EZV Algorithms: Sequential Return Risk And Drawdown Protection

Summary

• Recently an EZV Algorithms Marketplace subscriber highlighted how anyone retiring or near retirement needs to understand “sequential return risk."
• While average returns might be good over your retirement, if the early years are negative, you could be in trouble – compounding on a smaller investment base.
• Some people run numbers as though the world were a nice, neat continuity of returns. It’s not, and I’ll illustrate the problem.
• Combine that risk with the lack of returns available from safer fixed-income investments, and there is a serious dilemma.
• The obvious solution is reduced drawdown risk while generating strong returns, but how?
• Looking for a portfolio of ideas like this one? Members of The Easy VIX get exclusive access to our model portfolio. Get started today »

Sequential Return Risk

Sequential return risk is the possibility that the combination of withdrawals and sub-par returns in the early years depletes your retirement nest egg, rendering an otherwise viable plan insolvent sometime before the full retirement horizon. In other words, the investment base depletes early and despite good average returns on the reduced balances over the period, you go broke before you die.

The problem is best illustrated by example, and I’ll ignore taxes to keep it simple. Consider Joe, a 65-year-old retiree who wants a plan that will get him through the next 25 years. (Hoping to die at 90 I guess!) He’s saved $1 million and expects to withdraw $58,000 per year at the start, escalating at 2.0% per year. Somebody tells him that if he can earn 7% annually on his investments, he’ll reach 90 years old with his full $1 million balance intact. So he runs the numbers and his plan looks like this:

Retirement Scenario - Even Distribution of Returns

Source: Michael Gettings

What could possibly go wrong? Well, suppose the first two years’ investment performance is not so good, losing 21% and 10%, respectively – a bear market. Here is what poor Joe might actually encounter despite the same average return of 7.0% over the entire period.

Source: Michael Gettings

Joe literally might be "Poor Joe" by his mid-80s, and he would be stressing over it by his early 70s – not a peaceful way to spend his golden years. Here is a summary of Joe’s sequential return risk:

Poor Joe’s Sequential Return Risk Problem

Source: Michael Gettings

Mitigation

Consider how Joe might mitigate his risk.

1. He could work an extra 5 years – not his preference.
2. He could raise his fixed-income allocations, but given bond yields, returns become paltry before risk becomes acceptable.
3. He could buy out-of-the-money put options – a ‘tax’ on his returns.
4. He could buy the VIX – a bigger ‘tax’ on his returns since it declines incessantly.
5. He could place standing stop-loss orders – and he’d be whipsawed in bear traps occasionally.
6. He could look for a way to identify the emergence of risk-off periods – not so easy! But history says it can work. I'll explain.

There are other ways to attempt to mitigate the risk - annuities, buffered funds, etc., but finding anything that is safe and also stays ahead of inflation is a chore.

Yet option 6 works and I can explain how, but first, as background, I’ll share my own perspective on how markets move, and why I focus on identifying the green cycles in the graph below.

How Markets Move

Source: Michael Gettings

There are three component cycles at work in market rhythms and the way they interplay makes it hard to distinguish what is exploitable from what is just noise. The underlying patterns are fundamental cycles which are typically multiple years from peak to trough - the business cycle. Fundamentals offer little in the way of market-timing opportunity because fundamental data progresses so slowly and irregularly. Plus, any sense of a peak or trough is obscured and overwhelmed by the shorter-period cycles – news stories and sentiment.

There are news cycles which are daily or weekly. News stories drive daily gyrations, but in the end, they are almost always just noise.

Finally, there are psychological or sentiment cycles (risk-on/risk-off) which can run weeks or months from peak to trough. And sentiment cycles can be captured in exploitable metrics. The most reliable way that I’ve found to do so is to monitor changes in the shape of the VIX futures curve. Traders of VIX futures telegraph sentiment more reliably than price charts or other indicators, and signals derived from their trades can avoid serious downturns.

EZV Algorithms Methodology

If you’re not familiar with EZV Algorithms methodology, consider reading this welcome article for a detailed description of how it works. The important thing to know is that by measuring the rate of change in the shape of the VIX futures curve, the methodology identifies the emergence of risk-off periods and dramatically reduces drawdown risk. And in doing so, returns are materially improved. Here is the drawdown performance (worst loss for rolling holding periods of X days) using a basket of five broad-based ETFs compared to buying and holding (“B&H”) the same basket since early 2008.

Source: Michael Gettings Data Sources: Fidelity, VIXCentral.com, CBOE

The methodology provides another advantage: the confidence to hold positions when media hyperbole is causing others to panic. For two months now, I’ve been writing “hold equities” while the media spent much of that time in a state of hyperbole about inverted yield curves, a coming recession, trade wars, political turmoil, and everything else they could find to sensationalize. When markets sold off sharply in the first days of October, I published I Smell a Bear Trap in the midst of it and the market turned up and has now rebounded to new highs. Returns since the last buy signal, a little over two months ago, have been 5.84%, a 35.1% annualized rate.

So, if you’re planning for retirement or already there, consider the risk of early return shortfalls, and consider how to mitigate it.

Recent Market Action

The last 12 months provide a good illustration of how EZV Algorithms algorithm works. The algorithm returned 20.8% versus 12.9% for a buy-and-hold approach. The entirety of that advantage could be attributed to side-stepping the December 2018 correction. All of the other sell intervals turned out to be zero-sum noise.

EZV Algorithms Signals & SPY, Last 12 Months

Source: Michael Gettings Data Sources: Fidelity, VIXCentral.com, CBOE

Viewing all sell intervals since 2008 shows a similar pattern. The worst sell-interval outcomes showed small disadvantages to a buy-and-hold strategy, but occasionally the serious downturns resulted in very large advantages. Since May of 2008, the algorithm returned 18.5% versus 10.9% for the buy-and-hold strategy. The graph below shows the texture of that story:

Advantage/Disadvantage of All Sell Intervals Since May-2008

Source: Michael Gettings Data Sources: Fidelity, VIXCentral.com, CBOE

So, if you’re in or approaching retirement, you might want to consider a different approach to riding the buy-and-hold cycles and take the emotion out of risk-management decisions by looking at a new approach.

Disclosure: I am/we are long SPY. 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.