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ARIMA: An Applied Time Series Forecasting Model for the Bovespa Stock Index
8 references·4 citing·38 second hop
ARIMA: An Applied Time Series Forecasting Model for the Bovespa Stock Index (2014)ARIMA: An Applied Time Series Forecasting…Operations management (2010)Operations managementOperations management research methodologies using quantitative modeling (2002)Operations management researc…Forecasting: Methods and Applications, 3rd Edition (1998)Forecasting: Methods and Appl…Forecasting methods and applications (1993)Forecasting methods and appli…the delphi method: techniques and applications (1975)the delphi method: techniques…EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)EFFICIENT CAPITAL MARKETS: A …Efficient Capital Markets: A Review of Theory and Empirical Work (1970)Efficient Capital Markets: A …A Simplified Model for Portfolio Analysis (1963)A Simplified Model for Portfo…A comparative study on effect of news sentiment on stock price prediction with deep learning architecture (2023)A comparative study on effect…A Hybrid Modeling Method Based on Linear AR and Nonlinear DBN-AR Model for Time Series Forecasting (2021)A Hybrid Modeling Method Base…An Applied Time Series Forecasting Model for Yield Prediction of Agricultural Crop (2020)An Applied Time Series Foreca…Advances in Statistical Forecasting Methods: An Overview (2018)Advances in Statistical Forec…Book Review: Time Series Analysis: Forecasting and Control (1977)Simulation Modeling and Analysis. (1983)Case Study Research: Design and Methods (1984)A review of modeling approaches for sustainable supply chain management (2012)Quantitative models for sustainable supply chain management: Developments and directions (2013)A comparison between Fuzzy AHP and Fuzzy TOPSIS methods to supplier selection (2014)Portfolio Selection: Efficient Diversification of Investments (1959)THE PERFORMANCE OF MUTUAL FUNDS IN THE PERIOD 1945–1964 (1968)The Adjustment of Stock Prices to New Information (1969)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)CAPITAL ASSET PRICES: A THEORY OF MARKET EQUILIBRIUM UNDER CONDITIONS OF RISK* (1964)The Behavior of Stock-Market Prices (1965)The Valuation of Risk Assets and the Selection of Risky Investments in Stock Portfolios and Capital Budgets (1965)ON THE PRICING OF CORPORATE DEBT: THE RISK STRUCTURE OF INTEREST RATES* (1974)Theory of the firm: Managerial behavior, agency costs and ownership structure (1976)Users of the world, unite! The challenges and opportunities of Social Media (2009)Fitting autoregressive models for prediction (1969)Time series forecasting using a hybrid ARIMA and neural network model (2003)A novel hybridization of artificial neural networks and ARIMA models for time series forecasting (2010)Portfolio optimization and return prediction by integrating modified deep belief network and recurrent neural network (2022)A hybrid approach to time series forecasting: Integrating ARIMA and prophet for improved accuracy (2025)Random Walks in Stock Market Prices (1995)Stock Price Prediction Using the ARIMA Model (2014)Stock price prediction using LSTM, RNN and CNN-sliding window model (2017)Navigating Uncertainty: Enhancing Markowitz Asset Allocation Strategies through Out-of-Sample Analysis (2024)Evaluation of Cost-Sensitive Learning Models in Forecasting Business Failure of Capital Market Firms (2025)Another look at measures of forecast accuracy (2006)Automatic Time Series Forecasting: The forecast Package for R (2008)To Explain or to Predict? (2010)Prediction intervals for exponential smoothing using two new classes of state space models (2005)Time series forecasting using a weighted cross-validation evolutionary artificial neural network ensemble (2013)Another look at forecast selection and combination: Evidence from forecast pooling (2018)The External Control of Organizations. (1978)Research guidelines for the Delphi survey technique (2000)The Delphi method as a research tool: an example, design considerations and applications (2004)An exploration towards a production theory and its application to construction (2000)Mass customization: Literature review and research directions (2001)Action research for operations management (2002)
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References

  • 1970EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK*24,470 cited
  • 1970Efficient Capital Markets: A Review of Theory and Empirical Work13,616 cited
  • 1975the delphi method: techniques and applications5,236 cited
  • 1963A Simplified Model for Portfolio Analysis2,740 cited
  • 1993Forecasting methods and applications2,400 cited
  • 2010Operations management1,800 cited
  • 2002Operations management research methodologies using quantitative modeling670 cited
  • 1998Forecasting: Methods and Applications, 3rd Edition133 cited

Cited by

  • 2021A Hybrid Modeling Method Based on Linear AR and Nonlinear DBN-AR Model for Time Series Forecasting48 cited
  • 2023A comparative study on effect of news sentiment on stock price prediction with deep learning architecture42 cited
  • 2018Advances in Statistical Forecasting Methods: An Overview34 cited
  • 2020An Applied Time Series Forecasting Model for Yield Prediction of Agricultural Crop28 cited

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