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Q3 Update: Hedgewise Outperforming Every Asset Class in 2017
Posted in Market Commentary on 2017-08-28

Summary

  • Year-to-date, Hedgewise continues to outperform equities as well as most major competitive benchmarks.
  • Both the Risk Parity and Momentum frameworks have exceeded the 10% return of the S&P 500 (at comparable risk levels) while maintaining the benefits of risk management.
  • Many investors have missed this rally or transitioned to cash for fear of potential negative shocks, but Hedgewise client portfolios remain uniquely prepared for changing market conditions.
  • Various strategies have done well in this remarkably calm environment, but few are well-prepared if volatility returns. I've examined some of the largest negative events of the last 50 years to explore how Hedgewise frameworks build in protection.

Bull or Bear Market? Doesn't Matter Much

Since the election last November, I read about one article a day discussing equity outflows, stock bubbles, bond bubbles, and every kind of warning in between. Of course, many raise valid concerns and highlight lots of indicators that suggest a downturn is right around the corner. Despite that, stocks have been on an incredible run, gaining over 10% this year and nearly 20% since November. Unfortunately, an estimated 45% of the country has missed out on it, perhaps in no small part due to the warnings around every corner.

Events like 2008 tend to leave an unforgettable mark on investors, and who can blame them? Yet the possibility of a 50% loss - and the corollary temptation to try and wait for the 'right time' to get in - results in an enormous hidden drag on most portfolios. While most investors naturally use the S&P 500 as a benchmark, that is deceptive if they would never be comfortable using a 100% stock portfolio. This is why I consider risk management techniques to be far more than some absolute return; the extra protection can fundamentally change the ability for many to invest at all.

In my last article, I discussed a few of the underlying theories that drive the construction of Hedgewise portfolios. A significant recurring theme in that research is the ability to use a combination of leverage and risk management to add protection to a portfolio without sacrificing returns. This is a departure from traditional hedging techniques, like covered calls, protective puts, or moving some of your portfolio to cash, which all have a substantial expected cost. 2017 has been a nearly picture-perfect example of this concept in action, as both the Hedgewise Risk Parity and Momentum strategies have outperformed the S&P 500 while still retaining significant downside protection.

However, what most excites me is not the absolute return itself, but rather the success of the risk management techniques underlying it and how those factors continue to provide protection that most traditional portfolios do not. For example, Hedgewise frameworks successfully avoided much of the energy correction in the first half of this year, added copper exposure to better hedge against inflation, and remained patiently overweight in equities despite the incessant political turmoil. These systematically-driven adjustments have driven better performance than major competitive funds this year, but I expect their value to become even clearer when stock volatility inevitably returns.

Year-to-Date Performance Review

Here is how Hedgewise products have performed against every major asset class. This is the composite performance across all live clients in Risk Parity or Momentum at the "Max" risk level, which uses a similar target volatility to the S&P 500. All fees and costs have been included.

2017 YTD Performance of Hedgewise Products vs. Major Asset Classes

Benchmarks based on end-of-day prices of publicly available index data.

This performance is particularly notable for Risk Parity, which has beaten stocks despite a significant allocation to bonds and commodities. Momentum has remained heavily weighted to equities throughout the year, ignoring the political noise that has had little long-term impact on the trend.

Hedgewise products have also outperformed most major competitive benchmarks, such as the iShares Core Allocation Funds (AOK, AOM, AOA), the PowerShares and Cambria Momentum Funds (PDP, GMOM), and the AQR and Invesco Risk Parity Mutual Funds (AQRNX, ABRYX).

Hedgewise YTD Performance vs. Comparable Traditional Benchmarks


ProductYTDBenchmark (Ticker)
RP Med.7.5%5.5% (AOK)
RP High9.4%6.45% (AOM)
RP Max12.7%10.65% (AOA)
MM Max15.7%14.26% (PDP)
Hedgewise performance based on a composite of all live client portfolios in each risk level and includes all costs and fees. Benchmarks based on end-of-day prices and include all dividends re-invested.

Hedgewise YTD Performance vs. Risk Parity Mutual Funds

Hedgewise performance based on a composite of all live client portfolios in each risk level and includes all costs and fees. Benchmarks based on end-of-day prices and include all dividends re-invested.

Hedgewise YTD Performance vs. Momentum ETFs

Hedgewise performance based on a composite of all live client portfolios at the Max risk level and includes all costs and fees. Benchmarks based on end-of-day prices and include all dividends re-invested.

Across every dimension, Hedgewise products have consistently outperformed. While this is very exciting, many of the competitive funds - especially in the Momentum space - are not built with the same level of downside protection. The value of this protection will only become evident during a sustained, multi-month equity drawdown event. Since that hasn't happened recently, we can model history to get a better sense of what this might mean.

Preparing for Shocks: What to Expect in the Next Correction?

Quantitative frameworks like Risk Parity and Momentum can be difficult to evaluate because fund managers often run them quite differently. Above, you can see that despite a high level of correlation, the Invesco Risk Parity fund has returned about 4% this year compared to more than double that for Hedgewise. While that is relatively easy to evaluate, differences are often more muted in normal market conditions. For example, almost every variation of Momentum has had a relatively good year.

The problem with many quantitative frameworks is that they work only within an asset class rather than across multiple asset classes. In the case of Momentum, many strategies invest in the top trending equities at any point in time, but would never invest in a separate asset class like bonds. This can work very well so long as equities as a whole are trending up - a rising tide lifts all boats. In a severe market correction, though, such techniques often provide little protection.

To get a sense of this, I examined the performance of the PowerShares Momentum ETF (PDP), one of the oldest public frameworks available, during the last recession. I also compared this to the simulated model results of the Hedgewise Momentum strategy set at a similar level of risk.

PowerShares Momentum ETF (PDP) vs. Hedgewise Momentum Model, 2007 to 2009

See full disclosures on Hedgewise model simulations at the bottom of this article. PDP performance based on end-of-day prices and includes all dividends re-invested.

The simple explanation for this enormous difference in performance is that the Hedgewise model moved entirely into bonds prior to the recession, while PDP is limited to always being 100% equities by rule. To be clear, there is absolutely no guarantee that the Hedgewise framework will always catch such events. Yet at least it has a chance to get out of the way, while frameworks like PDP are limited by definition.

Again, there remain a wide range of events in which Hedgewise could not avoid losses, and 2008 performance is more of an exception than the rule. But the strategy frameworks are entirely built with these kinds of events in mind. To get a better sense of the range of likely outcomes, I examined the worst equity pullbacks since the 1970s to see how Risk Parity and Momentum held up (both set to the Max risk level).

Historical Performance of Hedgewise Momentum and Risk Parity Models


PeriodStocksMom.RP
Aug. 08 - Nov. 08-34.5%24.1%1.2%
Jun. 74 - Nov. 74-27.7%1.3%-9.1%
Aug. 87 - Nov. 87-26.1%-22.2%-6.5%
Mar. 02 - Jul. 02-21.2%3.2%7.7%
Jul. 11 - Sep. 11-17.5%-3.1%10.2%
Jul. 01 - Sep. 01-15.7%9%8.6%
Jun. 98 - Sep. 98-13.8%-10.3%14.1%
Simulated models rely on end-of-day index prices and use identical risk management algorithms to those in place today. Asset classes limited to equities, bonds, gold, and oil. All dividends assumed re-invested. See full model disclosures at the end of the article.

Across the board, both Hedgewise models consistently outperformed equities over the course of these "worst case" events. There will absolutely be some years, like 1987 or 1998, in which losses are inevitable. If you can successfully hedge even a few of these events, though, the impact on your long-run return will be enormous. Yet this will only be possible if you are using a quantitative framework that is focused on this type of risk.

The important hidden advantage of this approach is how it can shift your mentality as an investor outside of the raw returns. Once you know that a sophisticated quantitative approach is doing everything it can to manage timing risk for you, you can pay far less heed to the hundreds of warnings in the news every day. You won't avoid every loss, but you gain the confidence to stay patient regardless as the probabilities are engineered to be heavily tilted in your favor.

Looking Forward: Late-Cycle Environment

It would be unrealistic to expect the low volatility and stable positive returns of the past year to continue unabated. There's a good chance we will remain in a 'late-cycle' environment for the foreseeable future, which means that the economy will grow fast enough for the Fed to be concerned about inflation, but investors will stay nervous that growth is slowing down or that some geopolitical shock will throw everything into disarray. Against this backdrop, I'd expect quite a bit of chop across all asset classes, but it's unlikely that much of it will be meaningful. Both Hedgewise frameworks remain excellent choices for such an environment, regardless of short-term returns.

While I don't see any major systemic financial risks currently unfolding, I'm far less nervous about that possibility than most since Hedgewise frameworks have been so carefully constructed to account for it. In a sense, this bull market has actually been a challenging stretch because investors may fail to see the value of risk management when stocks continue to do so well. Fortunately, Hedgewise techniques are built to weather all kinds of conditions, and have consistently outperformed equities regardless. Whenever the next bear market does unfold, it will be exciting to observe what I expect to be an even bigger difference between Hedgewise and most traditional benchmarks.

Disclosure

This information does not constitute investment advice or an offer to invest or to provide management services and is subject to correction, completion and amendment without notice. Hedgewise makes no warranties and is not responsible for your use of this information or for any errors or inaccuracies resulting from your use. Hedgewise may recommend some of the investments mentioned in this article for use in its clients' portfolios. Past performance is no indicator or guarantee of future results. Investing involves risk, including the risk of loss. All performance data shown prior to the inception of each Hedgewise framework (Risk Parity in October 2014, Momentum in November 2016) is based on a hypothetical model and there is no guarantee that such performance could have been achieved in a live portfolio, which would have been affected by material factors including market liquidity, bid-ask spreads, intraday price fluctuations, instrument availability, and interest rates. Model performance data is based on publicly available index or asset price information and all dividend or coupon payments are included and assumed to be reinvested monthly. Hedgewise products have substantially different levels of volatility and exposure to separate risk factors, such as commodity prices and the use of leverage via derivatives, compared to traditional benchmarks like the S&P 500. Any comparisons to benchmarks are provided as a generic baseline for a long-term investment portfolio and do not suggest that Hedgewise products will exhibit similar characteristics. When live client data is shown, it includes all fees, commissions, and other expenses incurred during management. Only performance figures from the earliest live client accounts available or from a composite average of all client accounts are used. Other accounts managed by Hedgewise will have performed slightly differently than the numbers shown for a variety of reasons, though all accounts are managed according to the same underlying strategy model. Hedgewise relies on sophisticated algorithms which present technological risk, including data availability, system uptime and speed, coding errors, and reliance on third party vendors.

Understanding the Theory Behind Better Returns
Posted in Investment Strategy on 2017-06-21

Clients in the Momentum Max product have an average of a 15% YTD return compared to a 9% YTD return in the S&P 500, including all dividends re-invested and all costs and fees. Clients in the Risk Parity Max product have a 25% lower volatility of daily returns compared to the S&P 500 since 2016. Past performance is no guarantee of future returns. Different Hedgewise products are more suitable for different client goals, and will have different risk and return profiles. See full disclosures at end of article.

The Foundation of Outperformance

Hedgewise was founded on the idea that core financial theory can be used to improve returns and reduce risk. By focusing on 'first principles' of markets - why they function the way they do, what drives prices, and how they relate to broader economic trends - Hedgewise develops theories that are similar in nature to those found in the physical world, like the laws of gravity. Any truly superior and lasting investment strategy must have such a basis to be relied upon over many decades.

While it may initially sound outlandish to compare financial theory to the laws of nature, there are a number of well-known ideas that already rise to this level. Diversification is probably the most familiar, which asserts that holding a basket of assets will always result in better returns with less risk than holding just a few. This largely explains why more than 90% of stock-picking managers have failed to beat index benchmarks over the last 15 years.

On the other hand, there is also a misperception that passive index funds are the best and final application of financial theory. For example, if you are relatively young, should you invest entirely in equities? Should you account for radical events like the real estate crash? Should you use leverage in your portfolio? These questions can dramatically alter the composition of your portfolio, but passive funds provide few compelling answers.

The reality is that passive index funds are better building blocks of a portfolio than individual stocks, yet they only represent the tip of the iceberg in terms of understanding and applying financial theory. As time goes on, I believe 'active' management will remain alive and well, but will be represented only by funds which have developed a deeper and more accurate understanding of how markets operate, rather than a handful of individual stocks. These new kinds of portfolios will naturally outperform simple passive strategies in the same way that those simple strategies have outperformed stock-picking: because the theory represents something true and unavoidable in the marketplace.

Every Hedgewise product is built on this same philosophical foundation, and there have been a number of recent market developments that lend further proof that the theories in use are quite powerful, and already producing superior outcomes for Hedgewise clients.

Theory One: A Foundation of Risk Premia

A 'risk premium' is the amount that an investor discounts the expected returns from any investment to compensate for the possibility of loss, and to account for other competitive potential investments. For example, if you might realistically lose half your money, you'd expect a higher potential return than if you might only lose 5% of your money.

We can call the amount an investor is willing to pay for an investment today it's 'Present Value', and represent that calculation with the following formula:

Where 'rf' is the risk-free rate, and 'rp' is the risk premium attached to that investment. The higher the risk, the less you are willing to pay for an investment today. The more skilled investors are at understanding and predicting the future, the closer you'd expect their realized return to match the risk-free rate plus the assigned risk premium.

If this theory holds, you'd also expect to see higher realized returns for stocks than government bonds, since you are basically guaranteed a return on bonds if you are willing to wait until maturity. You'd also expect a higher return on bonds than on commodities, since commodities have many various uses outside of being a pure investment (e.g., you can use sugar to make food products for a profit).

If this theory is true conceptually, you'd expect return curves to look something like the following:

Theoretical Realized Return Bell Curve, by Asset Class

This conceptual basis is important because it provides a framework for answering some interesting questions, mainly:

  • How skilled are investors in different asset classes at predicting the future? The more skilled they are, the more that returns should converge with the assigned risk premium.
  • Does the theory hold up over certain time horizons but not others? For example, if the theory generally holds up for annual returns but not for monthly returns, then it might be reasonable to attribute monthly returns to random noise and not worry too much about explaining them.

With that in mind, let's take a look at the actual bell curves of asset class returns over a number of different time frames. I'm using the returns of the S&P 500, 10yr Treasury Bonds, and gold as a proxy for commodities. These returns represent the trailing gain or loss for the given time frame, in other words, for the 1yr horizon, you are seeing the trailing 1yr returns for that asset class for every month in history.

One Month Trailing Return Distribution by Asset Class

One Year Trailing Return Distribution by Asset Class

Three Year Trailing Return Distribution by Asset Class

In the final graph using three year trailing returns, the curves are certainly starting to resemble what we expected in theory. This suggests that risk premia are a real force, and that investors are always expecting a positive return from the markets. Because the curves tighten as you look over longer timeframes, it's likely that investors are modeling risk well enough to smooth out most short-term volatility, especially over one month or one year. However, every asset class (especially stocks and commodities) still has a nagging 'left tail' of significant losses even over three years.

Since we just established that investors are formulaically expecting a return, and attempting to account for future risks, the only reasonable explanation for long-term losses are substantial, low probability, or entirely unforeseen negative events.

This leads to a few key parts of how Hedgewise manages its funds:

  • I primarily care about gathering as many risk premia as possible, which means I never fight against the markets via things like covered calls or naked puts (although I may short negative risk premia, like in the oil markets).
  • I care very little about the normal deviation of prices or upcoming events that are well-known, the impact of which are pretty efficiently smoothed out over time. Instead, almost all of my research is based on managing potential hidden or poorly forecasted shocks that will radically shift markets.

Tying this back to the theory, this is how I think about the earlier bell curve of one month trailing returns:

This also helps explain why I do not consider short-term losses, especially week-to-week or month-to-month, to be much of a concern. In other words, I am never trying to predict near-term price movements. Rather, I am managing the risk that a major, negative event might occur. Unless such an event happens, your best move is generally just to do nothing and trust that the odds are heavily in your favor.

Interestingly, this sheds light on why so many active investors get into trouble. There is an enormous amount of noise in short-term returns, and trying to predict it is both really hard and mostly unnecessary. It also dispels the notion that economic indicators like price-to-earnings ratios or the length of the current bull market matter. Investors are pretty reliable in applying risk premia to all currently known information, and they are still building in a positive return expectation. Given that, it's usually a bad idea to avoid the market because it feels 'overvalued'.

Since launching last November, the Hedgewise Momentum framework has provided a nice example of this theory in action. The theory suggests that most of the time, especially over periods of five years or more, equities will yield a positive return. Then it follows that most of the time, it is safe to be 100% in equities - in fact, it might even sometimes make sense to use leverage and go more than 100% into equities, especially if you ignore normal monthly noise and don't overreact to market events that aren't meaningful, like the types described earlier. The Momentum product is structured to primarily revolve around these ideas and is usually overweight equity markets to varying degrees.

Here's how the Momentum product has performed in live Hedgewise client portfolios since launch. This data is a composite of all live client portfolios using the "Max" risk level, and includes all costs, fees, and dividends as of end of day on June 14th, 2017.

MonthMomentumS&P 500
November 20167.02%4.81%
December 20162.87%2.00%
January 20172.35%1.97%
February 20176.56%3.90%
March 2017-0.46%0.14%
April 20172.18%1.08%
May 20172.68%1.33%
June 20171.98%1.25%
Total27.87%17.64%

The outperformance of the product so far ties directly back to the concepts being discussed: equity markets are behaving in a normal range, and the types of market events that have been unfolding over this period, like the US elections, are relatively normal and foreseeable. While the return looks great, it's simple market theory at work.

A natural question is whether this performance would quickly reverse if stocks start to do badly. However, unlike a purely passive index, Hedgewise layers on additional kinds of risk management to maximize the chance that clients will hold on to their gains.

Theory Two: Behave Conservatively in High Risk Environments

The other major piece of the puzzle is the ability to catch major negative market shocks. However, theory suggests that you don't actually need to do be able to predict such events with great accuracy; even if you are only right 20-30% of the time, you'd still expect such a bet to be profitable.

There are two main reasons for this. First, there is the simple law of percentages: If you lose 50%, you then need to then gain 100% to get back to breakeven. Every time you successfully avoid one negative return, you can afford to miss out on a positive return of a greater relative size.

Second, there is the assumption that markets will be working normally far more often than not. Essentially, you are not usually expecting to have an equal chance of making or losing a large amount. Rather, you are expecting a very small chance of losing a large amount and a very large chance of making a small amount. If this is true, you can afford to be wrong about negative shocks far more often then you are right (since you usually don't miss out on very much when you are wrong, but you save a ton when you are right).

To understand this, it is useful to look at another view of the data. The following is a distribution of all realized one month returns for the S&P 500.

All One Month Trailing Returns of the S&P 500

The goal is to develop an ability to manage risk such that you can avoid a few of the extremely negative returns above. As laid out in the theory, you don't have to have a high probability of success for this to be worthwhile: avoiding one large negative return will compensate for missing many smaller positive returns. There is also no expectation that we can avoid every loss - we only expect that our overall returns will be higher than if we had done nothing to manage risk at all.

The following compares the original chart to a new distribution that removes all historical points deemed 'high risk' using the Hedgewise risk filter.

Comparison of All S&P 500 Monthly Returns to Risk Filtered Monthly Returns

Notice that the overall distribution of the risk filtered returns has shifted slightly upward, resulting in an average monthly return that is 0.56% higher than the unfiltered data. Even though not all negative months were caught, the impact of removing a few was more than enough to significantly improve the result.

Of course, the results above depend entirely on the quality of the Hedgewise risk filter, which was modeled with the benefit of hindsight. Luckily, we now have a few live data points to examine how it has been performing in real portfolios.

The current iteration of the Hedgewise risk filter was rolled out to live client portfolios in August 2016, and there have been two asset classes which have had months identified as 'high risk' since then: bonds and energy. Let's take a look at how the risk filter performed over this time period.

Comparison of 10yr Bond Monthly Returns to Risk Filtered Monthly Returns Since August 2016

Note that the "X" represents the mean of the data series.

In the bond markets, the average monthly return shifted up by 0.55% using the live risk filter.

Comparison of WTI Oil Monthly Returns to Risk Filtered Monthly Returns Since August 2016

Note that the "X" represents the mean of the data series.

In the energy markets, the average monthly return shifted up by 2.5% using the live risk filter.

These results are incredibly encouraging but consistent with what was expected. To review, we are behaving conservatively in high risk environments even though we will be wrong most of the time. Because of the nature of markets, the few times that we are right will still lead to improved returns in the portfolio.

Creating risk filters for individual asset classes is only one pillar of risk management at Hedgewise, though. You can layer on additional techniques, like hedging, to improve even further.

Theory Three: Commodities as Free Insurance

I've already written a number of previous articles on how hedging works, so I want to focus here specifically on the role of commodities, specifically gold. As you may have noticed earlier, gold has a realized return close to zero, so it makes sense to wonder why it belongs in any portfolio. You may be even more surprised to learn that I usually expect gold to be a drag on the portfolio, but it is still absolutely worth holding.

To understand this, you need to reframe the different functions that an asset can have. The most intuitive function is to drive positive returns, and I discussed how risk premia drive such returns in assets like stocks and bonds in the first section. However, an asset can also serve a role as insurance, and if it does so effectively, it no longer requires any expectation of a return.

Consider a case where you could actually buy insurance on a portfolio invested 100% in equities. You'd expect to pay a premium to an insurer, who would then agree to reimburse you if stocks fell below a certain value. Most of the time, you'd be losing money by having the insurance, but it gives you protection against extreme events.

In theory, gold provides almost exactly the same kind of protection as this hypothetical insurance, but is basically available for free. As a physical metal, gold will generally retain value over time and keep up with inflation, as it is often used as a substitute for currency. This also makes it useful as a safe haven for investors who fear radical events like a run on banks or a government default, since their bank accounts or bond holdings would no longer be secure. As such, gold prices do particularly well in times of runaway inflation or when investors feel very afraid, like during a major global crisis.

Still, gold is not useful in a portfolio if you have to remove something with a higher expected return to make room for it. For example, a portfolio of 100% stocks would have a higher return over time than a portfolio of 85% stocks and 15% gold, since the gold portion would probably yield very little. However, you can transform gold into a form of insurance with no drag on returns if you introduce leverage to the portfolio.

For example, consider a portfolio of just 100% stocks versus a portfolio of 105% stocks and 15% gold. The latter portfolio is leveraged by 20%, meaning you took out a form of loan. This loan will have a small cost, typically near the risk-free rate, but in exchange you now have protection from global crises and runaway inflation. In theory, the cost of adding gold to the portfolio will be less than the amount you gain by leveraging extra exposure in other asset classes.

This theory is easy to test by modeling the exact portfolios mentioned. These numbers use end-of-day index prices, include the cost of leveraged measured as the rate on the 1yr Treasury Bond, and include all dividends and coupons re-invested. Gold first became tradable in 1970.

Comparison of 100% Stocks to 105% Stocks / 15% Gold, 1970 to Current

This result is both unsurprising but incredible at once: you increased your annual return by almost 1% with very little increase in risk or maximum losses! Yet this makes perfect sense: you increased your expected return by owning more stocks, but you mitigated the risk of that extra exposure by adding the insurance of gold. Leverage allows you to manipulate the portfolio to effectively gain insurance and boost returns at the same time.

However, just like insurance, gold will rarely have a positive return except in circumstances of elevated fear or inflation. Outside of these events, the expectation is that gold will be flat or negative. This in no way changes the fact that it is having a positive overall effect on your portfolio.

As a result, it is unfair to judge gold on its raw performance over a few months or even a few years. A better way to evaluate it is whether it is properly hedging the kinds of events you expect. While we haven't had any kind of major global crisis or hyperinflation since Hedgewise opened its doors, gold has still demonstrated its safety whenever the possibility has arisen. Here's how gold performed during the three worst months for the S&P 500 since 2015:

DateStocksGold
August 2015-8.61%4.62%
December 2015-4.11%0.60%
January 2016-3.47%5.02%

Gold nicely hedged the losses of August 2015 and January 2016, which were driven by worries of systemic economic problems in China. It didn't do much in December 2015, as that pullback was centered around actions at the Fed, but it clearly remains a safe haven whenever a global crisis gets more likely. There was another nice example of this on the day of the Brexit in June 2016, as gold rallied 5% overnight.

While none of these events materialized into an economic downturn, gold provides a persistent hedge that allows us to improve portfolio construction in other ways. When the next downturn finally does arrive, gold will even more dramatically redeem its value.

Wrapping Up: Financial Theory in Practice

The past two years have provided an excellent, real life demonstration of the financial concepts underlying every Hedgewise product. Unlike active managers of the past, Hedgewise rests on a foundation of theory that, if true, can fundamentally improve returns and reduce risk in the same way that simple diversification does. While it is still relatively early days, the evidence so far has been amazingly close to what you'd expect to see, and this has already been driving outperformance for clients.

By understanding and gathering risk premia, Hedgewise products have a basis of positive returns built-in. Then, multiple risk management techniques are layered on top of this to make the portfolio less likely to be impacted by sudden negative shocks. Portfolios gain a kind of 'free insurance' by more effectively managing and hedging high risk environments, and leverage is used to make this possible without weighing down returns.

In the short-term, this can sometimes be confusing to watch. Assets like gold frequently have a negative return, and sometimes there are large losses which cannot be avoided. Risk algorithms are imperfect, and frequently appear to move in or out of an asset at just the wrong time. Yet when you step back and examine the underlying theory, this is all within the range of expectations. Even better, when you look at the evidence available since Hedgewise opened, it's obvious that the net result has been quite positive. I'm very confident that the more time goes on, the clearer the benefits will become.

Disclosure

This information does not constitute investment advice or an offer to invest or to provide management services and is subject to correction, completion and amendment without notice. Hedgewise makes no warranties and is not responsible for your use of this information or for any errors or inaccuracies resulting from your use. Hedgewise may recommend some of the investments mentioned in this article for use in its clients' portfolios. Past performance is no indicator or guarantee of future results. Investing involves risk, including the risk of loss. All performance data shown prior to the inception of each Hedgewise framework (Risk Parity in October 2014, Momentum in November 2016) is based on a hypothetical model and there is no guarantee that such performance could have been achieved in a live portfolio, which would have been affected by material factors including market liquidity, bid-ask spreads, intraday price fluctuations, instrument availability, and interest rates. Model performance data is based on publicly available index or asset price information and all dividend or coupon payments are included and assumed to be reinvested monthly. Hedgewise products have substantially different levels of volatility and exposure to separate risk factors, such as commodity prices and the use of leverage via derivatives, compared to traditional benchmarks like the S&P 500. Any comparisons to benchmarks are provided as a generic baseline for a long-term investment portfolio and do not suggest that Hedgewise products will exhibit similar characteristics. When live client data is shown, it includes all fees, commissions, and other expenses incurred during management. Only performance figures from the earliest live client accounts available or from a composite average of all client accounts are used. Other accounts managed by Hedgewise will have performed slightly differently than the numbers shown for a variety of reasons, though all accounts are managed according to the same underlying strategy model. Hedgewise relies on sophisticated algorithms which present technological risk, including data availability, system uptime and speed, coding errors, and reliance on third party vendors.

April 2017: A Great Start to the Year
Posted in Market Commentary on 2017-04-10

Summary

  • Hedgewise products have significantly outperformed benchmarks in 2017, with YTD returns of over 8% for clients in higher risk levels.
  • The tumultuous political environment has pushed many investors to be overly cautious due to a misperception of how much influence the President has on the economy.
  • Meanwhile, Hedgewise risk algorithms have navigated the environment quite smoothly, including a significant reduction of oil exposure prior to the recent pullback.
  • While Hedgewise performance has been strong, there were moderate losses in the first two weeks of March. However, this was quite natural and no cause for concern. In fact, it presents a great case study for why short-term losses rarely matter within the Hedgewise framework.

Politics Dominate the News, but Not the Economy

Recently, the headlines have been overwhelmed by news coming from the White House. There has already been post-election euphoria, a failed Repeal and Replace effort, an escalation of conflicts in the Middle East, and an endless stream of Russian intrigue. Given that, many pundits have naturally attributed the stock market rally since November to optimism over President Trump, and now worry that recent turmoil will quickly reverse the gains.

While this makes for a good story, it doesn't hold up in the real world. Outside of major economic crises requiring government intervention, like the bailouts in 2009, policy doesn't have all that much to do with Wall Street. Investors are largely rational, and value every individual company based on its bottom line and future growth prospects. Given that, it's hard to imagine that every company was suddenly worth 10% more because Trump might reduce regulation, cut taxes, and invest in infrastructure. Even if all of this happened - and everyone knows that is a big if - it wouldn't come close to justifying such an increase in valuation.

The reality is that the US economy had significant tailwinds up until the last month or so. Unemployment continued to drop, inflation finally started to pick up, and the Fed became confident enough to significantly accelerate interest rate increases. This explains most of the stock rally, as well as the dramatic correction in bonds last October and November. The macroeconomic data coming in for the first quarter has cooled off a bit, though, and stocks along with it.

The point is that it makes far more sense to follow the data than to follow the news. Thus far, the numbers say that investors aren't particularly worried about Trump destroying the economy. He would need to bungle something major (like starting a trade war) to have any real impact, but nothing that has happened so far has caused much worry.

Against this backdrop, it has actually been a relatively stable few months in terms of risk. Since the Hedgewise framework is entirely quantitative, there was no chance of overreaction to the news, leading to significant gains for most clients. To better frame relative performance, I've compared Hedgewise products to more "traditional" portfolio mixes, represented by the iShares Conservative ETF (AOK), the iShares Moderate ETF (AOM), and the iShares Aggressive ETF (AOA). I've also shown a separate graph of the Hedgewise Risk Parity+ strategy compared to the largest competitive mutual funds.

Hedgewise YTD Performance vs. Traditional Portfolio Benchmarks

ProductYTDBenchmark (Ticker)
RP+ Medium4.22%2.51% (AOK)
RP+ High5.34%2.9% (AOM)
RP+ Max7.51%5.19% (AOA)
Momentum8.55%5.96% (SPY)
L/S Oil-6.86%N/A

Hedgewise Risk Parity+ vs. Largest Competitive Mutual Funds

All Hedgewise YTD returns based on a compilation of live client performance in each product, including all costs and fees. Note that Momentum is set to the "Max" risk level, which best approximates a similar risk level to the S&P 500. Clients in lower risk levels will have lower performance. Benchmarks based on end-of-day prices and include all dividends and fees.

These performance numbers are exactly what you'd want to see: for a given level of risk, clients have generally achieved higher returns. While Long-Short Oil has incurred losses, they are quite typical of the swings inherent to that strategy, which tends to be both streaky and extremely volatile (Note that I generally will not provide more detail on alpha products due to their proprietary nature).

Looking forward, it's likely that one of stocks, bonds, or gold will reverse course, as it doesn't really make sense for them all to have appreciated together. While this may result in a short-term dip, as we saw in early March, this is a natural part of the process and has no bearing on long-term returns. As risk unfolds, Hedgewise algorithms shift to ensure your outlook remains bright regardless.

How Risk Algorithms Are Driving Performance

In the first quarter of this year, risk signals were relatively low in every asset class besides oil, which had its exposure reduced beginning in January. These signals are not meant to be predictive of positive or negative returns; rather, they reflect some possibility of a large correction. Oil provided an excellent example of such a risk unfolding over many months. Even though net losses have not been significant, the system was still accurate in identifying the possibility of severe downside.

Oil Exposure By Month In Hedgewise Risk Parity+ Model

Data based on Hedgewise models that are broadly consistent with those currently being used in client portfolios.

YTD Price Change of WTI Oil

Source: EIA

This is a great example of the kind of risk that is the primary focus at Hedgewise. As intended, the system was overly conservative, and reduced exposure to oil all the way back in January. Oil went on to rally slightly from mid-to-late February, but this had little impact on the overall risk assessment since short-term movements are not the focus. By March, the risk had been fully realized, with oil prices dropping by over 10% in a matter of days. Despite a subsequent recovery, the risk assessment was spot on. Even if oil manages to fully recover from its losses, it was still absolutely worthwhile to trim exposure given the general environment.

Conversely, all other major asset classes have been relatively stable (in other words, not demonstrating a risk of a major downside event). This doesn't mean all these assets were expected to appreciate; in normal conditions, you'd expect some to do well and others to do poorly, and thus drive a balanced positive return. However, markets frequently behave oddly over short periods of time, as can be seen by the YTD returns below.

YTD Returns by Asset Class

AssetYTD
S&P 5005.96%
Treasury Bonds2.0%
TIPS Bonds2.11%
Gold8.98%
Oil-2.7%
Based on end-of-day index prices. Includes all dividends and coupons.

While these returns suggest some disagreement across markets, they still led to a great few months of performance for Hedgewise clients. That said, it's easy to see that this is not sustainable. If real economic growth is high, TIPS should be doing terribly unless there is a great deal of inflation. However, in that case, Treasury Bonds should be tanking. This generally indicates that the players in the different markets have different views, at least one of which is not correct.

This means that one of these asset classes is probably overvalued, but no one knows which one yet. This is a very different category of risk than the one discussed in the oil markets: this involves short-term price distortion despite a generally solid base. To address it, you'd need to accurately predict weekly directional price movements - which is incredibly difficult and resource-intensive.

Rather than seek such precision, Hedgewise simply waits for these forces to play out and bets on an overall positive return regardless. A good example of this process happened in early March which is instructive to examine in greater detail.

Examining the March Dip

Here's a closer look at the pullback in the Risk Parity strategy in March.

All Hedgewise YTD returns based on a compilation of live client performance in each product, including all costs and fees. Benchmarks based on end-of-day prices and include all dividends and fees.

There's three key reasons this particular pattern should raise no concern. First, notice the symmetry in the graph: almost immediately prior to the pullback, there was a nearly equivalent rally. Such fast gains, especially in a balanced portfolio like Risk Parity, often suggest that something is out of balance and will need to correct. Second, there's absolutely no need to try and avoid that correction because it won't matter in the big picture. Finally, attempts to manipulate performance in this short of a time period are very dangerous and can easily backfire.

To better prove this, I took a look at the limited Risk Parity model that runs back to 1972, and isolated all of the years in which there was a single month with losses of 7% or more. I compared that alongside the annual return for that same year to see how much of an effect those large short-term losses had overall.

Impact of Large Short-Term Losses on Annual Returns, Risk Parity Model

YearWorst MthAnn. Return
1973-7.0%-7.49%
1976-7.1%35.44%
1978-12.4%-3.06%
1979-7.8%34.94%
1980-8.1%44.36%
1981-10.7%-11.59%
1982-8.8%69.10%
1984-7.3%1.56%
2000-7.6%9.77%
2003-8.2%28.41%
2004-8.0%8.95%
2011-7.8%31.18%
2012-7.1%8.05%
2015-8.1%-11.89%
Avg.-8.28%16.98%
Based on a hypothetical model using the same risk algorithms in place today, but limited to the S&P 500, Treasury bonds, and gold. Set to the "Max" risk level. Uses end-of-day index prices and accounts for all dividends and coupons. This is not based on a live portfolio.

In years when you lost 8% in a single month, you went on to gain an average of 17% regardless! While this may seem counterintuitive, it all comes back to balance and effective risk management. Since all assets tend to appreciate over time, you almost always win simply by waiting for markets to work things through.

Looking Ahead

Summing all this up, the outlook is generally positive but with expected chop along the way. Too many assets have gone up together in the past few months, but it's impossible to say how long that will last or what is currently overvalued right now. That's perfectly fine, though, as the Hedgewise risk algorithms have continued to catch major events and short-term swings will have little impact by the end of the year.

More importantly, Hedgewise has already driven significant gains for clients in 2017 and beaten most major benchmarks, and I fully expect that trend to continue.

Disclosure

This information does not constitute investment advice or an offer to invest or to provide management services and is subject to correction, completion and amendment without notice. Hedgewise makes no warranties and is not responsible for your use of this information or for any errors or inaccuracies resulting from your use. Hedgewise may recommend some of the investments mentioned in this article for use in its clients' portfolios. Past performance is no indicator or guarantee of future results. Investing involves risk, including the risk of loss. All performance data shown prior to the inception of each Hedgewise framework (Risk Parity in October 2014, Momentum in November 2016) is based on a hypothetical model and there is no guarantee that such performance could have been achieved in a live portfolio, which would have been affected by material factors including market liquidity, bid-ask spreads, intraday price fluctuations, instrument availability, and interest rates. Model performance data is based on publicly available index or asset price information and all dividend or coupon payments are included and assumed to be reinvested monthly. Hedgewise products have substantially different levels of volatility and exposure to separate risk factors, such as commodity prices and the use of leverage via derivatives, compared to traditional benchmarks like the S&P 500. Any comparisons to benchmarks are provided as a generic baseline for a long-term investment portfolio and do not suggest that Hedgewise products will exhibit similar characteristics. When live client data is shown, it includes all fees, commissions, and other expenses incurred during management. Only performance figures from the earliest live client accounts available or from a composite average of all client accounts are used. Other accounts managed by Hedgewise will have performed slightly differently than the numbers shown for a variety of reasons, though all accounts are managed according to the same underlying strategy model. Hedgewise relies on sophisticated algorithms which present technological risk, including data availability, system uptime and speed, coding errors, and reliance on third party vendors.

2016 Year In Review: Hedgewise Outperformed
Posted in Market Commentary on 2017-01-28

Summary

  • In 2016, every Hedgewise product exceeded the performance of comparable benchmarks while incurring significantly lower risk of loss. Client portfolios achieved an average return of over 12%.
  • The Hedgewise flagship product, Risk Parity, consistently outperformed competitive funds by 2% to 4% due to its superior risk management, lower costs, and tax efficiency. The portfolio remained stable throughout significant geopolitical events, such as the Brexit and the US election, continuing to prove its resilience in any economic environment.
  • Hedgewise also launched two new products this year, Momentum and Long-Short Oil, as part of its broader vision to better fulfill any client goal. These products help risk-seeking clients achieve higher expected returns while maintaining the benefits of risk management, and initial results have been excellent.

Overview of 2016: Better Performance, Less Risk, More Innovation

2016 was a fantastic year for Hedgewise, which delivered on its core promise to clients: better returns with less risk of loss, whatever your goals. Here's a summary of how Hedgewise products performed last year compared to the S&P 500.

Product2016 Performance2016 Max Loss
Risk Parity+12.2%-5.4%
Momentum24.0%-6.4%
Long-Short Oil86.7%-13.3%
S&P 50011.7%-9.1%
Hedgewise figures are based on hypothetical models which are broadly consistent with those currently being used in client portfolios. Models rely on publicly available prices, assume dividends are re-invested, and include an estimate for all fees and commissions. Risk Parity and Momentum are set to the "High" risk level. "Max Loss" is defined as the distance from the peak point of gains during the year to the lowest subsequent point, measured daily. Momentum and Long-Short Oil products were launched mid-year, and realized client performance will differ from the numbers above depending on the date of portfolio inception. All products may be run at various risk levels, which will also influence client realized returns.

These numbers tell the story quite well. For any given level of risk - with risk defined as the maximum amount you might lose - Hedgewise offers products that perform better than traditional alternatives.

Risk Parity is ideal for minimizing drawdowns while achieving equity-like returns. It frees clients from having to worry about the future by hedging for any economic scenario. This year, performance remained steady despite various pullbacks in both the stock and bond market, providing many great examples of the theory working in practice. Hedgewise also outperformed comparable Risk Parity mutual funds throughout the year, further differentiating its risk management techniques.

However, Risk Parity still has an upper limit on risk based on its need for leverage, which has natural caps for a variety of reasons. For clients with a greater tolerance for occasional large losses and a long enough time horizon, it often makes sense to prioritize higher potential returns over minimizing potential losses. To better cater to this need, I created the Momentum and Long-Short Oil Products.

The Momentum framework still takes advantage of the Hedgewise risk monitoring system, but concentrates exposure rather than disperses it. This makes it quite likely that clients may experience losses similar to equity markets, but with the potential for far greater returns. Initial results this year were consistent with this vision, as the Momentum strategy returned 24% overall, along with a higher corresponding level of volatility.

Long-Short Oil is the first Hedgewise "alpha" strategy, which means it has very little correlation to broader markets and is more speculative in nature. If executed well, such strategies are extremely valuable additions to a portfolio because they provide a completely independent return stream and another effective means of diversification. I am planning on developing a number of these strategies and helping clients layer them together to construct even higher performing portfolios.

Overall, 2016 represented another great step forward. Hedgewise now offers multiple risk-managed products, all of which outperformed. Not only that, Hedgewise helps clients combine these products together to create a portfolio which is even greater than the sum of its parts. As time goes on, I believe the benefits of this approach will only become more and more obvious.

Risk Parity Weathers Every Shock, From Stocks to Interest Rates

In theory, a Risk Parity portfolio should create more stable, positive returns over time because it is constantly hedged for any kind of economic scenario. A number of events during 2016 helped to demonstrate that this is working just as it should:

EventS&P 500Risk Parity+
Jan-Feb Stock Correction -9.08%1.37%
Brexit-5.57%-1.08%
Pre-Election Jitters-3.3%-1.37%
Risk Parity+ returns based on a live client portfolio in the "High" risk level and includes all costs and fees. S&P 500 performance based on index prices and includes all dividends re-invested.

For most investors to avoid the risk of these events, they must rely on overly conservative portfolios with limited upside. However, the Hedgewise Risk Parity framework achieved this stability while still outperforming the S&P 500 for the year.

This is extremely powerful both financially and psychologically. Prior to the Brexit and the US election, I had numerous clients asking whether they should consider lowering their risk levels or liquidating altogether. My advice was to remain steady, as the strategy was already built to handle such events. However, investors in traditional portfolios had no such security, and were often compelled to jump in and out of the market or to remain in cash. This is a significant hidden cost to most investors. Risk Parity eliminates the need for this kind of timing concern and thus protects investors without sacrificing long-term returns.

While Risk Parity is an excellent general framework, it can be run in many different ways. In 2016, Hedgewise proved that its approach to managing risk and balancing assets is superior to that of other providers.

AQR and Invesco run two of the largest Risk Parity mutual funds. Last year, Hedgewise maintained a high overall correlation to these funds while consistently outperforming both. Hedgewise also accomplished this while charging half the fees and incurring a significantly lower tax burden for every client.

Hedgewise 2016 Risk Parity+ Performance vs. Competitors

Hedgewise performed based on model portfolio set to a similar level of volatility to these mutual funds. Mutual fund performance includes all dividends re-invested.

For clients who remain nervous about the future, especially in the stock market, Risk Parity has consistently proven to be a safer way to grow your money.

New Momentum Framework Drives Higher Potential Returns

While Risk Parity is an excellent product, it is naturally somewhat conservative even at the highest risk target. This is because it is hedged across many different assets, which drives stability above all. For younger or more speculative clients, though, stability is often not the primary goal. They might gladly accept a few years of large losses in exchange for a higher overall return. The new Hedgewise Momentum framework helps to address this need.

Generally, "Momentum" refers to the use of various timing signals to reduce the risk of significant drawdown events on your portfolio. Unlike Risk Parity, this means you concentrate risk in certain markets most of the time, rather than diversify. For example, you might stay 100% in equities unless you hit some sort of downside trigger, and 100% bonds otherwise.

However, similar to Risk Parity, the success of any Momentum strategy depends entirely on the quality of its risk management system. Whenever a timing signal fails, you run the risk of incurring significant losses and/or missing potential gains. Since Hedgewise already has deep risk management expertise, though, it made sense to translate that into a timing framework.

While I am planning on publishing additional literature on this strategy later this year, the early results have been excellent. Here's a look at the model's performance for 2016 compared to a couple of the largest competitive Momentum ETFs on the market. You can quickly see how much performance is driven by getting the signals right - or wrong.

Hedgewise 2016 Momentum Performance vs. Competitors

Hedgewise figures are based on hypothetical models which are broadly consistent with those currently being used in client portfolios. Models rely on publicly available prices, assume dividends are re-invested, and include an estimate for all fees and commissions. Like Risk Parity, Momentum can be run at different risk targets, and this is set to the "High" risk level. Client portfolios using lower risk levels achieved lower returns. This framework was launched mid-year and these full year results are hypothetical.

While returns this year were very high, they come with additional risk. You maintain some protection from drawdowns, but it is not nearly as robust or layered as Risk Parity. As such, it makes sense to view this as a more "equity-like" return stream, including the possibility of a year like 2008. However, in exchange for that possibility, you gain the potential for far higher returns - like the 24% achieved in 2016.

This is an especially attractive proposition for investors who have most of their money in equities already. Since they are already assuming the risk of a year like 2008, why not utilize risk management to potentially boost returns further?

When discussing this product with clients, there is often confusion as to how to choose between Momentum and Risk Parity. Luckily you don't have to. Just like diversifying across assets makes a portfolio more robust, so does diversifying across risk management frameworks. This kind of quantitatively-driven portfolio construction is unlike anything you else you can find on the market.

Looking Forward to 2017

While lots of research is continuing behind the scenes, Hedgewise has already become a very powerful investing platform. Each individual Hedgewise product outperformed the competition as well as the S&P 500 last year. Whether your goal is conservative or aggressive, Hedgewise can customize a portfolio to exactly suit your needs. By combining different products together, clients have access to an even more robust portfolio. All of this can be done without any additional fee and in any kind of account - IRAs and even 401ks.

Despite this progress, there is still so much more potential. Unlike ETFs and mutual funds, Hedgewise is constantly continuing its research. Soon, there will be a number of alpha streams to choose from and advice on how to optimally layer them into your portfolio. More improvements will be made to the underlying risk system behind Risk Parity and Momentum. Hedgewise already offers a best-in-class product, but there is always the potential to make it even better.

I'm excited to continue to share the results, and 2017 is already off to a great start.

Disclosure

This information does not constitute investment advice or an offer to invest or to provide management services and is subject to correction, completion and amendment without notice. Hedgewise makes no warranties and is not responsible for your use of this information or for any errors or inaccuracies resulting from your use. Hedgewise may recommend some of the investments mentioned in this article for use in its clients' portfolios. Past performance is no indicator or guarantee of future results. Investing involves risk, including the risk of loss. All performance data shown prior to the inception of each Hedgewise framework (Risk Parity in October 2014, Momentum in November 2016) is based on a hypothetical model and there is no guarantee that such performance could have been achieved in a live portfolio, which would have been affected by material factors including market liquidity, bid-ask spreads, intraday price fluctuations, instrument availability, and interest rates. Model performance data is based on publicly available index or asset price information and all dividend or coupon payments are included and assumed to be reinvested monthly. Hedgewise products have substantially different levels of volatility and exposure to separate risk factors, such as commodity prices and the use of leverage via derivatives, compared to traditional benchmarks like the S&P 500. Any comparisons to benchmarks are provided as a generic baseline for a long-term investment portfolio and do not suggest that Hedgewise products will exhibit similar characteristics. When live client data is shown, it includes all fees, commissions, and other expenses incurred during management. Only performance figures from the earliest live client accounts available or from a composite average of all client accounts are used. Other accounts managed by Hedgewise will have performed slightly differently than the numbers shown for a variety of reasons, though all accounts are managed according to the same underlying strategy model. Hedgewise relies on sophisticated algorithms which present technological risk, including data availability, system uptime and speed, coding errors, and reliance on third party vendors.

Hedgewise Systematically Avoids Bond Correction
Posted in Market Commentary on 2016-12-03

Summary

  • Long-term government bonds lost over 9% in November, the second largest monthly loss since 1950.
  • Hedgewise algorithms automatically detected this risk and moved out of long-term bonds ahead of time, which significantly reduced losses in client portfolios.
  • Dynamic risk management will continue to protect the gains of this year, and to take advantage of higher yields and more attractive valuations when the bond market stabilizes.

Hedgewise Avoids Post-Election Bond Correction; Remains Up Over 10% YTD

The result of the election caught many investors off-guard, as most expected equities to collapse and safe-haven assets to soar if Trump won. However, his policy mash-up of "conservative populism" has most investors betting on heavy infrastructure spending, reduced taxes, and higher deficits. This has led to a dramatic crash in government bond prices along with a stronger dollar, which has lowered the value of commodities like gold.

While many Risk Parity mutual funds performed poorly as a result, Hedgewise algorithms nimbly avoided most of the losses in government bonds as a result of the improved risk framework rolled out over the summer. This provides another excellent, real-life example of how the system protects clients from drawdowns regardless of the environment, and further pierces the myth that Risk Parity is overly sensitive to interest rates. By managing risk intelligently, Hedgewise locked-in gains as bonds rallied through the first half of the year, while largely avoiding the subsequent reversal.

In November, Hedgewise portfolios were down approximately 1%. For comparison, a number of Risk Parity mutual funds lost 5% or more.

October Performance Summary, Indexes vs. RP High

Hedgewise performance based on a composite of live client portfolios using the Risk Parity "High" framework and includes all fees and commissions.

Hedgewise Significantly Reduced Bond Exposure As Risk Increased

From January to June of this year, bonds gained over 15% and were one of the main drivers of outperformance for Hedgewise clients. However, as interest rates continued to fall, the risk of a reversal began to rise. The Hedgewise system is constantly monitoring such risks, which led to a dramatic reduction in long-term bond exposure beginning in August.

Long-Term Bond Exposure By Month

Data based on Hedgewise models that are broadly consistent with those currently being used in client portfolios.

These adjustments have helped Hedgewise maintain its strong performance in 2016 despite a complete reversal in the bond market.

Looking Forward, Bonds Will Present Another Opportunity

Though asset class corrections typically result in mild losses for Hedgewise portfolios, they also create significant opportunities for future gain. In the bond market, for example, interest rates are now rising to much healthier levels, and will likely present an attractive entry point when the market stabilizes. This pattern helps explain why Hedgewise portfolios are so resilient. The algorithms are built to avoid the largest asset losses, but then to take advantage of the attractive valuations that ensue.

That said, it is never fun to lose money as we have for the last few months. Historically, however, there are many reasons to believe this will not last much longer or get much worse. Most significantly, the Hedgewise model portfolio has never experienced a maximum drawdown that exceeds the gains of this year. In the Risk Parity "High" portfolio, performance peaked near 14% in September, and has since given back about 3% or so. However, the maximum model drawdown (tested back to 1972) is a little over 12%. This means that if history is any guide, clients will never lose more than they gained in just one year.

It is important to reflect on this last point, as it helps demonstrate how drastically the odds are stacked in your favor. Many clients struggle to invest aggressively because of the fear of an upcoming crash, but within the Hedgewise framework, you will frequently make enough in a single year to offset even the worst-case scenarios. Given that, it really never makes sense to wait on the sidelines.

Disclosure

This information does not constitute investment advice or an offer to invest or to provide management services and is subject to correction, completion and amendment without notice. Hedgewise makes no warranties and is not responsible for your use of this information or for any errors or inaccuracies resulting from your use. Hedgewise may recommend some of the investments mentioned in this article for use in its clients' portfolios. Past performance is no indicator or guarantee of future results. Investing involves risk, including the risk of loss. All performance data shown prior to the inception of each Hedgewise framework (Risk Parity in October 2014, Momentum in November 2016) is based on a hypothetical model and there is no guarantee that such performance could have been achieved in a live portfolio, which would have been affected by material factors including market liquidity, bid-ask spreads, intraday price fluctuations, instrument availability, and interest rates. Model performance data is based on publicly available index or asset price information and all dividend or coupon payments are included and assumed to be reinvested monthly. Hedgewise products have substantially different levels of volatility and exposure to separate risk factors, such as commodity prices and the use of leverage via derivatives, compared to traditional benchmarks like the S&P 500. Any comparisons to benchmarks are provided as a generic baseline for a long-term investment portfolio and do not suggest that Hedgewise products will exhibit similar characteristics. When live client data is shown, it includes all fees, commissions, and other expenses incurred during management. Only performance figures from the earliest live client accounts available or from a composite average of all client accounts are used. Other accounts managed by Hedgewise will have performed slightly differently than the numbers shown for a variety of reasons, though all accounts are managed according to the same underlying strategy model. Hedgewise relies on sophisticated algorithms which present technological risk, including data availability, system uptime and speed, coding errors, and reliance on third party vendors.

November Commentary: Election Risk Is Just Like Any Other Risk, And It Is Being Managed
Posted in Market Commentary on 2016-11-07

Summary

  • Risk signals have rocketed in every asset class over the past few weeks, as markets are now pricing in a great deal of uncertainty related to the election.
  • Hedgewise strategies continue to strongly outperform YTD despite losses in October.
  • Client portfolios are well-prepared for any outcome on Tuesday.

Election Nerves Rattling Markets, But Some Assets Look Worse Than Others

Markets hate uncertainty. This is probably why until mid-October, election news was not having much impact. However, as the race has tightened, the general perception of risk has increased in every asset class, resulting in a sell-off across the board.

October Performance: Investors Selling Everything as Risk Increases

Bonds, Cmdty, and Stocks figures based on index prices and do not include any commissions or fees. Hedgewise Risk Parity and Momentum based on live client portfolios and do include all costs and fees. All dividends included and assumed re-invested.

In this kind of environment, losses are inevitable. However, some assets continue to look far riskier than others. Long-term bonds, in particular, are pricing in a greater possibility of continued losses than equities, and Hedgewise models have been adjusting accordingly. This kind of dynamic, asset class-specific risk management is key to long-term outperformance, which has been easy to see so far this year.

YTD Performance: Hedgewise Portfolios Continue to Significantly Outperform Equities

Bonds, Cmdty, and Stocks figures based on index prices and do not include any commissions or fees. Hedgewise models broadly consistent with those being used in live client portfolios and include all costs and fees. All dividends included and assumed re-invested.

While there will still be months of losses like October, all Hedgewise portfolios remain quite resilient against sustained drawdowns. It is impossible to say whether one will happen due to the election, but by systematically accounting for the possibility, your outlook is better regardless.

Avoiding the Biggest Losses is Hugely Meaningful and Very Possible

It is entirely possible to build a more stable, positive return stream by spreading risk across multiple asset classes and accounting for the possibility of extreme losses.

To help demonstrate this, I took a few different cuts of data going back to the 1970s. First, I examined the distribution of monthly returns of the S&P 500 compared to Hedgewise model portfolios (which use the same algorithms being used today, but a more limited set of asset classes and risk data).

Single month returns are a useful measure because they help show how months of poor performance, like October, are rare events. While they will still occur, they happen far less frequently in Hedgewise portfolios and have a far lower chance of repeating.

Distribution of Monthly Returns, 1972 to Present

Based on hypothetical models which are broadly consistent with those currently being used in live client portfolios, though limited to fewer asset classes and risk data. These do not include an adjustment for fees, but do include the cost of leverage and commissions. All dividends accounted for and assumed re-invested.

The bars in the graph show the frequency of one-month returns within each strategy. I've highlighted the portion of the graph which shows monthly losses. The S&P 500 has both higher and more frequent losses than either Hedgewise framework, meaning you experience many more months of small losses (3 to 5%) as well as a few which are catastrophic (10% or more). Also notice how much more effectively the Hedgewise portfolios cluster positive returns. This is consistent with the theory: we are optimizing for a stable portfolio with more consistent gains.

This remains true if you expand your time horizon to annual returns, which help to better highlight cumulative performance over time.

Distribution of Annual Returns, 1972 to Present

Again, the S&P 500 has a far greater likelihood of loss than either Hedgewise strategy. Risk management helps to eliminate significant drawdowns without decreasing overall returns or limiting gains. Importantly, this also demonstrates how equities often experience many consecutive months of poor returns, resulting in annual drawdowns of 40% or more. Hedgewise strategies show the opposite: poor monthly returns usually reverse, thus limiting your maximum annual drawdowns.

As an aside, notice that Momentum is a slightly more aggressive framework, and thus has a higher average return than Risk Parity but also a higher risk of loss. As such, it is generally only recommended to clients with a longer time horizon and higher risk tolerance.

Finally, I thought it would be a bit more intuitive to look at the realized return in each strategy by calendar year.

Return by Calendar Year, 1972 to 2015

I am particularly fond of this graph for a few reasons. It highlights both the consistency and severity of equity pullbacks, which have historically happened 1-2x per decade. It shows how the Hedgewise frameworks, while not immune to loss, have far fewer bad years and with relatively moderate drawdowns. Finally, it emphasizes one of the most important keys to successful investing regardless of where you have your money: if you just had a bad year (or month, or day), be patient. Historically, you have always been rewarded so long as you stay steady.

Wrapping Up: The Election Is Just Another Day

Markets could very well be surprised this Tuesday, but Hedgewise portfolios are already constructed to help mitigate any losses and to adapt as market conditions change. The reality is that risk is a constant force across all assets, and events like Election Day simply make it more obvious. In a way, such events help to shine a light on why financial risk management continues to gain prominence. While I certainly hope the outcome on Tuesday leads to more stability and economic growth in this country, I'm grateful to have my own money invested in strategies built on the foundation that anything might happen.

Disclosure

This information does not constitute investment advice or an offer to invest or to provide management services and is subject to correction, completion and amendment without notice. Hedgewise makes no warranties and is not responsible for your use of this information or for any errors or inaccuracies resulting from your use. Hedgewise may recommend some of the investments mentioned in this article for use in its clients' portfolios. Past performance is no indicator or guarantee of future results. Investing involves risk, including the risk of loss. All performance data shown prior to the inception of each Hedgewise framework (Risk Parity in October 2014, Momentum in November 2016) is based on a hypothetical model and there is no guarantee that such performance could have been achieved in a live portfolio, which would have been affected by material factors including market liquidity, bid-ask spreads, intraday price fluctuations, instrument availability, and interest rates. Model performance data is based on publicly available index or asset price information and all dividend or coupon payments are included and assumed to be reinvested monthly. Hedgewise products have substantially different levels of volatility and exposure to separate risk factors, such as commodity prices and the use of leverage via derivatives, compared to traditional benchmarks like the S&P 500. Any comparisons to benchmarks are provided as a generic baseline for a long-term investment portfolio and do not suggest that Hedgewise products will exhibit similar characteristics. When live client data is shown, it includes all fees, commissions, and other expenses incurred during management. Only performance figures from the earliest live client accounts available or from a composite average of all client accounts are used. Other accounts managed by Hedgewise will have performed slightly differently than the numbers shown for a variety of reasons, though all accounts are managed according to the same underlying strategy model. Hedgewise relies on sophisticated algorithms which present technological risk, including data availability, system uptime and speed, coding errors, and reliance on third party vendors.

How to Open An Account
Posted in Account on 2016-10-01

Hedgewise can begin managing your portfolio once you establish an account at Interactive Brokers, an unaffiliated company which has been rated the top online brokerage by Barron's for multiple years. By keeping an account at an independent custodian, you get peace of mind that your assets are fully SIPC insured and always under your control. Hedgewise is simply given permission to manage your portfolio on your behalf. After opening, funding, and linking the account to Hedgewise, your work is basically done.

Note that Hedgewise pays for all trading commissions and Interactive Brokers' account fees, such as monthly minimums and IRA fees. Hedgewise may also provide advice on outside accounts, such as 401ks, when your initial Interactive Brokers account has been established.

Once your portfolio is live, Hedgewise provides a separate client dashboard where you can see real-time performance. After account set-up, most clients only log-in to Interactive Brokers to manage deposits and tax statements.

Option 1: Request an Invitation from Hedgewise

Contact us at info@hedgewise.com to request an invitation from Interactive Brokers to set-up an account that will be automatically linked to Hedgewise upon approval. Then, follow these instructions when setting up the new account.

Option 2: Set Up a New Interactive Brokers Account Independently

If you don't have an Interactive Brokers account yet, you can set one up in about 30 minutes. Simply visit their site and note the following instructions when opening the account.

If you will be transferring assets from another brokerage, make sure you set-up the same account type in both places and that all of the information matches, like your name and social security number. For example, you would need to set-up a Roth IRA if you will be transferring assets from that type of account. If you will be funding the account from a bank, you can set-up an ACH relationship or wire money near the end of the application process.

Select an account type of "Reg T Margin", or simply "Margin" for IRA accounts, when presented the option. The default will be "Cash", but a Margin account is required with Hedgewise.

Request permission to trade US Stocks and Options contracts. Indicate that you have sufficient experience in these instruments.

Once your new account is approved, the final step is to link it to Hedgewise, which you can do via these instructions.

Option 3: Link an Existing Interactive Brokers Account

If you have an existing Interactive Brokers account, you can move it under Hedgewise, or partition it so that only part of the account is under Hedgewise control. See these instructions to do so.

We're Here to Help

If you have any questions about the account set-up, feel free to reach out along the way. After your account is set-up, we'll check to make sure everything looks right. It's easy to make adjustments if necessary.

Disclosure

This information does not constitute investment advice or an offer to invest or to provide management services and is subject to correction, completion and amendment without notice. Hedgewise makes no warranties and is not responsible for your use of this information or for any errors or inaccuracies resulting from your use. Hedgewise may recommend some of the investments mentioned in this article for use in its clients' portfolios. Past performance is no indicator or guarantee of future results. Investing involves risk, including the risk of loss. All performance data shown prior to the inception of each Hedgewise framework (Risk Parity in October 2014, Momentum in November 2016) is based on a hypothetical model and there is no guarantee that such performance could have been achieved in a live portfolio, which would have been affected by material factors including market liquidity, bid-ask spreads, intraday price fluctuations, instrument availability, and interest rates. Model performance data is based on publicly available index or asset price information and all dividend or coupon payments are included and assumed to be reinvested monthly. Hedgewise products have substantially different levels of volatility and exposure to separate risk factors, such as commodity prices and the use of leverage via derivatives, compared to traditional benchmarks like the S&P 500. Any comparisons to benchmarks are provided as a generic baseline for a long-term investment portfolio and do not suggest that Hedgewise products will exhibit similar characteristics. When live client data is shown, it includes all fees, commissions, and other expenses incurred during management. Only performance figures from the earliest live client accounts available or from a composite average of all client accounts are used. Other accounts managed by Hedgewise will have performed slightly differently than the numbers shown for a variety of reasons, though all accounts are managed according to the same underlying strategy model. Hedgewise relies on sophisticated algorithms which present technological risk, including data availability, system uptime and speed, coding errors, and reliance on third party vendors.

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