Prediksi Harga Saham Perusahaan Perbankan Menggunakan Regresi Linear Studi Kasus Bank BCA Tahun 2015-2017

2019 ◽  
Vol 11 (1) ◽  
pp. 11-15
Author(s):  
Merfin Merfin ◽  
Raymond Sunardi Oetama
Keyword(s):  
Stock Price ◽  
Historical Data ◽  
Listed Company ◽  
Market Price ◽  
Local Economy ◽  
Average Error ◽  
Stock Investment ◽  
The People ◽  
Mining Tool ◽  
A Company

Stock investment is important for financial development in a company. Moreover, the stock price displayed by the company can be known by the people and the local economy because the company has gone public on the Indonesia Economic Exchange (IDX) at www.idx.co.id. There are several fundamental factors that influence the stock market price in a listed company and as a result the number of stock investors in Indonesia is very small. This cause made it difficult for the community to predict the stock price of banking companies at inconsistent prices. The method to be used in this paper is Linear Regression using Excel tools to perform calculations and SPSS 16.0 as a data mining tool. The research data taken is historical data of banking companies for 3 periods as a whole in the form of excel that has been downloaded from the Yahoo Finance website. The final results are in the form of MAPE charts in 3 years period, and Average error chart in 3 years period.

scholarly journals Analysis of Share Buyback Announcements on Stock Price Returns: A Study of BSE Listed Stocks

2020 ◽  
Vol 16 (3) ◽  
pp. 98
Author(s):  
Vaddula V. Krishna Reddy
Keyword(s):  
Stock Price ◽  
Market Price ◽  
Secondary Data ◽  
Data Availability ◽  
P Value ◽  
Event Window ◽  
Significant Difference ◽  
Level Of Significance ◽  
Information Technology Companies ◽  
A Company

Buyback is a procedure that enables a company to repurchase its shares from its existing shareholders, usually at a price near to or higher than the prevailing market price. The present study is based on secondary data and the event window period of 21 days (10 days before the announcement and 10 days after the announcement) are taken to measure its impact. Based on data availability 24 sample companies cover public sector undertakings and information technology companies selected for the study. The cumulative abnormal return for the entire 21-day period is 1.31%. T-statistic 2.066 with p-value (0.069 > 0.05) at a 5% level of significance indicates that accept the null hypothesis and conclude that there is a significant difference of ARR between pre and post buyback announcement of sample companies.

scholarly journals VALUATION OF FINANCIAL PERFORMANCE AND STOCK PERFORMANCE (Case Study PT Holcim Indonesia Tbk)

2019 ◽  
Author(s):  
Yuniza Nurunniza ◽  
Yoyon Supriadi
Keyword(s):  
Financial Performance ◽  
Asset Management ◽  
Stock Price ◽  
Stock Exchange ◽  
Market Price ◽  
Cement Industry ◽  
Financial Statement ◽  
Stock Performance ◽  
Financial Report ◽  
A Company

The main purpose of a company is to prosper the shareholders. The shareholders will get profit from the company they own after one year of operation by selling their products or services. Therefore, company’s manager has responsibility to regulate the company to be profitable and needs to know and analyze how was the company has performed for period of time so the manager could correct mistakes in the decision making and maintain the company’s strengths. Besides the company’s manager, the shareholders also need to know about how the company’s performance to monitor whether investments they have is need to defend or could be abandoned. Succeed or not the management of a company written in annual report contained financial report or financial statement. Company and the shareholders need to understand the valuation of financial performance from the financial statement which are financing, asset management and profitability, also stock performance which consider the share market price in the stock exchange. This financial and share performance research is studied to PT Holcim Indonesia Tbk in cement industry who has gotten loss for two years, then compare with companies in the same subsector in Indonesia Stock Exchange. The used research data is financial report for year 2012 until 2016 which are secondary data obtained from Indonesia Stock Exchange. The result of the research shows that compare to the companies in the same industry, PT Holcim Indonesia Tbk from 2012 until 2016 has decreased performance escpecially in profitability. It was caused of the sales were not optimal and cost inefficiency, that caused stock price is declining. During those five years, PT Holcim Indonesia Tbk expanded it’s company which is financed by debt, so PT Holcim Indonesia being a company that the operation dominant use of debt. Keywords : Profitability, Asset Management, Financing, Stock

scholarly journals Comparative study of Ohlson and cash flow discounting models in the prediction of the stock price

2021 ◽  
Vol 18 (2) ◽  
pp. 162-168
Author(s):  
Faten Nasfi Salem
Keyword(s):  
Cash Flow ◽  
Stock Price ◽  
Value Relevance ◽  
Listed Company ◽  
Evaluation Model ◽  
Market Price ◽  
Company Value ◽  
Residual Income Model ◽  
Income Model ◽  
Ohlson Model

Two models derived from the dividend discount model attracted the attention of researchers: the residual income model (RIM) and the Ohlson model. These models are said to be dualistic since they combine both aspects of the economic and accounting vision. We propose, in our study, to test the performance of the dualistic evaluation model and to show the importance of accounting information. To do this, we will calculate the value of a listed company according to the actuarial valuation model, namely: the available cash flow discounting model (DCF) and the Ohlson model as a dualistic model. Then, we will determine, based on the expectation and the variance of the signed prediction error (SPE), the model that comes closest to the market price in the case of a Tunisian listed company. The results found in the Tunisian context show the superiority of the Ohlson model in the prediction of stock market prices. This model underlies the traditional belief that the company value is compounded of two main parts: the net value of the investment made in it (book value) and the present value of the period benefits (earnings) that together bring the “clean surplus” concept of the shareholders’ equity value. Specifically, Ohlson (1995) motivates the adoption of the historical price model in value relevance studies, which expresses value as a function of earnings and book values

PENGARUH IT SPENDING TERHADAP KINERJA PERUSAHAAN PADA PERUSAHAAN TELEKOMUNIKASI YANG TERDAFTAR DI BURSA EFEK SELURUH ASIA TENGGARA PADA TAHUN 2009-2011

MODUS ◽  
2016 ◽  
Vol 26 (2) ◽  
pp. 93
Author(s):  
Irene Adrayani
Keyword(s):  
Stock Price ◽  
Sampling Method ◽  
Capital Expenditure ◽  
Stock Exchange ◽  
Market Price ◽  
Market Value ◽  
Company Performance ◽  
Corporate Value ◽  
Accounting Information System ◽  
Company Value

This study aims to get empirical evidence about the infuence of IT spending on corporate value by testing the efect of IT spending on corporate value by using Tobin’s Q. Te higher the stock price, the higher the company value as well as investors’ assessment. The market price of the company’s stocks refects investors’ assessment of the overall equity held. Of the stock price refects investor can provide an assessment of a company. Tobin’s Q is the ratio of the market value of the company’s assets as measured by the market value of the outstanding stocks and debt (enterprise value) to the replacement cost of the assets of the company. The sampling method is based on purposive sampling method with the purpose to obtain a sample that meets the criteria. Tis study used a sample taken from a telecommunications company listed on the Stock Exchange throughout Southeast Asia during the period of 2009-2011. The hypothesis in this study was tested using simple regression. Based on data analysis, the result that the variable IT spending does not afect the company value.Keywords: accounting information system, Tobin’s Q, IT spending, capital expenditure, company performance

A Historical Data based Ensemble System for Efficient Stock Price Prediction

2019 ◽  
Vol 12 ◽  
Author(s):  
Vijay Kumar Dwivedi ◽  
Manoj Madhava Gore
Keyword(s):  
Stock Price ◽  
Prediction Models ◽  
Historical Data ◽  
Stock Exchange ◽  
Primary Objective ◽  
Lasso Regression ◽  
Stock Price Prediction ◽  
Price Prediction ◽  
Consistent Manner ◽  
Selection Operator

Background: Stock price prediction is a challenging task. The social, economic, political, and various other factors cause frequent abrupt changes in the stock price. This article proposes a historical data-based ensemble system to predict the closing stock price with higher accuracy and consistency over the existing stock price prediction systems. Objective: The primary objective of this article is to predict the closing price of a stock for the next trading in more accurate and consistent manner over the existing methods employed for the stock price prediction. Method: The proposed system combines various machine learning-based prediction models employing least absolute shrinkage and selection operator (LASSO) regression regularization technique to enhance the accuracy of stock price prediction system as compared to any one of the base prediction models. Results: The analysis of results for all the eleven stocks (listed under Information Technology sector on the Bombay Stock Exchange, India) reveals that the proposed system performs best (on all defined metrics of the proposed system) for training datasets and test datasets comprising of all the stocks considered in the proposed system. Conclusion: The proposed ensemble model consistently predicts stock price with a high degree of accuracy over the existing methods used for the prediction.

Purchase, Pooling, and Equity Analysts' Valuation Judgments

2000 ◽  
Vol 75 (3) ◽  
pp. 257-281 ◽  
Author(s):  
Patrick E. Hopkins ◽  
Richard W. Houston ◽  
Michael F. Peters
Keyword(s):  
Stock Price ◽  
Joint Effect ◽  
Financial Accounting ◽  
Business Press ◽  
The Past ◽  
Income Statement ◽  
Business Combination ◽  
Separate Line ◽  
Acquisition Premium ◽  
A Company

We provide evidence that analysts' stock-price judgments depend on (1) the method of accounting for a business combination and (2) the number of years that have elapsed since the business combination. Consistent with business-press reports of managers' concerns, analysts' stock-price judgments are lowest when a company applies the purchase method of accounting and ratably amortizes the acquisition premium. The number of years since the business combination affects analysts' price estimates only when the company applies the purchase method and ratably amortizes goodwill—analysts' price estimates are lower when the business-combination transaction is further in the past. However, this joint effect of accounting method and timing is mitigated by the Financial Accounting Standards Board's proposed income-statement format requiring companies to report separate line items for after-tax income before goodwill charges and net-of-tax goodwill charges. When a company uses the purchase method of accounting and writes off the acquisition premium as in-process research and development, analysts' stockprice judgments are not statistically different from their judgments when a company applies pooling-of-interest accounting.

scholarly journals An Approach to Sustainability Risk Assessment in Industrial Assets

2021 ◽  
Vol 13 (12) ◽  
pp. 6538
Author(s):  
Fco. Javier García-Gómez ◽  
Víctor Fco. Rosales-Prieto ◽  
Alberto Sánchez-Lite ◽  
José Luis Fuentes-Bargues ◽  
Cristina González-Gaya
Keyword(s):  
Risk Assessment ◽  
Risk Management ◽  
Asset Management ◽  
Analysis And Evaluation ◽  
The People ◽  
Preliminary Study ◽  
Assessment Procedures ◽  
Identification Analysis ◽  
A Company ◽  
Industrial Company

Asset management, as a global process through which value is added to a company, is a managerial model that involves major changes in strategies, technologies, and resources; risk management; and a change in the attitude of the people involved. The growing commitment of companies to sustainability results in them applying this approach to all their activities. For this reason, it is relevant to develop sustainability risk assessment procedures in industrial assets. This paper presents a methodological framework for the inclusion of sustainability aspects in the risk management of industrial assets. This approach presents a procedure to provide general criteria, methodology, and essential mandatory requirements to be adopted for the identification, analysis, and evaluation of sustainability aspects, impacts, and risks related to assets owned and managed by an industrial company. The proposed procedure is based on ISO 55,000 and ISO 31,000 standards and was developed following three steps: a preliminary study, identification of sustainability aspects and sustainability risks/opportunities, and impact assessment and residual risks management. Our results could serve as a model that facilitates the improvement of sustainability analysis risks in industrial assets and could be used as a basis for future developments in the application of the standards to optimize management of these assets.

scholarly journals Stock Market Trading Rules Discovery Based on Biclustering Method

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Yun Xue ◽  
Zhiwen Liu ◽  
Jie Luo ◽  
Zhihao Ma ◽  
Meizhen Zhang ◽  
...  
Keyword(s):  
Stock Price ◽  
Historical Data ◽  
Probability Model ◽  
Trading Rules ◽  
Normal Probability ◽  
Long Time ◽  
Local Patterns ◽  
Short Term Prediction ◽  
Stock Market Trading ◽  
The Impact

The prediction of stock market’s trend has become a challenging task for a long time, which is affected by a variety of deterministic and stochastic factors. In this paper, a biclustering algorithm is introduced to find the local patterns in the quantized historical data. The local patterns obtained are regarded as the trading rules. Then the trading rules are applied in the short term prediction of the stock price, combined with the minimum-error-rate classification of the Bayes decision theory under the assumption of multivariate normal probability model. In addition, this paper also makes use of the idea of the stream mining to weaken the impact of historical data on the model and update the trading rules dynamically. The experiment is implemented on real datasets and the results prove the effectiveness of the proposed algorithm.

EXPECTED SHORTFALL PADA PORTOFOLIO OPTIMAL DENGAN METODE SINGLE INDEX MODEL (Studi Kasus pada Saham IDX30)

2021 ◽  
Vol 10 (2) ◽  
pp. 269-278
Author(s):  
Eis Kartika Dewi ◽  
Dwi Ispriyanti ◽  
Agus Rusgiyono
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Market Price ◽  
Expected Shortfall ◽  
Optimal Portfolio ◽  
Share Price ◽  
Single Index ◽  
Index Model ◽  
Single Index Model ◽  
Stock Investment

Stock investment is a commitment to a number of funds in marketable securities which shows proof of ownership of a company with the aim of obtaining profits in the future. For obtaining optimal returns from stock investments, investors are expected to form optimal portfolios. The optimal portfolio formation using the Single Index Model is based on the observation that a stock fluctuates in the direction of the market price. It shows that most stocks tend to experience price increases if the market share price rises, and vice versa. Selection of optimal portfolio-forming stocks on IDX30 using the Single Index Model method produces 4 stocks, that are BRPT (Barito Pacific Tbk.) with weight 31.134%, ICBP (Indofood CBP Sukses Makmur Tbk.) 17.138%, BBCA (Bank Central Asia Tbk.) 51.331% and SMGR (Semen Indonesia (Persero) Tbk.) 0.397%. Every investment must have a risk, for that investors need to calculate the possible risks that occur before investing. To calculate risk, Expected Shortfall (ES) is used as a measure of risk that is better than Value at Risk (VaR) because ES fulfill the subadditivity. At the 95% confidence level, the ES value is 23.063% while the VaR value is 10.829%. This means that the biggest possible risk that an optimal portfolio investor will receive using the Single Index Model for the next five weeks is 23.063%.Keywords : Portfolio, Single Index Model, Expected Shortfall, Value at Risk.

scholarly journals Revenues from related parties: A risk factor in Italian listed company financial statements

2015 ◽  
Vol 13 (1) ◽  
pp. 254-265
Author(s):  
Fabrizio Bava ◽  
Melchiorre Gromis di Trana
Keyword(s):  
Risk Factor ◽  
Listed Company ◽  
Financial Statements ◽  
Related Party Transactions ◽  
Corporate Scandals ◽  
A Company

In recent decades, related party transactions (RPTs) have played a prime role in major corporate scandals, obliging regulators to strengthen the rules with new bans and expensive requirements on companies. This study aims to contribute to the literature on RPTs, providing evidence to justify increasingly expensive and mandatory regulation. Results show that the intensity of related party revenues increases where a company has lost profitability as well as turnover.

Sign in / Sign up

Export Citation Format

Share Document