Happy New Year to everyone. With the new year I thought it would be a good idea to review the performance of the Ivy-10 Portfolio for 2013.
What is the Ivy-10 Portfolio?
Back in 2012 I finished reading a very interesting book called, “The Ivy Portfolio”. This book was written by two money managers, Mebane Faber and Eric Richardson, who work at Cambria Investment Management. The authors wanted to answer the question of why money managers who manage some of the world’s best Ivy League schools produce such consistent results. Routinely Harvard and Yale endowments produce double digit annual returns. Since 1985 Yale University has returned around 16% annual returns and Harvard over 15% annual returns. Not only did they produce outstanding returns, but they did it by also reducing volatility and drawdown. This inspired me to create the Ivy-10 Portfolio which I track here. If you want to learn more about it, please read the original article here.
2013 Performance
Below is the performance summary for the year 2013 only. Please note, returns include dividends but exclude commissions and slippage. First up is the equity curve. The Ivy-10 Portfolio is the green colored equity curve while the benchmark (SPY) is the blue equity curve.
Below is the performance summary for both the Ivy-10 (Backtest) and the benchmark (SPY). We can see the Ivy-10 is underperforming the bench market significantly. The benchmark had a very strong year as the overall market rocketed into new nominal highs. However, the Ivy-10 did produce a 9.8% return. It’s not surprising the market outperformed and where the Ivy-10 Portfolio really shines is protecting capital during prolonged bear markets.
Performance Since Financial Crash
Expanding our view out to the last major market bottom of 2009 we can see the portfolio (chart below) performed slightly better than the benchmark right up until very recently. It’s only over the past 7 months or so have we seen the benchmark strongly outperform. You will notice the drawdowns are not as severe for the Ivy-10 Portfolio. For example, take a look at the debt crisis crash in the late summer of 2011. You see a strong drawdown in the SPY but the Ivy-10 Portfolio fairs much better.
As of this writing, both the benchmark and the portfolio have generated a CAGR of just around 17% – nothing to complain about. The portfolio has slightly lower volatility than the benchmark and around half the drawdown. As seen in the equity graph we can see the Ivy-10 experienced a 12.6% drawdown vs. the 27.1% drawdown of SPY. Again, this is one of the strengths of the Ivy-10 Portfolio. Enduring a 12.6% drawdown is a lot easier to handle than a 27.1% drawdown.
Out-of-Sample Performance
The Ivy Portfolio book was published back in 2006. Since this portfolio concept was conceived before that date I think it’s safe to say we can use 2007 as the starting period for our out-of-sample data for the portfolio. Below are the results from 2007 through the close of 2013.
The out-of-sample performance is producing a 13.8% CAGR which is very solid. The max drawdown when compared to the benchmark is significantly better.
Shorting
A few readers have brought up the idea of adding a shorting component to the Ivy-10 to see how it affects the performance. Currently during bear markets the portfolio is sitting in cash (SHY). In the following test I’m going to introduce the inverse SPY ETF called SH. I will simply add this to the portfolio to create a collection of 11 different ETFs. When a bear market arrives we would expect the SH to perform better than all the other ETFs within the portfolio and it would get selected for trading. The following results were executed over the out-of-sample period. During this period, 245 trades were closed over a total of 1,762 days.
The addition of a single shorting component does seem to help the portfolio by reducing the maximum drawdown and very little expenses to the CAGR. Keep in mind the Ivy-10 Portfolio selects the top three performing ETFs. Thus, during a bear market at most SH will represent 33% of the portfolio while the remaining will be allocated to “cash”. Exploring the use of other inverse ETFs may prove useful in further reducing drawdown and maybe even increasing total return. This will be a great topic for a future article.
Get The Book
Amazon: The Ivy Portfolio
Hi Jeff,
Thanks for the update. The Ivy method is clearly a long term approach and little can be drawn from a year of trading, but it is interesting to see the strategy produce typical 10% returns 6-7 years deep into out of sample data.
The use of an inverse ETF is an interesting idea. Correct me if I’m wrong, but entering the inverse long when it crosses an average is not the same as entering the inverse’s reference index short when it crosses below the same average?
One idea I had was as follows: rather than choose either the relative strength or the timing (moving average) model, why not use the timing model as a base system to take positions, and then use relative strength as a mechanism to size those positions relative to one another.
In other words, rather than only trade the top three markets in terms of relative strength, still trade all five markets, but with an equity allocation in each according to rank (say 1st=35%, 2nd=30%, 3rd=20%, 4th=10%, 5th=5%). This may just help to smooth the equity curve when the lower ranking components outperform the higher ones (especially over a larger portfolio).
Kind regards,
BlueHorseshoe
You’re right it’s not the same. Just because the reference index falls below the moving average does not mean the inverse is purchased. While your idea is an interesting one, it’s completely different system. The point of the Ivy-10 is to buy on relative performance and allocate equal amount of capital to the top three performers. This keeps things simple, which is an important feature of this system. However, I like your idea. It would be worth testing and would make for an interesting topic for another article. Thanks!
I interpreted the book a little differently, I think . . . relative strength seemed more like a footnote to the end of a long section focussing on the SMA for market timing, with equal assignment of capital to each component of the portfolio.
The problem with the relative strength approach, is that it potentially concentrates risk in the porfolio more – there is more chance of any three of five components becoming highly correlated than of all five becoming correlated. So finding ways both to retain that diversification and to improve performance with relative strength would be a worthwhile goal – there is no certainty that the approach I suggested is the best way to achieve this though!
Thanks again for the update.
BlueHorseshoe
A tactical strategy that works the best for the basket is to trade every two month by selecting the top two from VTI, EFA, VNQ, DBC and TLT on the basis of the performance of the prior three months, and computing the weights by using risk parity on the basis of the daily return data for the prior three months. This yields a CAGR of over 16% during 2007-2013 and volatility of 15.7%.
Replacing DBC by IGE with the same strategy increase the CAGR by about 1%.