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Two weeks ago I wrote a post about the All Weather Portfolio. Since the beginning of 2022, there has been an extensive discussion about “static stock&bond allocations” because both assets suffered significant losses. We were promised uncorrelated returns and yet, not only did they move in the same direction, they moved in the wrong direction.

With static stock&bond allocations, I refer to portfolios that invest all or part of the funds in the two assets in fixed percentages; the classic example is the 60% stocks, 40% bonds portfolio.

It is a great occasion to clarify a few misconceptions.

“Bonds hedge stocks but stocks do not hedge bonds”

It is true that when stocks dive usually Treasuries, not all bonds, go up. But this happens during standard recessions: stocks go down because the market expects lower profits and Treasuries go up because Central Banks cut rates in an attempt to sustain the economy. Bonds (Treasuries) hedge stocks.

In 2022, the market experienced an inflationary shock. The movement started with bond prices going down because markets started to price Central Banks increasing rates to combat inflation. Even if the effect is rates going up, this movement is different from CB hiking during an economic expansion to normalize and potentially prevent the economy from overheating. When bonds suffer from inflationary risks, stocks do not hedge bonds, at least not in the short term.

Bonds are a volatility dampener

The role of bonds in the 60/40 portfolio is not (necessarily) to bring uncorrelated returns but to lower portfolio volatility. Even in this sense, bonds did not perform as intended this year. A 50/50 portfolio of S&P500 and 10yrs Treasury had the same return as an investment allocated 100% in stocks.

Look at the infamous Hedgefundie Excellent Adventure portfolio, a different take on stock/bond static portfolios:

A 60% bonds, 40% stocks (with a lot of leverage) underperformed a 3x 100% stocks allocation; note that the above equity line is based on a logarithmic scale, meaning in 2022 the portfolio lost bit less than 50% of its value (from 250k to 140k as of the end of April).

How is that possible?

Bond returns fall faster than risk as interest rates approach zero. They also become more convex instruments: smaller changes in interest rates drive bigger changes in bond prices. In short, lower rates mean bonds become more volatile. While this works both ways, up and down, this year rates went up and the movement crushed bond prices.

As I wrote multiple times in the past, I am not sympathetic with people that found it easy to dump their bond allocation in favor of cash just because rates were zero or negative. A recent article from Morningstar explains the reason quite well. We do not know what type of bear market we have ahead of us and it’s been almost 20 years since I hear about imminent inflation risk. Without Covid, we might have had a standard recession and no inflation, in which case bonds would have performed better than cash. I think we can all agree on two elements:

  • in the long term, a bond allocation increases returns compared to cash
  • moving from bonds to cash in selective instances, for example when rates go to 0, changes the portfolio strategy from static to dynamic; it might be possible to achieve higher returns but this has to be done with a rule-based approach and ideally with some data back-up

Back to the All Weather

The balanced approach suggested by Morningstar actually points to the All Weather solution, a portfolio that includes intermediate and long-term bonds along with assets that hedge inflation risk.

How is the AWP performing this year? Not great and in line with the S&P500:

I could not find the All Weather Portfolio in Composer, so I did it with M1.com

The idea behind the AWP is to combine various types of assets that perform differently and allow the portfolio to thrive in all possible economic environments: stocks and commodities for periods of high economic growth, intermediate bonds and gold for inflation, long term bonds for recessions and so on.

What if we rotate the portfolio into the assets that work best in the economy’s specific environment at that point in time?

A Dynamic Approach

If long-term bonds are performing poorly right now, why do we hold them? Well…because we learned that market timing is a bigger sin than putting pineapple on a pizza…and we do not want to sin, do we? Also because we should have sold them in November last year, when the regime changed, and now might be too late.

According to this research, the likelihood that genuine ‘all weather’ strategies exist is slim because:

  • markets are adaptive.
  • investors learn from mistakes: some strategies are ‘circular’ (active portfolio management leads to passive which leads to active again) but markets tend to get more efficient through time and trading opportunities are arbitraged away.
  • even long-dated backtests cannot encompass all possible future scenarios: global zero-rate policies have happened only recently. Backtests risk to be unrepresentative.

The (only?) solution is to use regime-specific investment strategies that focus only on the quadrant the economy is in and switch between them:

Death to the Lost Decade — Verdad

With a focus on a shorter time scale, that’s how market-making firms already operate: they provide liquidity in risk-on environments but they ‘turn off’ their algos when risk-off is prevalent.

The main problem is a combination of how and how long it takes to identify the specific market regime we are in. GDP and inflation official data are published with a big lag, at least a month; by the time we receive them, they are already part of the past. The above linked paper suggests employing a strategy called Nowcasting: the employment of datasets that can be directly observed or rely on short term predictions instead of long-term ones.

We can evaluate our investment strategy according to this simple formula:

Effectiveness = Identification x Suitability

Regime Identification
Identifying regimes can be based on more or less complex logic based on directly observable market measures (security prices, P/E ratios, interest rates, curve steepness, credit spreads, implied volatility, skew, etc.), derived indicators (price volatility, moving averages, momentum, etc.), or any combination thereof.

Strategy Suitability
The choice of which strategy to apply to which regime is essential to the effectiveness of a regime-switching strategy. It consists of selecting strategies that are well suited to the different regimes being considered.

An Empirical Example

Verdad wrote a paper on the usefulness of employing high-yield spreads as a proxy to nowcast business cycle stages. Here is a summary of how different assets performed in different high-yield spread regimes:

Figure 2.png

The beauty of this model is that high-yield spreads are easily observable and signals are based on trailing data, with no foresight bias. Here is a nice visualization of the overall process:

Figure 3.png

The median spread is the average of the last 10 years and the change is the last three months’ difference. Verdad proposes the following portfolio asset allocation for each regime:

Figure 4.png
still closer to a blended approach than a pure all-in one

According to their backtest, this strategy (unlike the AWP) even outperforms the S&P500 on a pure return basis:

Figure 5.png

I run a backtest using the following ETFs (Bloomberg tickers):

  • S&P500: SPY US Equity
  • Small Value: SLYV US Equity
  • Oil: CRB FP Equity
  • Gold: GLD US Equity
  • IG Bonds: AGG US Equity
  • 10Y Treasuries: IEF US Equity

The rationale behind each individual choice is pretty straightforward; when I had the chance, I tried to use the ETF with the longer history; instead of a pure oil ETF, I used the CRB Index because I prefer the more diversified exposure to commodities, maintaining a tilt toward energy.

I could only go back until 2006 but the results I got are in line with Verdad:

The Verdad model outperforms until the end of 2010 and the underperform in the next 10 years.

But…

Before publishing a 30 pager pdf on “The Strategy That REALLY beats the S&P500!!1!” and charge you €77 for it, few caveats.

The regime we are currently in might have happened only in the ’70s and Verdad’s backtest does not cover that period. Since the beginning of 2021, the Verdad model is outperforming the S&P500 by more than 6% but it might be just a fluke. In general, nothing assures us that in the future, a new regime will appear or that our portfolios will still perform as they did in the past in the regime they were designed for.

Using only 1 indicator to establish the stage of the business cycle is neat and clean but makes the system quite fragile. What if the bond regulation will change in the future? What if Credit rating Agencies change the way they define below investment-grade issuers? What if companies start to fund themselves from p2p loans? ;P

The more variables and assumptions we include in a model, for example moving from a static allocation to a dynamic one, the more precise we can be but we also increase the risk of some relationship or assumption ‘breaking’. The strength AND potential weakness of Verdad model can be that the portfolios designed for each stage of the cycle make a lot of sense from an intuitive point of view: that’s exactly where an adaptive market might go to punish investors, especially if this model see widespread utilization.

Conclusion

Looking for the fanciest optimizer, the strategy that only goes up and right is fundamentally wrong, we have to accept losses. Consider again Hedgefundie Excellent Adventure, before 2022 the strategy produced these results (starting from 2010):

Can’t be that easy.

Stocks and bonds have been positively correlated on the upside for a long time, we had to expect the inverse to happen at a certain point. Obviously, nailing these turning points would be great. But remember that one thing is finding the right narrative, and the right signal, for the past and another is to expect to do it in the future. Maybe today’s pain is exactly what will make the 60/40 portfolio and friends work again in the future.

What I am reading now:

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