Algorithmic Trading & Computational Finance using Python & R

Become a Successful Algo & Computational Finance Programmer:

  • Technical Trading (Using Python)
  • Options Trading (Using Python)
  • Grey Box & Black Box Trading (Using Python)
  • Equity & Fixed Income Analytics (Using R)
  • Portfolio Analytics & Risk Management (Using R)

Duration: 5 Months Weekend Course including 1 Month for Project
Next Batch Start Date:
Current Batch Date: 28th Aug 2020
Weekend Batch Time: Sat & Sun from 10am to 4pm

Practical: Each Student will get access to our proprietary Codes and setups, which has unique features like

Strategy Builder

BackTesting

Portfolio Analytics

Other facilities you have when you enroll into this course are :

  1. Separate forum for Algorithmic Trading & Computational Finance using Python & R, to post your doubts for immediate clarifications from other students or trainer
  2. Chatrooms, to discuss with your co-students in the course
  3. Priority chance to participate in events and trading contests across India

Course Curriculum

Technical Trading (Using Python):

  • Basics of Technical Analysis : Chart Types, Chart Patterns, Gap Theory, Candle Pattern, Technical Indicators.
  • Designing of Strategy Builder using Technical Indicators & Price Theory.
  • Designing of Back-Testing platform to achieve strategy optimization.
  • Real-time API Connectivity by handling Broadcast, OMS & RMS.
  • Real-time API Connectivity by handling Broadcast, OMS & RMS.
  • Comprehensive LIVE Strategy Engine.

Options Trading (Using Python):

  • Basics of Options Trading : Option Payoffs, Black Scholes Calculator, Greeks Profile.
  • Implementing Option Strategies in Live Market using Python.
  • Designing Greeks Dashboard for hedging mechanism
  • Delta Neutral, Gamma Hedging & Volatility Trading using Live Simulators.
  • Design Back-Testing platform for IV Trading, OI Analysis & Results Trading.
  • Strategy based on Volatility Smile & Volatility Skew.

Grey Box & Black Box Trading (Using Python):

  • Implementation of Scalping, Scaling, Advance Jobbing & Trend Jobbing in Live Market Environment.
  • Triangular Arbitrage Strategies for Forex & Commodities.
  • Mean Reverting Strategies like Pair Trading using Z score Model.
  • Basket Strategy (Index-Index, Index-Stocks).
  • Statistical Arbitrage Strategies.
  • Pre & Post Result based Trading Strategies using Sentiment Indicators.
  • Overview on High Frequency Trading.
  • Overview on Artificial Intelligence and Machine Learning in Trading.

Computational Finance

Equity & Fixed Income Analytics (Using R):

  • Fundamental Analysis using Ratio Calculations
  • Peer Group Comparison.
  • Stock Selection Strategy based on Decision Trees.
  • DCF Valuation and Sensitivity analysis.
  • Bond Pricing along with duration and convexity.
  • BFX & Interest Rate Derivatives like Interest Rate Futures, Swaps, Currency Options.

Portfolio Analytics & Risk Management (Using R):

  • Pair Trading
  • Long Short Equity
  • Bank Nifty Vs Nifty
  • Long Short Commodity

3 Leg Strategies

  • Implementation of CAPM, APT & Fama French Model.
  • Market Neutral Portfolio & Balanced Portfolio.
  • Model Portfolio using Efficient Portfolio Theory.
  • Risk Estimation – VAR, Beta, Covariance Matrices, Correlation.
  • Historical VAR, Stress analysis, Monte Carlo Simulation.
  • Credit Rating Matrix & Credit Risk Models.

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