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Developing an approach to evaluate stocks by forecasting effective features with data mining methods
16 references·8 citing·44 second hop
Developing an approach to evaluate stocks by forecasting effective features with data mining methods (2014)Developing an approach to evaluate stocks…Analysis of financial statements (2016)Analysis of financial stateme…Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques (2014)Predicting stock and stock pr…Applying Artificial Neural Networks to prediction of stock price and improvement of the directional prediction index – Case study of PETR4, Petrobras, Brazil (2013)Applying Artificial Neural Ne…Size, value, and momentum in international stock returns (2012)Size, value, and momentum in …A hybrid stock selection model using genetic algorithms and support vector regression (2011)A hybrid stock selection mode…Combining multiple feature selection methods for stock prediction: Union, intersection, and multi-intersection approaches (2010)Combining multiple feature se…Predicting Global Stock Returns (2009)Predicting Global Stock Retur…The Use of DuPont Analysis by Market Participants (2008)The Use of DuPont Analysis by…The use of data mining and neural networks for forecasting stock market returns (2005)The use of data mining and ne…Predicting returns with financial ratios (2004)Predicting returns with finan…Empirical evidence on corporate governance in Europe: The effect on stock returns, firm value and performance (2004)Empirical evidence on corpora…A comparison between Fama and French's model and artificial neural networks in predicting the Chinese stock market (2004)A comparison between Fama and…The Valuation of Cash Flow Forecasts: An Empirical Analysis (1995)The Valuation of Cash Flow Fo…Common risk factors in the returns on stocks and bonds (1993)Common risk factors in the re…Principles of corporate finance (1982)Principles of corporate finan…The Investment, Financing, and Valuation of the Corporation (1963)The Investment, Financing, an…Systemic risk prediction using machine learning: Does network connectedness help prediction? (2024)Systemic risk prediction usin…Evaluating the performance of ensemble classifiers in stock returns prediction using effective features (2022)Evaluating the performance of…Stock Price Movements Classification Using Machine and Deep Learning Techniques-The Case Study of Indian Stock Market (2019)Stock Price Movements Classif…A Comparative Study of SVM and LSTM Deep Learning Algorithms for Stock Market Prediction. (2019)A Comparative Study of SVM an…ACFLN: artificial chemical functional link network for prediction of stock market index (2018)ACFLN: artificial chemical fu…Fusion of multiple diverse predictors in stock market (2016)Fusion of multiple diverse pr…Wrapper ANFIS-ICA method to do stock market timing and feature selection on the basis of Japanese Candlestick (2015)Wrapper ANFIS-ICA method to d…Stock market trend prediction using dynamical Bayesian factor graph (2015)Stock market trend prediction…CAPITAL ASSET PRICES: A THEORY OF MARKET EQUILIBRIUM UNDER CONDITIONS OF RISK* (1964)Risk, Return, and Equilibrium: Empirical Tests (1973)The Cross-Section of Expected Stock Returns (1992)Illiquidity and stock returns: cross-section and time-series effects (2002)A five-factor asset pricing model (2014)Efficient Capital Markets: A Review of Theory and Empirical Work (1970)EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)Business conditions and expected returns on stocks and bonds (1989)Forecasting daily stock market return using dimensionality reduction (2016)Systematic analysis and review of stock market prediction techniques (2019)Financial time series forecasting using support vector machines (2003)Forecasting stock market movement direction with support vector machine (2004)Evaluating multiple classifiers for stock price direction prediction (2015)Sentiment analysis on social media for stock movement prediction (2015)CNNpred: CNN-based stock market prediction using a diverse set of variables (2019)On Persistence in Mutual Fund Performance (1997)Value and Momentum Everywhere (2013)Choosing factors (2018)Climate risks and market efficiency (2018)Theory of the firm: Managerial behavior, agency costs and ownership structure (1976)Corporate social responsibility and corporate financial performance: Evidence from Korea (2010)The wages of social responsibility — where are they? A critical review of ESG investing (2015)The impacts of environmental, social, and governance factors on firm performance (2018)Asset returns and inflation (1977)Dividend yields and expected stock returns (1988)The Dividend-Price Ratio and Expectations of Future Dividends and Discount Factors (1988)Efficient tests of stock return predictability☆ (2006)The conditional CAPM does not explain asset-pricing anomalies☆ (2006)Forecasting the Equity Risk Premium: The Role of Technical Indicators (2014)CORPORATE INCOME TAXES AND THE COST OF CAPITAL: A CORRECTION (1963)Principles of Corporate Finance. (1981)Comparing the Accuracy and Explainability of Dividend, Free Cash Flow, and Abnormal Earnings Equity Value Estimates (2000)Social Mood and Financial Economics (2005)Estimating the Intertemporal Risk–Return Tradeoff Using the Implied Cost of Capital (2008)Editor's Choice Digesting Anomalies: An Investment ApproachThe Cost of Capital, Corporation Finance and the Theory of Investment (1958)Increasing Returns and Long-Run Growth (1986)… and the Cross-Section of Expected Returns (2015)Replicating Anomalies (2018)Top-Management Compensation and Capital Structure (1993)Relationship between innovativeness, quality, growth, profitability, and market value (2005)Does Investor Misvaluation Drive the Takeover Market? (2006)THE VALUATION OF RISK ASSETS AND THE SELECTION OF RISKY INVESTMENTS IN STOCK PORTFOLIOS AND CAPITAL BUDGETS**This paper is another in a series of interrelated theoretical and statistical studies of corporate financial and investment policies being made under grants from the Rockefeller Foundation, and more recently the Ford Foundation, to the Harvard Business School. The generous support for this work is most gratefully acknowledged. The author is also much indebted to his colleagues Professors Bishop, Christenson, Kahr, Raiffa, and (especially) Schlaifer, for extensive discussion and commentary on an earlier draft of this paper; but responsibility for any errors or imperfections remains strictly his own.[Professor Sharpe's paper, “Capital Asset Prices: A Theory of Market Equilibrium Under Conditions of Risk” (Journal of Finance, September 1964) appeared after this paper was in final form and on its way to the printers. My first section, which parallels the first half of his paper (with corresponding conclusions), sets the algebraic framework for sections II, III and VI, (which have no counterpart in his paper) and for section IV on the equilibrium prices of risk assets, concerning which our results differ significantly for reasons which will be explored elsewhere. Sharpe does not take up the capital budgeting problem developed in section V below.] (1975)Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average? (2007)
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References

  • 1993Common risk factors in the returns on stocks and bonds26,615 cited
  • 2012Size, value, and momentum in international stock returns1,822 cited
  • 2014Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques1,139 cited
  • 2004Predicting returns with financial ratios1,002 cited
  • 1982Principles of corporate finance990 cited
  • 1963The Investment, Financing, and Valuation of the Corporation958 cited
  • 2008The Use of DuPont Analysis by Market Participants606 cited
  • 1995The Valuation of Cash Flow Forecasts: An Empirical Analysis512 cited
  • 2004Empirical evidence on corporate governance in Europe: The effect on stock returns, firm value and performance498 cited
  • 2005The use of data mining and neural networks for forecasting stock market returns465 cited
  • 2010Combining multiple feature selection methods for stock prediction: Union, intersection, and multi-intersection approaches378 cited
  • 2009Predicting Global Stock Returns306 cited
  • 2011A hybrid stock selection model using genetic algorithms and support vector regression243 cited
  • 2016Analysis of financial statements226 cited
  • 2013Applying Artificial Neural Networks to prediction of stock price and improvement of the directional prediction index – Case study of PETR4, Petrobras, Brazil

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220 cited
  • 2004A comparison between Fama and French's model and artificial neural networks in predicting the Chinese stock market220 cited
  • Cited by

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    • 2018ACFLN: artificial chemical functional link network for prediction of stock market index64 cited
    • 2019Stock Price Movements Classification Using Machine and Deep Learning Techniques-The Case Study of Indian Stock Market55 cited
    • 2015Stock market trend prediction using dynamical Bayesian factor graph54 cited
    • 2019A Comparative Study of SVM and LSTM Deep Learning Algorithms for Stock Market Prediction.51 cited
    • 2022Evaluating the performance of ensemble classifiers in stock returns prediction using effective features46 cited
    • 2024Systemic risk prediction using machine learning: Does network connectedness help prediction?28 cited