The Exact Trigger that Indicates Volatility in Service Properties Trust
Service Properties Trust (NASDAQ:SVC) : The Exact Trigger that Indicates Volatility
Date Published: 2020-09-26
Disclaimer
The results here are provided for general informational purposes from the CMLviz Trade Machine Stock Option Backtester as a convenience to the readers. The materials are not a substitute for obtaining professional advice from a qualified person, firm or corporation.Preface
There is a trigger in Service Properties Trust (NASDAQ:SVC) that has preceded a large stock move and that move has created a powerful option trading opportunity in the past. The strategy won't work forever, but for now it is a volatility back-test that has not only returned 226%, but has also shown a win-rate of 53% while taking no stock direction risk.Simply owning puts and calls together, like a straddle or a strangle, can be a huge winner, as it was at the end of 2018. But, equally, it has been a huge losing strategy outside of that time frame. So, the need has arisen -- an empirical and structured trigger that indicates when a large stock move is coming so owning a strangle has a higher probability of succeeding.
There is such a technical condition, and we will review it, right now.
Here is a quick 3 minute video that demonstrates the back-test:
The Short-term Option Volatility Trade in Service Properties Trust
It's time to take advantage of volatility. Fear, uncertainty, doubt, unclear news headlines -- these are all trade-able events. Today we look at exactly what has worked in SVC, and the special technical trigger that starts it off.We will examine the outcome of going long a short-term out-of-the-money (40 delta) strangle (buying an out of the money call and buying an out of the money put), in options that are the closest to 14-days from expiration. But we follow three rules:
* Never Trade Earnings
Let's not worry about stock direction or earnings, let's try to find a back-test that benefits from volatility. Here it is, first, we enter the long strangle.
* Use a technical trigger to start the trade, specifically:
Wait until the day that the stock price crosses below the 200-day moving average and the stock price is below the 10-day moving average. Here is a nice simple image of the technical requirement:
* Finally, we set a very specific type of limit:
* Use a 20% limit
* Close the trade after 10 days, if the limit has not been hit.
At the end of each day, the back-tester checks to see if the long strangle is up 20%. If it is, it closes the position. If after 10-days the limit has not been hit, the strangle is closed so not to suffer total time decay.
RESULTS
Here are the results over the last five-years in Service Properties Trust:| SVC: Long 40 Delta Strangle | |||
| % Wins: | 53% | ||
| Wins: 17 | Losses: 15 | ||
| % Return: | 226% | ||
Tap Here to See the Back-test
The mechanics of the TradeMachine® stock option backtester are that it uses end of day prices for every back-test entry and exit (every trigger).
We can also see that this strategy hasn't been a winner all the time, rather it has won 17 times and lost 15 times, for a 53% win-rate and again, that 226% return in less than six-full months of trading. The trade will lose sometimes, but over the most recent trading history, this momentum and optimism options trade has won ahead of earnings.
Setting Expectations
While this strategy had an overall return of 226%, the trade details keep us in bounds with expectations:➡ The average percent return per trade was 6.68%.
Checking the Moving Average
You can check to see the moment a stock dips below the 200-day MA for SVC on the Pivot Points tab on www.CMLviz.com.WHAT HAPPENED
This is how people profit from the option market, its empirical testing, not luck. Trade Machine gives you the capacity to trade beyond luck. This is just one example of what has become a tradable phenomenon in Service Properties Trust.Please note that the executions and other statistics in this article are hypothetical, and do not reflect the impact, if any, of certain market factors such as liquidity and slippage.