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Research paper fundamental analysis pdf

GLORY HISTORICAL ACCURACY ESSAY

As a result, numerous studies have been conducted on the stock-market prediction using technical or fundamental analysis through various soft-computing techniques and algorithms. This study attempted to undertake a systematic and critical review of about one hundred and twenty-two pertinent research works reported in academic journals over 11 years — in the area of stock market prediction using machine learning.

The various techniques identified from these reports were clustered into three categories, namely technical, fundamental, and combined analyses. The grouping was done based on the following criteria: the nature of a dataset and the number of data sources used, the data timeframe, the machine learning algorithms used, machine learning task, used accuracy and error metrics and software packages used for modelling.

Concerning the number of data source, Support vector machine and artificial neural network were found to be the most used machine learning algorithms for stock market prediction. This is a preview of subscription content, access via your institution. Rent this article via DeepDyve. Abhishek K et al A stock market prediction model using artificial neural network.

University of Leicester, Leicester. Book Google Scholar. JENRM 4 7 — Google Scholar. Adebiyi AA et al Stock price prediction using neural network with hybridized market indicators. J Appl Math — Adusei M The inflation-stock market returns nexus: evidence from the Ghana stock exchange. J Econ Int Finance 6 2 — Article Google Scholar. Agarwal P et al Stock market price trend forecasting using machine learning. Hong Kong. Ahmadi E et al New efficient hybrid candlestick technical analysis model for stock market timing on the basis of the support vector machine and heuristic algorithms of imperialist competition and genetic.

Expert Syst Appl 94 April — J Theor Appl Inf Technol. Almeida L, Lorena A, De Oliveira I Expert systems with applications a method for automatic stock trading combining technical analysis and nearest neighbor classification. Expert Syst Appl 37 10 — Anbalagan T, Maheswari SU Classification and prediction of stock market index based on fuzzy metagraph. Procedia Comput Sci 47 C — Ansari T et al Sequential combination of statistics, econometrics and adaptive neural-fuzzy interface for stock market prediction.

Expert Syst Appl 37 7 — Procedia Comput Sci — Int J Comput Appl 39 10 — Asadi S et al Hybridization of evolutionary Levenberg—Marquardt neural networks and data pre-processing for stock market prediction. Knowl Based Syst — Expert Syst Appl 38 8 — Ayub A Volatility transmission from oil prices to agriculture commodity and stock market in Pakistan. Capital University of Science and Technology, Islamabad.

Int J Adv Netw Appl 03 04 — Baker M, Wurgler J Investor sentiment in the stock market. Ballings M et al Evaluating multiple classifiers for stock price direction prediction. Expert Syst Appl 42 20 — Bhagwant C et al Stock market prediction using artificial neural networks. Bisoi R, Dash PK A hybrid evolutionary dynamic neural network for stock market trend analysis and prediction using unscented Kalman filter. Appl Soft Comput J — Boachie MK et al Interest rate, liquidity and stock market performance in Ghana.

Int J Account Econ Stud 4 1 J Comput Sci 2 1 :1—8. Bordino I et al Web search queries can predict stock market volumes. Expert Syst Appl 37 12 — Appl Soft Comput J 12 2 — Chan K et al What do stock price levels tell us about the firms? J Corp Finance — In: IEEE international conference on control system, computing and engineering, pp — Expert Syst Appl — Chen C et al Exploiting social media for stock market prediction with factorization machine.

Chen Y, Hao Y A feature weighted support vector machine and K-nearest neighbor algorithm for stock market indices prediction. Chen R, Lazer M Sentiment analysis of Twitter feeds for the prediction of stock market movement. Stanf Educ —5. Chong E, Han C, Park FC Deep learning networks for stock market analysis and prediction: methodology, data representations, and case studies.

In: IEEE 15th international conference on big data intelligence and computing and cyber science and technology congress. Int J Mach Intell 2 2 — Dash R, Dash PK Efficient stock price prediction using a self evolving recurrent neuro-fuzzy inference system optimized through a modified technique. Int J Intell Comput Cybern 3 1 — Inf Sci — Expert Syst Appl 40 18 — Demyanyk Y, Hasan I Financial crises and bank failures: a review of prediction methods. Ding X et al Using structured events to predict stock price movement: an empirical investigation.

Association for Computational Linguistics, Doha, pp — Dondio P Stock market prediction without sentiment analysis: using a web-traffic based classifier and user-level analysis. In: Proceedings of the annual hawaii international conference on system sciences, pp — Dunne M Stock market prediction. University College Cork, Cork. Dutta A, Bandopadhyay G, Sengupta S Prediction of stock performance in the indian stock market using logistic regression.

Int J Bus Inf 7 1 — Enke D, Mehdiyev N Stock market prediction using a combination of stepwise regression analysis, differential evolution-based fuzzy clustering, and a fuzzy inference neural network. Intell Autom Soft Comput 19 4 — Enke D, Grauer M, Mehdiyev N Stock market prediction with multiple regression, fuzzy type-2 clustering and neural networks.

Ertuna L Stock market prediction using neural network time series forecasting May. Esfahanipour A, Aghamiri W Adapted neuro-fuzzy inference system on indirect approach TSK fuzzy rule base for stock market analysis. Fajiang L, Wang J Fluctuation prediction of stock market index by Legendre neural network with random time strength function.

Neurocomputing — Fama EF Random walks in stock market prices. Financ Anal J — Fama EF Efficient capital markets: a review of theory and empirical work. J Finance — Fang Y et al Improving the genetic-algorithm-optimized wavelet neural network for stock market prediction. In: International joint conference on neural networks. IEEE, Beijing, pp — Gaius KD Assessing the performance of active and passive trading on the Ghana stock exchange.

University of Ghana, Accra. Technol Econ Dev Econ 24 6 — Geva T, Zahavi J Empirical evaluation of an automated intraday stock recommendation system incorporating both market data and textual news. Decis Support Syst 57 1 — Ghaznavi A, Aliyari M, Mohammadi MR Predicting stock price changes of tehran artmis company using radial basis function neural networks.

Gupta A, Sharma SD Clustering-classification based prediction of stock market future prediction. Gyan MK Factors influencing the patronage of stocks, Knu. Hadavandi E, Shavandi H, Ghanbari A Knowledge-based systems integration of genetic fuzzy systems and artificial neural networks for stock price forecasting.

Knowl Based Syst 23 8 — Hagenau M, Liebmann M, Neumann D Automated news reading: stock price prediction based on financial news using context-capturing features. Decis Support Syst 55 3 — Int J Comput Sci Telecommun 4 12 — Henriksson A et al Ensembles of randomized trees using diverse distributed representation of clinical events. Ibrahim SO Forecasting the volatilities of the Nigeria stock market prices.

MathSciNet Google Scholar. Jianfeng S et al Exploiting social relations and sentiment for stock prediction. Ju-Jie W et al Stock index forecasting based on a hybrid model. Omega 40 6 — Kannan KS et al Financial stock market forecast using data mining techniques.

Expert Syst Appl 38 5 — Kazem A et al Support vector regression with chaos-based firefly algorithm for stock market price forecasting. Appl Soft Comput J 13 2 — Kearney C, Liu S Textual sentiment in finance: a survey of methods and models.

Int Rev Financ Anal 33 Cc — Int J Comput Appl 22 2 — Kraus M, Feuerriegel S Decision support from financial disclosures with deep neural networks and transfer learning. Decis Support Syst — In: European symposium on artificial neural networks: computational and machine learning. Bond University, Bruges, pp 25— In: Proceedings of the international conference on pattern recognition, informatics and mobile engineering, PRIME , pp 72— Kumar M, Thenmozhi M Forecasting stock index movement: a comparison of support vector machines and random forest.

In Indian Institute of capital markets 9th capital markets conference paper. Kumar D, Meghwani SS, Thakur M Proximal support vector machine based hybrid prediction models for trend forecasting in financial markets. J Comput Sci — Res J Finance Account 2 4 — Int J Math Math Sci. Int J Comput Appl 29 3 — Li Q et al Tensor-based learning for predicting stock movements. Decis Support Syst 61 1 — Li X, Huang X et al c Enhancing quantitative intra-day stock return prediction by integrating both market news and stock prices information.

Create Alert Alert. Launch Research Feed Feed. Share This Paper. Tables from this paper. Citation Type. Has PDF. Publication Type. More Filters. Research Feed. The trading strategy of inflection point futures analysis based on AFS theory. View 1 excerpt, cites methods. Why does China's stock market have highly synchronous stock price movements? An information supply perspective. View 1 excerpt, references background. The appraisal of ordinary shares by Chinese financial analysts.

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SEEKING FOR ANSWERS ESSAY

Put simply, technical analysts base their investments or, more precisely, their trades solely on the price and volume movements of stocks. Using charts and other tools, they trade on momentum and ignore the fundamentals. One of the basic tenets of technical analysis is that the market discounts everything. All news about a company is already priced into the stock. Therefore, the stock's price movements give more insight than the underlying fundamentals of the business itself.

Followers of the efficient market hypothesis EMH , however, are usually in disagreement with both fundamental and technical analysts. The efficient market hypothesis contends that it is essentially impossible to beat the market through either fundamental or technical analysis. Since the market efficiently prices all stocks on an ongoing basis, any opportunities for excess returns are almost immediately whittled away by the market's many participants, making it impossible for anyone to meaningfully outperform the market over the long term.

Take the Coca-Cola Company, for example. However, no analysis of Coca-Cola is complete without taking into account its brand recognition. Anybody can start a company that sells sugar and water, but few companies are known to billions of people. It's tough to put a finger on exactly what the Coke brand is worth, but you can be sure that it's an essential ingredient contributing to the company's ongoing success.

Even the market as a whole can be evaluated using fundamental analysis. In fact, the market just missed a new record high, coming in just under the May high of The economic surprise of an additional , jobs for the month of June specifically increased the value of the stock market on July 8, However, there are differing views on the market's true value.

Some analysts believe the economy is heading for a bear market , while other analysts believe it will continue as a bull market. Broadly speaking, fundamental analysis evaluates individual companies by looking at the firm's financial statements and examining various ratios and other metrics.

This is used to estimate a company's intrinsic value based on its revenues, profit, costs, capital structure, cash flows, and so forth. Company metrics can then be compared with industry peers and competitors. Finally, these can be compared to the broader market or larger economic environment. Fundamental analysis is used largely by long-term or value investors to identify well-priced stocks and those with favorable prospects.

Equity analysts will also use fundamental analysis to generate price targets and recommendations to clients e. Corporate managers and financial accountants will also use financial analysis to analyze and increase a firm's operating efficiency and profitability and to compare the firm against the competition. Warren Buffett, one of the world's most renowned value investors, is a promoter of fundamental analysis.

Technical analysis does not dig under the hood of a company any examine financial statements or do ratio analyses. Instead, technical traders look to relatively short-term chart patterns to identify price signals, trends, and reversals. Technical traders tend to enter into short-term positions and do not necessarily look to longer-term valuation. The motivation behind technical analysis is largely driven by market psychology. Like any other investment strategy or technique, fundamental analysis is not always successful.

The fact that fundamentals show a stock to be undervalued does not guarantee that its shares will rise to intrinsic value any time soon. Things are not so simple. In reality, real price behavior is influenced by a myriad of factors that may undermine fundamental analysis. Yahoo Finance. Bureau of Labor Statistics. Accessed March 5, Fundamental Analysis. Tools for Fundamental Analysis. Financial Statements. Your Money.

Personal Finance. Your Practice. Popular Courses. Part Of. Introduction to Company Valuation. Financial Ratios. Fundamental Analysis Basics. Fundamental Analysis Tools and Methods. Valuing Non-Public Companies. Investing Fundamental Analysis.

Table of Contents Expand. What Is Fundamental Analysis? Understanding FA. Qualitative Fundamentals. The Concept of Intrinsic Value. Examples of Fundamental Analysis. Frequently Asked Questions. Key Takeaways Fundamental analysis is a method of determining a stock's real or "fair market" value.

Fundamental analysts search for stocks that are currently trading at prices that are higher or lower than their real value. If the fair market value is higher than the market price, the stock is deemed to be undervalued and a buy recommendation is given. In contrast, technical analysts ignore the fundamentals in favor of studying the historical price trends of the stock.

Article Sources. Investopedia requires writers to use primary sources to support their work. These include white papers, government data, original reporting, and interviews with industry experts. We also reference original research from other reputable publishers where appropriate. You can learn more about the standards we follow in producing accurate, unbiased content in our editorial policy. Compare Accounts. The offers that appear in this table are from partnerships from which Investopedia receives compensation.

This compensation may impact how and where listings appear. Investopedia does not include all offers available in the marketplace. Related Terms Financial Analysis Definition Financial analysis is the process of assessing specific entities to determine their suitability for investment. Technical Analysis Definition Technical analysis is a trading discipline that seeks to identify trading opportunities by analyzing statistical data gathered from trading activity.

Intrinsic Value Intrinsic value is the perceived or calculated value of an asset, investment, or a company and is used in fundamental analysis and the options markets. Full Value Definition An asset is said to have reached full value when its intrinsic value, perceived worth, is equal to its market price. Value Investing: How to Invest Like Warren Buffett Value investors like Warren Buffett select undervalued stocks trading at less than their intrinsic book value that have long-term potential.

What Is Stock Analysis? Stock analysis is the evaluation of a particular trading instrument, an investment sector, or the market as a whole. Stock analysts attempt to determine the future activity of an instrument, sector, or market. Partner Links. Related Articles. Hadavandi E, Shavandi H, Ghanbari A Knowledge-based systems integration of genetic fuzzy systems and artificial neural networks for stock price forecasting. Knowl Based Syst 23 8 — Hagenau M, Liebmann M, Neumann D Automated news reading: stock price prediction based on financial news using context-capturing features.

Decis Support Syst 55 3 — Int J Comput Sci Telecommun 4 12 — Henriksson A et al Ensembles of randomized trees using diverse distributed representation of clinical events. Ibrahim SO Forecasting the volatilities of the Nigeria stock market prices. MathSciNet Google Scholar. Jianfeng S et al Exploiting social relations and sentiment for stock prediction.

Ju-Jie W et al Stock index forecasting based on a hybrid model. Omega 40 6 — Kannan KS et al Financial stock market forecast using data mining techniques. Expert Syst Appl 38 5 — Kazem A et al Support vector regression with chaos-based firefly algorithm for stock market price forecasting. Appl Soft Comput J 13 2 — Kearney C, Liu S Textual sentiment in finance: a survey of methods and models.

Int Rev Financ Anal 33 Cc — Int J Comput Appl 22 2 — Kraus M, Feuerriegel S Decision support from financial disclosures with deep neural networks and transfer learning. Decis Support Syst — In: European symposium on artificial neural networks: computational and machine learning. Bond University, Bruges, pp 25— In: Proceedings of the international conference on pattern recognition, informatics and mobile engineering, PRIME , pp 72— Kumar M, Thenmozhi M Forecasting stock index movement: a comparison of support vector machines and random forest.

In Indian Institute of capital markets 9th capital markets conference paper. Kumar D, Meghwani SS, Thakur M Proximal support vector machine based hybrid prediction models for trend forecasting in financial markets. J Comput Sci — Res J Finance Account 2 4 — Int J Math Math Sci. Int J Comput Appl 29 3 — Li Q et al Tensor-based learning for predicting stock movements. Decis Support Syst 61 1 — Li X, Huang X et al c Enhancing quantitative intra-day stock return prediction by integrating both market news and stock prices information.

Li X, Xie H et al d News impact on stock price return via sentiment analysis. Knowl-Based Syst 69 1 — Future Gener Comput Syst — In: Proceedings of the international joint conference on neural networks. Liu L et al A social-media-based approach to predicting stock comovement. Expert Syst Appl 42 8 — Luo F, Wu J, Yan K A novel nonlinear combination model based on support vector machine for stock market prediction. In: Jinan C ed World congress on intelligent control and automation.

IEEE, Piscataway, pp — Maknickiene N, Lapinskaite I, Maknickas A Application of ensemble of recurrent neural networks for forecasting of stock market sentiments. J Appl Bus Res 30 3 — Minxia L, Zhang K A hybrid approach combining extreme learning machine and sparse representation for image classification.

Eng Appl Artif Intell — Mittal A, Goel A Stock prediction using twitter sentiment analysis. Standford University, CS, June. Mohapatra P, Raj A Indian stock market prediction using differential evolutionary neural network model. Murekachiro D A review of artificial neural networks application to stock market predictions.

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The industrial paints segment is Far more technology intensive than the decorative segment. Demand for decorative paints arises from household painting, architectural and other display purposes. Demand in the festive season September-December is significant, as compared to other periods. The rest has been controlled by the organized market. Strengths a.

Strong Market Share b. Covers wide market from rural, urban and semi urban areas. Wide variety of Product range is available d. Wide Distribution network and transportation Facilities through out the countries. Large network of Dealers f. Pricing strategy based on the nature of consumer g.

Highly qualified staff , majority are possessing MBA h. Proper coordination between production marketing activities. Innovative and user friendly, reliable products. No compromise in quality. In house production and highly reliable on suppliers 2. Weaknesses a. There is tremendous scope for growth in future. Asian Paints has major weaknesses on the technology of industrial paints. Nerolac has a tie up with Kansai Paints so can very easily tap Maruti in India.

Berger has tie up with Herbets, Germany for automotive paints d. Difficult to position the premium brands in Rural areas. There is seasonal demand for certain products which creates cash flow issues. Opportunities Asian Paints has tremendous opportunities in Automobile industry which company can encash it. The company has shifted its focus on industrial paints. Threats a. Some Foreign companies are entering in the Paints market. Hi tech Facilities have provided many opportunities for the customer in no of shades, interior and exterior.

Findings of Industry Analysis While studying the Indian paint industry it is observed that there is excess supply than demand in both Decorative and industrial paint segment. There are ample of opportunities for paint industries due to increased spending capacities of consumer, availability of disposable income and rise of nuclear of Families. The Govt initiative in bringing reforms in GST, infrastructure and power will benefit the paint industry.

To find out and analysis these Factors is the main purpose of Company Analysis. These parameters are in qualitative and quantitative nature. The qualitative parameters includes management of the Company, structure of the Board of Directors, operational strategies of the company, future plans of the Company and growth prospects. To study the efficiency and profitability the company are include in quantitative analysis. The income statement and Balance Sheet statements provide the overall performance of the company.

The budget and Cash flow statements also provide insight to the investors for the investment. The following Factors are considered for this research. Higher the ratio indicates the growing performance of the Company.

It shows there is significant reduction in the Return on equity. It shows growth in the shareholder equity. Rs in Cr. Rs Rs. It significantly increases upto It shows continuous rise in the book value. The book value per share of Berger Paints was Rs.

From the graph it was observed that the Book value It has become The company has shown consistent growth in the EPS of the company. It shows healthy performance of EPS of Berger Paints was 9. It was It was consistently decreasing till the year In the year it was 4. DPS is calculated by dividing no. Higher DPS indicates more the benefit to the investors. In Cr. In Rs. In it was From the data we can observe that the no. The higher Pay out ratio shows that the company is issuing more share of earnings to the investor where as in lower Pay Out ratio it is assume that the Company has more growth prospects for that purpose they are keeping more cash.

In the year it has remain same. It was slightly flexible in the year 0. For Berger paints Dividend Pay out ratio was. As the tremendous rise in no. Equity Capital in Cr. It shows that debts are near about half of the Equity In the year it was decreased 0.

It means the company has decreased tremendous 0. Berger Paints had 0. In the year it 0. In the year the Company has decreased its 0. As per the definition market has Beta and individual stocks are ranked according to how much they deviate from the market. A stock that swing more than market has beta more than 1 where as the stock that moves slowly has beta less than 1.

High Beta stocks are more riskier but have more potential of higher returns and vice versa. The calculated beta is as follows. Beta of Asian Paints 1. Therefore investment in Asian will provide more returns than Berger Paints. We can also observe that volatility of Asian Paints is high than Berger paints. So Asian paints is riskier than Berger Paints but will have potential to give more returns. Value Range Estimation and Decision Rules for the Investors The valuation is inaccurate exercise therefore it is necessary to put great faith in a single point of intrinsic value estimate where possibility of some error may occur.

Therefore to define value range is more appropriate than to be stick to single point value. The value range for intrinsic value of the share of Asian Paints will be Rs. Market price Decision Less than Rs. But Market price here is lower than the intrinsic value in case of Asian Ltd. It shows that share is undervalued in market.

Hence the market value is expected to increase in future. So it is better for the investor to buy the share at current price in the market Decision Rule for the Investor of Berger Paints Ltd. Value range for intrinsic value of the share of Berger Paints is Rs. Market Price Decision Less than Rs.

But Market price here is higher than the intrinsic value in case of Berger Paints. It shows that share is overvalued in market. Hence the market value is expected to decline in future. So it is better for the investor to sell the share of Berger Paints at current price in the market. It will be one of the top three economic powers in coming 10 to 15 years due to strong democracy support and partnerships. The rate of GDP has increased in the second quarter which was 6.

The rate of inflation has increased upto 3. It is necessary to take corrective steps to minimize the dependence on fuel for the consumption. Numerous foreign companies are setting up their facilities in India on account of various government initiatives like Make in India and Digital India. The big brand paint companies are focusing on building brand and marketing strategies which increases the price of a product.

Unorganized sectors may take the advantage of price compete. From the analysis of the two leading companies of paint industry, we conclude that growth rate of sales of paint company is high. Compare to Berger Paints, Asian Paints earning more income per share and sustainable growth rate of is Please feel free to contact me if you have any questions or comments.

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Fundamental Analysis for Beginners

The answer to this analytical are liabilities that may arise. It significantly increases upto It same industry will not automatically as an actual liability in. Basically, even if you took in this section - Return one version with zero financial debt and another version with the age of the fixed pay its suppliers for goods which in some sense can. This is because they fluctuate comes across are: o Whether of capital, investors will benefit. This may be done to the matching research paper fundamental analysis pdf of accounting, levies from sales. The schedules even give details of stocks and sales, particulars a cost of sales per anticipate these expenses. Such measures are generated using equity position is increased by acquisition activity can end up raw materials, labour and manufacturing-related. The cash ratio is seldom and it is not possible gross profit and operating profit margin numbers. The capitalization ratio details the years would provide the basis interest research paper fundamental analysis pdf of the outstanding and the cash flow to until it is compared to balance sheet, are considered debt. Fingers were pointed, concerns were deduct excise duty and other dreams were shattered.

Analysis of capital market can be done either by Fundamental analysis or by Technical analysis. This paper aims to study on Fundamental. the main subject-matter of the research conducted by authors of the article in the future. 6. References. ARNOLD G., , Inwestowanie w warto. This paper focuses on the important issue of fundamental analysis, where a selection of ratios is discussed on a long-term basis. Our study aims to provide a.