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Will We Ever Kill The Bug?

There is something very attractive about vintage items that just wont die.
Its not just cars. Its investment strategies, too.
Vintage strategies are often simple, easy to execute and provide amble 'out-ofsample' data. In other words one can see how they performed in real life years
after they have been proposed. And like the VW bug, they are "safe" choices.
Tried and true.
Can you imagine a 1965 VW running in the Autobahn?
Although the essence counts for a lot, for the car to survive at today's highway
speeds the tech needs to be up to date.
So lets take my favourite oldie and bring it up to speed: Harry Brownes
Permanent Portfolio.
From Investopedia:
one of the four possible macroeconomic scenarios that exist.

Stocks would thrive during periods of economic prosperity.

Bonds would do well in deflation and acceptably well during periods of
true defence against a deteriorating currency.
Cash would act as a buffer against losses during a routine recession or tightmoney episode, and would act well in deflationary times.

So lets see how it has performed.

The original rules:
25% in a stock market Index (SP500)
25% in Treasuries.
25% in Gold.
25% in Cash or similar.

since 1992.
For a far more detailed analysis of the so called "PP" you can see Gestaltu's
excellent "PP Shakedown" series as well as Scott's Investments analysis. There

Building a new strategy.

So let's update this strategy by using some recent tactics.

All further rules assume monthly rebalances.

1. Volatility Targeting per Asset

as to reduce risk to the overall portfolio.

This decreases annual returns but also limits drawdown to under 9%. Overall,
risk adjusted returns benefit. CarMDD is at 0.8.

2. Momentum
There's been a fair amount of talk about momentum. Let's try it. We will not
limit our assets to just the few best. We are only trading four assets. Instead we
will identify the worst performer. We will decrease funds invested in that asset
and distribute those funds to the rest. So if gold underperforms all other assets,
we will sell some gold, divide the proceeds in three and buy equal amounts of
the SP550 index, Treasuries and Cash.
Let's try by pulling 15% of equity from the worst asset.

This seems to help. Annual return is up to 8.3% while draw-down comes in at a

low and very respectable 7%.

3. Mean Reversion
What about mean reversion. Can we maybe try to sell shares of the best shortterm performer and distribute the money to the others?

This marginally improves risk adjusted returns by further limiting draw-down

to 6.78% while keeping annual returns almost the same.

4. Timing
Let's use the good old simple average rule. If an asset's price is below its own
200-day simple moving average then we sell it. If it crosses up then we buy it.
Trade only on the beginning of the month.

And to get things more interesting, lets use leverage up to 2x. That the
portfolio can be invested from 0% all the way to 200%.

So now we are up to almost 12% annual returns with a drawdown of less than
What about over-fitting parameters. Lets run a permutation of all parameters
(10,401). We will assume no leverage (1x).

The mean for the CarMaxDD is 0.772381 with a standard deviation of


Modifying the Asset base and using ETFs.

Finally lets include some newer asset classes that were not easily accessible
during the 80s.
Convertible bonds (CWB)
Foreign bonds (PCY)
Inflation protected Treasuries (TIP)
First of all, you may notice that all three assets are less volatile assets, at least
compared to the equity/commodities class.
Convertible Bonds lie somewhere between Bonds and Equities. They do carry
a lower interest rate risk than straight bonds but also carry some equity-like
Foreign Bonds is a diversifier out of U.S. debt.
Inflation protection Treasuries also carry some inflation (albeit, limited)
protection from interest rate hikes.

So lets go ahead and backtest using these 7 ETFs. We will use all layers
mentioned before, as well as 2x leverage.

Since there is a good chance of over-optimizing parameters we will go through

a number of parameters to get a sense of robustness:
First, lets look at Annual Return and Drawdowns. Each dot is one combination
of parameters. What we are interested in is the range of results.
Maximum drawdown is less than 12% while compound annual return comes in
above 8%. Keep in mind that this system is designed for moderate growth with
low volatility and risk. It is not meant to provide astonishing returns.

One more graph: Sortino Ratio and correlation to the S&P 500 index. Again we
are looking for ballpark ranges.
Let me remind the reader that the Sortino Ratio is a risk adjusted metric similar
to the sharpe ratio but only takes into account downside volatility. The
correlation to the S&P 500 is important to many investors that already have
active investments in equity. If the strategy is too correlated to the S&P 500
then it often does not fit into larger portfolios and could be replaced by the
The Sortino ration comes in above 1 while correlation to the S&P 500 index
comes in between 0.005 and 0.25.

This strategy trades monthly. For the backtests the assumption is that one buys
at the opening price of the second day of the month.
Therea plenty of ETFs to choose from. As a stock index proxy one can choose
from a wide selection that includes SPY, IVV, VOO as well as VTI, SCHB.
For treasuries one can use TLT. Gold can be traded through GLD or IAU. And
one of many options for cash is using SHY.
Its always interesting to look to the past for ideas on strategy development. In
building a core, capital preservation strategy one can go back to such strategies
as Harry Brownes Permanent and Bridgwaters All-Weather Portfolio. The
main feature of these portfolios is a price-agnostic view of the markets and
basic protection by using simple asset and weight selection.
In addition, in their most basic form, they have proven themselves in true,
decade long, out-of-sample testing.
So once the essence of the strategies are incorporated, there is no reason not to
include more recent rebalancing practices that have been introduced by
academia as well as quant research: Momentum, mean reversion, volatility
targeting and the more controversial timing rules.

Four Asset Base case System:

The base case system uses only the 4 core assets and variable leverage.
The system has a compound annual return of 12% with a 13% drawdown since
Most importantly it has behaved well in recent market corrections.

Moving Forward Expanded Assets

On top of these layers we introduce three more assets that provide a slightly
larger opportunity for diversification and a slight bias towards increasing rates.
The corresponding ETFs are CWB, TIP and PCY.
Since 2007 the expanded strategy gave an annual return of 12% with a
maximum drawdown of 6.74%. An impressive number, especially the
drawdown, for a conservative investor.
Too optimistic?
Running through a parameters test we still come up with Sortino ratios
between 1 and 1.8 and drawdowns below 12%.

But is there a bias in the look-back of the Timing rule? Is the 200-day simple
moving average chosen after-the-fact?
Well, because of the multiple layering, results seem robust in terms of picking
look-back period. In other words, momentum and timing are, in some ways,
similar in their effect. If an asset underperforms, it will go underweight using
the momentum rule until it crosses its own average and then will be sold. So
shifting through parameters in timing or momentum will have less effect than if
they stood as single rules.
As for selection bias, keep in mind that the main 4 assets have been tested outof-sample for some 20 years. The additional three assets, TIPS, Convertible
Bonds and Foreign bonds are lower volatility assets that could provide an
additional edge in the current environment and should not add excessive risk to
the strategy.
Backtesting Bias
Backtesting a strategy does not mean that backtested returns guarantee future
It does mean that one has thought about the strategy and detailed it enough as
to create rules that keep an investor disciplined and protect him from his own
emotions and the daily market noise.

Bug 4
Bug 7