Signal Processing for Business Applications

Unit 1

Introduction - Fourier Vs Wavelets - Seasonality filtering - Signal denoising - Identification of structural breaks – Scaling - Aggregate heterogeneity and time scales - Multiscale Cross Correlation. Review of linear filters – The EWMA and volatility estimation - The Hodrick – Prescott filter - Baxter – King filter - Filters in technical analysis of financial markets. Optimum linear estimation - Weiner filer - Recursive filtering and Kalman filter - Prediction with Kalmanfilter - Vector Kalman filter estimation - Applications.

Unit 2

Discrete Wavelet transforms – properties - DWT filters - The maximal overlap DWT - Multi resolution analysis – ANOVA - practical issues - Filtering FX intraday seasonalities - Causality and co-integration in economics - Money growth and inflation - Long memory processes -Fractional difference processes (FDP) - The DWT of FDP - Simulation of FDP - OLS estimation of FDP - Approximate Maximum likelihood estimation of FDP - Application to stock prices - Generalization of DWT and MODWT - Applications to money supply - Wavelets and seasonal long memory – Applications to money supply – GNP - Seasonality and trends - Unemployment - Consumer price index - Tourism revenues.

Unit 3

Market modes - Moving averages - Momentum functions - Hilbert transforms - Measuring cycle periods - Signal to noise ratio - Sine wave indicator - Instantaneous trend line - Identifying market modes - Designing profitable trading system - Transform arithmetic - FIR, IIR, Removing lag - Adaptive moving averages - Ehlers filters - Measuring market spectra - optimum predictive filters - Adapting standard indicators