COURSE SUMMARY
Course Title: 
Signal Processing for Business Applications
Course Code: 
15ECE379
Year Taught: 
2015
Type: 
Elective
Degree: 
Undergraduate (UG)
School: 
School of Engineering
Campus: 
Bengaluru
Chennai
Coimbatore
Amritapuri

'Signal Processing for Business Applications' is an elective course offered for the B. Tech. (Bachelor of Technology) in Electronics and Communication Engineering at School of Engineering, Amrita Vishwa Vidyapeetham.

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

TEXTBOOKS

  1. Ramazan Gencay, FarukSelcuk& Brandon Whitdly “An Introduction to Wavelets and other filtering methods in Finance and Economics,” Academic Press 2002
  2. John F Ehlers “Rocket Science for Traders: Digital Signal Processing Applications”, John Wiley 2001.

REFERENCES

  1. Jack Clark Francis, Richard W. Taylor, “Investments”, Schaum’s Outlines, Tata McGraw Hill, 2006