Dynamic Asset Allocation

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Checking In

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It’s been a while since my last blog. I wanted to check in, and review some topics that I’ve covered in the past.

So much has changed in the year and a half since I last wrote. For example, there is now an “AI” button in my blog editing window that is offering to write this blog for me.

At the same time, so many things are “same as ever”. For example, everyone continues see “a lot of uncertainty in the markets” and things continue to look foggy ahead and clear in hindsight.

Uncomfortable IS PROFITABLE

Unlike the generally agreed upon yet not very useful concept of “market uncertainty”, the much less appreciated and more useful concept that also stays the same is that markets (stocks, factors etc.) continue to move in the direction that is most uncomfortable to predict, because the comfortable direction is already priced in.

For example:

  • Last year, it was uncomfortable to predict that inflation will be solved by now.

  • This year, it was uncomfortable to predict that a full recession will be avoided.

In September, I had the honor of speaking on Meb Faber’s podcast, where we discuss this idea in more detail. I gave an example that predicting a market doubling is much less comfortable than market halfling. What is comfortable is already priced in and so it’s only the uncomfortable views (if correct) that make money. That’s why forecasters are famously always wrong - even when they are correct, their forecasts are already priced in.

What’s the most uncomfortable view can you have today? - that’s the one to watch out for.

Long-Run Evidence alleviates ABANDONMENT RISK

On the podcast, we also discussed my latest academic paper on long-run asset allocation where I use almost a century of data (building on top of other long-run work of the past 10 years) for many asset classes and factors. I run a horse race between the popular asset allocation approaches from 60/40 to Risk Parity, Endowment Based, Factor Based and Dynamic Asset Allocation. At this point, it’s not news to anyone paying attention that Dynamic allocation historically crushed the other approaches on drawdown protection in traditional growth recessions.

However in 2022, things were different. Both stocks and bonds suffered a drawdown during inflation driven correction, so Dynamic approach came down as hard as the other approaches, in the 20-30% range. Yet the absolute drawdown was still much better than the max drawdowns of 60/40, which ranges from 30-70%.

STRATEGY timing REDUCES RETURN

Unfortunately, most investors continue to ignore historical evidence of crashes and dry spells of their chosen approaches. That leads them to sell out of their allocations when either of these two risks shows up.

Poor timing contributes to the difference between dollar-weighted returns (the ones investors actually get to earn) and the time-weighted counterparts. Watching my own clients add and remove assets from their accounts based on recent deviations from trend return confirms this human tendency. Sticking with a negative deviation is uncomfortable and yet was the right choice when the underlying source of return is reliable. Remaining invested in reliable approaches continues to be the most prudent answer - albeit much easier said than done.

FactorS BOUNCED BUT ALPHA decayED

Speaking of staying invested, my 2020 blog on why value investors should not give up was well timed. The bounce back from the extreme drawdown gave factor investors a short-term relief. However, my other point stands that the long-term “alpha” in traditional factor investing is likely gone. Because factors were not some "reliable premia” as the academics would have us believe, but were basic anomalies that generated alpha by identifying types of companies that were uncomfortable to hold. Proliferation of quants and smart beta, made these approaches comfortable and unprofitable. As a quant, this is hard to admit (and i have dedicated a lot of time to showing that these factors were real over the long run and not results of datamining). But ironically, it is the contrast of the flat return of last two decades vs the positive return of the prior two centuries, that is the most alarming evidence of factor’s decay.

For anyone who still doubts that factors can get arbitraged away just watch how the top hedge funds manage their capacity. Most of the top funds are closed to new investors and have been closed for a long time. These funds are giving up tens (if not hundreds) of millions of fees by not accepting the easily available additional demand. Something that traditional asset managers would gladly accept. Why do they forgo these easy profits? Because additional AUM would eat into their ability to generate alpha and hence their long-term profits. So if a hedge fund choses to close at 50billion to avoid the risk of alpha decay (where alpha is made up of hundreds of signals), how can traditional factors take in a couple trillion of AUM into a small handful of factors and still maintain their alpha?

  • What’s is the main antidote to alpha decay? - innovation.

  • What’s the main enemy of innovation? - bureaucracy.

ALPHA IN Intangibles

Intangibles are one way to generate innovative alpha as they continue to play a large role in company dynamics. There isn’t a week that goes by, that I don’t see a headline about some company’s culture deterioration causing a crisis or CEO style impacting company culture. These are hard to value assets that are material to the future fundamentals. Just because they are hard to measure, does not mean they are not important. In fact, from the perspective of alpha, this difficulty of measurement makes them even more valuable.

I recently gave a series of talks on intangibles investing at QuantStrats NYC and London, Nuedata, and in this Interactive Brokers webinar that you can watch for free. The webinar is filled with examples of how intangibles can be measured in innovative ways, using language. In one example, I show how we can trace Steve Job’s language in the Apple’s 10Ks. It points to the creative direction in which he took the company when he returned as the CEO in 1998.

Although intangibles investing has proven to be a huge source of alpha over the past two decades, this approach did experience underperformance in 2022. The rise in long-term interest rates affected companies with longer duration assets, which intangibles by definition are.

Beyond Diversification: An Insightful New Book on Dynamic Asset Allocation

I have just completed reading the 2021 book Beyond Diversification by Sebastien Page (Chief Investment Officer of T. Rowe Price who manages over $200 billion in multi-asset portfolios). It has been a pleasure to read as it blends academic richness with practical application on topics that are important to Two Centuries Investments.

The author did really well balancing rigor, utility, humor and personal meaning - for example by using well placed quotes from his father, while at the same time providing insights from two perspectives, given his background with both quantitative and fundamental investing.

The book is an inside view of how some of the largest asset managers think about total portfolios, often in contrast to the more traditional advisor or individual approaches.

I believe our readers and clients will find many of the concepts either familiar or clarifying, so I highly recommend that you buy the book as well as read the summary below. I have organized and cited various concepts that clarify many of the most important ideas in investing.

I also link to our content where the Two Centuries philosophy aligns with Page’s thinking. For example, the concept of moderate risk portfolio crashes being beyond typical investor’s risk tolerance has really resonated with me. Let’s dig in.

CHALLENGES FACING PORTFOLIOS & INVESTORS

  • Risk: Many successful investors create their own definition of risk in order to fine-tune their overall understanding of the primary challenge that can prevent long-term compounding. Our own thoughts on Volatility vs Risk in many ways align to the author’s:

    • “Volatility is not always a good proxy for risk, especially if we define risk as exposure to loss” (pg. 89)

    • “we should put risk at the center of the asset allocation decision” (pg. 212)

  • Crash Risk: Two Centuries often talks about failure of traditional portfolios like a 60/40 due to their outsized drawdowns. We agree, as the book title suggests, that traditional diversification does not work because it exposes investors to a loss that “is higher in crisis than what typical investor’s risk tolerance can withstand”:

    • “In financial markets, fear is more contagious than optimism” (pg. 132)

    • “Diversification fails across styles, sizes, geographies, and alternative assets. Essentially, all the return-seeking building blocks that asset allocators typically use for portfolio construction are affected” (pg. 127)

    • “fixed weight asset allocation does not deliver a constant risk exposure. To a certain extent, it invalidates most financial planning advice. Is a 60/40 portfolio appropriate for a relatively risk-averse investor? The answer depends on the volatility regime.

      In some relatively calm environments, a 60/40 portfolio may deliver 5% volatility, which seems appropriate for a conservative investor. However, in turbulent markets, the same portfolio maybe deliver as much as 20% volatility, which seems more appropriate for an aggressive investor, with a thick skin and high risk tolerance” (pg. 95)

  • Correlations: One of the main reasons why diversification fails is correlations are not stable over time. Instead, they cluster together and even increase during crash periods, such as during March 2020, which we highlighted in our One Factor World post.

    • “real-world correlations differ substantially from their normally distributed counterparts” (pg. 125)

    • For example, a “25-sigma event (observed in quant factors during August of 2007), corresponds to an expected occurrence … that is 10 times larger than the estimated range for the number of particles in the universe” (pg. 152)

    • It appears that correlations belong to either a low-risk or a high-risk regime. “The idea is that the fat tails (crashes) belong to another probability distribution altogether - the risk-off regime, which is characterized by investor panics, liquidity events, and flights to safety”

    • Using author’s extreme events correlation table on page 126, we estimate that during market sell-offs, the average correlation between 10 most prevailing asset classes (corporate bonds net of duration, real estate, hedge funds, high-yield bonds, MBS, EM bonds, EM stocks, EAFE Stocks, small vs large stocks, value vs growth stocks), rises to 76% from the 7% correlation experienced during market rallies. That’s a huge move!

    • “if we ignore fat tails (crashes), we underestimate exposure to loss and take too much risk relative to investor’s risk tolerance” (pg. 149)

Solutions:

  • Dynamic Investing: Our core belief that moderate risk investing is only achievable if advisors and investors accept that risk itself is dynamic and time-varying. This is a core principle of our Dynamic Balanced strategy that explicitly targets 8-9% volatility during rebalances. Page, himself, gives plenty of praise to volatility-managed strategies.

    • “What’s the solution? Managed volatility strategy is designed for that purpose. The asset mix becomes dynamic, but portfolio volatility is stabilized” (pg. 95)

    • “The strategy of managed volatility can be a particularly effective and low cost approach to overcome the failure of diversification (pg. 135)

  • Simplicity: Like the author, we believe that simple models are often as good or better than complicated ones that seem to draw more attention:

    • “when I assume that next month’s volatility would be the same as this month’s…this model is perhaps the easiest to implement and…it’s very hard to beat” (pg. 91)

    • “many economists and financial analysts focus on risk models to satisfy their ‘physics envy’ (pg. 89)

  • Government bonds: We are often asked why we use long-term treasuries in strategic asset selection and whether this allocation is a concern in a rising rate environment? The author explains the reason powerfully and concisely:

    • “When market sentiment suddenly turns negative and fear grips markets, government bonds almost always rally because of the flight-to-safety effect” (pg. 132)

    • “In a sense, duration risk (i/e treasuries) may be the only true source of diversification in a multi-asset portfolio” (pg. 132)

    • “Don’t blindly assume that rising rates are bad for risk assets such as stocks and credit bonds” (pg. 87)

  • Momentum: Our dynamic expected returns for Dynamic Balanced are heavily influenced by recent asset class momentum, which also aligns with the author’s experience:

    • “studies and my own experience suggest that momentum is a useful building block for return forecasting in an asset allocation context, especially when combined with valuation and other signals” (pg. 69)

    • It was a pleasant surprise for me to discover the relatively extensive coverage of our Two Centuries of Price Momentum research in the chapter on momentum. I was especially pleased that Page mentions that, as early as 2013, we ‘warn of increased strategy risk overcrowding’, which we have observed since then in many equity factor strategies (pg. 71)

    • However, in asset allocation, momentum provides a critical and reliable risk protection role because “momentum strategies that sell risk assets in down markets provide left-tail diversification, almost by definition” (pg. 130)

  • Yields: In our Dynamic Balanced model, we use bond yields as estimates of expected returns for the fixed income asset class. This aligns with the author’s strong support of this methodology.

    • “For fixed income asset classes, if your time horizon is long enough (3-10 year), current yield to maturity is a reasonable accurate predictor of future return” (pg. 39)

  • Gold: Surprisingly, Page does not explicitly discuss gold in the book. However, one of the reasons we allow Dynamic Balanced to tactically invest in gold is because it tends to diversify the bond risk during the“rare scenarios”of unexpected positive changes in inflation and negative changes in growth. In addition, there is the unlikely but possible risk that treasuries will become less safe from credit risk perspective. In sum, gold acts as hedge to the hedge.

    • “Bonds diversify stocks when stocks sell off, but stocks do not diversify bonds when bonds sell off” (pg. 124)

    • “there might be a breaking point in the future. Treasuries could become a risk asset. Beyond their inflation risk, default risk could begin to drive part of their volatility” (pg. 161)

  • Optimization: In our model, we utilize a constrained mean variance optimization process, which has been the subject of debate with some calling optimizers ‘error maximizers’. I was delighted to read the author’s support of optimization:

    • “Optimizers are helpful tools if used correctly” (pg. 211)

    • error maximization - a popular critique of optimizers - “only occurs when assets are highly correlated” (pg. 212)

    • “investors endowed with modest forecasting ability benefit substantially from mean-variance approach” (pg. 212)

  • Calibration Alpha: Throughout my quant career, I often found untapped alpha in model calibration as well as via model invention. Page validates my experience, stating that calibrating volatility and correlation models can have a larger impact on the outcome:

    • “it’s not always clear how to calibrate the models, let alone questions on the lookback widow and data frequency, irrespective of the volatility-forecasting model” (pg. 112)

    • “perhaps answers to these mundane questions don’t bestow academic merit because they are deemed too basic and self-evident. Or maybe the hard truth is that the answers to these questions matter more than the choice of risk model itself” (pg. 145)

  • Conviction: Beliefs are an integral part of any investing strategy. They build conviction and, without conviction, investors will not be able to hold on through market turbulence. Many of the concepts in this blog post represent our beliefs and our conviction that holding on to a dynamic strategy is much easier than staying invested in a static one:

    • “One of the greatest misconceptions on portfolio theory is that it precludes the use of judgement and experience. It doesn’t. It’s right there in Markowitz’s 1952 seminal paper:

    • ‘The process of selecting a portfolio may be divided into two stages. The first stage starts with observation and experience and ends with beliefs about the future performances of available securities. The second stage starts with the relevant beliefs about future performances and ends with the choice of a portfolio’” (pg. 84)

  • The Unexpected: A commonly understood, and as commonly forgotten, insight is that only forecasts that are not already priced-in move the markets. Page often mentions that he compares views to what is priced in:

    • “Survey data may be useful, but they rarely reveal what markets are truly pricing in” (pg. 67)

OTHER USEFUL CONCEPTS:

  • Macro: Page agrees that economic factors are better for explaining than forecasting. We also dedicate effort to monitoring and communicating the main macro trends in our monthly market insights blog to help our clients understand the investment context:

    • “with our macro dashboards, we don’t claim to identify causation, which is almost impossible to do given the complex and dynamic nature of how factors drive asset returns. Rather, we merely identify correlations that appear meaningful and leave it to investor to assess causation. Investors shouldn’t build systematic tactical asset allocation strategies based solely on these macro data” (pg. 67)

  • CAPE: Although the author is more positive about applying the CAPE ratio to investing decisions than we are, we both agree that practical use of valuation ratios like CAPE is hard:

    • “if we put it all together, CAPE gives us a back-of-the-envelope signal that we shouldn’t ignore, and it’s on the pessimistic side. Despite good track record, the CAPE doesn’t tell the whole story” (pg. 28)

  • Factor Investing: Over the past decade we have often predicted and observed that traditional Risk Premia are fading and many factors are only good for risk estimates versus establishing expected returns:

    • “The argument in favor of risk factor diversification is more about the removal of the long-only constraint and the expansion of the investment universe than anything else” (pg. 130)

    • “Unfortunately, there’s a lot of hype around risk factors. Major firms have developed commercial applications and products based on factors. Often their goal is to define factors as “asset classes” to raise assets” (pg. 174)

    • many factors '“help measure risk but they’re not expected to deliver a risk premium” (pg. 179)

  • Risk Parity: We both concur that many elements of risk parity construction are very useful, but they are  not the “end all” solutions, especially when tested over the long-run

    • “Though most quantitative investors understand and manage tail risk, it’s not always obvious how risk parity portfolios, most of which are constructed based on volatility, account for non-normal distributions” (pg. 215)

  • Active vs Passive: We also concur that blending active and passive investing, rather than being a devotee of one or the other, makes sense:

    • “my view is that there’s a place for both passive and active management in financial markets. Passive investors and stock pickers can happily coexist” (pg. 243)

  • Private Equity and Real Estate: In our upcoming paper on comparing long-run asset allocation portfolios, we analyze private asset classes and adjust them for autocorrelation. Page also warns about potentially misleading returns from the private equity industry:

    • “Beware of diversification free lunches in privately held assets.”

    • “Private asset diversification advantage is almost entirely illusionary…reported quarterly returns represent a moving average of the true unobserved marked-to-market returns” (pg. 129)

    • “while quarterly correlation between real estate and US stocks was 29%, it jumped to 67% on a rolling annual basis. For private equity, quarterly correlation was 13%, compared to 85% on a rolling annual basis” (pg. 130)

Interesting Papers that are relevant to us today:

Bond Investing in Rising Rate Environment (2014) by Helen Guo and Niels Pedersen

  • Addressing the concern that fixed income is a autonomically a poor investing in rising rates, the authors observe that ‘if rates risk gradually, or if the increase occurs later in the investment horizon, then it takes longer for the reinvestment risk…bottom line is that the impact of rising rates on bonds is both bad in the short run and good in the long run

Long-Term Bond Returns under Duration Targeting (2014) by Marty Leibowitz, Anthony Bova, and Stanley Kogeman

  • Providing evidence that it is relatively straightforward to estimate expected returns for fixed income, the authors observe that fixed income “returns have consistently converged toward the initial yield to maturity on the index…historically, the simplest rule of thumb seems to have prevailed: returns have converged to the initial yield to maturity at a time horizon that matches duration…If the time horizon is long enough, it doesn’t matter whether rates go up, down or sideways”.

Practical Issues in Forecasting Volatility (2005) by Ser-Huang Poon and Clive Granger

  • Although the complexity of statistical tools has increased, often simple tools work just as well, for example, in this mega study of various risk forecasting techniques, the authors find that “across 93 academic studies, there’s no clear winner of the great risk forecasting horse race”.

Volatility Managed Portfolios (2017) by Alan Moriera and Tyler Muir

  • To answer the question about the apparent contradiction between volatility managed portfolios which end up selling equities as their risk goes up and value investing which advocates buying equities when they drop, the authors observe “that expected returns adjust more slowly than volatility. Therefore, managed volatility strategies may re-risk the portfolio when market turbulence has subsided and still capture the upside from attractive valuations”.

Tail Risk Mitigation with Managed Volatility Strategies (2019) by Anna Dreyer and Stefan Hubrich

  • Managed volatility strategies are a “fundamentally different strategic, very long-term asset allocation - rather than an active strategy benchmarked to the underlying that can be evaluated quarterly”.

  • “Managed volatility portfolios reduce risk taking during these bad times - times when the common advice is to increase or hold risk taking constant…(which) turned out to work well throughout several crisis episodes, including the Great Depression, the Great Recession, and the 1987 stock market crash”

  • And one of my favorite quotes: “Warren Buffet once said that if the internet had been invented first, we wouldn’t have newspapers. I tend to believe that if managed volatility had been invented first, we might not have as many traditional balanced funds”

When Diversification Fails (2018) by Sébastien Page and Robert Panariello

  • “Full-sample correlations are misleading. Prudent investors should not use them in risk models, at least not without adding other tools, such as downside risk measures and scenario analyses. To enhance risk management beyond naive diversification, investors should re-optimize portfolios with a focus on downside risk, consider dynamic strategies”

  • “Many investors do not fully appreciate the impact of correlation asymmetries on portfolio efficiency - in particular on exposure to loss. During left-tail events, diversified portfolios may have greater exposure to loss than more concentrated portfolios”

The stock–bond correlation (2014) by Nic Johnson, Vasant Naik, Sebastien Page, Niels Pedersen, Steve Sapra

  • Similar to today’s environment, the authors conclude that “when inflation and interest rates drive market volatility, the stock-bond correlation often turns positive.”

At Two Centuries, we follow the principle of “Deliberately Different” investing by providing our clients access to dynamic portfolios constructed around these concepts.