With potentially too much time on my hands over the University break, I've decided to write-up and post the following piece (exciting life, I know). The concepts outlined in this piece aren't new or groundbreaking- the options market has existed for a long time. However, what I found interesting about it is the intersection it provides between two sects of finance: derivatives and deep-value investing. The goal of the strategy is to earn a consistent income on top of any returns gained through holding equities in the portfolio. Ideally, it provides downside protection while asymmetrically allowing an investor to realize most of the upside. This trade-off is the major discussion point of the piece. I should note that this isn't a "research paper," per se. It isn't peer-reviewed, and some of the analysis may seem anecdotal. I like to think of it more as "formalized musings" to introduce the strategy and open a discussion. With all of that said, I hope everyone enjoys this light Wednesday evening reading. Should anyone have questions, improvements or corrections, I am more than happy to hear them. #finance #research #options #valueinvesting #incomegeneration #returns #strategy #portfoliomanagement #derivatives
Forbes Mailler
9mo
Nice work and an good read! Interesting to think about the similarities between being short a put and long the underlying. It could also be worthwhile to consider the impact of the put skew (generally higher implied vol at lower strikes, leading to higher option premiums) and ITM options generally having less liquidity.
Epic work Ryan!! 👏🏻
Oliver Byrne
9mo
This is a very impressive piece of analysis Ryan!
Awesome work Ryan Phillips!!
Kirby Wraith
9mo
Great piece Ryan Phillips!
Student at ANU College of Business and Economics
9moInteresting read! Knowing how well this strategy would perform over a bull market cycle in conjunction with a long portfolio would be fascinating. I have only considered LEAP options as a tool for value investors previously. You mention also value investing and DCFs; how do you avoid creating biases in your models? (I avoid them), given how easy it is to sway the outcome of a DCF due to the adjustable inputs of the model. This has been apparent in the last few years, with fund managers justifying absurd valuations based on their "DCF models".