Rajandran R Creator of OpenAlgo - OpenSource Algo Trading framework for Indian Traders. Building GenAI Applications. Telecom Engineer turned Full-time Derivative Trader. Mostly Trading Nifty, Banknifty, High Liquid Stock Derivatives. Trading the Markets Since 2006 onwards. Using Market Profile and Orderflow for more than a decade. Designed and published 100+ open source trading systems on various trading tools. Strongly believe that market understanding and robust trading frameworks are the key to the trading success. Building Algo Platforms, Writing about Markets, Trading System Design, Market Sentiment, Trading Softwares & Trading Nuances since 2007 onwards. Author of Marketcalls.in

How Fund Managers Use VaR to Survive Market Shocks

1 min read

When you’re managing serious capital in the markets, making money is only half the job. The other half is not losing too much when things go wrong. That’s where Value at Risk, or VaR, becomes a core tool in a fund manager’s playbook.

Let’s walk through a simple, real-world-style story of how a fund manager uses VaR to protect capital while still taking meaningful trades.


Meet Raj, a Fund Manager with a ₹1 Crore Portfolio

Raj actively trades Indian options using intraday strategies. His goal is to earn consistent returns without exposing the portfolio to wild drawdowns. He knows that the market is unpredictable and that even with great strategies, things can go wrong. So, he sets a clear rule for himself:

“I don’t want to lose more than ₹2 lakhs in a single day under worst-case conditions.”

That 2 percent of his capital is his daily Value at Risk (VaR) limit.


How Raj Uses VaR in Day-to-Day Trading

Pre-trade Risk Checks Before taking any trade, Raj runs simulations to estimate worst-case losses. If a trade carries too much risk, he either avoids it or reduces size. For complex options positions, he ensures that even in volatile swings, the estimated loss doesn’t cross the 2 lakh boundary.

Hedging for Stability Raj uses protective puts or call spreads as hedges. If he’s bullish on a stock, he might still buy a far out-of-the-money put to cap potential downside. These hedges cost a bit but act like insurance when markets behave erratically.

Smarter Position Sizing Instead of going all-in on a single opportunity, Raj divides his capital across strategies and symbols. This diversification, combined with VaR checks, prevents one bad move from sinking the entire day.

Real-Time Monitoring and Auto-Cutoffs Raj regularly keep track of VaR in real-time. If market volatility increases or something unexpected happens (like broker execution delays), the system alerts him or automatically reduces exposure to stay within limits.


    The Day Something Went Wrong

    One trading day, Raj faced broker-side execution issues. Orders were delayed. Slippage shot up. In such a scenario, it’s easy to lose control, but Raj’s risk systems kicked in. His portfolio took a hit of ₹1.8 lakhs, but because of his hedges and proper sizing, it stayed within the VaR threshold.

    No panic. No disaster. The system worked as intended.


    Why This Matters

    A lot of traders obsess over profits. Raj obsesses over risk. That’s the difference between trading for a living and gambling with capital.

    VaR isn’t about preventing losses. It’s about knowing how much you’re willing to lose and ensuring you don’t exceed that line. It’s the safety net that allows you to take calculated risks without jeopardizing the entire portfolio.


    Conclusion

    Value at Risk (VaR) may sound like a technical finance term, but at its core, it’s a common-sense discipline. Whether you’re managing ₹1 crore or ₹1 lakh, having a clear boundary on how much pain your portfolio can absorb is essential.

    In API-driven world of trading, execution issues and volatility are part of the game. The question isn’t whether risk will show up. It’s whether you’ll survive it.

    And with VaR, you just might.

    Rajandran R Creator of OpenAlgo - OpenSource Algo Trading framework for Indian Traders. Building GenAI Applications. Telecom Engineer turned Full-time Derivative Trader. Mostly Trading Nifty, Banknifty, High Liquid Stock Derivatives. Trading the Markets Since 2006 onwards. Using Market Profile and Orderflow for more than a decade. Designed and published 100+ open source trading systems on various trading tools. Strongly believe that market understanding and robust trading frameworks are the key to the trading success. Building Algo Platforms, Writing about Markets, Trading System Design, Market Sentiment, Trading Softwares & Trading Nuances since 2007 onwards. Author of Marketcalls.in

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