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If you’re new here, I share “buy-and-hold portfolios” that I think can double in 3-5 years. My investment philosophy is simple: Try to find the best stocks I can and let them sit for years. Incur no costs with such a portfolio, and it is simple to manage.
Performance of our Currently Active Portfolios
The $8 Million Oracle Options Trade
On September 10th, Oracle ($ORCL) stock exploded 40% higher following earnings, driven by a massive cloud infrastructure deal with OpenAI that sent their Remaining Performance Obligations (RPO) soaring.
Within hours, social media was flooded with screenshots claiming someone made 80,000% returns on ORCL calls, turning a $10,000 bet into $8 million.
Sounds too good to be true?
It probably is.
The "Miracle Trade" Doesn't Add Up
Let's examine the math behind this supposed windfall:
First, The Volume Problem:
On September 8th and 9th (the 2 trading days before earnings), the $340 calls only had volume of 1,119 and 457 contracts respectively.
But to place a $10,000 bet at $0.01/contract, you would need to buy 10,000 contracts.
Second, The Commission Reality:
Most brokers charge around $0.65 per options contract.
On 10,000 contracts, that's $6,500 in commissions alone, just to open the trade!
Third, The Market Mechanics:
For such volume to trade at $0.01, there would need to be quite a bit of selling. But why would someone sell so many contracts for just a penny?
The viral screenshot likely represents a small trade that got lucky.
Options Lottery Trading
Options "lottery" trades involve buying cheap, far out-of-the-money options close to expiration, hoping for a massive, unexpected price move. While the potential rewards seem astronomical, the math reveals why this strategy is fundamentally flawed.
The Probability Problem
Consider the typical lottery options trade:
Win Rate: Extremely low
Average Loss: Nearly 100% (options expire worthless)
Required Average Win: Must overcome the 99%+ loss rate!
For a strategy to be profitable, the expected value must be positive:
Expected Value = (Win Rate × Average Win) - (Loss Rate × Average Loss)
Let's run the numbers:
The Brutal Reality:
Even with a 1% win rate, you need your average winner to be a 99-bagger just to break even!
And remember, this is the average winner, meaning you need some trades to perform even better to offset the inevitable winners that fall short.
Let's say you make 100 lottery trades of $100 each:
Total Investment: $10,000
Expected Losses: 99 trades × $100 = $9,900
Break-even Requirement: Your 1 winner must return $9,900+ just to breakeven!
I don’t like those odds.
A Better Approach: Strategic Options
Instead of gambling on lottery tickets, I would much rather Play For Doubles instead…of course I’m a little biased 🙂
Consider a more systematic approach that harnesses options' unique properties while maintaining mathematical discipline.
The Power Law Advantage
Unlike stocks that could take many many years to deliver exponential returns, options offer something unique in investing: the ability to experience power law outcomes (where a few big winners drive most returns) in very compressed timeframes.
The key is approaching options like a venture capitalist approaches startups:
Make multiple small bets with asymmetric risk/reward profiles
Accept that many will lose money
Size positions to survive the inevitable losers
Focus on scenarios with multiple paths to success
That’s exactly what I did.
I began sharing such options starting in Coffee Can 13.
My hypothesis was that by using options we can generate some additional alpha.
So far, that’s been the case.
Performance Data
So far, I’ve shared 33 options bets across 3 coffee cans, and here are the results.
The 24 worst performing bets generated a cumulative return of -80%.
The 9 best performing bets generated a return of +2248%, essentially generating all the returns.
This is the power law in action.
Overall Performance:
Total Bets: 33
Position Size: 1-2% of portfolio
Win Rate: 67% (significantly higher than lottery trading)
Average Winner: +117%
Average Loser: -38%
Win To Loss Ratio: 3
Expected value: +65.72%
Realized Returns (Closed Positions):
Total Bets: 16
Win Rate: 62.5%
Average Winner: +91%
Average Loser: -42%
Win To Loss Ratio: 2.18
Expected value: +41.35%
Results by Position Size
2% Position Bets (8 bets):
Win Rate: 75%
Average Winner: 280%
Average Loser: -33%
Win To Loss Ratio: 12.7x
Expected Value: +202%
1% Position Bets (25 Bets):
Win Rate: 64%
Average Winner: 56%
Average Loser: -39%
Win To Loss Ratio: 1.4x
Expected Value: +22%
What’s really interesting to see here is that, so far, my 2% bets have significantly outperformed the 1% bets.
Perhaps that’s an indication that if I don’t have the conviction to place at least a 2% bet, it might not be worth it.
On the other hand, the 1% bets do have a very high win rate of 64% and a very good expected value of 22%.
All that said, these numbers are not statistically significant yet. Not enough bets have been placed, not enough time has passed, and not enough market conditions have been experienced.
But the initial results are promising.
In Conclusion
The viral Oracle options trade makes for great social media content, but terrible investment strategy.
Real wealth is built through systematic approaches that harness market inefficiencies while respecting the mathematical realities of probability and risk.
Lottery Options Are Mathematically Doomed:
The required win rates and return multiples make consistent profitability nearly impossible. This is simply gambling, with worse odds than Vegas.
Strategic Options Can Work:
As shown above, with proper sizing, selection, and risk management, options can enhance portfolio returns while maintaining reasonable risk levels.
Related Articles:
Disclaimer: This is not financial advice. Options trading involves substantial risk and is not suitable for all investors.