저자: UngerAcademy코치 · 외국인
요약 보기
Ray Dalio의 All Weather 전략을 소개하고 백테스트 결과 연 1회 리밸런싱 버전이 가장 효율적이라고 주장. 전략 구성: 미국주식 30%, 장기국채(TLT) 40%, 중기국채(IEF) 15%, 금 7.5%, 원자재(DBC) 7.5%, 연 1회 리밸런싱. 백테스트 수치: ETF 기준 최대낙폭 약 14.6%로 S&P 500의 약 57%보다 낮고, 연수익률은 바이앤홀드 대비 약 0.5%p만 낮음. 1995년부터 지수로 테스트해도 최대낙폭 약 15%, 연수익 약 7.6%. 최근 강세장에서는 S&P 500이 전략보다 나았을 것이라고 인정하며, 어려운 시장에서 성과가 더 좋았을 것이라고 설명. 월 리밸런싱은 낙폭만 소폭 증가(16.11%)하고 수익 개선이 없으며, 거래 수수료가 5배 많아지므로 연 1회 리밸런싱을 권장. 전략은 인플레이션, 디플레이션, 경제성장, 경기침체 네 요인에 대응하도록 분산되어 있다고 설명. 구독과 좋아요를 요청하는 영상.
다듬은 글
Hello, everybody! I'm one of the coaches of Unger Academy and I'd like to welcome you to this brand new video. Today we are going to be talking about one of the most well-known strategies in the investment world: the All Weather strategy invented by Ray Dalio. But before we start, if you haven't done it yet, I invite you to please subscribe to our channel and click on the bell below this video to stay updated on all the new content that will be released.
So, the All Weather strategy, which is also called "All Weather Portfolio", was invented many years ago by Ray Dalio, who is a famous fund manager and owner of the Bridgewater Associates investment fund. The name of the strategy should already give you an idea of its purpose, which is to withstand all the "seasons" of the market, that is, all its different phases and conditions.
In order to fulfil this function, the strategy requires a diversified portfolio that is made up of different asset classes based on their functionality, that is, asset classes that are going through a "different" economic cycle. This kind of diversification should lead to a reduction in the total volatility of the portfolio and, so, to a more or less constant growth of the portfolio itself over time.
In particular, according to Ray Dalio, there are four parameters, or factors, that affect investments: inflation, deflation, economic growth, and economic decline. So let's say that, by theory, thanks to a good level of diversification on completely different asset classes, this strategy should be able to produce good results in these different market conditions.
The basic strategy is quite simple. More in detail, there should always be 5 instruments in the portfolio, and these instruments should have fixed weights, and the portfolio should be rebalanced every year in order to restore the correct weights of each of the 5 instruments it contains. According to the original strategy, 30% of the portfolio should be invested in US stocks; 40% in US long-term government bonds (I’ll do the test using TLT, as the duration of the government bonds in this EFT is at least 20 years); 15% in medium-term government bonds (I will use IEF, as the duration of its government bonds ranges from 7 to 10 years).
Then, 7.5% of the portfolio should be invested in Gold, and the remaining 7.5% should be invested in raw materials (in this case, I’ll use the DBC ETF). So the weights of these 5 instruments should be rebalanced once per year in order to restore the balance between the various components and preserve the correct diversification of the portfolio.
So let's start with a test on the ETFs of the original version, so the one with the annual rebalancing. As you can see, the drawdown of the strategy is significantly lower than that of the benchmark, especially in 2008 when, as we all know, the long strategies for the stock market suffered quite a lot.
In fact, the maximum drawdown of the strategy is 14.6% whereas that of S&P 500 was about 57%. All in all, the annual return is only half a percentage point lower than the buy and hold, which is the S&P 500. Among other things, you can also see here that in recent times, the S&P 500, due to its sudden rise, would have outperformed the strategy.
However, it’s also clear that the strategy would have performed way better in difficult times. If we want to analyze what would happen on a much longer time horizon we’ll need to change the instruments in the portfolio, taking indexes instead of ETFs. The reason is that, unfortunately, some of the ETFs I included in this portfolio didn't exist before a certain date.
So I replaced ETFs with indexes that allow for the kind of evaluation we're currently making and I tested the portfolio again on a much longer time horizon. So here are the results of the test, which goes from 1995 to today. As you see, even in such a long period of time, the maximum drawdown has been around 15%, while that of S&P 500 would has been around 57%.
The annual return continues to be around 7.6% per year, even with a longer time horizon. One possible variation to this strategy consists in changing the rotation interval, that is, in rebalancing the instruments in the portfolio once per month instead of once per year. To evaluate the results we'd get by doing so, I took another test rebalancing the portfolio monthly.
As you can see, there are no significant differences in the results we get. The portfolio I used for this test is the one made up of ETFs and not of indexes, and the testing period starts from 2006. There is a slight increase in drawdown, which is now 16.11%, and no significant increase in returns, so I'd say that the version with the annual rebalancing is the most effective.
Repeating the test with indexes instead of ETFs, we can see that the annual return is almost the same as the one we’ve seen when we used ETFs. Moreover, it isn't significantly higher than the one you get with an annual rebalancing, so, also in this case, I'd definitely opt for the version with the annual rebalancing, which, moreover, is also less expensive in terms of commissions.
In fact, if you rebalance the portfolio each month you need to pay commissions on 5 transactions per month - one for each instrument - whereas if you rebalance it once per year, you need to pay commissions on 5 transactions per year. So you know using the All Weather strategy with the annual rebalancing is definitely much cheaper and, so, somehow more accessible.
Okay, this video about the All Weather strategy has come to an end. If you liked it please leave us a "like" and subscribe to our channel not to miss out any new content. Thanks you so much for watching, and we’ll see you next time! Bye-bye!
Comments 0