An Introduction to Wavelets and Other Filtering Methods in Finance and EconomicsAn Introduction to Wavelets and Other Filtering Methods in Finance and Economics presents a unified view of filtering techniques with a special focus on wavelet analysis in finance and economics. It emphasizes the methods and explanations of the theory that underlies them. It also concentrates on exactly what wavelet analysis (and filtering methods in general) can reveal about a time series. It offers testing issues which can be performed with wavelets in conjunction with the multiresolution analysis. The descriptive focus of the book avoids proofs and provides easy access to a wide spectrum of parametric and nonparametric filtering methods. Examples and empirical applications will show readers the capabilities, advantages, and disadvantages of each method.

Dentro del libro
Resultados 15 de 42
Página 11
As the wavelet scale increases (from bottom to top in the figure), ... This is to be expected since each increase in the scale captures lower and lower ...
As the wavelet scale increases (from bottom to top in the figure), ... This is to be expected since each increase in the scale captures lower and lower ...
Página 24
Coefficients of a simple moving average may increase and then decrease with increasing lags. A special case in economics is known as Almon lag (Almon, ...
Coefficients of a simple moving average may increase and then decrease with increasing lags. A special case in economics is known as Almon lag (Almon, ...
Página 25
(d) The value of the coefficients increases first, then decreases with increasing lags. Therefore, the corresponding moving average is 1 y = 05:(0.10, ...
(d) The value of the coefficients increases first, then decreases with increasing lags. Therefore, the corresponding moving average is 1 y = 05:(0.10, ...
Página 38
... gain is zero at zero frequency (f = 0) and increases with increasing f, reaching its maximum at frequency f = 1/2. Therefore, it is a highpass filter.
... gain is zero at zero frequency (f = 0) and increases with increasing f, reaching its maximum at frequency f = 1/2. Therefore, it is a highpass filter.
Página 40
If the exchange rate declines, the firm would register a loss, whereas an increase in the exchange rate is favorable. The standard deviation of the return ...
If the exchange rate declines, the firm would register a loss, whereas an increase in the exchange rate is favorable. The standard deviation of the return ...
Comentarios de la gente  Escribir un comentario
No encontramos ningún comentario en los lugares habituales.
Contenido
1  
15  
51  
CHAPTER 4 DISCRETE WAVELET TRANSFORMS  96 
CHAPTER 5 WAVELETS AND STATIONARY PROCESSES  161 
CHAPTER 6 WAVELET DENOISING  202 
CHAPTER 7 WAVELETS FOR VARIANCECOVARIANCE ESTIMATION  235 
CHAPTER 8 ARTIFICIAL NEURAL NETWORKS  272 
NOTATIONS  315 
BIBLIOGRAPHY  323 
INDEX  349 
Otras ediciones  Ver todas
An Introduction to Wavelets and Other Filtering Methods in Finance and Economics Ramazan Gençay,Faruk Selçuk,Brandon Whitcher Sin vista previa disponible  2002 
Términos y frases comunes
analysis applied approximate associated assumed basis beta calculated components computed correlation covariance cycle decomposition defined determined difference discrete distribution dynamics Equation error estimator example feedforward network Figure Fourier transform frequency function gain function Gaussian given Haar hidden units increases indicate input interval Kalman filter known lags length linear matrix mean method MODWT moving average network model neural network noise observations obtained original output parameter performance period phase plotted points prediction presented procedure produce properties random recurrent respectively response returns rule sample scale seasonal sequence shift shows signal simple simulation smooth spectral spectrum squared standard stationary statistical studied term thresholding values variables variance vector volatility wavelet coefficients wavelet details wavelet filter wavelet scale wavelet transform wavelet variance weights zero