Certified Programme on "Algorithmic Trading & Computational Finance using Python & R"
Certified Programme on "Algorithmic Trading & Computational Finance using Python & R"
| TOTAL DURATION | COURSE FEES | COURSE TYPE |
|---|---|---|
| 100 Hours | 99,000 | Hybrid |
This course will provide exposure to application of Python for Algorithmic Trading and "R" for Computational Finance. Students will learn to develop Real-Time Strategies and create a trading engine that will be supported by advance data analytics. Python and R provides a quantitative edge in Advance Capital Markets - Our students will be a step ahead of competition
Program Highlights are as follows:
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Program conducted by faculty with extensive trading experience.
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100 Hours program to build Algorithmic Trading strategies with advanced data analytics.
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Ready to use Strategies & Template with back testing feature.
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Understand High Frequency Trading, AI & Machine Learning.
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Faculty with industry experience.
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Two months internship for top successful candidates.
Algorithmic Trading using Python
Technical Trading (Using Python):
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Basics of Technical Analysis : Chart Types, Chart Patterns, Gap Theory, Candle Pattern, Technical Indicators.
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Designing of Strategy Builder using Technical Indicators & Price Theory.
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Designing of Back-Testing platform to achieve strategy optimization.
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Real-time API Connectivity by handling Broadcast, OMS & RMS.
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Real-time API Connectivity by handling Broadcast, OMS & RMS.
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Comprehensive LIVE Strategy Engine.
Options Trading (Using Python):
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Basics of Options Trading : Option Payoffs, Black Scholes Calculator, Greeks Profile.
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Implementing Option Strategies in Live Market using Python.
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Designing Greeks Dashboard for hedging mechanism.
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Delta Neutral, Gamma Hedging & Volatility Trading using Live Simulators.
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Design Back-Testing platform for IV Trading, OI Analysis & Results Trading.
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Strategy based on Volatility Smile & Volatility Skew.
Grey Box & Black Box Trading (Using Python):
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Implementation of Scalping, Scaling, Advance Jobbing & Trend Jobbing in Live Market Environment.
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Triangular Arbitrage Strategies for Forex & Commodities.
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Mean Reverting Strategies like Pair Trading using Z score Model.
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Basket Strategy (Index-Index, Index-Stocks).
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Statistical Arbitrage Strategies.
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Pre & Post Result based Trading Strategies using Sentiment Indicators.
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Overview on High Frequency Trading.
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Overview on Artificial Intelligence and Machine Learning in Trading.
Computational Finance
Equity & Fixed Income Analytics (Using R):
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Fundamental Analysis using Ratio Calculations.
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Peer Group Comparison.
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Stock Selection Strategy based on Decision Trees.
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DCF Valuation and Sensitivity analysis.
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Bond Pricing along with duration and convexity.
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FX & Interest Rate Derivatives like Interest Rate Futures, Swaps, Currency Options.
Portfolio Analytics & Risk Management (Using R):
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Implementation of CAPM, APT & Fama French Model.
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Market Neutral Portfolio & Balanced Portfolio.
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Model Portfolio using Efficient Portfolio Theory.
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Risk Estimation – VAR, Beta, Covariance Matrices, Correlation.
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Historical VAR, Stress analysis, Monte Carlo Simulation.
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Credit Rating Matrix & Credit Risk Models.
NSE Academy & TRADING CAMPUS presents "Algorithmic Trading & Computational Finance using Python & R" - a certified course enabling students to understand practical implementation of Python and R for trading across various asset classes.
Eligibility: 12th + Graduation (Basic coding background/knowledge)
For further queries please call on: 7802078720 / 9619497907 / 9619497906 / 7045300842 / 9869934643
Updated on: 20/06/2019
