Looking Into A Quantitative Approach To Tactical Asset Allocation

Sep. 17, 2018 10:09 AM ETSPY, IEF, DBC, GSP, IYR, EFA, SPXL49 Comments10 Likes
Christopher VanWert profile picture
Christopher VanWert


  • The 200-day SMA is proposed as a useful tool.
  • Research done to prove it going back further than original academic paper.
  • Leverage applied and optimization attempted.

I recently read a paper on the effect of simply using a 200-day simple moving average on various asset classes, called "A Quantitative Approach to Tactical Asset Allocation" published in The Journal of Wealth Management (A Quantitative Approach to Tactical Asset Allocation by Meb Faber :: SSRN). The concept is simple, buy into the S&P 500 (SPY) after it exceeds the average value of the last 200 days. On the other end, sell if it drops below the average of the last 200 days. This simple technique aims to take advantage of the benefit provided by investing in the market long term while avoiding the major stock market drops. After looking at the results, I couldn't help but be amazed; I mean look at this!

(Source: A Quantitative Approach to Tactical Asset Allocation by Meb Faber :: SSRN)

By using the simple timing system you can improve upon the average return of the market while reducing the risk you're taking. Add in some diversification to your portfolio, by including various types of assets and the results get even better:

Set of 5

(Source: A Quantitative Approach to Tactical Asset Allocation by Meb Faber :: SSRN)

Set of 13

(Source: A Quantitative Approach to Tactical Asset Allocation by Meb Faber :: SSRN)


(Source: A Quantitative Approach to Tactical Asset Allocation by Meb Faber :: SSRN)

An average return of 10.48% with a volatility of 7% and max drawdown (largest loss from the peak of the portfolio up to that point) of less than 10% for just using the first 5 assets listed with an even distribution. So, of course, I wanted to prove what I was seeing. I ran the timing system using historical data myself to verify the results.

Doing the research

Equities are what I spend most of my time looking at and trading in my personal accounts, so I repeated the research using my own model. I gathered data from the S&P 500 dating back to the 1950's and constructed a 200 days simple moving average indicator.

(Source: Created By Author using data from finance.yahoo.com)

The use of trading is the same. We own the market (SPY) if it's above the 200-day simple moving average from the previous day and exit if it drops below that number limiting our loss for that day to the previous day's 200-day simple moving average and staying out until we enter back in above it limiting those days gain to what is above the simple moving average.

(Source: Created By Author using data from finance.yahoo.com)

After finding these results, I wanted to see how much leverage could be applied to maximize return if we kept the maximum drawdown about the same. It didn't take long:

(Source: Created By Author using data from finance.yahoo.com)

Of course, these numbers are insane, outlandish and must come with the potential to lose your whole account. Well, only if you include data that yahoo finance doesn't have from the great depression.

Major risks to leverage with this trading method

The whipsawing that occurred during that period would have a larger maximum drawdown of our trade method and caused an irreversible loss of capital. Could something that financially volatile happen again? The financial crisis that started in 2008 could be the introduction to something worse as financial skeptics have pointed towards since the crisis started.

Another flash crash, especially one that lasts for more than a trading day could also lead to the destruction of this leveraged portfolio.

How to fix it

By adding diversification, we can limit the amount of exposure we would have to these events that would lead to a destruction of the portfolio but still benefit from leverage and this trading method. I ran my normal approach of finding a max Sharpe ratio between the assets over the historical I could get from yahoo finance (Start date of 6/9/2006).

(Source: Created By Author using data from finance.yahoo.com)

All data is compiled from daily returns on these ETFs.

(Source: Created By Author using data from finance.yahoo.com)

Over this period, bonds performed exceptionally well (because of the financial crisis) while commodities performed badly because it starts in the middle of their last bull run and ends in the middle of the currently still bear market. Stating that commodities have a negative daily return is correct over this time period but in general is just wrong. If we look over a longer period using google finance we get a positive return.

(Source: Google.com)

Especially when the normal performance of basic material towards the end of a bull market is taken into consideration.

Despite my instinct to not just evenly divide an allocation to these funds, based on the flaws in the covariance matrix and Sharpe ratio for this case I can't argue against it.

In Conclusion

The ability to limit your max drawdowns and avoid the losses of the last financial crisis, the tech bubble, 1987's Black Monday, and even 2015's dip quickly adds incredible results to a portfolio. With these results verified, I believe this approach is a great way to reduce risk and massively increase returns by simply using the 200-day SMA as an entry and exit point for holding your portfolio's equity positions.

It's hard to beat the market, but this system uses a simple tool to improve the market's return and limit your losses. It's not often that a great investing opportunity is so clearly in front of you, and I don't think anyone would want to miss out on these returns.

This article was written by

Christopher VanWert profile picture
Masters in Finance, CFA exam I passed and a passion for Value, Quantitive Tactical Asset Allocation, Dalio's leading economic indicators and situation driven investing

Disclosure: I am/we are long TQQQ, SPXL, IYR, DBC, DRN. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

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