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A novel hybrid model based on Hodrick–Prescott filter and support vector regression algorithm for optimizing stock market price prediction
16 references·1 citing·38 second hop
A novel hybrid model based on Hodrick–Prescott filter and support vector regression algorithm for optimizing stock market price prediction (2017)A novel hybrid model based on Hodrick–Pre…Introduction to Time Series and Forecasting (2016)Introduction to Time Series a…A survey on forecasting of time series data (2016)A survey on forecasting of ti…The Econometrics of the Hodrick-Prescott Filter (2015)The Econometrics of the Hodri…Predicting stock market price using support vector regression (2013)Predicting stock market price…Cycle Extraction: A Comparison of the Phase-Average Trend Method, the Hodrick-Prescott and Christiano-Fitzgerald Filters (2011)Cycle Extraction: A Compariso…Financial time series forecasting with machine learning techniques: A survey (2010)Financial time series forecas…Forecasting Gold Prices Using Multiple Linear Regression Method (2009)Forecasting Gold Prices Using…Financial time series forecasting using independent component analysis and support vector regression (2009)Financial time series forecas…Evolving and clustering fuzzy decision tree for financial time series data forecasting (2008)Evolving and clustering fuzzy…Analysis of Financial Time Series (2005)Analysis of Financial Time Se…Financial time series forecasting using support vector machines (2003)Financial time series forecas…Introduction to Time Series and Forecasting (2002)Introduction to Time Series a…The Band Pass Filter (1999)The Band Pass FilterMeasuring Business Cycles: Approximate Band-Pass Filters for Economic Time Series (1999)Measuring Business Cycles: Ap…Postwar U.S. Business Cycles: An Empirical Investigation (1997)Postwar U.S. Business Cycles:…Measuring Business Cycles Approximate Band-Pass Filters for Economic Time Series (1995)Measuring Business Cycles App…Indonesian Stock Price Prediction including Covid19 Era Using Decision Tree Regression (2020)Indonesian Stock Price Predic…Application of neural networks to an emerging financial market: forecasting and trading the Taiwan Stock Index (2002)Forecasting stock market movement direction with support vector machine (2004)A deep learning based stock trading model with 2-D CNN trend detection (2017)Application of deep reinforcement learning in stock trading strategies and stock forecasting (2019)A Comprehensive Survey on Portfolio Optimization, Stock Price and Trend Prediction Using Particle Swarm Optimization (2020)Forecasting with artificial neural networks: (1998)Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange (2010)Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques (2014)Stock market's price movement prediction with LSTM neural networks (2017)Time Series Analysis: Forecasting and Control (1977)Comparing Predictive Accuracy (1994)Stock price prediction using support vector regression on daily and up to the minute prices (2018)Optimizing LSTM for time series prediction in Indian stock market (2020)Machine learning techniques and data for stock market forecasting: A literature review (2022)The General Theory of Employment, Interest and Money, by John Maynard Keynes (1936)The General Theory of Employment, Interest and Money. (1936)Macroeconomics and Reality (1980)On Adjusting the Hodrick-Prescott Filter for the Frequency of Observations (2002)Measuring Uncertainty (2015)A Positive Theory of Monetary Policy in a Natural Rate Model (1983)Are Technology Improvements Contractionary? (2006)Fiscal Volatility Shocks and Economic Activity (2015)Distribution of the Estimators for Autoregressive Time Series with a Unit Root (1979)Generalized autoregressive conditional heteroskedasticity (1986)Co-Integration and Error Correction: Representation, Estimation, and Testing (1987)Analysis of Financial Time Series (2006)Cross‐validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure (2016)Financial time series forecasting model based on CEEMDAN and LSTM (2018)Heterogeneous Information Arrivals and Return Volatility Dynamics: Uncovering the Long‐Run in High Frequency Returns (1997)Chapter 14 Resuscitating real business cycles (1999)When it Rains, it Pours: Procyclical Capital Flows and Macroeconomic Policies (2004)THE EVOLUTION OF STOCK MARKET EFFICIENCY OVER TIME: A SURVEY OF THE EMPIRICAL LITERATURE (2010)Econophysics review: I. Empirical facts (2011)The impact of the Russian-Ukrainian war on global financial markets (2023)An Empirical Characterization of the Dynamic Effects of Changes in Government Spending and Taxes on Output (2002)A review on singular spectrum analysis for economic and financial time series (2010)SutteARIMA: Short-term forecasting method, a case: Covid-19 and stock market in Spain (2020)An Advanced CNN-LSTM Model for Cryptocurrency Forecasting (2021)
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82 cited
  • 2013Predicting stock market price using support vector regression74 cited
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    • 2020Indonesian Stock Price Prediction including Covid19 Era Using Decision Tree Regression40 cited