Intraday Strategy & algorithm Course

Intraday Strategy & algorithm Course

Course Modules:

Module 1: Introduction to Algo Trading

• What is algorithmic trading?
• Evolution of algo trading
• Manual vs automated trading
• Overview of the algo trading ecosystem

Module 2: Market Microstructure & Data

• Understanding market participants and order

types

• Bid-ask spread, slippage, and liquidity
• Types of data (tick, OHLCV, fundamental)
• Data providers and APIs

Module 3: Programming Basics for Traders

• Working with trading data
• Data visualization and preprocessing

Module 4: Strategy Design &Backtesting

• Strategy logic and hypothesis developent
• Risk-reward and position sizing
• Backtesting frameworks (Backtrader, VectorBT,

Zipline)

• Avoiding overfitting and lookahead bias

Module 5: Technical & Quantitative Strategies

* Moving average crossovers

* RSI/MACD/Volatility-based strategies

* Statistical arbitrage and mean reversion

* Machine learning basics for strategy development

* Moving average & adaptive moving average strategies

* Super trend strategies

* Know sure thing (KST) Strategies

* Directional trend index Strategies

* Gann swing strategies

* Elliott wave based strategies

* Fibonacci -Harmonic Patterns based strategies

* Open interest future-option strategies

* Intraday ticker window & tick Query strategy

* Price spike & volume spike strategy

* Morning 30 minute trade strategies

* 30 minute before closing strategies

* Gap up- gap down strategies

* Bollinger – band (HA-BB) intraday strategy

* ATR- MA- RSI Strategy

* ADX-DMI COMBO strategy

* Dynamic zone RSI With Bollinger Band strategy

* Alligator strategy

* Aroon indicator strategy

* Inside/Outside day trading strategy

* Dollar index correlation strategy

* Fake-out breakout day trading strategy

* Day trading patterns strategies

Module 6: Execution & Brokerage APIs

* Placing trades programmatically

* Broker API integration (Zerodha Kite, Interactive

Brokers, Alpaca, etc.

* Handling live order execution

* Paper trading and real-time simulation

Module 7: Risk Management & Optimization

* Portfolio allocation techniques

* Risk metrics: Sharpe, Sortino, Max Drawdown

* Stop-loss and trailing stop automation

* Drawdown control & capital preservation

Module 8: Live Deployment & Monitoring

* Running algos in real-time (VPS, cloud, local)

* Logging, error handling, and alerts

* Monitoring performance and debugging

* Scaling and automation tools (Docker, cron

jobs:

Module 9: Compliance, Ethics, and Regulations

* SEBI regulations (India-specific)

* Global algo trading rules

* Ethical concerns and transparency

FEE Structure: