Q4 Market Commentary

“Bull markets are more fun than bear markets.” – Bob Farrell

The historical average US Stock market return (S&P 500 Index) since 1950 for the month of December is 1.49%1. Since 1950, there have been 17 Decembers exhibiting flat or negative returns (out of 69 years). Of those 17 years, only 6 had losses worse than -3.0%. In December 2002 the market returned -6.03%, the (at the time) worst December during this time period, and almost 2.5 standard deviations from the average historical December return.

December 2018 was the worst December in the US Stock market since the Great Depression, posting a -9.18% loss. This means we saw nearly $3 trillion in market cap2 disappear. October 2018 also saw $3 trillion in lost market cap, putting the quarter near almost a $5 trillion dollar loss in the value of US Stocks, on an estimated $33 trillion market. That is nearly equivalent to the size of the Australian, German, and Canadian stock markets combined3. It is also larger than the GDP of the World’s third largest Economy, Japan4. In short, December’s losses in the US (and globally) were extraordinary.

It is hard to pinpoint which specific events or data points explain the corrections in October and December, but fears of a global growth slowdown, a lack of clarity surrounding the US/China Trade war, and fears of a Federal Reserve policy error seem plausible.

I think sell-offs in Q4 were largely event-driven rather than the result of deterioration in economic or company fundamentals. October was initiated by a very poorly received outlook by the Federal Reserve wherein Chairman Jerome Powell stated that “…we are a long way from neutral on interest rates.”

There are many implications of higher interest rates such as; higher interest payments by consumers (and thus less money to spend on goods and services), higher borrowing costs for companies (curbing growth & expansion), and tightened underwriting standards for banks.

In my opinion, the worst implication of a Fed policy error (hiking rates too high too fast) is limiting the flow of capital in the economy, as this is directly related to banks’ willingness to extend credit. Banks may be less willing to lend if their costs are rising
(short term rates) and their interest income is not.

Combine the potential for a Fed-manufactured downturn in the Economy with a constant barrage of conflicting news on the US/China Trade war, and you get frothy markets. Add in algorithmic trading and you can end up with violent, rapid swings in prices that are disconnected from rationality, much as what we saw in December; however, I would like to remind investors that although it is uncomfortable to go against the crowd, it often provides the opportunity to generate outsized returns relative to the market.

We expect to see more volatility in 2019 unless we get clarity on the US/China Trade talks, and unless earnings are better than expected. If earnings start to show deterioration, or if companies release negative outlooks, this will add fuel to the volatility fire. On the positive, the Fed has cleared up some confusion from their December 17 statements and investors have priced this into the market, making it not as big of a question mark heading into 2019.

Of course, it is hazardous to try and predict which direction the market will go with a high degree of confidence. As we go into 2019, Silverhawk will stick with our Core investment philosophy and we will continue to hedge our tail risk exposures. We will also be reallocating into more high-quality companies with stable margins, strong cash flows, and low leverage (Value stocks). A defensive strategy in this environment makes the most sense. Stay invested, hedge the downside risk, and just expect to see more volatility ahead so you are not surprised when it occurs.



Political risks, unwelcomed Fed comments, and technical resistance levels came to a head and created what you might call a “perfect storm” in December. The S&P 500 was bumping against its prior resistance levels from the October selloff, the White House caused confusion on a Trade Truce with China, and then the Fed raised rates and took an unexpected hawkish stance. Throw on top of this that managers were tax-loss harvesting both in the normal course of year end business, and perhaps this loss selling was exacerbated by the substantial increase in stock values since 2009, and you get multiple veins of selling pressure. Then the day after Christmas, markets rallied nearly 5.0% across the board and look to be bouncing off the December 24 low for a retest of 2600.

4Q2018: US Stocks (as measured by the S&P 500 Total Return Index) returned -14.0% during Q4, led by the selloff in Energy (-24.3%), Industrials (-17.8%), Technology (-17.7%), and Discretionary stocks (-15.5%). The latter three sectors are also the top outperformers in the markets the past three years, and (generally speaking) the companies that have crushed the market leading up to a selloff are the ones to come crashing down as smart money takes their gains and moves on, leaving retail investors to finish the job.

Defensive sectors (as measured by the SPDR select Sector Real Estate, Utilities, and Consumer Staples ETFs) faired less poorly but still were negative (with the exception of Utilities) on the quarter. Despite the large selloff in Consumer Discretionary stocks, they actually managed to stay in the green on the year (+30 basis points).

Q4 saw two meaningful market corrections in the months of October and December (-10.6% and -15.2%, respectively, peak to trough). The selloff in October really began the day of the Fed Policy meeting (October 3) when Jerome Powell made the statement that “We’re a long way from neutral on interest rates.” This is an indication that the Federal Reserve will continue to hike interest rates, which raises the cost of borrowing and price of expansion to the economy. It is reasonable to understand why investors in the US Equity markets are so frustrated with these comments, as the Fed is likely meeting their dual mandate of maximum employment (unemployment is at its lowest level since 1969) and stable prices (inflation was around 2.25% compared to the average level since 1940 of 3.79%). However, all we can go off is what the Federal Reserve communicates, and what they communicated in October is higher interest rates are coming. The uncertainty behind the impact these rate increases can have on the Economy is one thing that shook markets, and eventually led to the first 10% correction on the S&P 500 since 2015. Fed Policy errors have occurred repeatedly since its inception in 1913, and in some cases have even triggered recessions. It is difficult to say if they are following a similar path now, but I do not believe we are at the point where 25 to 50 basis point higher interest rates will have a material impact on the credit cycle. Interest rates (while rising) are still very low by historical standards, and in previous environments when the Fed is raising interest rates it has been to help fight inflation/an overheating economy, neither of which are flashing red at the moment.

That brings us to the December selloff, fresh in everyone’s memory. The start of the December correction really was kick-started the week following the G20 Summit in Buenos Aires, which culminated December 1st when President Trump announced that there would be a temporary “Trade Truce” on Tariff escalations after he and Xi Jinping discussed the issue over the weekend.

This news came only three days after Jerome Powell (in stark contrast to the October communication) stated that current interest rate levels are “just below normal” at the November 28 Fed meeting and the market was in full-blown rally mode heading into the weekend. Prior to these developments, the market was slowly rebounding from its retest of the October lows that began on November 9th when the S&P 500 failed to close above 2800 for the second time since October.

From the day of the November 28 Fed meeting, to the Monday following the G20 summit (December 3), the S&P rallied from 2670 to 2800 around market open on Monday (a 4.90% increase in a matter of really 2.5 trading days). Too high, too fast, and right into the previous resistance level we failed to break through in October and November. Combine this significant technical breaking point with same-day news from the White House that there wasn’t an actual agreement made between Trump and Xi Jinping at the summit, and you get December 2018.

If the dual mandate boxes are checked, and we are “just below neutral” interest rates, what reason could there be to increase interest rates? This is the question of 2019. The Fed SHOULD raise interest rates to prevent an economy from overheating as inflation begins to increase; however, there have been no signs inflation is going to rise in a meaningful way. The past quarter was brutal to say the least, but I think it makes sense when you consider the implications of what a potential escalation in Tariffs could mean, what a Fed policy error might trigger, and all of this right around the time of tax loss harvesting and portfolio rebalances. To me, the week leading up to Christmas and Christmas Eve was more a function of a type of “volatility momentum” in which as the selloff deepened, Managers were provided with more opportunities to book losses for tax-planning purposes that weren’t available just a few weeks prior.

What transpired this past year in the financial markets is a perfect reminder that no matter how sophisticated your forecasting abilities or how many hours you put into research, there will always be an unpredictable component to investing. This unpredictability, confusion, and uncertainty is what has fueled the recent market sell-offs, not deteriorating fundamentals of the economy or companies operating inside of it. This is also why having investing rules is so important.

Since their December rate hike, members of the Federal Reserve (and Powell) have softened their tone a bit; however, until we get a clear understanding of the US/China Trade war, the conversation will continue to be centered around uncertainty, which means more volatility ahead. A


When markets become volatile and wave after wave of losses begins taking hold, it is easy to panic. It is easy to fall victim to a state of fear and the feeling of uncertainty, questioning just how far the losses will go.

It is near impossible to predict with any degree of confidence when and where markets will correct down, and when they will recover; however, we know and accept that these types of events are normal in the course of a full market cycle (normally 8 -10 years). Corrections in the financial world are generally defined as a -10% decline in price from its recent highs. Bear markets are generally defined as -20% in losses off of recent highs. But bear markets do not happen overnight, corrections do not mean bear markets, and bear markets do not always mean recessions. We will refer to corrections that resulted in recessions within one year of the start of the correction as “cyclical corrections” and corrections that do not as “structural corrections”.

It is too early to conclude if this is the start of a cyclical or structural correction; however, it is prudent to review what the economic environment was like in prior corrections that preceded recessions. We also take a look at some technicals to see if the charts confirm/refute the fundamental story.

If we go back to 1954, there were 15 corrections worse than -10%5. December 2018 was the 11th worst correction during this time period. Eight of these corrections ultimately preceded recessions that occurred within 1 year from the most recent high (see notes section for years), while six of them (seven if you include 2018) did not. One indicator that gives some perspective into the stage of an economy (and if corrections likely structural rather than cyclical) is the level of unemployment.

The 1960 and 1982 recessions were very short, and came very quickly (both within 2 years) after a previous recession occurred. These back to back recessions never really gave the economy a chance to recover and evolve into a full market cycle, and thus the unemployment levels during these periods were already at higher levels (6.2 and 7.5, respectively). January 2019 will mark the 104th month from the end of the Great Recession in June 2009, making this the third longest economic expansion going back to 18546. As such, we will focus on the corrections that occurred following (or within) a normal business cycle; all figures and discussions hereafter will exclude 1960 and 1982 from the analysis.

The six cyclical corrections going back to 1957 were associated with unemployment levels near cycle lows in the year leading up to the correction with the average level of unemployment at 4.5% (year preceding start of correction). In addition, in all six cyclical corrections the unemployment rate increased from the year preceding the start of the correction up to the market lows, with an average increase of +34% (+1.50 percentage points). This compares to the average level of unemployment for structural corrections at 6.6%. In addition, from the year prior to the start of the correction to lows of the correction, unemployment levels decreased in all six periods, with the average decrease being -19% (-1.30 percentage points).

Using this sample, it seems that cyclical corrections begin when unemployment is near lows and further into the expansion, whereas structural corrections occur more toward the middle of expansion when unemployment still has room to move lower as the economy continues its recovery. Unemployment currently sits at 3.90%, down from 4.20% at September 30th, 2017 (the year prior to the start of this recent correction, which began in September). The unemployment rate declines over the past three years have been slowing down in the speed at which they are falling. We are also likely near “maximum employment” as judged by traditional economics of supply and demand in the labor force. The data suggests that the current unemployment level is nearing (or at) cycle lows, and that the corrections in 4Q seem more likely to be a precursor to a cyclical, rather than structural correction. The only thing missing to really validate that theory is inflation, which remains at or near to the Fed’s long-run target of 2.0%. We will caveat this with it is impossible to predict recessions, especially from a review of only one economic indicator. In addition, the average full correction has taken 357 days going back to the 1950s, and we are at day 100 of the current correction. Nonetheless, the numbers tell a compelling story, the chart is freaky, and when you consider the length of the current expansion and widening positive output gap7, it is hard for me to accept a scenario in which unemployment moves lower in any meaningful way without some sort of catalyst.

Inflation is another useful measure to review when considering structural versus cyclical corrections. The sample period shows that for cyclical corrections, by the end of the correction the average rate of inflation was at 4.60% compared to 2.33% for the structural corrections. Inflation currently sits at 2.18% but has increased from 1.70% at September 30th, 2017. If the inflation story is going to support this is a cyclical correction, we would likely need to see inflation continue to rise in 2019. The current 5-year breakeven inflation rate is at 1.51%8 and the general consensus among Fed members is that inflation should remain checked around 2.0%8 into 2019. Both of these figures suggest a structural correction for now; however, it is possible to see inflation picking up as slack in the labor force continues to tighten and the impact of tariffs continues to widen.


Whether you believe that charts and technical analysis can help to predict stock price patterns or not, fund managers, traders, and retail investors do use them. A lot. Not to mention the amount of algorithmic trading that is done in the market today that is in most cases based purely on technical trading levels, moving averages, and volume.

The above chart shows the S&P 500 price (^SPX; green and red), and the 20, 50, and 100-week simple moving averages (SMA) back to year 1997 to capture three bull markets and two (almost three?) bear markets. The 100-week SMA ORANGE LINE has been a fairly consistent level of support and resistance around transitions from bull to bear markets. It was the level of support from the October selloff, and then held support four additional times during the initial stages of the most recent selloff in December. After the Fed’s December 17 press conference (discussed above), the support failed, and sellers were able to push the price well below the 100-week SMA for the first time since June 2016. The measure is not perfect, as it has failed on support before (late 2015/early 2016 correction) and subsequently broken back above into new highs. We currently are sitting at 2531, about 3.0% below the average. The moving average also is beginning to align almost perfectly with the 2600 level, another key level to watch price and volume action around.

As we head into 2019 I think both the 100 week SMA and the 2600 level will tell the story of what is likely to happen during the next quarter. If we can break back above the 100 week SMA like we did in 2016 and then close above that level multiple days (preferably a week or two), then it is possible we attempt to test 2700. Stronger than expected earnings and some clarity of the US/China trade truce could push prices back above that level. I am not confident we will see stronger than expected earnings; however, as there tends to be more analysts than not that overshoot forecasts toward the top of a cycle both due to behavioral biases and also due to their bottom-up forecasting models.

Taking a step back, it seems that the economy still has juice left in the tank. Borrowing costs (while rising) are still low, the labor force is strong and stable, inflation is low, and companies are still generating solid earnings. However, it is likely that we are going to see slowing growth into 2019 both domestically and internationally. To us, there are more signs pointing to increased volatility and further price declines ahead than there are positive signs.


How do you protect against volatility and further downward pressure on the market? You can hedge using derivatives such as options contracts or futures, or you can invest in lower-risk assets such as bonds and cash or even defensive equity strategies. You can also diversify into non-correlated assets and use certain types of insurance products, such as fixed indexed annuities, to reduce risk in your portfolio while maintaining a steady stream of income and upside potential to the market. We use a combination of all four which we feel allows us to control the absolute level of risk taken in the portfolio at any given time without sacrificing returns.


The timing of when to reduce your risk exposure is impossible to know head of time, so all you can do is develop rules to follow so that no matter what happens in the market, there is a plan to follow and execute. This helps to eliminate the possibility that you make an emotional decision as wave after wave of bad news comes through media, and the crowd mentality starts to creep its way into the decision-making process. We provided an example of a simple trend- $1.00 following risk $0 management strategy. It compares the returns and drawdowns of a passive, buy and hold S&P 500 index portfolio, and an S&P 500 portfolio with a trend-following risk management rule that rotates to 3-month treasury bills if the price of the S&P 500 is below its 12-month moving average.









Across the lookback period from 1954 to 2018, the trend following strategy was triggered in 216 out of 780 months, or 27% of the time. The drawdowns of the portfolio were reduced from -52.6% on the S&P 500 buy and hold strategy to -24.1% on the trend following strategy. The graph above provides the hypothetical growth of $1.00 and overlays (the gray bars) the months during which the portfolio using the trend-following rule was in treasury bills.

Trend following strategies are not guaranteed to work in the future, but the benefits of such a risk management strategy warrant consideration for any investor in stocks. Invest in stocks when the trend is positive and get out when the trend turns negative. For taxable investors it becomes more challenging due to tax implications; however, derivatives markets allow us to hedge the portfolio in a way that mimics a cash position, usually called a “synthetic cash” position. The point is that nobody knows which way the market will go. Up, down, sideways, or in circles. But by following the trend, it can help to curb losses during large drawdown periods and reduce the psychological agony (called loss aversion) that nearly all investors feel when markets free-fall.


Despite the ongoing Tariff war headlines with China, the World is becoming more globally integrated every year. This has allowed companies to access new markets outside their boarders, improve cost efficiency and inventory management, and has undoubtedly helped fuel the growth we’ve seen the past two decades in global GDP. This has also led to a reduction in the diversification benefit of using International Equity exposures as a component of a well-diversified portfolio.

The most relevant case of when nearly all publicly traded (and some non-publicly traded) asset class correlations go to 1.0 is the Global Financial Crisis of 2008. Correlations between International Equities and US Equities went from 0.60 (June 2007) to 0.97 (June 2009). Investors following a globally diversified portfolio witnessed drawdowns in excess of 60% on a buy and hold strategy (S&P lost roughly 56% from high to low; MSCI EAFE lost roughly 62%; Emerging markets lost nearly 66%). While this magnitude of recession is not frequent, similar increases in correlations occurred back in the 2000-2001 correction/recession, and the 2015-2016 market selloff fueled by the devaluation of the Yuan.

What transpired in 2018 is a perfect demonstration of how diversification through only publicly traded asset classes produces costly (and painful) results. Just when you need the benefit of diversification most (via an international equity, or fixed income exposure), it has failed to provide such benefit. What has not failed to do this? What types of asset classes can you add to a publicly-traded securities portfolio to truly obtain diversification? The answer to this varies across countries and across time periods, but we feel (and the data supports us) alternative assets (specifically, direct-investment into hard assets) provide the best opportunity to accomplish this. Alternative (Opportunistic) assets can really be thought of as non-traded, or “non-traditional” assets and include such investments as Real Estate, Energy assets, Commodities, Hedge Funds, Lending, Private Equity, among others.

One of the main reasons publicly traded markets become so volatile and highly correlated is a combination of behavioral bias, and easy access to funds. When the crowd starts panicking and sell-offs begin to ensue, investors have the ability to sell out of their position within minutes (provided liquidity is there). With alternatives, they generally cannot be liquidated in a timely fashion without high costs of doing so. This has the added benefit of saving investors from themselves when they normally would be selling low, which is the classic retail investor mistake as they can no longer stomach the losses. Selling breeds more selling as the herd mentality takes over. This is an evolutionary behavior exhibited by most living animals, as our chances of survival increase if we stay with the herd.

To take just one asset class, Real Estate, and put it up on the same chart as before when looking at International Equity is a useful exercise:

The yellow dotted line shows that the average correlation between the National Council of Real Estate Investment Fiduciaries (NCREIF) Index, which is a widely used benchmark for non-traded direct investment real estate, and the S&P 500. The average correlation is 0.04, almost no linear correlation between the two. This compares favorably to the MSCI ACWI Ex-US in terms of diversification benefits to a portfolio as it had an average correlation of 0.81 across the same period. An observation to take away is that during severe financial disasters such as 2008, most all correlations between assets increase toward 1.0; however, as we discussed above the key difference between publicly traded securities and hard assets/alternatives is that panic selling cannot ensue (which reduces the problem and helps to avoid locking in real losses to the portfolio). In addition, real estate is backed by hard assets in most cases, which typically have tangible value whereas publicly traded equity securities can go to or near to zero.

In summary, investors can no longer can allocate blindly to a balanced portfolio of global publicly traded asset classes and accept that will have reduced risk and reasonable returns. It is necessary to go beyond what is easy, or simple to invest in and do the work necessary to understand how these other markets can provide real benefits to client portfolios.


The sell-offs in October and December seem to be precursors for what to expect heading into 2019. Volatility tends to cluster, going from sustained low/stable periods of trading to sustained elevated/volatile periods of trading10. As long as there is uncertainty around the Federal Reserve’s policy stance, Trade, European political issues, and domestic political risks, volatility should be here to stay as investors struggle to figure out the best place to invest their capital. If earnings start to come in worse than expected, or if companies issue negative outlooks, this could fuel the fire. The US Government shutdown might also begin to cause more concern than I think people realize is possible, especially if it drags into the first quarter. How far it goes and the real impacts it will have on local economies can’t be known, but I think the surprise there is to the downside, not positive.

We will be looking to overweight our exposure to high quality value stocks that demonstrate stable operating cash flows, margins, and efficiency through business cycles. If you can find these types of companies trading at a discount, there is additional risk protection embedded in that discount. We have already implemented our hedging strategy which was triggered at the December 31, 2018 monthly close on the S&P 500 below its 100-week moving average. With the high level of uncertainty in the market and the recent rebound in stocks, it is likely that we rally back up to 2600 or 2700 on the S&P 500 by mid-January but it is very likely that we retest the December lows at some point in the 1st quarter. A scenario in which we may break through those levels would require clarity on the US/China Trade Agreement, the Fed’s stance going forward, and stronger than expected earnings.

In the current market, it makes sense to play defensively but not completely abandon your long portfolio strategy. There are very real risks to the sustainability of the current economic expansion, and investor psychology seems to be shifting toward the pessimistic versus optimistic; however, there are certain outcomes to this scenario in which we can sustain another leg up in the markets to potential new highs during 2019. Right now, though, it seems more likely that the 2018 selloff was a precursor to a larger cyclical move lower.


Past performance is not a guarantee or reliable indicator of future results. All investments discussed herein contain risk and may lose value. US Treasury Bonds are considered risk-free assets under the assumption that the initial principal invested into the bond is secured by the full faith and credit of the United States Government. An investment in Treasury Securities may still lose value depending on your time horizon relative to the maturity date of the bond. Equities can decline in value from both perceived and actual market, economic and industry conditions. The views expressed herein are that of the Portfolio Management Division of Silverhawk Financial and do not necessarily represent the views or opinion of Silverhawk Financial as an entity. The discussion herein is broad in scope and its purpose is purely informational in nature. This document does not represent a financial recommendation, proposal, or suggested allocation strategy. The data used in the graphics was derived from reliable sources widely used in the financial marketplace but is not guaranteed to be accurate. No part of this material may be referred to in other publications or reproduced in any form without express written permission by Silverhawk.


1. S&P 500 Price Index (^SPX).
2. Based on holdings in the Russell 3000 Index, and estimated market caps at December 31, 2018 versus September 31, 2018.
3. Australian stock exchange (www.asx.com.au); German Deutsche Börse AG; TMX Group Limited
4. World Bank’s national account data. https://data.worldbank.org/indicator/NY.GDP.MKTP.CD?locations=JP
5. S&P 500 Price return Index (^SPX) historical price data from Ycharts. Correction defined as % decline in price from most recent all time high. Days calculated from the day after the all time high, to the correction period trough (low).
6. NBER previous trough to this peak data; www.nber.org/cycles.html
7. Referred to as the Output Gap, measured as the actual output of an economy minus the potential output of an economy.
8. FRED; https://fred.stlouisfed.org/series/T5YIE
9. December 18-19 Fed minutes; https://www.federalreserve.gov/monetarypolicy/fomccalendars.htm
10. https://www.lpsm.paris/pageperso/ramacont/papers/clustering.pdf