On the Design and Development of a Novel Real-Time Transaction Price Estimation System

2011 ◽  
Vol 393-395 ◽  
pp. 213-216 ◽  
Author(s):  
Chi Hua Chen ◽  
Szu Yin Lin ◽  
Hsu Chia Chang ◽  
Chi Chun Lo
Keyword(s):  
Real Time ◽  
Open Economy ◽  
Stock Price ◽  
Investment Decision ◽  
Efficient Market Hypothesis ◽  
Estimation Model ◽  
Investment Decision Making ◽  
Price Estimation ◽  
Estimation System ◽  
Transaction Price

In global open economy, transaction price estimation is an important issue in finance under stock price fluctuation. However, the transaction price is depend on the investors’ expect price which is difficult to be captured in used and implemented models for transaction price estimation. Therefore, this paper proposes the Transaction Price Estimation Model (TPEM) and designs a novel Real-time Transaction Price Estimation System (RTPES) which adopts the TPEM based on the efficient market hypothesis to estimate the investors’ expect price. In experiments, the simulation results show that the average accuracy of TPEM is 99.37%. This approach is feasible for stock investment decision-making.

scholarly journals Differences In Intrinsic Value With Stock Market Prices Using The Price Earning Ratio (Per) Approach As An Investment Decision Making Indicator (Case Study Of Manufacturing Companies In Indonesia Period 2016 - 2017)

2019 ◽  
Vol 1 (1) ◽  
pp. 82-92
Author(s):  
Ardy Indra Lekso Wibowo Putra ◽  
Aditya Dwiansyah Putra ◽  
Murni Sari Dewi ◽  
Denny Oktavina Radianto
Keyword(s):  
Decision Making ◽  
Stock Market ◽  
Stock Price ◽  
Stock Exchange ◽  
Intrinsic Value ◽  
Investment Decision ◽  
Manufacturing Companies ◽  
Market Prices ◽  
Investment Decision Making

An investor must be able to consider all kinds of steps that will be taken or that will be carried out, assessing stocks - shares that will provide optimal benefits in making an investment decision. By analyzing the intrinsic value of the price of a company's stock, investors can assess the fairness of the stock price. The method used to analize intrinsic value is fundamental analysis using the Price Earning Ratio (PER) approach. The samples to be taken in this research are manufacturing companies in Indonesia which are listed on the Indonesia Stock Exchange (IDX) for the period 2016 - 2017 with certain criteria. The results of this research will show that the shares of companies listed are in overvalued, undervalued or correctly valued conditions. So investors can decide to buy, hold or sell their shares.

scholarly journals Evidence Of Investors Responses To Managerial Investment Decision-Making

2011 ◽  
Vol 15 (3) ◽  
pp. 55
Author(s):  
Robert J. Walsh
Keyword(s):  
Decision Making ◽  
Stock Price ◽  
Investment Decision ◽  
Investment Decisions ◽  
Price Movement ◽  
Investment Expenditure ◽  
Price Reaction ◽  
Investment Decision Making ◽  
Significant Difference ◽  
Stock Price Reaction

<span>This paper investigates the stock price reaction of some pre-management buyout (MBO) investment decisions of managers. This paper finds that managers who engage in non-acquisition type investment expenditures (like plant expansions) in the pre-MBO period could lower the firms stock price. In addition, managers whose companies buy the assets or a stake in another firm give their company a positive stock price movement. Lastly, there is a statistically significant difference in stock price reaction depending on whether the investment expenditure is non-acquisition or acquisition.</span>

scholarly journals Investment Decisions through Total Asset Growth toward Price to Book Value on the Jakarta Islamic Index

2021 ◽  
Vol 12 (1) ◽  
pp. 63-74
Author(s):  
Syaugi Syaugi ◽  
Aulia Rahmah
Keyword(s):  
Stock Price ◽  
Time Series Data ◽  
Investment Decision ◽  
Investment Decisions ◽  
Study Data ◽  
Total Asset ◽  
Series Data ◽  
Book Value ◽  
Investment Decision Making ◽  
Asset Growth

This research analyzes the effect of investment decisions through Total Asset Growth (TAG) on Price to Book Value (PBV). Since PVB indicates stock measurement based on the ratio of stock price to book value, it is used by investors to assess the price offered. This research uses time-series data from 2014-2020 to examine seven companies selected using purposive sampling but based on fairly good asset developments from 2014 to 2020. Furthermore, this quantitative causal study data were collected using documentation from various sources and analyzed using a simple linear regression test. The results show that the TAG variable has no effect on PBV with a significance value of 0.89 0.05. This shows that TAG does not describe a stable company and is not always useful in investment decision-making.

scholarly journals A földrajzi diverzifikáció szerepe a globális tőkepiacokon

2020 ◽  
Vol 144 (3) ◽  
pp. 258-273
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Market News ◽  
Capital Markets ◽  
Capital Market ◽  
Statistical Data ◽  
Investment Decision ◽  
Market Prices ◽  
Investment Decision Making ◽  
Geographical Diversification

This study illustrates the effectiveness of geographical diversification using capital market data. The paper uses historical capital market prices to show how the neglect of geographical diversification results in a deterioration in investment decision-making. In addition, the correlations between the capital markets of the former socialist countries are presented, which in many cases can be explained by real economic processes and geopolitical events. Quantitative, real-time financial and statistical data provided by capital markets can also be used to justify the dependence systems between countries and groups of countries, but the method can also be used in many cases to show the economic and geopolitical changes between countries. The study shows how concentrated the world’s stock markets are, which means that smaller capital markets cannot separate themselves from economic events, money and capital market news, or events of the largest ones.

scholarly journals The Informational Content Of Changes In Stock Recommendation: Chaebol Vs. Non-Chaebol Affiliated Analysts

2016 ◽  
Vol 32 (6) ◽  
pp. 1687
Author(s):  
Youngtae Yoo ◽  
Hyunjun Park
Keyword(s):  
Decision Making ◽  
Stock Returns ◽  
Stock Price ◽  
Investment Decision ◽  
Earnings Forecasts ◽  
Informational Content ◽  
Inside Information ◽  
Stock Recommendations ◽  
Investment Decision Making ◽  
Decision Making Factors

Accurate analysts’ reports alleviate information asymmetry between companies and investors by providing accounting information that is useful in investment decision-making for market participants. Investors evaluate the credibility of stock recommendations based on the accuracy of the earnings forecasts of analysts, applying them in the decision-making process. Studies of stock recommendations have focused on their informational content, systematically analyzing the characteristics of recommendations and, to a lesser degree, decision-making factors. For most analysts, when stock recommendations and forecast changes are simultaneously disclosed, a large bias results if analysts fail to consider the magnitude of the market reaction relative to the earnings forecast and stock recommendations. In most previous studies, the informational content of both individual stock recommendations and changes in stock recommendations was investigated. In this study, we examine differences in the informational content depending on the stock recommendations of the report released immediately previous to the current report for the same recommendation. An upgraded (or downgraded) revision within the same recommendation category is associated with a greater (lower) stock price return. Even the same recommendation in the market may cause different reactions depending on both the recommendation itself and on the direction of change of the recommendation. Affiliated analysts have more access to inside information of the companies they analyze. The stock returns after revisions of Chaebol-affiliated analysts are significantly higher than those of non-Chaebol-affiliated analysts.

scholarly journals Forecasting Nestle Stock Price by using Brownian Motion Model during Pandemic Covid-19

2021 ◽  
Vol 7 (2) ◽  
pp. 58-64
Author(s):  
Siti Raihana Hamzah ◽  
Hazirah Halul ◽  
Assan Jeng ◽  
Umul Ain’syah Sha’ari
Keyword(s):  
Brownian Motion ◽  
Stock Prices ◽  
Stock Price ◽  
Investment Decision ◽  
Primary Objective ◽  
Percentage Error ◽  
Economic Downturn ◽  
Term Prediction ◽  
Investment Decision Making ◽  
Short Term Prediction

In the modern financial market, investors have to make quick and efficient investment decisions. The problem arises when the investor does not know the right tools to use in investment decision making. Different tools can be implemented in trading strategies to predict future stock prices. Therefore, the primary objective of this paper is to analyse the performance of the Geometric Brownian Motion (GBM) model in forecasting Nestle stock price by assessing the performance evaluation indicators. To analyse the stocks, two software were used, namely Microsoft Excel and Python.  The model is trained for 16 weeks (4 months) of data from May to August 2019 and 2020. The simulated sample is for four weeks (1 month) which is for September 2019 and 2020. The findings show that during the Pandemic Covid-19, short-term prediction using GBM is more efficient than long-term prediction as the lowest Mean Square Error (MSE) value is at one week period.  In addition, the Mean Absolute Percentage Error (MAPE) for all GBM simulations is highly accurate as it shows that MAPE values are less than 10%, indicating that the GBM method can be used to predict Nestle stock price during an economic downturn.

Pengaruh Rasio Keuangan terhadap Perubahan Harga Saham

2006 ◽  
Vol 1 (1) ◽  
pp. 106
Author(s):  
Umi Murtini ◽  
Shinta Mareta
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Investment Decision ◽  
Profit Margin ◽  
Financial Statement ◽  
Return On Assets ◽  
Stock Investment ◽  
Investment Decision Making ◽  
Net Profit ◽  
Equity Ratio

One factor that supports investors' trust on capital market istheir perception to the fiuingness of stock price. The more appropriate and quicker the information reflected by stock price delivered to investors, the more fficient the stock market. fhe information needed from the firm's financial statement if it's tooked from investor needs who would purchase a stock are stock price information, earning per sltare, total asset, earning after tax, net sale, total liabitity, and totat equity which is used to the company financing source. This research aims toexamine the effect of Price Earning Ratio (PER), Return on Assets (RoA), Net Profit Margin (NPM), Debt Equity Ratio (DER) changes to stock price changes either partially or simultaneously. This research proves that Price Earning ratio (PER) and Net Profit Margin (NpM) changes partially influence the change of stock price, whereas those four variables simultaneously influence the change of stock price. Thisresearch hopefully could give benefits to investors, emitens, and other partles as additional evaluating tools in the relation with the process of stock investment decision making when stock prices are fluctuative. This research is hopefully beneficial for emitens in making a wisdom relating to PER, RoA, NPM, and DER and can give additional lorcwledge and information for parties who need reference as well as literqture about financial management.Keywords: closing price, EAT, PER, DER, NPM, ROA

scholarly journals Analyst coverage and future stock price crash risk

2019 ◽  
Vol 20 (1) ◽  
pp. 63-77 ◽  
Author(s):  
Guanming He ◽  
Lu Bai ◽  
Helen Mengbing Ren
Keyword(s):  
Stock Price ◽  
Risk Measure ◽  
Investment Decision ◽  
Financial Analysts ◽  
Crash Risk ◽  
Analyst Coverage ◽  
Content Type ◽  
Information Intermediaries ◽  
Investment Decision Making ◽  
The Impact

Purpose Whether financial analysts play an effective role as information intermediaries and monitors has triggered a wide spread of debate among academics and practitioners to date. The purpose of this paper is to complement this debate by investigating the association between analyst coverage and firm-specific future stock price crash risk. Design/methodology/approach Regression analysis is based on a large sample of US public firms and the crash risk measure of Hutton et al. (2009). Potential endogeneity concerns are alleviated by restricting the sample period to the post-Regulation-FD period and conducting an analysis of the impact threshold for a confounding variable method per Larcker and Rusticus (2010). Findings Evidence reveals that a high level of analyst coverage is associated with lower future stock price crash risk. Furthermore, the negative association between analyst coverage and stock price crash risk is stronger for firms that have high financial opacity. Additionally, analyst forecast pessimism is negatively associated with future crash risk. Research limitations/implications Our research provides evidence in support for the view that financial analysts play an active information intermediary role in a way that increases information transparency of a firm and reduces its crash risk. Also, our study offers support for the view that analysts perform an effective monitoring role in a way that constraints management’s bad news hoarding activities and reduces future crash risk. Practical implications This study is of interest to investors who seek analyst reports for their investment decision making and for information providers who demand external financing. The findings of this study also have some other important implications for practitioners, given the economic and welfare consequences of stock price crashes. Originality/value This study offers support for the view that analysts serve positive roles as information intermediaries and monitors in the US stock market.

Foresight for stock market volatility – a study in the Indian perspective

foresight ◽  
2019 ◽  
Vol 22 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Jitendra Kumar Dixit ◽  
Vivek Agrawal
Keyword(s):  
Stock Market ◽  
Stock Price ◽  
Stock Exchange ◽  
Investment Decision ◽  
Market Volatility ◽  
Future Research ◽  
Stock Market Volatility ◽  
Content Type ◽  
Constant Variance ◽  
Investment Decision Making

Purpose Volatility is a permanent behavior of the stock market around the globe. The presence of the volatility in the stock price makes it possible to earn abnormal profits by risk seeking investors and creates hesitancy among risk averse investors as high volatility means high return with high risk. Investors always consider market volatility before making any investment decisions. Random fluctuations are termed as volatility of stock market. Volatility in financial markets is reflected because of uncertainty in the price and return, unexpected events and non-constant variance that can be measured through the generalized autoregressive conditional heteroscedasticity family models and that will give an insight for investment decision-making. Design/methodology/approach Daily data of the closing value of Bombay Stock Exchange (BSE) (Sensex) and National Stock Exchange (NSE) (Nifty) from April 1, 2011 to March 31, 2017 is collected through the web-portal of BSE (www.bseindia.com) and NSE (www.nseindia.com) for the analysis purpose. Findings The outcome of the study suggested that P-GARCH model is most suitable to predict and forecast the stock market volatility for both the markets. Research limitations/implications Future research can be extended to other stock market segments and sectoral indices to explore and forecast the volatility to establish a trade-off between risk and return. Originality/value The results of previous studies available are not conducive to this research, and very limited scholarly work is available in the Indian context, so required to be re-explored to identify the appropriate model to predict market volatility.

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