A Python-Based Financial Modeling Program
Ultimate Python for Finance [No Prior Experience Required] | Intermediate | Advanced
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.
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PYTHON-BASED MODELS
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Master the Most Sought-After Skills in Finance and Advance Your Career
Are you ready to become a professional in the field of financial modeling? Our program is here to help you achieve your goals! Through hands-on experience, you'll learn how to build financial models that are used in finance and other industries.
You'll learn how to write algorithms and create simulators fo 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!
Premium Subscription
Ultimate Python for Finance
reach out to us at contact@thefinanalytics.com
INR 25,000
USD 320
Inclusions
Welcome to Python Basics
INR 5,000
The Financial Book
INR 100
Ace Your Python Programming Interview
INR 100
Financial Derivatives Interview Handbook
INR 100
Mastering Market Risk: An Interview Prep Guide
INR 100
CV/Resume, Interviews, and Placement
Includes Welcome to Python Basics [ 30+ hours ] training program, plus . . .
6-months [ 100+ hours ] training program.
Get hands-on experience on real-world projects [ 25+ projects ] and team collaboration.
Q&A support incl. python model assistance.
Online instructor-led weekend live batch + recorded sessions available as fallback option.
Access to financial books, interview guides, CV/resume preparation, reference materials through SharePoint.
Restrictions: No access to excel and python scripts, 12 months access to resources, and 250 hours watch time.
Life time access to participate in live sessions at no extra cost.
Our Expert-Led Resources For Your Journey
Unleash your full potential with expert-led resources that focus on practical understanding by taking advantage of our step-by-step self-paced materials to learn and practice at your own pace.
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Notifications
Your Ultimate Roadmap for Python Basics
It's about setting up your development environment. You'll familiarize yourself with Anaconda Navigator and Jupyter..
Expected: 29th Sept. 2023
Test Your Skills | Batch 3.7 & 3.8
Challenge Yourself: Prove Your Python Programming Skills with Our 25-Question Assessment
Results: Available
Test Your Skills | Batch 3.7 & 3.8
Push Your Limits: Prove Your Python Programming Skills with Our 15-Question Assessment
Submission Date: 17th March 2023
Program Coverage Curated By Experienced Mentors
We're focused on delivering practical skills to finance & risk professionals with an in-depth understanding & implementation using python. We never stop adding more content to it.
Introduction to Python Platforms and Programming
→ Everything You Need To Get Started On Your Machine | Installation Process | Integrated Development Environment vs. Code Editor vs. Compiler Learnings | Python Libraries & Packages | Recommendations
→ Open-Source Web-Based Interactive Computing Platform Launching Application | Default Directories | Creating a New Jupyter Notebook | Menu Options & Toolbar | Keyboard Shortcuts | Code Cell
→ Python DataTypes - String | Integer | Float | Boolean | Functions - Print | Type | Python Comments
→ Python Concepts - Variables | Functions - Type | Casting Functions - Str | Int | Float | Rule of Indentation
→ Creating Variables | Concatenation of String DataType | Tagging Print Content | Modifying Variables using Python Built-In Methods - Upper, Lower, Replace
Python Data Structures
→ Operators - Arithmetic | Assignment | Logical | Comparison
→ Creating Python List | List of Multiple Lists | Indexing Python List → Methods - Append | Insert | Extend | Remove | Reverse | Sort → Creating Python Tuple | Tuple of Multiple Tuples | List of Multiple Tuples | Indexing Python Tuple | Functions - Type | Length | Casting Functions - List | Tuple | Methods - Count | Index → Python Set - Creating | List of Multiple Sets | Tuple of Multiple Sets | Functions - List | Set | Methods - Add | Union | Intersection | Difference
→ Key-Value Pair Concept | Python Dictionary - Static DataTypes I Sequential DataTypes | Nested Dictionary | Methods - Items | Keys | Values | Clear Dictionary
Python Statements and Dynamics
→ Performing Operations - Comparison Operators | Logical Operators | Python Statements - IF Statement - Static & Sequential DataTypes | IF-ELSE Statement | IF-ELIF Statement | IF-ELIF-ELSE Statement | Nested Statements - Nested IF Statement | Nested IF-ELSE Statement | Nested IF-ELIF-ELSE Statement
→ FOR LOOP Statement | WHILE LOOP Statement | Conditional Loop Statements | Range Function | Break Statement | Comprehension - List | Set | All Possible Combinations
→ Input Function | TRY-EXCEPT Statements | TRY-EXCEPT-FINALLY Statements | Nested TRY-EXCEPT Statements | Python Exceptions/Errors - ZeroDivisionError | ValueError
Python Functions and Methods | Object-Oriented Programming
→ Python Class | Functions | Methods | Parameters/Arguments | Attributes/Variables | Return Statement → Global vs. Local Variable → Class - Functions & Methods | Constructors & Objects | OOP Concepts - Inheritance | Encapsulation | Polymorphism | Abstraction
→ Bank Account System: An Object-Oriented Finance Project | New Account Creation | Deposit Funds | Withdraw Funds | Transfer Funds Between Accounts | Update & Print Balance on Screen
Data Analysis with Python Libraries
→ Introduction to Pandas Library | Installation | Import | Pandas Data Structures - Data Series | DataFrames Methods - Describe | Append | Drop Duplicates | Difference | Fill NaN | Head | Tail Data | Filter - Single Condition → Pandas Data Structures - DataFrames | Dynamics of Creating DataFrames - Single Column | Multiple Columns | Indexing - loc | iloc | Slicing DataFrame | View DataFrame → Import & Export Data | Data Summary | Data Cleaning and Operations – Selection, Sorting, Filtering | Data Aggregation and Analysis – GroupBy, Resample, PivotTable | Data Restructuring | Data Visualization
Building Blocks – Python for Finance
→ Extract Historical & Intraday Time-Series Data - Stocks - Single | Multiple → Absolute Returns/Shocks | Proportional/Relative Shocks - Discrete | Continuous | ShockType Use | Comparison → Treasury Yield Curve - Normal | Inverted | Humped/Flat | Historical Time-Series of Interest Rates | 2007-08 & 2022-23 Interest Rate Profiles | Market Sentiments → Option Derivatives - Definition | Bullish & Bearish Belief - Buyer & Seller | Long & Short Positions | Option Premium | Payoff & Profit Profile | Use Case → Extract Historical Time-Series Data - Multiple Options | Prepare Option Chain for Calls & Puts for Multiple Strike for Single & Multiple Expiries → Extract Historical Time-Series Data - Multiple FX Prices, Interest Rates, Commodities, and Cryptocurrencies | Extract Financial Statements - Balance Sheets, Income Statements, Cashflow Statements, and Analyst Reports
Data Visualization for Data Science
→ Installation of Data Visualization Libraries
→ Plotting Charts & Sub-Charts - Line | Histogram | Scatter | Pie | Bar | Box | Heatmaps | Conditional Formatting
→ Multiple SubPlots | Images | Three-Dimensional
→ Customizing Plots - Title | Axis Labels & Ticks | Data Labels | Legends | Resizing | Font Style | Font Color | Alpha | Line Style | Alignments | Colors | Styles | Markers
→ Handling Missing Data | Performing Calculations | Reassigning Values | Adding Annotations
→ Highlighting Data Points/Results & Labels | Plotting Time-Series Data | Continuous & Categorical Data
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
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
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
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
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
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
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
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