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In this video, Mohak Pachisia, Senior Quant at QuantInsti, presents a deeper perspective on portfolio rebalancing from a quantitative lens. He explains the rationale behind rebalancing and how to apply it effectively using Python.
This video is ideal for traders, investors, and financial analysts who want to go beyond textbook methods and implement rebalancing decisions in real portfolios.
Mohak draws from real-world experience to show that rebalancing is strategic. It’s a powerful tool that shapes risk, return, and responsiveness to market conditions, and when done thoughtfully, it can redefine how a portfolio performs over time.
This is not just a theoretical discussion. It is a practical, data-driven walkthrough that includes coding, logic, and strategy evaluation.
What You Will Learn
The true purpose of portfolio rebalancing
How rebalancing impacts portfolio performance and risk
Implementing rebalancing workflows in Python
About the Speaker
Mohak Pachisia is a Senior Quantitative Researcher at QuantInsti, specializing in trading strategy development, financial modeling, and quantitative research. Before joining QuantInsti, he worked in the Risk and Quant Solutions division at Evalueserve, where he also led the learning and development function for the Quant team.
Mohak is an alumnus of EPAT and has cleared all levels of the Chartered Market Technician (CMT) program and two levels of the CFA program. He is currently pursuing the Certificate in Quantitative Finance (CQF). He has also consulted for organisations such as Upstox, Motilal Oswal, Spider Software, and TradeSmart. His expertise lies in simplifying complex quant problems and turning them into structured, executable strategies.
Learn More with EPAT and Quantra
EPAT by QuantInsti is a globally recognized certification for professionals aiming to build or advance their careers in algorithmic trading and quantitative finance. The curriculum covers Python, statistics, machine learning, trading strategy design, and risk management. Participants receive mentorship from industry experts and lifetime access to learning resources.
Quantra is QuantInsti’s interactive, self-paced learning platform that covers topics such as trading strategies, portfolio optimization, options trading, volatility-based strategies, and backtesting. The platform is designed for both beginners and advanced learners who want to build practical skills quickly.
Chapters
00:00 – Introduction: What Most Tutorials Miss
01:40 – What Portfolio Rebalancing Really Means
03:30 – Calendar-Based vs Threshold-Based Rebalancing
07:50 – The Problem with Frequent Rebalancing
09:10 – Volatility-Based Allocation Explained
13:20 – Python Code Demonstration
16:45 – Optimal Rebalancing Frequency
19:00 – Evaluating Rebalancing Performance
21:00 – Final Summary and Key Takeaways
Hashtags
#PortfolioRebalancing #QuantInsti #QuantitativeFinance #AssetAllocation #AlgoTrading #PythonTrading #VolatilityTargeting #InvestmentStrategy #QuantEducation #EPAT #QuantTrading #RebalancingStrategy #PythonForFinance #Backtesting #PortfolioOptimization