Course Overview

Backtesting Strategies (45h) হলো একটি Advanced & Practical Course, যেখানে historical market data ব্যবহার করে trading strategy-এর performance, reliability এবং robustness systematically evaluate করা শেখানো হবে।

এই course-এ Historical Data, Strategy Coding, Entry & Exit Rules, Transaction Costs, Slippage, Performance Metrics, Drawdown Analysis, Strategy Optimization, Out-of-Sample Testing, Walk-Forward Analysis এবং Monte Carlo Testing শেখানো হবে।

Practical Projects-এর মাধ্যমে learners realistic backtest তৈরি এবং strategy-এর performance ও robustness professionally analyse করার দক্ষতা অর্জন করবে।

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What You Will Learn

✔ Backtesting Fundamentals
✔ Historical Market Data
✔ OHLCV Data
✔ Data Cleaning
✔ Strategy Rules
✔ Entry & Exit Logic
✔ Signal Generation
✔ Position Management
✔ Portfolio Simulation
✔ Vectorized Backtesting
✔ Event-Based Backtesting Fundamentals
✔ Transaction Costs
✔ Brokerage Costs
✔ Slippage
✔ Market Impact Fundamentals
✔ Order Execution Assumptions
✔ P&L Calculation
✔ Equity Curve
✔ Drawdown Analysis
✔ Sharpe Ratio
✔ Sortino Ratio
✔ Calmar Ratio
✔ Win Rate
✔ Profit Factor
✔ Risk-Reward Ratio
✔ Look-Ahead Bias
✔ Survivorship Bias
✔ Data Leakage
✔ Data Snooping
✔ Overfitting
✔ Curve Fitting
✔ In-Sample Testing
✔ Out-of-Sample Testing
✔ Walk-Forward Testing
✔ Parameter Optimization
✔ Robustness Testing
✔ Monte Carlo Testing Fundamentals
✔ Stress Testing
✔ Strategy Comparison
✔ Portfolio Backtesting
✔ Risk Management
✔ Professional Backtest Reporting

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Course Curriculum

Module 1 — Introduction to Backtesting

• What is Backtesting?
• Why Backtesting Matters
• Backtesting vs Forward Testing
• Historical Simulation
• Systematic Strategy Evaluation
• Backtesting Workflow
• Advantages
• Limitations
• Common Backtesting Mistakes
• Realistic Expectations

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Module 2 — Trading Strategy Fundamentals

• What is a Trading Strategy?
• Trading Hypothesis
• Entry Rules
• Exit Rules
• Long Strategy
• Short Strategy
• Stop-Loss
• Take-Profit
• Position Sizing
• Strategy Parameters
• Strategy Documentation

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Module 3 — Market Data for Backtesting

• Historical Market Data
• OHLCV
• Daily Data
• Intraday Data
• Tick Data Fundamentals
• Timeframes
• Adjusted vs Unadjusted Prices
• Missing Data
• Duplicate Data
• Data Alignment
• Data Quality Checks

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Module 4 — Python Environment for Backtesting

• Python Setup
• NumPy
• Pandas
• DataFrames
• DateTime
• Functions
• Data Structures
• Financial Calculations
• Vectorized Operations
• Reusable Backtesting Functions

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Module 5 — Data Preparation

• Loading Historical Data
• Cleaning Data
• Handling Missing Values
• Sorting Time Series
• Resampling
• Adjusting Data
• Removing Duplicates
• Handling Corporate Actions Fundamentals
• Data Validation
• Preparing Backtest Dataset

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Module 6 — Return & Performance Calculations

• Simple Return
• Log Return
• Cumulative Return
• Daily P&L
• Trade P&L
• Portfolio Return
• Annualized Return
• Volatility
• Rolling Return
• Risk-Adjusted Return

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Module 7 — Building a Basic Backtesting Engine

• Backtesting Architecture
• Data Layer
• Signal Layer
• Position Layer
• Portfolio Layer
• P&L Layer
• Performance Layer
• Trade Log
• Equity Curve
• Basic Backtest Implementation

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Module 8 — Entry & Exit Logic

• Buy Signal
• Sell Signal
• Entry Price
• Exit Price
• Position Tracking
• Holding Period
• Multiple Trades
• Long Positions
• Short Positions Fundamentals
• Trade Execution Rules

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Module 9 — Technical Strategy Backtesting

• Moving Average Strategy
• EMA Strategy
• RSI Strategy
• MACD Strategy
• Bollinger Bands
• Breakout Strategy
• Trend Following
• Mean Reversion
• Momentum
• Strategy Comparison

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Module 10 — Portfolio Backtesting

• Single Asset Backtest
• Multi-Asset Backtest
• Portfolio Weights
• Asset Allocation
• Rebalancing
• Portfolio Return
• Portfolio Volatility
• Correlation
• Portfolio Drawdown
• Portfolio Performance

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Module 11 — Transaction Costs & Slippage

• Why Costs Matter
• Brokerage
• Commission
• Bid-Ask Spread
• Slippage
• Market Impact Fundamentals
• Fixed Transaction Cost
• Percentage-Based Cost
• Cost Modeling
• Net vs Gross Return

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Module 12 — Realistic Execution Modeling

• Market Orders
• Limit Orders
• Stop Orders
• Order Timing
• Execution Price
• Liquidity
• Partial Execution Fundamentals
• Delayed Execution
• Execution Assumptions
• Realistic Backtesting

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Module 13 — Performance Metrics

• Total Return
• Annualized Return
• CAGR
• Volatility
• Sharpe Ratio
• Sortino Ratio
• Calmar Ratio
• Win Rate
• Average Win
• Average Loss
• Profit Factor
• Expectancy
• Risk-Reward Ratio

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Module 14 — Drawdown & Risk Analysis

• What is Drawdown?
• Maximum Drawdown
• Average Drawdown
• Drawdown Duration
• Recovery Period
• Rolling Drawdown
• Risk of Ruin Fundamentals
• Portfolio Exposure
• Risk per Trade
• Strategy Risk Profile

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Module 15 — Equity Curve Analysis

• Building Equity Curve
• Cumulative P&L
• Equity Highs
• Drawdown Curve
• Performance Stability
• Monthly Returns
• Yearly Returns
• Return Distribution
• Performance Consistency

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Module 16 — Backtesting Biases

• Look-Ahead Bias
• Survivorship Bias
• Selection Bias
• Data Snooping
• Data Leakage
• Overfitting
• Curve Fitting
• Incorrect Benchmarking
• Unrealistic Assumptions
• Bias Detection

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Module 17 — Overfitting & Curve Fitting

• What is Overfitting?
• Model Complexity
• Too Many Parameters
• Historical Data Fitting
• In-Sample Performance
• Out-of-Sample Performance
• Parameter Stability
• Robust Strategy Design
• Avoiding Curve Fitting

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Module 18 — In-Sample & Out-of-Sample Testing

• Training Period
• Validation Period
• Testing Period
• Data Splitting
• In-Sample Optimization
• Out-of-Sample Evaluation
• Performance Comparison
• Model Validation
• Generalization

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Module 19 — Walk-Forward Testing

• What is Walk-Forward Testing?
• Rolling Window
• Expanding Window
• Training Period
• Testing Period
• Parameter Recalibration
• Walk-Forward Optimization
• Out-of-Sample Validation
• Strategy Stability

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Module 20 — Strategy Optimization

• What is Optimization?
• Strategy Parameters
• Parameter Search
• Grid Search
• Parameter Ranges
• Optimization Objectives
• Sharpe Optimization
• Drawdown Constraints
• Return Optimization
• Robust Parameter Selection

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Module 21 — Robustness Testing

• What is Robustness?
• Parameter Stability
• Different Time Periods
• Different Markets
• Different Timeframes
• Cost Sensitivity
• Slippage Sensitivity
• Execution Sensitivity
• Strategy Stability
• Robustness Checklist

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Module 22 — Monte Carlo Testing

• Monte Carlo Fundamentals
• Randomized Trade Sequences
• Resampling
• Return Simulation
• Drawdown Simulation
• Probability of Loss
• Risk Estimation
• Confidence Intervals
• Strategy Reliability

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Module 23 — Stress Testing

• Market Crash Scenarios
• High Volatility
• Low Liquidity
• Increased Transaction Costs
• Increased Slippage
• Large Drawdowns
• Extreme Market Conditions
• Strategy Stress Test
• Risk Interpretation

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Module 24 — Strategy Comparison

• Comparing Multiple Strategies
• Return Comparison
• Risk Comparison
• Sharpe Comparison
• Drawdown Comparison
• Win Rate Comparison
• Profit Factor Comparison
• Consistency
• Risk-Adjusted Performance
• Strategy Selection

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Module 25 — Professional Backtest Workflow

• Trading Idea
• Historical Data
• Data Cleaning
• Strategy Definition
• Coding
• Backtesting
• Cost Modeling
• Performance Analysis
• Bias Checking
• Optimization
• Out-of-Sample Testing
• Walk-Forward Testing
• Robustness Testing
• Final Backtest Report

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Practical Backtesting Projects

📊 Project 1 — Moving Average Strategy Backtest

একটি SMA/EMA strategy-এর জন্য complete backtest তৈরি করা হবে:

Historical Data → Indicator → Signal → Position → P&L → Equity Curve → Performance

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📈 Project 2 — RSI Strategy Backtest

RSI-based entry ও exit rules ব্যবহার করে strategy performance analyse করা হবে।

Analysis-এ থাকবে:

• Total Return
• Win Rate
• Drawdown
• Sharpe Ratio
• Profit Factor

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📉 Project 3 — Bollinger Band Mean Reversion

Bollinger Bands ব্যবহার করে একটি mean-reversion strategy backtest করা হবে এবং বিভিন্ন parameter-এর performance compare করা হবে।

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🚀 Project 4 — Momentum Strategy Backtest

Multiple assets-এর historical return ব্যবহার করে momentum strategy তৈরি ও backtest করা হবে।

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💼 Project 5 — Multi-Asset Portfolio Backtest

একাধিক asset নিয়ে portfolio backtest করা হবে এবং—

• Portfolio Return
• Volatility
• Correlation
• Drawdown
• Sharpe Ratio

analyse করা হবে।

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⚙️ Project 6 — Transaction Cost & Slippage Model

একটি profitable-looking strategy-তে বিভিন্ন brokerage, spread ও slippage assumptions যোগ করে Gross vs Net Performance compare করা হবে।

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🧪 Project 7 — In-Sample vs Out-of-Sample Test

Historical dataset split করে strategy-এর training/optimization এবং unseen data-এর performance compare করা হবে।

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🔄 Project 8 — Walk-Forward Backtest

Rolling training/testing windows ব্যবহার করে strategy-এর robustness evaluate করা হবে।

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🎯 Project 9 — Parameter Optimization

একটি strategy-এর multiple parameters test করে optimal এবং stable parameter range identify করার process শেখানো হবে।

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🎲 Project 10 — Monte Carlo Strategy Test

Historical trade results resample করে সম্ভাব্য future equity curves এবং drawdown scenarios simulate করা হবে।

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🏆 Final Project — Professional Strategy Validation

Course শেষে একটি complete backtesting & validation framework তৈরি করা হবে:

Strategy Idea → Data Preparation → Strategy Coding → Backtest → Transaction Costs → Slippage → Performance Metrics → Bias Check → Optimization → Out-of-Sample Test → Walk-Forward → Monte Carlo → Robustness Report

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Course Features

✅ 45 Hours Professional Training

✅ বাংলা + English Explanation

✅ Intermediate to Advanced Level

✅ Python-Based Backtesting

✅ Financial Market Data

✅ Data Cleaning

✅ Strategy Development

✅ Entry & Exit Logic

✅ Technical Strategy Backtesting

✅ Quantitative Strategy Backtesting

✅ Portfolio Backtesting

✅ Transaction Cost Modeling

✅ Slippage Modeling

✅ Realistic Execution

✅ Performance Metrics

✅ Sharpe Ratio

✅ Sortino Ratio

✅ Maximum Drawdown

✅ Profit Factor

✅ Equity Curve Analysis

✅ Backtesting Bias Detection

✅ Overfitting Prevention

✅ In-Sample Testing

✅ Out-of-Sample Testing

✅ Walk-Forward Testing

✅ Strategy Optimization

✅ Robustness Testing

✅ Monte Carlo Testing

✅ Stress Testing

✅ Strategy Comparison

✅ Practical Backtesting Projects

✅ Professional Strategy Validation Capstone

✅ Instructor Support

✅ Class Recording (যদি প্রযোজ্য হয়)

✅ Certificate of Completion (যদি প্রদান করা হয়)

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Who Can Join?

• Stock Market Traders
• Forex Traders
• Futures Traders
• Crypto Trading Learners
• Algorithmic Traders
• Quantitative Finance Learners
• Finance Students
• Financial Analysts
• Investment Analysts
• Quantitative Analysts
• Python Programmers
• Data Analysts
• Portfolio Analysts
• Risk Analysts
• FinTech Professionals
• যারা Trading Strategy test করতে চান
• যারা Algorithmic Trading শেখার পর strategy validation করতে চান

Basic Python এবং financial market knowledge recommended।

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After Completing This Course

এই course শেষ করার পর আপনি—

• Trading strategy-এর জন্য professional backtesting framework বুঝতে পারবেন।
• Historical market data prepare ও clean করতে পারবেন।
• Python ব্যবহার করে trading strategy backtest করতে পারবেন।
• Entry এবং exit logic implement করতে পারবেন।
• Single এবং multi-asset portfolio backtest করতে পারবেন।
• Brokerage, transaction costs এবং slippage model করতে পারবেন।
• Gross ও Net trading performance-এর difference analyse করতে পারবেন।
• Equity curve এবং drawdown analyse করতে পারবেন।
• Sharpe Ratio, Sortino Ratio, Calmar Ratio, Win Rate ও Profit Factor calculate করতে পারবেন।
• Look-ahead bias, survivorship bias, data leakage ও data snooping identify করতে পারবেন।
• Overfitting ও curve fitting-এর ঝুঁকি বুঝতে পারবেন।
• In-Sample এবং Out-of-Sample testing করতে পারবেন।
• Walk-Forward Analysis ব্যবহার করে strategy validate করতে পারবেন।
• Strategy parameters optimize ও compare করতে পারবেন।
• Different markets, timeframes ও cost assumptions-এর মাধ্যমে robustness test করতে পারবেন।
• Monte Carlo simulation ব্যবহার করে সম্ভাব্য risk ও drawdown scenarios analyse করতে পারবেন।
• Stress testing-এর মাধ্যমে extreme market conditions evaluate করতে পারবেন।
• Multiple trading strategies-এর risk-adjusted performance compare করতে পারবেন।
• একটি professional backtest report তৈরি করতে পারবেন।
• Live deployment-এর আগে strategy validation-এর জন্য systematic workflow তৈরি করতে পারবেন।