Our program offers hands-on training to give you the skills and experience you need to succeed in the field of python-based financial modeling. You'll learn how to write algorithms, create simulators, develop predictive engines, and backtest investment and risk models, trading strategies, and a lot more. With our comprehensive program, you'll gain the practical knowledge and experience necessary to become proficient in using python in the field of financial modeling.
You'll learn how to write algorithms and create simulators of financial investment and risk models, develop predictive engines, formulate and implement trading strategies, and a lot more. You'll also learn how to backtest financial investment and risk models to ensure their effectiveness.
But that's not all - this program will also help you develop the mindset of a programmer and the approach of an engineer. You'll learn how to think logically and systematically, and you'll gain a strong foundation in the principles of model building.
By the end of the program, you'll have the skills and knowledge needed to succeed as a professional in the field of financial modeling. The practical experience you'll gain through this program is essential for anyone who wants to become proficient in using python in the field of financial modeling.
Whether you're a finance professional looking to learn python programming or a programmer who wants to learn more about finance, this program will provide you with the knowledge and experience you need to succeed.
With a strong foundation in python-based financial modeling, you'll be well-equipped to take on challenging projects and make a positive impact in your field. Don't miss out on this exciting opportunity to advance your career in financial modeling. Sign up for our program today and start your journey toward professional success!
Module-01: Building Blocks – Quantitative & Computational Finance
Extract Company Information
Extract Historical & Intraday Data - Stocks | Indices
Extract Corporate Events - Dividends | Splits → Fetching Real-time Prices - Stocks | Indices | Cryptocurrencies
Computation of Historical Time-Series Market Shocks - Absolute | Proportional - Discrete | Continuous
Extract TimeSeries of Options for Multiple Strikes for Multiple Expiries & Prepare Options Chain
Generating Random Numbers to be used for Estimation Engines → Read & Export Excel Files
Dynamics of Extracting Data - Multiple Stocks | Multiple Indices | Multiple Options with Multiple Strikes & Expiries - Call Option | Put Option
Python Project: Building a Stock Screening and Ranking Tool
Module-02: Big Data Analytics
Libraries - Pandas - Data Series - Part 1 | 2 | DataFrames - Part 1 | 2 | 3 | Numpy - Part 1 | 2
Data Briefing & Data Control - Shape | Information | Describe | Datatypes
Data Cleaning - Handling #N/A | Handling 0 | Handling Missing Values
Data Manipulation - Creating | Sorting | Filtering | Merging | Splitting | Renaming | Relocating - Rows | Columns
Data Import/Export - Python from/to Excel
Data Indexing - Location | Index Location - Rows | Columns
Data Profiling & Pivoting Data - Values | Index | Columns → Data Visualization
Module-03: Statistical & Quantitative Techniques
Statistics Data Analysis - Mean - Arithmetic & Geometric | Median | Mode | Range | Variance | Absolute Deviation | Standard Deviation | Skewness | Kurtosis | Covariance | Correlation | Slope
Sampling | Sampling Distribution | Central Limit Theorem in Action
Probability Distribution [Probability Mass Function | Probability Density Function | Cumulative Distribution Function | Percent Point Function] - Uniform | Normal | Log-Normal | Binomial | Gamma | Exponential | Poisson | Bernoulli
Time Series Analysis | Regression Analysis - Auto-Regression | Simple & Multi Linear Regression
Simulation Methods & Stochastic Processes
Module-04: Investment Portfolio Construction & Optimization
Risk (Standard Deviation) & Return (Mean) Profile - Stocks | Portfolio | Benchmark
Variance-Covariance & Correlation Matrices
Portfolio Construction & Optimization using - Equal Weights | Random Weights | Passive Weights (Benchmark Index) | Simulated Weights | Optimizer Engine
Security Selection | Asset Allocation - Strategic | Tactical vs. Benchmark Index
Replicating Benchmark Index (Passive Fund) & Active-Passive Asset Allocation Mix
Optimal Portfolio - Weights | Quantities using Latest Prices & Unallocated Funds
Signals to Churn Existing Portfolio - Buy-Sell Quantities | Rebalancing Decision
Module-05: Investment Performance Monitoring & Evaluation
Beta - Individual Stock | Portfolio → Risk-Return Profile - Individual Stocks vs. Portfolio vs. Benchmark
Risk-Adjusted Return from Capital Asset Pricing Model (CAPM)
Active Risk (Tracking Error) and Active Return (Excess Return)
Performance - Sharpe Ratio | Sortino Ratio | Treynor Ratio | Information Ratio | Diversification Ratio | CAGR | Maximum Drawdown | Calmar Ratio
Optimal Portfolio vs. Replicated Benchmark Portfolio (Passive Fund)
Analytics - Individual Stocks | Optimal Portfolio | Benchmark Index
Module-06: Risk Measurement Models | Model Development & Validation
Value-at-Risk (VaR) Models - Historical Simulation Method | Monte-Carlo Simulation Method → Value-at-Risk (VaR) Models - Parametric Method
Downside Risk | Tail Risk | Conditional Value-at-Risk (CVaR | Expected Shortfall)
Stressed Value-at-Risk (SVaR), Incremental & Marginal Value-at-Risk (IVaR & MVaR)
Scenario Analysis | Stress Testing - Scenario Creation for Identified Shocks - Spot Shocks [Positive | Negative | Antithetic] - Equity, Rates, FX, Commodity | Volatility Shocks - Normal/Local | Log-Normal/ATM Implied | Full Revaluation Model | Scenario Profit & Loss | Risk - EQ, IR, FX, COM | Cross Risk
Model Validation through Backtesting | Traffic Light Approach | Breaches in Position Risk Flags/Limits
Module-07: Pricing & Valuation Models | Model Development & Validation
Interest-Rate Bonds, IR Swaps - Discounting Cash Flow Model → Equity Futures, Forwards, FRAs - Cost of Carry Model → Equity, Rates, FX Option Derivatives - Binomial Model (Single-Period | Two-Period | Multi-Period) - Risk-Neutralization Approach | Delta-Hedging Approach | Replicating Portfolio Approach | Black-Scholes-Merton Option Pricing Model | Monte-Carlo Simulation - Point Estimation | Path Estimation
Full Revaluation vs. Partial Revaluation - Taylor Series Expansion/Approximation | Ladder-Based Interpolation Technique → Testing Option's Price under Put-Call Parity Theorem
Model Validation - Challenging Assumptions - Distributional, Constant Volatility, Interest Rate | Model Inputs & Model Formula
Module-08: Option Greeks & Hedging Techniques
Risk Sensitivities - Duration | DV01 | Credit Spread CS01 | Delta | Gamma | Vega | Theta | Rho | Vanna | Volga
Impact on Price & Greeks due to - Moneyness | Volatility | Time-Decay [Incl. ITM | ATM | OTM]
Hedging Tool - Static Hedging | Dynamic Hedging | Rebalancing Portfolio & Frequency
Delta Hedging & Rebalancing to Remain Delta-Neutral → Gamma Hedging & Rebalancing to Remain Gamma-Neutral → Vega Hedging & Rebalancing to Remain Vega-Neutral → Delta-Gamma Hedging & Rebalancing to Remain Delta-Gamma-Neutral → Delta-Vega Hedging & Rebalancing to Remain Delta-Vega-Neutral
Module-09: Predictive & Volatility Engines | Modeling Interest Rates
Price Prediction Engines - Monte-Carlo Simulation | Long Short-Term Memory with Machine Learning Algorithms → Volatility Engines - Implied Volatility | Exponentially Weighted Moving Average | Generalized AutoRegressive Conditional Heteroskedasticity (1,1) → Normal & Log-Normal Volatilities
US Treasury Rates & Yield Curve - Spot Rates | Forward Rates | Zero Rates | Par Rates | Historical Time-Series of Interest Rates & Interest Rate Shocks - Absolute | Proportional - Discrete | Continuous |
Yield Curve Construction - Linear Interpolation & Extrapolation | Bootstrapping | OLS Method for Interest Rates Modeling - Linear | Polynomial - Quadratic | Cubic Spline Piecewise Segmentation | Quartic | Nelson-Siegel Model | Nelson-Siegel-Svensson Model
Module-10: Technical Indicators & Strategies
Relative Strength Index (RSI) | Simple Moving Average (SMA) | Exponential Moving Average (EMA) | Stochastic Oscillator | Bollinger Bands | Moving Average Convergence & Divergence (MACD)
Trading Strategy - Automating | Backtesting | Simulating Backtest Period
Identifying Best Entry & Exit Points under a Trading Strategy → Generating Market Signals & Trade Orders
Support & Resistance Level with Pivot Points - Cash Market | Option Market
Option Strategies - Long & Short Straddle | Long & Short Strangle
Open Interest & Change in Open Interest | Positional & Intraday Sentiments | Put-Call Ratio (PCR) using Option Chain - Stock | Index