Traders Earned ₹850 Crores in 20 minutes During Crude Oil Crash — Explained with shocking strategies, loopholes, and market secrets.

 Of course. This event, which occurred on April 20, 2020, is one of the most dramatic and controversial episodes in modern financial history. The claim that traders earned ₹850 crores (approximately $100 million at the time) in 20 minutes is not an exaggeration, but it requires a deep dive into the unique circumstances of that day.


Let's break down the "shocking strategies, loopholes, and market secrets" that made this possible.

The Stage: The Day Oil Went Negative

On April 20, 2020, the front-month May 2020 West Texas Intermediate (W T I) crude oil futures contract did the unthinkable: it traded in negative territory. It didn't just dip slightly below zero; it plummeted to a settlement price of -$37.63 per barrel.

This meant sellers were paying buyers to take oil off their hands.







Traders Earned ₹850 Crores in 20 minutes During Crude Oil Crash — Explained with shocking strategies, loopholes, and market secrets.

Of course. This event, which occurred on April 20, 2020, is one of the most dramatic and controversial episodes in modern financial history. The claim that traders earned ₹850 crores (approximately $100 million at the time) in 20 minutes is not an exaggeration, but it requires a deep dive into the unique circumstances of that day.

Let's break down the "shocking strategies, loopholes, and market secrets" that made this possible.

The Stage: The Day Oil Went Negative

On April 20, 2020, the front-month May 2020 West Texas Intermediate (WTI) crude oil futures contract did the unthinkable: it traded in negative territory. It didn't just dip slightly below zero; it plummeted to a settlement price of -$37.63 per barrel.


This meant sellers were paying buyers to take oil off their hands.


Why did this happen?


The COVID-19 Crash: Global demand for oil evaporated due to lockdowns.


No Storage Left: The primary U.S. delivery point in Cushing, Oklahoma, was nearly full. If you held a futures contract at expiry, you were contractually obligated to take physical delivery of 1,000 barrels of oil per contract. If you had no place to put it, you were in serious trouble.


The Expiry Cliff: The May contract was expiring the next day (April 21). This was the last chance for traders who didn't want physical oil to get out of their positions.

A massive "short squeeze in reverse" was set in motion. Traders who were short (betting prices would fall) were now forced to buy back their contracts to close their positions and take profits. But the traders who were long (betting prices would rise) were in a state of panic, desperate to sell at any price to avoid taking delivery of worthless, physically burdensome oil.

This created a historic liquidity vacuum where there were almost no buyers, only desperate seller

The Shocking Strategies and Loopholes Used to Profit
The massive profits weren't made by betting that oil would go negative (though some did). The biggest fortunes were made by a small group of sophisticated traders who provided liquidity in this vacuum and exploited the market's structure.

1. The "Negative Lottery Ticket" Strategy
The Loophole: The trading systems and risk models of most brokers, exchanges, and retail traders were not built to handle negative prices. Many trading platforms simply didn't allow for orders to be placed at or below $0. This meant a huge portion of the market was effectively blind and unable to participate on the sell-side.

The Strategy: A few savvy traders (often at proprietary trading firms or market-making shops) could place bids below zero. They stepped into the market as the only buyers.

They would place a bid to buy a contract for, say, -$10.

A panicked seller, whose stop-loss was triggered or who was forced to sell by their broker's risk management, would hit that bid and sell to them for -$10.

The buyer now owns a contract at a price of -$10. Minutes later, as the market continued its chaotic collapse, they could turn around and place an offer to sell that same contract for, say, -$30.









Another even more desperate trader would be forced to buy it from them at that price.

The Profit: They bought at -$10 and sold at -$30. This is a profit of $20 per barrel ($20,000 per futures contract). They were essentially trading the degree of negativity.


2. The "Physical Settlement" Arbitrage

This was the grand slam, the strategy that likely generated the hundreds of millions in profits.


The Loophole: The futures contract allowed for physical delivery. The entities that profited the most (like certain large trading firms) had two things others didn't:

1)Access to Physical Storage: They had vacant storage tanks in Cushing.


2)Capital and Guts: They had the balance sheet to handle the massive margin calls and the nerve to hold positions into the settlement chaos.

The Strategy:


As prices plunged deep into negative territory (below -$35), these traders started buying up thousands of contracts.


They were willing to take delivery of the physical oil because they had a place to put it.


By buying a contract at, for example, -$37, they were being paid $37,000 per contract (1,000 barrels * -$37) to take possession of the oil.

They could then store that oil and sell it later at a positive price (the June futures contract was still trading at around $20 per barrel). They locked in a risk-free profit: the negative purchase price + the positive future sale price + storage costs.


They weren't just trading paper; they were arbitraging the difference between the panicked financial market and the real-world physical market.

Exploiting ETF and Retail Innocence

The Loophole: Popular Oil E T Fs like USO (United States Oil Fund) were forced to roll their futures contracts from May to June on this exact day. Their prospectuses dictated they must sell the front-month contract right before expiry. They were gigantic, predictable, and forced sellers into a market with no buyers.


The Strategy: Sophisticated traders front-ran this trade. They knew USO had to sell millions of barrels worth of May contracts, no matter the price. They positioned themselves to be on the other side of this trade, buying these contracts at absurdly negative prices from the ETF, knowing they could immediately profit by selling them to the next desperate entity or by taking physical delivery.

The "Market Secrets" and Hard Truths

It Wasn't Luck, It Was Asymmetric Information and Preparedness: The winners weren't gamblers; they were experts who understood the futures delivery mechanism better than anyone else. They had risk models that accounted for negative prices and the infrastructure (legal, operational, financial) to handle physical delivery.

The House Always Wins: The biggest profits went to players who were already entrenched in the physical commodities world. Retail traders, and even many large financial funds, were structurally unable to play this game. They were the "dumb money" feeding the "smart money" in this event.

Liquidity is a Mirage in a Panic: The event proved that market liquidity can disappear in an instant. The existence of buyers and sellers is conditional on normal market functioning. During a true crisis, the market structure can break down, and those who can provide liquidity (or force others to demand it) reap enormous rewards.


Regulatory Gray Zone: While likely not illegal (exploiting a flawed system is different from breaking its rules), these actions raised serious ethical and regulatory questions. It exposed critical flaws in how financial products like ETFs are structured and how exchanges handle extreme events.








The ₹850 crore earn during the crude oil crash was a "perfect storm" of:

  1. An unprecedented global event (COVID-19) causing a supply-demand shock.2)

  2.  structural flaw in the futures market (physical delivery with no storage).Systemic unpreparedness for negative prices across the industry.

Sophisticated traders with physical market knowledge and capital, ready to exploit the chaos created by forced selling from ETFs, retail traders, and algorithmic systems.




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