Series ◽  
Active Portfolio Management ◽  
Multiple Regression Technique ◽  
Indian Stock Market ◽  
Returns On Investment

The primary objective of the study is to investigate the existence of seasonality in stock price behavior in Indian stock market and more specifically in the IT sector. The period of the study is from 3rd November 1994 to 31st December 2010. The study has employed daily price series of selected seven IT companies obtained from the official website of National Stock Exchange (NSE). The study used multiple regression technique to examine the significance of the regression coefficient for investigating day of week effects and week of the month effect, and Kruskal Wallis for analysis of trading strategy. It is found that all the seven selected IT companies evidenced day of the week effect and mostly either on Monday, Tuesday or Wednesday. Only Patni and Wipro evidenced significant Thursday effect. Similarly, evidence on week of month effect mostly either on 1st week, 2nd week or 3rd week. This implies that active portfolio management taking into account the findings will provide superior returns on investment in the IT sector in India.

scholarly journals Evaluating Post Merger Pakistan Stock Exchanges’ Market Efficiency

2021 ◽  
Vol 3 (2) ◽  
pp. 127-137
Author(s):  
MUHAMMAD AMIN KHAN ◽  
IHTESHAM KHAN ◽  
DR. ADNAN AHMAD
Keyword(s):  
Financial Markets ◽  
Market Efficiency ◽  
Portfolio Management ◽  
Stock Exchange ◽  
Abnormal Returns ◽  
Stock Exchanges ◽  
Market Information ◽  
Investment Environment ◽  
Great Opportunity ◽  
Markets And Institutions

The development and the formation of financial markets and institutions is indeed very instrumental for causing the robust economic growth. Although, as a fact the security prices are readily fluctuated by the market information known as market efficiency, making it a riskier investment. Subsequently, the investors accept the undiversifiable risk (Systematic risk) and cancel out the diversifiable risk (Unsystematic risk) through active diversified Portfolio Management, such a portfolio of securities, selected through market information reflects market efficiency. Thus, this study investigates the post- merger market efficiency for the Pakistan stock exchange as the three stock exchanges of the country has recently merged into Pakistan stock exchange. The analysis is based on event methodology, covering the pre-post-merger accumulated daily abnormal returns for a duration of 90 days (three months). Thus, the study proofs with respect to the accumulated daily abnormal returns, that the merger has increased the market efficiency. Consequently, the study supports the extant literature on merger and related market efficiency and provides another empirical evidence with respect to a developing country such as Pakistan. Rationally, the recent increase in the market efficiency will assure the supply of correct market information; consequently, boosting confidence of all investors and the regulators have a great opportunity to pursue continuous improvement in the present regulatory polices to promote healthy investment environment and increase the national revenue as well.

The performance of Bursa Malaysia and its causality effect with South Korea, Taiwan and Japan stock exchanges : 2000 – 2004

2006 ◽  
Vol 3 (2) ◽  
pp. 41
Author(s):  
Omar Samat ◽  
Zuraidah Ismail ◽  
Jaslin Md Dahlan
Keyword(s):  
South Korea ◽  
Portfolio Management ◽  
Stock Markets ◽  
Stock Exchange ◽  
Stock Exchanges ◽  
International Investors ◽  
Year 2000

This study examines the effect of returns from South Korea, Taiwan and Japan Stock Exchanges on the Bursa Malaysia in the year 2000 to 2004. The return from an individual stock exchange is no longer exclusive but with effect of globalization, it is also influenced by activities happening in other countries. The sources ofco-movements between stock markets are of great importance both for international investors and academics. A better knowledge of the underlying factors may improve portfolio management and help to assess the degree offinancial integration and efficiency.

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