One of the participants in our last IOI 100-Series course in San Francisco, D. Chen, sent through a question about the performance of the IOI method as part of his due diligence process before taking the course.
This exchange, which includes statistics about my win / loss ratio for an extended period of time while I was developing the IOI valuation and option investment method, is instructive on a few fronts. First, you can see the actual statistics (I include an Excel sheet below). Second, you’ll see some examples of what I consider to be good examples of the IOI methodology working in a variety of circumstances.
Take a look and drop me a line with any questions!
As per our recent phone conversation, would you be able to share with me some examples of past trades (both successful and unsuccessful) that have resulted from your detailed fundamental analysis, as well as how long has the approach been utilized.
If you could also comment on the general success/failure rate that would be helpful.
Erik’s Response #1
Thanks for the mail and the excellent questions!
Because I worked at Morningstar for so long and was publishing all the time there, I’ve got some good historical data going back to 2008 regarding performance.
Near the end of my time at Morningstar, I pulled together a summary of wins and losses from my recommendations at that time and further split out statistics for “high conviction” investment ideas.
I made a total of 41 investment recommendations; of these 33 were realized wins and 8 were realized losses for a Win / Loss percentage of 80%. At the time, 6 investments were still in process and 5 of those were unrealized wins at that point for a Win / Loss percentage of 83%. (I think that all 6 ended up winning, but I didn’t keep track after I left Morningstar).
Out of the total recommendations, I made 23 high-conviction recommendations (I stated a conviction level when I published the reports). Of these 20 were realized and 3 were unrealized at the time I made the summary. All 20 realized investments were gains. All 3 unrealized investments were gains at that time, so my overall Win / Loss percentage for high conviction investments was 100%. Realized returns for the high conviction set was 30% annualized.
Since starting IOI, I haven’t kept such careful track of statistics. But my sense is that they are not that different now than when I was at Morningstar. Here are a few examples.
Oracle – High Conviction investment that I started writing about in mid-2013. I have invested in Oracle since then using all the tools of the IOI arsenal – increasing leverage opportunistically, decreasing leverage when the stock looked fairly valued, selling calls on the stock to increase income when it looked overvalued. There is a good summary of the Oracle investment on the IOI homepage (it’s not current because we can’t keep updating the graphic, but I increased my exposure to ORCL hugely at the beginning of the year with a “Levered Long” position and have made very strong returns on that stock this year.
General Electric – Another High-Conviction investment that I first wrote about in January of 2015. This was another example where I recommended a position that tailored leverage using several types of option investments – short puts, buying the stock, buying in-the-money options. I lowered my leverage on GE at the beginning of this year (realizing some of my 30% or so profits on the investment over last year in favor of a larger position in a relatively more-undervalued Oracle) but still have a levered long position in the stock and am writing about it.
Ford – Low-conviction investment that I started writing about in 2014. The valuation range was very wide, but the upper valuation mark was very high, so I was tempted to take a small, unlevered position in the stock. I wrote at the time that I was uncomfortable adding investment leverage to the already prodigious operational and financial leverage embodied in the firm’s operations. At the beginning of this year, as I was reviewing positions, I realized that my original fair value estimate had missed an important factor. Correcting for this brought my fair value range down a great deal and I advised using options to end up with a break-even or slightly better return on this investment.
You can read about these by just searching the Articles section on the IOI website.
As far as the “Bond Replacement” investments, a few good examples are Wal-Mart, Oracle, and IBM.
I originally looked at Wal-Mart last summer when it was trading in the $70 range and had fallen heavily after a bad quarterly report. Stocks falling heavily are good ones to write puts / sell covered calls against because the price received for the options is usually very high. In my first Tear Sheet on WMT, I suggested doing nothing because I saw the worst-case valuation being closer to $60, so I didn’t want to sell puts on a stock trading at $70. In October of last year, WMT’s price fell again to $60 and I immediately published another Tear Sheet advising to sell puts on it. This investment expired with the investor holding the shares and I wrote a note saying either hold onto the shares to realize a good potential upside on the stock or write a covered call on the held position. Investors who did the former have seen gains of around 20% on their investment; investors who did the latter realized gains of around 12% over six months.
Oracle I wrote about earlier. I also suggested writing puts on Oracle back in October (on the same day as WMT actually) and those expired in the money. I suggested keeping that position open and investors have seen a gain of around 14% since October.
I originally wrote about IBM in the summer of 2015 when it had fallen to around $160 / share. I recommended a short put on it at that time and wrote that while the upside of IBM was pretty uncertain, the downside of IBM looked okay. In an article, I suggested that if IBM’s price were to fall (my original Tear Sheet suggested there was a price risk down to the 117 or so area), it would be a good time to pick up more shares of stock. In fact the shares did fall down to $123 or something and I picked up a few more shares of stock then. The orginal bond replacement is still just under break-even, but I now have a larger position in IBM that is profitable to offset the bond replacement and if you read my recent articles on IBM, I’m feeling better that I understand the true valuation range of the company.
All of these examples show the key elements of IOI investments:
- Viewing success or failure on the basis of testable, operational metrics rather than frenetic price levels.
- Being able to clearly see when to act and when to step away.
- Using options to tailor risk / reward levels
- A much less frenetic level of activity in general
In working with really good portfolio managers, this is what I’ve seen them do. They leave the day trading to the kids and look at how to position themselves appropriately over a long period of time.
Thanks again for your mail, D., and for your continued consideration!
All the best,
Erik’s Response #2
(To a follow-up question about whether gains and losses were of the same magnitude)
Thanks for your follow-up! Good question!
I’m attaching the data that I have for my performance at Morningstar. It’s not the whole thing because I lost some of that data when I lost a hard drive a few years back.
Percentage loss and gain is not a great way to look at investments, in my opinion. It’s a good tool for comparing returns sometimes, but at the end of the day, it is dollar value that matters. (Many times, you see tout services talking about 1479% annualized returns or something, but this is crazy stuff. At the end of the day, you can’t buy a coffee with percentage returns…)
On the performance sheet, it’s split into Realized and Unrealized and “Pay Me Now” and “Pay Me Later”. Pay Me Now is what I call “Bond Replacement”; Pay Me Later is a growth strategy. Generally, I benchmarked my Pay Me Now statistics against bond yields and Pay Me Later against S&P returns.
There is a “Batting Avg.” in one of the columns. When I would publish ideas (I don’t think any of the articles I wrote that were behind the Morningstar paywall are visible to people – you may mainly be seeing the public pieces, which are not very meaty, if I remember correctly), I would put a “batting average” which was my assessment of conviction in the idea.
If you look at the “Equal-Weighted” columns, that shows how much I risked (normalized to $100) in the hope of winning some amount. The “Overall Return” number in the equal weighted columns just shows, if you put an equal amount of money into each of my ideas, what would your overall return be.
Looking at the “Confidence-Weighted” columns, you’ll see the amount risked multiplied by the batting average. This means that I am assuming that I would invest less in ideas in which I had less conviction and more in which I had more – sensible.
My Equal-Weighted returns outperformed my benchmarks, to the degree that if I had still been working for a fund, I would have retired by now. My confidence-weighted returns were stronger still.
Thanks again for writing in. Please feel free to drop me a line with any questions!
All the best,