Case Study: Applying Width Selection Analysis to a Real-World Trade
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This article will walk through a case study of a real-world credit spread trade, demonstrating how to apply the concepts of width selection analysis that have been discussed in this series. The trade will be a bull put spread on the SPDR S&P 500 ETF (SPY).
The Setup
The date is January 15, 2023. The SPY is trading at $400. The implied volatility is 20%. We are bullish on the market and we want to enter a bull put spread with an expiration date of February 17, 2023 (33 days to expiration).
The Analysis
First, we will calculate the one-standard-deviation move for the SPY over the next 33 days:
One Standard Deviation Move = $400 * 0.20 * sqrt(33 / 365) = $24.08
This means that there is a 68% probability that the SPY will be trading between $375.92 and $424.08 at expiration.
Next, we will consider two different spread widths: a narrow spread ($5 wide) and a wide spread ($10 wide).
The Narrow Spread
For the narrow spread, we will place the short strike at the one-standard-deviation level, which is $375.92. We will round this down to $375. The long strike will be $370.
- Short Put Strike: $375
- Long Put Strike: $370
- Net Premium: $0.80
- Max Profit: $80
- Max Loss: $420
- Breakeven Point: $374.20
- Approx. POP: 84%
The Wide Spread
For the wide spread, we will also place the short strike at the one-standard-deviation level, which is $375. The long strike will be $365.
- Short Put Strike: $375
- Long Put Strike: $365
- Net Premium: $1.50
- Max Profit: $150
- Max Loss: $850
- Breakeven Point: $373.50
- Approx. POP: 84%
The Decision
Both spreads have a high probability of profit. The wide spread offers a higher potential profit, but it also has a higher potential loss. The narrow spread has a lower potential profit, but it is more conservative.
Given our bullish outlook on the market, we will choose the wide spread. We are willing to take on the extra risk in exchange for the higher potential profit.
The Outcome
As it turned out, the market rallied over the next month, and the SPY was trading at $415 at expiration. Both the short and the long put options expired worthless, and we were able to keep the full premium of $150.
Data Table: Trade Summary
| Metric | Value |
|---|---|
| Entry Date | January 15, 2023 |
| Underlying | SPY |
| Strategy | Bull Put Spread |
| Short Strike | $375 |
| Long Strike | $365 |
| Net Premium | $1.50 |
| Expiration Date | February 17, 2023 |
| Outcome | Max Profit |
The Gini Coefficient
The Gini coefficient is a measure of statistical dispersion that is often used to measure income inequality. It can also be used to measure the risk of a trading strategy. A Gini coefficient of 0 represents a perfectly risk-free strategy, while a Gini coefficient of 1 represents a strategy with the maximum possible risk.
By calculating the Gini coefficient for different spread width strategies, a trader can get a more nuanced understanding of the risk of each strategy.
Actionable Example
This case study demonstrates the importance of a systematic and quantitative approach to credit spread trading. By using the concepts of standard deviation, breakeven analysis, and risk-reward analysis, a trader can make more informed decisions about spread width selection and improve their long-term profitability.
It is also important to note that this is just one example. The outcome of any individual trade is uncertain. However, by consistently applying a sound methodology, a trader can increase their chances of success over the long run.
In conclusion, this case study has shown how to apply the concepts of width selection analysis to a real-world trade. By following a similar process, a trader can make more informed and profitable decisions about their own credit spread trades.