scholarly journals Valuación de empresas de Telecomunicaciones con parámetros operativos

2017 ◽  
Vol 5 (9) ◽  
Author(s):  
J. Saldaña ◽  
M. Palomo ◽  
M. Blanco
Keyword(s):  
Stock Market ◽  
Stock Price ◽  
Asset Price ◽  
Capital Asset Price Model ◽  
Telecommunication Sector ◽  
Market Strategy ◽  
Stock Value ◽  
Telecommunication Companies ◽  
Strategy Acquisition ◽  
Para Determinar

Key words: Capita asset price, financial expectations, operative factorsAbstract. The value of telecommunication companies measured in terms of their stock value, may be explained not only by their historical financial results and their financial expectations, but also by the evaluation of other operative factors such as: technological change, organizational change, market strategy, acquisition cost, customers portfolio, fusions and institutional changes (regulations). Due to the importance of the telecommunication sector inthe stock market, as well as in the national economy, an analysis which improves its knowledge and allows a better valuation of these companies is required. Models for asset pricing CAPM (Capital Asset Price Model) and APT (Arbitrage Price Theory) have been developed and proved outside national context, besides, according to theory; their effectiveness for determining stock price depends on the stock market efficiencyPalabras Clave: Expectativas financieras, factores operativos, fijación de precios de capitalResumen. El valor de empresas de telecomunicaciones medidos en términos del valor de sus acciones, no solo se explica por la valuación de sus resultados financieros históricos y sus expectativas financieras si no también por la valuación de otros factores operativos tales como cambio tecnológico, cambio organizacional, estrategia de mercado, costo de adquisición, valor de la cartera de clientes, fusiones, y cambios institucionales (regulaciones).Por la importancia que presenta el sector de telecomunicaciones en el mercado de valores y en la economía nacional, se requiere de un análisis que permita su mejor conocimiento y control del valor. Los modelos desarrollados para la fijación de precios de activos; CAPM (Modelo de Fijación de Precios de Capital) y APT (Teoría de Fijación de  Precios de Arbitraje) han sido generalmente probados y desarrollados fuera del contexto nacional y su nivel de efectividad para determinar el precio de una acción y que de acuerdo a la teoría depende fundamentalmente del nivel de eficiencia del mercado de capitales.

Stock Price Prediction Using Fuzzy Time-Series Population Based Gravity Search Algorithm

2019 ◽  
Vol 7 (2) ◽  
pp. 50-64 ◽  
Author(s):  
Srinivasan N. ◽  
Lakshmi C.
Keyword(s):  
Stock Market ◽  
Stock Price ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Population Based ◽  
Fuzzy Time Series ◽  
Stock Price Prediction ◽  
Optimal Output ◽  
Stock Value ◽  
Total Turnover

The main motive of this research is to predict the future stock value of the particular day with minimum variation from the actual value of stock. In this research, a genetic algorithm-based gravity search algorithm is proposed for stock market prediction. It will be helpful for short-term investors in the National stock market. Some important factors that affect the value of stock are total stocks traded, total turnover of the company, gross domestic product (GDP) of the country, GDP per capita and political or external factors are some of the main factors that affect the stock value of that particular day. Opening and closing values of the stock market were predicted with the help of the above factors. Each factor will be considered as an object with mass, the mass of every object will be based on the importance. With the help of a Gravitational Search Algorithm (GSA) [1], the converging point of the entire object is determined and it is said to be the optimal output of the algorithm. The input considered are opening, closing, low and high values for a period of one year.

scholarly journals Detecting and Date-Stamping Rational Bubbles in Asset Price: An Empirical Investigation in the Tunisian Stock Market

2019 ◽  
Vol 11 (8) ◽  
pp. 91
Author(s):  
Siwar Mehri Helali
Keyword(s):  
Stock Market ◽  
Unit Root ◽  
Stock Price ◽  
Empirical Investigation ◽  
Asset Price ◽  
Unit Root Tests ◽  
Monthly Data ◽  
Empirical Application ◽  
Speculative Bubbles ◽  
Rational Bubbles

This study tests the existence of periodically collapsing speculative bubbles in the Tunisian stock market. We use the Phillips, Wu, and Yu (2011) and Phillips, Shi, and Yu (2015) approaches, based on right-tailed unit root tests, in order to explore the existence and to date-stamp the origination and termination of bubbles. An empirical application was conducted in the Tunisian stock market, using monthly data on stock price-dividend ratio, for the period running from January 2004 to December 2014. The empirical findings provide evidence for the existence of exuberance in the Tunisian stock market over the period and date-stamp its origination and collapse.

scholarly journals The Influence Of Return on Assets And Return on Equity to Companies Stock Price in the Telecommunication Sector registered in the Indonesia Stock Exchange

2019 ◽  
Vol 1 (1) ◽  
pp. 235-239
Author(s):  
Mu'tamaria Mu'tamaria
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Secondary Data ◽  
Free Variable ◽  
Telecommunication Sector ◽  
Return On Equity ◽  
Analytical Technique ◽  
Telecommunication Companies ◽  
Telecommunications Companies

The purpose of this research is to know the profitability ratios of telecommunication companies listed in Indonesia Stock Exchange period 2014-2017, particularly the influence of profitability ratio to stock price of telecommunication company. This research is conducted on twelve telecommunication companies listed in Indonesia Stock Exchange. The data used are secondary data of financial statements. The analytical technique mobilize multiple linear regression with two dependent variables of ROA and ROE and one free variable of stock price, to test the contribution of variable in influencing the stock price of companies. The results of research on Indonesian telecommunications companies show that the movement of stock prices are not significantly influenced by the value of ROE on Indonesian telecommunications companies. This study found that in the telecommunications company in Indonesia the increased or decreased value of ROA have an influence on the value of the company and the stock price of companies.

ENDOGENOUS JUMPING AND ASSET PRICE DYNAMICS

1998 ◽  
Vol 2 (2) ◽  
pp. 213-237 ◽  
Author(s):  
G. C. Lim ◽  
Vance L. Martin ◽  
Leslie E. Teo
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Asset Prices ◽  
Asset Price ◽  
Price Dynamics ◽  
Stock Market Crash ◽  
Time Period ◽  
The U.S

A model of asset price dynamics is derived in which large jumps in stock prices are determined endogenously. An important property of the model is that it can lead to asset price distributions that are multimodal. The model can explain how relatively small changes in dividends can lead to relatively large changes in asset prices and it can be used to identify the time period in which bubbles begin and end. The framework is applied to modeling the U.S. stock market crash in October 1987. Some forecasting experiments also are conducted with the result that the model is able to predict the size of the eventual crash in the aggregate stock price.

PENGARUH FREKUENSI PERDAGANGAN PADA SEKTOR PROPERTY DAN REAL ESTATE TERHADAP HARGA SAHAM

2019 ◽  
Vol 7 (02) ◽  
pp. 51
Author(s):  
Adri Wihananto
Keyword(s):  
Real Estate ◽  
Stock Price ◽  
Stock Exchange ◽  
Stock Trading ◽  
Trading Frequency ◽  
Important Thing ◽  
Know How ◽  
Stock Value ◽  
Measuring Frequency ◽  
Case Based

Trading frequency can be said as the implementation from trader of commerce. This case based on positive or negative trader reaction given by trader information.  Stock trading in BEI always fluctuate with price of volume value and frequency particularly. Frequency itself shows the company  involved or not. In trading frequency, if the indicator frequency it self shown the higher point, it means better. In spite of the most important thing is how the fluctuation or value conversion itself. On the frequencies we also could see which stocks is interested by the investor. When trading frequency high, it  may be create sense of interest from investors.The aim of this research, in order to know how far the effect of trading frequency (X) with stock value (Y) using cover stock value. The information used is begin 2008 with sample from twelve property and real estate companies. According to the research can be conclude from twelve companies in Indonesia Stock Exchange in 2008, 75 % of trading frequency samples doesn’t have signification degree between trading frequency and stock value. This case can be explained count on smaller than t tableEvaluation of this research is the trading measuring frequency at property sector and real estate not influence to stock priceKeywords : Trading Frequency, Stock Price 

Macroeconomic Factors and Pakistani Equity Market”

2004 ◽  
Vol 43 (4II) ◽  
pp. 619-637 ◽  
Author(s):  
Muhammad Nishat ◽  
Rozina Shaheen
Keyword(s):  
Stock Market ◽  
Industrial Production ◽  
Stock Prices ◽  
Stock Price ◽  
Consumer Price Index ◽  
Reverse Causality ◽  
Macroeconomic Factors ◽  
Macroeconomic Variables ◽  
Equilibrium Relationships

This paper analyzes long-term equilibrium relationships between a group of macroeconomic variables and the Karachi Stock Exchange Index. The macroeconomic variables are represented by the industrial production index, the consumer price index, M1, and the value of an investment earning the money market rate. We employ a vector error correction model to explore such relationships during 1973:1 to 2004:4. We found that these five variables are cointegrated and two long-term equilibrium relationships exist among these variables. Our results indicated a "causal" relationship between the stock market and the economy. Analysis of our results indicates that industrial production is the largest positive determinant of Pakistani stock prices, while inflation is the largest negative determinant of stock prices in Pakistan. We found that while macroeconomic variables Granger-caused stock price movements, the reverse causality was observed in case of industrial production and stock prices. Furthermore, we found that statistically significant lag lengths between fluctuations in the stock market and changes in the real economy are relatively short.

Maximal Overlap Discrete Wavelet Transform, Graph Theory And Backpropagation Neural Network In Stock Market Forecasting

2018 ◽  
Vol 5 (1) ◽  
pp. 41-46
Author(s):  
Rosalina Rosalina ◽  
Hendra Jayanto
Keyword(s):  
Neural Network ◽  
Graph Theory ◽  
Wavelet Transform ◽  
Stock Market ◽  
Discrete Wavelet Transform ◽  
Stock Price ◽  
Moving Average ◽  
Discrete Wavelet ◽  
Stock Market Forecasting ◽  
Artificial Neural

The aim of this paper is to get high accuracy of stock market forecasting in order to produce signals that will affect the decision making in the trading itself. Several experiments by using different methodologies have been performed to answer the stock market forecasting issues. A traditional linear model, like autoregressive integrated moving average (ARIMA) has been used, but the result is not satisfactory because it is not suitable for model financial series. Yet experts are likely observed another approach by using artificial neural networks. Artificial neural network (ANN) are found to be more effective in realizing the input-output mapping and could estimate any continuous function which given an arbitrarily desired accuracy. In details, in this paper will use maximal overlap discrete wavelet transform (MODWT) and graph theory to distinguish and determine between low and high frequencies, which in this case acted as fundamental and technical prediction of stock market trading. After processed dataset is formed, then we will advance to the next level of the training process to generate the final result that is the buy or sell signals given from information whether the stock price will go up or down.

scholarly journals Building stock market resilience through digital transformation: using Google trends to analyze the impact of COVID-19 pandemic

2020 ◽  
Vol 14 (1) ◽  
Author(s):  
Ding Ding ◽  
Chong Guan ◽  
Calvin M. L. Chan ◽  
Wenting Liu
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Digital Transformation ◽  
Google Trends ◽  
Building Stock ◽  
Market Sentiment ◽  
Price Performance ◽  
Novel Coronavirus ◽  
The Impact

Abstract As the 2019 novel coronavirus disease (COVID-19) pandemic rages globally, its impact has been felt in the stock markets around the world. Amidst the gloomy economic outlook, certain sectors seem to have survived better than others. This paper aims to investigate the sectors that have performed better even as market sentiment is affected by the pandemic. The daily closing stock prices of a total usable sample of 1,567 firms from 37 sectors are first analyzed using a combination of hierarchical clustering and shape-based distance (SBD) measures. Market sentiment is modeled from Google Trends on the COVID-19 pandemic. This is then analyzed against the time series of daily closing stock prices using augmented vector autoregression (VAR). The empirical results indicate that market sentiment towards the pandemic has significant effects on the stock prices of the sectors. Particularly, the stock price performance across sectors is differentiated by the level of the digital transformation of sectors, with those that are most digitally transformed, showing resilience towards negative market sentiment on the pandemic. This study contributes to the existing literature by incorporating search trends to analyze market sentiment, and by showing that digital transformation moderated the stock market resilience of firms against concern over the COVID-19 outbreak.

scholarly journals The Impact of COVID-19 on the Stock Price of Socially Responsible Enterprises: An Empirical Study in Taiwan Stock Market

2021 ◽  
Vol 18 (4) ◽  
pp. 1398
Author(s):  
Kuo-Jung Lee ◽  
Su-Lien Lu
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Abnormal Returns ◽  
Recovery Phase ◽  
Socially Responsible ◽  
Cumulative Impact ◽  
Study Approach ◽  
Price Performance ◽  
The Impact

This study examines the impact of the COVID-19 outbreak on the Taiwan stock market and investigates whether companies with a commitment to corporate social responsibility (CSR) were less affected. This study uses a selection of companies provided by CommonWealth magazine to classify the listed companies in Taiwan as CSR and non-CSR companies. The event study approach is applied to examine the change in the stock prices of CSR companies after the first COVID-19 outbreak in Taiwan. The empirical results indicate that the stock prices of all companies generated significantly negative abnormal returns and negative cumulative abnormal returns after the outbreak. Compared with all companies and with non-CSR companies, CSR companies were less affected by the outbreak; their stock prices were relatively resistant to the fall and they recovered faster. In addition, the cumulative impact of the COVID-19 on the stock prices of CSR companies is smaller than that of non-CSR companies on both short- and long-term bases. However, the stock price performance of non-CSR companies was not weaker than that of CSR companies during times when the impact of the pandemic was lower or during the price recovery phase.

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