Gamma hedging is a strategy that reduces risk by controlling how quickly an option’s delta changes with movements in the underlying asset. Gamma hedging comes in where delta hedging alone neutralises directional exposure, but fails to account for the instability of delta as prices move.
Gamma, the second derivative of the option price with respect to the underlying, measures convexity. A trader holding short options faces adverse gamma exposure because delta shifts rapidly against them during sharp price swings. By gamma hedging, they attempt to stabilize delta fluctuations and create smoother P/L curves.
Gamma hedging is the process of adjusting a portfolio to neutralize gamma exposure, ensuring delta remains stable even as the underlying price changes. It goes beyond delta hedging by addressing the curvature of the option’s sensitivity.
In formula terms
A portfolio with zero delta but negative gamma will still experience rapid losses during volatile moves. Gamma hedging solves this problem by using additional options to offset curvature.
For example, a short straddle is short gamma. If the stock price moves sharply, delta quickly shifts against the position, leading to large losses. By buying additional options (often OTM or long-dated), the trader offsets this gamma risk, slowing down delta drift.
Gamma hedging is therefore not about betting on direction but about managing exposure to volatility and convexity.
Gamma hedging works by rebalancing positions dynamically, so the portfolio remains delta-neutral as the underlying moves. This involves trading either the underlying asset or additional options to counteract delta changes caused by gamma.
The process follows three key steps
Formula for Hedge Adjustment
New Delta Exposure = Old Delta + (Gamma × Change in Price)
Hedge = – New Delta
Example: If a trader is short 2000 gamma and the stock moves up by 2 points, delta changes by +4000. To remain hedged, they short 4000 shares.
Thus, gamma hedging is essentially dynamic delta hedging with a focus on convexity.
Gamma hedging is used to reduce directional risk, stabilize option portfolios, and manage volatility-driven losses. It ensures delta neutrality remains intact even when prices swing sharply.
Without gamma hedging, delta-neutral strategies often collapse during extreme price movements. With gamma hedging, risk is redistributed in a more controlled way, though at the cost of frequent adjustments.
Gamma hedging is most effective during high-gamma conditions such as near expiry, at-the-money strikes, or volatile event-driven periods. Traders adopt it when delta is highly unstable.
For retail traders, gamma hedging is rarely practical due to cost. But for professional desks, it is indispensable during short-term volatility bursts.
Gamma hedging is primarily used by institutional players such as market makers, prop desks, and hedge funds. These entities manage large exposures and cannot afford uncontrolled gamma risk.
To implement a gamma hedge, you need to offset the risks of a short gamma position (like a short straddle) by adding long gamma exposure. Here’s a step-by-step breakdown.
This position is almost delta-neutral (Δ ≈ +0.06) but short gamma (Γ ≈ –0.0025), meaning it loses heavily on sharp price moves but benefits if the price stays near the strike.
This converts the naked straddle into an Iron Fly structure, reducing extreme convexity risk.
This adjustment gives more stability and reduces exposure to large price swings.
The short straddle, which was initially highly risky with unlimited loss potential, is now gamma-hedged into a controlled payoff structure. While there’s still some residual gamma exposure, the extreme risk is reduced, and losses are capped. This demonstrates practical gamma hedging by converting a naked position into a defined-risk strategy.
An example of gamma hedging is managing a short straddle position on Infosys during volatile market conditions. A short straddle has negative gamma, meaning delta changes rapidly against the trader when the stock moves.
Suppose Infosys trades at ₹1,500. A trader sells
Initial Net Delta = 0, Net Gamma = –0.12 (short).
If Infosys rises to ₹1,510:
If Infosys falls to ₹1,490:
This constant adjustment keeps the portfolio balanced. The trader earns from theta decay on the straddle while offsetting gamma-driven risks. The smoother P/L curve results from hedging delta shifts rather than leaving them unchecked.
Gamma hedging requires analytical tools that track Greeks, simulate positions, and suggest rebalancing. Without them, managing real-time exposures is nearly impossible That’s why new age traders use Strike Money.
Institutions use automated systems that adjust hedges intraday, while retail traders rely on semi-automatic monitoring. The more volatile the environment, the more sophisticated the tool required.
Gamma is the trigger for delta adjustments, but theta and vega also influence gamma hedging outcomes. Traders must monitor multiple Greeks simultaneously.
A comparison table
Greek | Impact on Gamma Hedging | Implication |
Delta | Needs neutralization | Frequent rebalancing |
Gamma | Triggers delta drift | Higher near expiry/ATM |
Theta | Offsets hedge costs | Short gamma collects decay |
Vega | Adds volatility risk | Unhedged, may swing P/L |
Thus, gamma hedging is never isolated—it is multi-dimensional risk control.
High implied volatility increases gamma, leading to more frequent rebalancing and higher hedging costs. Low implied volatility reduces gamma, making hedges more stable.
Example: Before Infosys earnings, IV spikes to 45%. A short straddle has massive gamma. Traders hedge aggressively. After results, IV falls to 25%. Gamma exposure reduces, allowing fewer hedges and more profit from premium collapse.
The main risks of gamma hedging include high transaction costs, slippage, and margin usage. While it reduces directional risk, it introduces practical execution challenges.
Gamma hedging thus involves a tradeoff: safety vs profitability. Institutions accept higher costs for survival, while retail traders struggle to balance efficiency.
Yes, gamma hedging is profitable when the cost of rebalancing is lower than the income from theta decay and volatility arbitrage. If costs exceed earnings, the strategy loses money.
For example,
In volatile markets, gamma scalping often works because frequent swings allow profitable re-hedges. In stable, trending markets, hedging costs outweigh theta income.
Thus, profitability depends on market conditions, execution skill, and cost management.
A gamma-neutral portfolio is constructed by balancing option positions and underlying assets so that total gamma exposure equals zero. Traders build it by mixing long and short options at different strikes and maturities.
For example, a trader holding a short ATM straddle has high negative gamma, which makes delta swing aggressively with small price moves. To neutralize, they add long OTM options that carry positive gamma, reducing the convexity risk.
The steps:
A gamma-neutral portfolio sacrifices some premium income but reduces violent delta swings. Many institutional desks prefer this method during volatile earnings or event-driven periods.
Gamma should be hedged more frequently during high-volatility periods or near expiry. This is because gamma is largest for ATM options close to expiration.
For intraday traders, hedging can be required every hour if the underlying stock is moving sharply. Longer-term traders often rebalance daily, unless markets are calm. The trade-off is between hedge accuracy vs transaction costs.
Automation is common here. Quant desks use algorithms to adjust exposure whenever net delta drifts beyond a threshold (say ±100). Manual traders often rely on broader triggers such as price moves beyond a support or resistance zone.
The key is to accept that over-hedging eats away premium, while under-hedging risks large drawdowns.
Alternatives to gamma hedging involve using static structures that naturally reduce convexity risk. These methods are cheaper but less precise.
These alternatives are popular with retail traders who lack the speed or capital for continuous gamma scalping.
The difference between gamma scalping and gamma hedging is that hedging reduces risk, while scalping seeks profit from volatility.
Feature | Gamma Hedging | Gamma Scalping |
Purpose | Risk reduction | Profit generation |
Method | Neutralize gamma to keep delta stable | Trade underlying around hedges to capture volatility |
Frequency | Event-based, as needed | Continuous intraday adjustments |
Profit driver | Stability, reduced drawdowns | Volatility swings and rebalancing gains |
Costs | Transaction + spread | Higher due to constant trading |
Both gamma scalping and gamma hedging strategies involve managing gamma exposure but have very different objectives.
The difference between delta hedging and gamma hedging is that delta hedging neutralizes immediate directional risk, while gamma hedging controls how that risk changes with price movement.
Feature | Delta Hedging | Gamma Hedging |
Purpose | Neutralize directional exposure (price moves) | Manage changes in delta caused by price movement |
Risk Managed | First-order (Δ) | Second-order (Γ) |
Method | Offset option delta with underlying/futures | Use additional options to stabilize delta drift |
Frequency | Requires rebalancing as delta changes | Requires even more frequent rebalancing during high gamma periods |
Users | Market makers, option writers, hedgers | Advanced traders, institutions managing large books |
Costs | Lower, due to fewer adjustments | Higher, due to continuous rebalancing and slippage |
Delta focuses on first-order risk, whereas gamma deals with second-order sensitivity.
Arjun is a seasoned stock market content expert with over 7 years of experience in stock market, technical & fundamental analysis. Since 2020, he has been a key contributor to Strike platform. Arjun is an active stock market investor with his in-depth stock market analysis knowledge. Arjun is also an certified stock market researcher from Indiacharts, mentored by Rohit Srivastava.
Sunder Subramaniam combines his extensive experience in fundamental analysis with a passion for financial markets. He possesses a profound understanding of market dynamics & excels in implementing sophisticated trading strategies. Sunder’s unique skill set extends to content editing, where he leverages his insights to develop equity analysis strategies at Strike.money.
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