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Course Detail

Course Name Signal Processing for Business Applications
Course Code 19CCE338
Program B. Tech. in Computer and Communication Engineering
Year Taught 2019


Unit 1

Structure of financial markets-financial instruments-stock price models-asset returns-modern portfolio theorycapital asset pricing model-relative value and factor models -Trading terminology-long and short positions-cost of trading – backtesting-pairs trading and mean reversion-statistical arbitrage-trend following- trending in multiple frequencies.

Unit 2

Measuring business cycles- The Hodrick – Prescott filter – Baxter– King filter – Technical Analysis – Indicators –Oscillators- Signal to noise ratio – Sine wave indicator – Instantaneous trend line – Identifying market modes– Transform arithmetic – FIR – IIR – Removing lag – Adaptive moving averages – Ehlers filters.

Unit 3

Measuring market spectra – optimum predictive filters – Adapting standard indicators- High frequency tradingDesigning profitable trading system.


  • Ali N. Akansu and Mustafa Torun, “A Primer for Financial Engineering: Financial Signal Processing and Electronic Trading”, Academic Press, 2015.
  • RamazanGencay, FarukSelcuk& Brandon Whitdly, “An Introduction to Wavelets and other filtering methods in Finance and Economics”, Academic Press, 2002.


  • John F Ehlers, “Rocket Science for Traders: Digital Signal Processing Applications”, John Wiley 2001.
  • Jack Clark Francis, Richard W. Taylor, “Investments, Schaum’s Outlines”, Tata McGraw Hill, 2006.

Evaluation Pattern

Assessment Internal External
Periodical 1 (P1) 15
Periodical 2 (P2) 15
*Continuous Assessment (CA) 20
End Semester 50
*CA – Can be Quizzes, Assignment, Projects, and Reports.

Objectives and Outcomes


  • To understand the functioning of financial markets and the behavior of financial time series
  • To provide an introduction to application of signal processing techniques for identifying and forecasting patterns in financial time series
  • To develop an understanding of the process for design of a profitable trading system

Course Outcomes

  • CO1: Able to understand the structure of financial markets and asset pricing, models
  • CO2: Able to analyze a financial time series and employ technical analysis to identify patterns in it
  • CO3: Able to employ filters for detection and analysis of business cycles
  • CO4: Able to design an adaptive filter based system for predicting financial time series

CO – PO Mapping

CO1 3 2 2 2
CO2 2 3 2 2
CO3 2 3 2 2 2
CO4 2 3 2 2 2

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