Module 4: Defining Entry, Exit, and Stop-Loss Strategies (Professional Level)
Name of Course- Module 4: Defining Entry, Exit, and Stop-Loss Strategies (Professional Level)
About Instructor-Mr Anupam Shukla (Certified Technical Analyst, F&O Strategist, Currency Derivative Strategist ,Research Analyst)
Duration of Course– Three Months+ 3 Months Mentorship (Live Market Trade selections & Trade testing -Simulated/Real TradingTesting ) (All five modules of Intraday Trading Expert (Alpha) Course)
Level-Advance
Prerequisite-Will to learn with discipline/Must Have completed Intraday Trading Expert Course by Trading Lab or Have Passed entrance Test With 80% Marks on Market Basics, through which one eligible to take direct admission in Intraday Trading Expert (Alpha)Course
Methodology-Offline/Online Classes/Concept Classes/Lab
Assessment-Worksheets
Course Material-Workbook
Course Fee-INR99999/(Total Fees of Intraday Trading Expert (Alpha)Course includes All five modules of Intraday Trading Expert (Alpha) Course)
Coupon Code-For True knowledge seekers will get on your phone number
Discounted Fees-INR74999/(with Coupon Code)
Certification of Completion-Certificate will be given on completion of course
Course Outline
Module 4: Defining Entry, Exit, and Stop-Loss Strategies (Professional Level)
Objective: The Defining Entry, Exit, and Stop-Loss Strategies module at the professional level is designed to provide participants with advanced skills in developing precise and effective entry, exit, and stop-loss strategies. Participants will explore various techniques, tools, and methodologies to optimize trade execution and risk management.
1: Entry Strategies
1.1 Importance of Entry Points
1.2 Technical Entry Signals
1.3 Order Flow and Level 2 Confirmations
2: Advanced Exit Strategies
2.1 Profit-Taking Approaches
2.2 Trailing Stop Strategies
2.3 Time-Based Exits
3: Stop-Loss Techniques
3.1 Importance of Stop-Loss Orders
3.2 ATR-Based Stop-Loss
3.3 Volatility Bands and Channels
4: Adaptive Strategies
4.1 Adaptive Exit and Stop-Loss Techniques
4.2 Dynamic Risk-Reward Ratios
5: Automation and Algorithmic Approaches*
5.1 Algorithmic Entry and Exit Signals
5.2 Machine Learning for Entry and Exit*
6: Case Studies and Simulation
6.1 Real-world Case Studies
6.2 Simulation Exercises
Assessment:
Participants will be assessed through case study analyses, simulation exercises, and a final project where they demonstrate their ability to define and implement precise entry, exit, and stop-loss strategies. Emphasis will be on practical application, adaptability, and risk management.
Note-The course will be modified regularly to meet Regulatory Body &Industry Standards
