Returning to an old strategy feels nice, but making more money the second-time around feels even better.
If you’ve been here awhile, you’d see that I experiment with a large array of strategies. This helps me learn new things and run a diverse portfolio, but sometimes, it makes me forget what worked in the past. So, as I reviewed my year-end trade history for tax reporting, I noticed a period of option trades that were shockingly profitable, and then I remembered what it was.
This strategy works by finding under/over valued options. The core idea is that on days of high volatility (positive and negative), the higher volatility will mean that more traders will be desperate to enter/exit positions and as a result, they may pay prices for options that may be too far from its true fair value.
Here is a background of how we capture these opportunities:
- Find a suitable stock. We will take a stock which is undergoing a volatile period. This can be found on earnings days, corporate actions(stock-split, merger, etc.), and even on just volatile days where the market is having a strong reaction to big news.
- Only look at options that expire around 30 days. 30-day options are the best for capturing these errors because they’re sensitive enough to actually profit with small price moves, but they have enough time-value to lose very little if the trade goes wrong.
- Use Options-Quant to price the options on the chain. We price the options chain until we get a big enough difference between the Options-Quant price and the market price.
- Put on the trade and wait for it to converge to/near the Options-Quant price.
Let’s see how that looks in action.
On January 10th, 2023 at 1:36 PM CST, Coinbase stock (NASDAQ: COIN) was up ~8%. This return is generally much larger than average, so naturally, we assume that there are a few mispricings in the option chain. The price of the stock at the time was $41.64, and this is what the option chain looked like:
Now that a suitable stock has been found, we enter the pricing parameters to Options-Quant:
- Model: MertonJumpDiff; Jump-Diffusion pricing model, arguably the most accurate option pricing model.
- Price: The price of the underlying stock
- Interest Rate: Risk-free rate of equivalent time-bond, in this case, the 4-week treasury bill at ~4.20%
- Gamma: Gamma of the option as shown by the broker
- Standard Deviation: Implied volatility as quoted by the broker
This outputs all strikes and the “true” prices of the options:
The model states that the call at the $41 strike has a true cost of about $5.57 and the put has a true cost of $4.78. Let’s look back at what the market is charging for those options:
The $41 put is only a few dollars off from the Options-Quant price, so there isn’t much opportunity there. However, the call seems to be priced for about $50 less than what our model says it should be! By our criteria, this call option is under-valued and should be sold at a higher price close to the one shown by the model.
So, we put the trade on:
Our target price was near $5.57, so we wait set a sell limit order and wait for the market to converge. As the day came to an end, the market price started to match the model price and the sell order was triggered:
After fees and commissions, we get a cool all-in profit of ~$335.
As you can see now, this is one of my favorite strategies because of its simplicity and effectiveness. Common investing wisdom is to avoid volatility, but as a trader, volatility is our bread and butter.
If you’d like to see more examples of Options-Quant in action, check out this specially-curated list: https://medium.com/@quant-galore/list/optionsquant-78b4e2a62921
If this article piqued your interest, you’d likely enjoy some of my other posts just like this one:
- Predicting The Market Might Be Easier Than I Thought
- Deconstructing a Quanta-mental Options Trade
- My Sports Betting Algorithm Might Be Bringing In Serious Dollars.