𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Quantile smoothing in financial time series

✍ Scribed by Klaus Abberger


Publisher
Springer-Verlag
Year
1997
Tongue
English
Weight
619 KB
Volume
38
Category
Article
ISSN
0932-5026

No coin nor oath required. For personal study only.


πŸ“œ SIMILAR VOLUMES


Time-dependent Hurst exponent in financi
✍ A. Carbone; G. Castelli; H.E. Stanley πŸ“‚ Article πŸ“… 2004 πŸ› Elsevier Science 🌐 English βš– 211 KB

We calculate the Hurst exponent HðtÞ of several time series by dynamical implementation of a recently proposed scaling technique: the detrending moving average (DMA). In order to assess the accuracy of the technique, we calculate the exponent HðtÞ for artificial series, simulating monofractal Browni

Neural Network Smoothing in Correlated T
✍ F. Badran; S. Thiria πŸ“‚ Article πŸ“… 1997 πŸ› Elsevier Science 🌐 English βš– 330 KB

We present in this paper a neural network (NN) smoothing architecture for non-parametric estimation of the trend of a time series, observed at constant regular time intervals. The NN-smoother computes the trend in the state domain and minimizes a cost function with a regularization term. The regular

Trend estimation of financial time serie
✍ VΓ­ctor M. Guerrero; Adriana Galicia-VΓ‘zquez πŸ“‚ Article πŸ“… 2009 πŸ› John Wiley and Sons 🌐 English βš– 245 KB πŸ‘ 1 views

## Abstract We propose to decompose a financial time series into trend plus noise by means of the exponential smoothing filter. This filter produces statistically efficient estimates of the trend that can be calculated by a straightforward application of the Kalman filter. It can also be interprete

Hausdorff clustering of financial time s
✍ Nicolas Basalto; Roberto Bellotti; Francesco De Carlo; Paolo Facchi; Ester Panta πŸ“‚ Article πŸ“… 2007 πŸ› Elsevier Science 🌐 English βš– 999 KB