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Wavelet Neural Network Model for Yield Spread Forecasting

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/(sici)1099-131x(200004)19:3<201::aid-for753>3.0.co;2-4openalex-snapshot
Neural network versus econometric models in forecasting inflation
inferredcites →https://doi.org/10.1002/for.2270openalex-snapshot
A Neuro‐wavelet Model for the Short‐Term Forecasting of High‐Frequency Time Series of Stock Returns
inferredcites →https://doi.org/10.1007/978-0-8176-8418-1openalex-snapshot
Wavelet Transforms and Their Applications
inferredcites →https://doi.org/10.1007/s00181-013-0705-6openalex-snapshot
The predictive power of yield spread: evidence from wavelet analysis
inferredcites →https://doi.org/10.1016/0304-405x(88)90073-6openalex-snapshot
The real term structure and consumption growth
inferredcites →https://doi.org/10.1016/b978-0-12-279670-8.x5000-9openalex-snapshot
An Introduction to Wavelets and Other Filtering Methods in Finance and Economics
inferredcites →https://doi.org/10.1016/b978-012279670-8.50004-5openalex-snapshot
INTRODUCTION
inferredcites →https://doi.org/10.1016/j.econlet.2007.05.026openalex-snapshot
Forecasting with the yield curve; level, slope, and output 1875–1997
inferredcites →https://doi.org/10.1016/j.ememar.2010.03.001openalex-snapshot
The predictive power of the yield spread in timing the stock market
inferredcites →https://doi.org/10.1016/j.eswa.2008.08.073openalex-snapshot
An analysis of the yield spread as a predictor of inflation in Brazil: Evidence from a wavelets approach
inferredcites →https://doi.org/10.1016/j.eswa.2010.02.086openalex-snapshot
Forecasting industrial production in Brazil: Evidence from a wavelet approach
inferredcites →https://doi.org/10.1016/j.ijforecast.2016.08.001openalex-snapshot
Forecasting the Brazilian yield curve using forward-looking variables
inferredcites →https://doi.org/10.1016/j.japwor.2004.01.003openalex-snapshot
The term structure of interest rates in Japan: the predictability of economic activity
inferredcites →https://doi.org/10.1016/j.jeconom.2005.01.032openalex-snapshot
What does the yield curve tell us about GDP growth?
inferredcites →https://doi.org/10.1016/j.physa.2005.12.048openalex-snapshot
The reaction of stock markets to crashes and events: A comparison study between emerging and mature markets using wavelet transforms
inferredcites →https://doi.org/10.1016/j.physa.2008.01.063openalex-snapshot
Using wavelets to decompose the time–frequency effects of monetary policy
inferredcites →https://doi.org/10.1016/s0014-2921(96)00050-5openalex-snapshot
The predictive power of the term structure of interest rates in Europe and the United States: Implications for the European Central Bank
inferredcites →https://doi.org/10.1016/s0148-6195(97)00012-xopenalex-snapshot
The effect of economic regimes on the relation between term structure and real activity in Japan
inferredcites →https://doi.org/10.1016/s0167-9236(03)00092-7openalex-snapshot
On neuro-wavelet modeling
inferredcites →https://doi.org/10.1016/s0169-2070(00)00063-7openalex-snapshot
Neural network forecasting of Canadian GDP growth
inferredcites →https://doi.org/10.1016/s0169-2070(97)00044-7openalex-snapshot
Forecasting with artificial neural networks:
inferredcites →https://doi.org/10.1016/s0264-9993(03)00042-7openalex-snapshot
Why did the term structure of interest rates lose its predictive power?
inferredcites →https://doi.org/10.1016/s1059-0560(03)00014-5openalex-snapshot
Inflation changes, yield spreads, and threshold effects
inferredcites →https://doi.org/10.1017/cbo9780511841040openalex-snapshot
Wavelet Methods for Time SeriesAnalysis
inferredcites →https://doi.org/10.1086/654119openalex-snapshot
New Indexes of Coincident and Leading Economic Indicators
inferredcites →https://doi.org/10.1090/s0002-9947-1989-1008470-5openalex-snapshot
Multiresolution approximations and wavelet orthonormal bases of 𝐿²(𝑅)
inferredcites →https://doi.org/10.1093/oso/9780198538493.001.0001openalex-snapshot
Neural Networks for Pattern Recognition
inferredcites →https://doi.org/10.1109/34.192463openalex-snapshot
A theory for multiresolution signal decomposition: the wavelet representation
inferredcites →https://doi.org/10.1109/72.165591openalex-snapshot
Wavelet networks
inferredcites →https://doi.org/10.1111/j.1540-6261.1991.tb02674.xopenalex-snapshot
The Term Structure as a Predictor of Real Economic Activity
inferredcites →https://doi.org/10.1142/s0219691303000153openalex-snapshot
Prediction Based on a Multiscale Decomposition
inferredcites →https://doi.org/10.1155/2015/308567openalex-snapshot
In Search of Leading Indicator Property of Yield Spread for India: An Approach Based on Quantile and Wavelet Regression
inferredcites →https://doi.org/10.1257/jel.41.3.788openalex-snapshot
Forecasting Output and Inflation: The Role of Asset Prices
inferredcites →https://doi.org/10.20955/r.91.419-440openalex-snapshot
Can the Term Spread Predict Output Growth and Recessions? A Survey of the Literature
inferredcites →https://doi.org/10.2139/ssrn.879636openalex-snapshot
Yield Spread as a Leading Indicator of Real Economic Activity: An Empirical Exercise on the Indian Economy
inferredcites →https://doi.org/10.5860/choice.31-5500openalex-snapshot
Neural networks for pattern recognition
inferredcites →https://doi.org/10.5860/choice.38-4508openalex-snapshot
Wavelet methods for time series analysis

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-030-80129-8_21openalex-snapshot
Wavelet Neural Network Model with Time-Frequency Analysis for Accurate Share Prices Prediction
inferred← citeshttps://doi.org/10.1007/978-981-99-7633-1_2openalex-snapshot
Predicting Holding Days for Equity Gain Using Wavelets
inferred← citeshttps://doi.org/10.1016/j.asoc.2023.110172openalex-snapshot
Veg-W2TCN: A parallel hybrid forecasting framework for non-stationary time series using wavelet and temporal convolution network model
inferred← citeshttps://doi.org/10.1038/s41598-022-09905-3openalex-snapshot
A novel wavelet decomposition and transformation convolutional neural network with data augmentation for breast cancer detection using digital mammogram
inferred← citeshttps://doi.org/10.2139/ssrn.5288324openalex-snapshot
Deep Impulse Response Functions for Macroeconomic Dynamics: A Hybrid LSTM-Wavelet Approach Compared to an ANN-Wavelet and VECM Models
inferred← citeshttps://doi.org/10.3233/jifs-189897openalex-snapshot
Analysis of GDP based on polynomial regression and BP neural network
inferred← citeshttps://doi.org/10.3390/math7050480openalex-snapshot
Coordinating Supply-Chain Management under Stochastic Fuzzy Environment and Lead-Time Reduction
inferred← citeshttps://doi.org/10.3390/math7111133openalex-snapshot
Discrete Mutation Hopfield Neural Network in Propositional Satisfiability
inferred← citeshttps://doi.org/10.3390/math9050522openalex-snapshot
Local Convergence of the Continuous and Semi-Discrete Wavelet Transform in Lp(R)
inferred← citeshttps://doi.org/10.3390/math9233041openalex-snapshot
A High-Resolution Dyadic Transform for Non-Stationary Signal Analysis
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