How to Create, Backtest & Deploy Options Strategies on AlgoTest | Complete Beginner Guide

In this complete beginner tutorial, we explain how to create, backtest, forward test, and live deploy options trading strategies using AlgoTest.

This video is specially made for new AlgoTest users who want to understand how to use the platform’s powerful features to build rule-based intraday, BTST, and positional strategies without coding.

🔹 What you’ll learn in this video:

✔️ How to create an options strategy on AlgoTest
✔️ Selecting instruments like Nifty, Bank Nifty, stocks, F&O, and crypto
✔️ Intraday, BTST, and positional strategy setup
✔️ Time-based and rule-based entries explained
✔️ Strike selection methods: ATM, ITM, OTM, premium range & closest premium
✔️ Momentum-based entries (simple & overall momentum)
✔️ Range breakout entry logic
✔️ Multi-leg strategies like straddles
✔️ Target, stop loss, trailing SL & exit conditions
✔️ Advanced re-entry logic: Re-accept, Re-momentum, Re-cost & Lazy Leg
✔️ How to analyze backtest performance properly
✔️ Difference between backtest, forward test & live deployment
✔️ Paper trading (Forward Test) on AlgoTest
✔️ How to integrate your broker and deploy strategy live
✔️ Execution settings: MIS, Normal, Market & Limit orders

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📌 Chapters

00:00 – Intro & Video Overview
02:00 – AlgoTest Dashboard Tour
04:00 – Creating a New Strategy
07:00 – Entry Types Explained
10:00 – Strike Selection Methods
13:00 – Rule-Based Trading Logic
17:00 – Exit, SL & Re-Entry
22:00 – Backtest & Forward Test
26:00 – Live Deployment Setup

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Disclaimer:
This video was created by AlgoTest for the sole purpose of education and demonstration of the AlgoTest futures and options backtesting platform as well as the live/paper deployment service that it provides. This is NOT financial advice and is also NOT a strategy recommendation. Please do your own backtesting, research and thorough due diligence before investing or trading in the stock market.
Options are leveraged financial instruments and can lead to financial loss of varying levels if trading is attempted without the requisite knowledge, research and/or experience. AlgoTest will not be responsible for the aforementioned loss or profit that is gained by the use of its platform.
Past performance does NOT guarantee of future results. For more information, visit algotest.in