SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Do artificial neural networks provide improved volatility forecasts: Evidence from Asian markets
16 references·0 citing·31 second hop
Do artificial neural networks provide improved volatility forecasts: Evidence from Asian markets (2023)Do artificial neural networks provide imp…Stock price prediction using LSTM, RNN and CNN-sliding window model (2017)Stock price prediction using …Stock market's price movement prediction with LSTM neural networks (2017)Stock market's price movement…Deep Learning for Finance: Deep Portfolios (2016)Deep Learning for Finance: De…Volatility forecast comparison using imperfect volatility proxies (2010)Volatility forecast compariso…A forecast comparison of volatility models: does anything beat a GARCH(1,1)? (2005)A forecast comparison of vola…CAViaR (2004)CAViaRTime series forecasting using a hybrid ARIMA and neural network model (2003)Time series forecasting using…Nonlinear Time Series Models in Empirical Finance (2000)Nonlinear Time Series Models …Coherent Measures of Risk (1999)Coherent Measures of RiskForecasting with artificial neural networks: (1998)Forecasting with artificial n…Evaluating Interval Forecasts (1998)Evaluating Interval ForecastsAnswering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts (1998)Answering the Skeptics: Yes, …Techniques for Verifying the Accuracy of Risk Measurement Models (1995)Techniques for Verifying the …Conditional Heteroskedasticity in Asset Returns: A New Approach (1991)Conditional Heteroskedasticit…Generalized autoregressive conditional heteroskedasticity (1986)Generalized autoregressive co…Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Autoregressive Conditional He…Book Review: Time Series Analysis: Forecasting and Control (1977)The accuracy of extrapolation (time series) methods: Results of a forecasting competition (1982)Financial time series forecasting using support vector machines (2003)DeepAR: Probabilistic forecasting with autoregressive recurrent networks (2019)Comparing Predictive Accuracy (1994)Strictly Proper Scoring Rules, Prediction, and Estimation (2007)CoVaR (2016)ARCH modeling in finance (1992)On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks (1993)By Force of Habit: A Consumption‐Based Explanation of Aggregate Stock Market Behavior (1999)Time Series Analysis: Forecasting and Control (1977)Multivariate Simultaneous Generalized ARCH (1995)An Overview of Value at Risk (1997)Modelling Extremal Events (1997)Conditional value-at-risk for general loss distributions (2002)Modeling and Forecasting Realized Volatility (2003)Theory of rational option pricing (2005)Lectures on Stochastic Programming (2009)The Behavior of Stock-Market Prices (1965)The Cross‐Section of Volatility and Expected Returns (2006)Introductory Econometrics for Finance (2008)Why Does Stock Market Volatility Change Over Time? (1989)Measuring and Testing the Impact of News on Volatility (1993)Measuring and Testing the Impact of News on Volatility (1993)Dynamic Conditional Correlation (2002)Econometric Analysis of Cross Section and Panel Data (2001)Global financial crisis, extreme interdependences, and contagion effects: The role of economic structure? (2010)Systemic Risk Measurement: Multivariate GARCH Estimation of CoVaR (2012)A hybrid ARIMA and support vector machines model in stock price forecasting (2004)A novel hybridization of artificial neural networks and ARIMA models for time series forecasting (2010)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)
this work references cited by second hop

References

  • 1986Generalized autoregressive conditional heteroskedasticity23,378 cited
  • 1982Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation21,185 cited
  • 1991Conditional Heteroskedasticity in Asset Returns: A New Approach10,394 cited
  • 1999Coherent Measures of Risk8,849 cited
  • 2003Time series forecasting using a hybrid ARIMA and neural network model4,583 cited
  • 1998Forecasting with artificial neural networks:4,282 cited
  • 1998Answering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts3,380 cited
  • 1998Evaluating Interval Forecasts2,689 cited
  • 1995Techniques for Verifying the Accuracy of Risk Measurement Models2,489 cited
  • 2004CAViaR2,210 cited
  • 2005A forecast comparison of volatility models: does anything beat a GARCH(1,1)?1,878 cited
  • 2010Volatility forecast comparison using imperfect volatility proxies1,348 cited
  • 2017Stock price prediction using LSTM, RNN and CNN-sliding window model1,134 cited
  • 2000Nonlinear Time Series Models in Empirical Finance1,111 cited
  • 2017Stock market's price movement prediction with LSTM neural networks986 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

  • 2016Deep Learning for Finance: Deep Portfolios954 cited
  • Cited by

    No citing works inside the corpus for this window.