Vault Series: Doug Ramsey, CFA, CMT, The Leuthold Group, LLC

Playing the Market Melt-Up


The CFA Society Chicago gathered in the Vault Room at 33 North LaSalle to hear Doug Ramsey, CFA of Leuthold Weeden Capital Management discuss the likely future direction of the equity market. Ramsey is the CIO of The Leuthold Group and co-portfolio manager of the Leuthold Core Investment Fund and Leuthold Global Fund. .

Ramsey is both a CFA charterholder and a Chartered Market Technician (“CMT”). Holders of the CMT have demonstrated expertise in the theory, practice and application of technical analysis. He maintains Leuthold’s proprietary Major Trend Index, a multi-factor model that utilizes mainly technical data. The model contains a long history of market data going back to 1930. The data and subsequent market behavior discussed in the Vault Room included data up to May 12th of this year.

The Major Trend Index is comprised of 130 indicators that roll-up into 5 categories. The categories are comprised of quantitative and qualitative factors that influence the direction of markets. A plus and minus figure is computed for each category and a ratio that includes all the data is computed. The Major Trend Index yielded a ratio of 1.14 as of May 12th,  a ratio over 1.00 is considered bullish.

The age of the current bull equity market has many speculating that the bull market is nearing an end. Ramsey spoke at length as to how his model can be used to forecast a market top. The Major Trend Index concludes that the current bull market has more room to run. He believes that the equity market sell-off in early 2016 has set the stage for another leg-up in the current bull market.

The model used by Ramsey uses seven (7) stock market indices to monitor the health of the equity market.  They are as follows:

  • Dow 65 Composite
  • Dow Transports
  • Dow Utilities
  • Russell 2000
  • S&P 500 Financials
  • S&P 500 Cyclicals
  • NYSE Advance/Decline Line

Negative performance in at least 5 of these 7 categories has foretold a market top. Ramsey characterizes a market top as a “lonely” one. The bull market is propelled at its end by only one or two sectors before a bear market begins.

DSC_3744Ramsey then spoke at some length about the market sell-off that occurred at the beginning of 2016 and its effect on the current bull market. In May of 2015 six (6) of the seven (7) categories were in negative territory which is a strong indication of a market top. The equity market was essentially flat in 2015 and the beginning of 2016 a market correction occurred. A bear market did not occur as the index only fell 14%, by definition a bear market does not begin before a 20% sell-off.

The fact that a bear market did not occur after the 2015 signal does not necessarily negate the usefulness of the model. The year 2015 coincided with a trough in corporate earnings and the market reflected that. Ramsey believes that the 14% pullback that occurred in early 2016 has given new life to the current bull market which in his opinion does not look to have reached its top.

Following his presentation Ramsey spoke with a group of attendees on a number of topics including:

  • Momentum investing works, investing in sectors or companies that have already experienced price appreciation can still yield profit.
  • Tech valuations are not in bubble territory. Several slides in his presentation illustrated the strong earnings that are now being realized by tech companies.
  • You can make an argument that low volatility (higher dividend)  stocks may have reached bubble territory since investors appear to be drawn to these.

Vault Series: David Ranson, HCWE & Co.

David Ranson provided an enlightening presentation during the second part of CFA Society Chicago’s new Vault Series held on March 15 in the Vault Room of 33 N. LaSalle. Ranson is President and Director of Research at HCWE & Co., an independent investment research firm that was formerly a division of H.C. Wainright & Co. Ranson presented a simple, but effective model–based on his extensive research into capital market returns and correlations–that his firm uses to advise clients on tactical asset allocation. Their process uses historical market price movements to uncover predictive relationships between leading indicators and, highly-correlated, consistent outcomes.

The model’s simplicity derives from viewing the investment universe as comprising just four primary asset classes (exhibit 1):

  • Domestic bonds
  • Gold
  • Domestic equities
  • Foreign assets and physical assets (commodities, real estate, etc.)

Ranson 1_Page_02

(It’s important to note that the model considers gold as uniquely different from all other commodities.)

Ranson began by describing the role of capital migration in investment performance (exhibit 2). Capital migrates away from countries or markets characterized by economic stagnation, lower asset returns, declining new investment, and rising unemployment, and will flow to areas where the opposite conditions apply. Causes of the poor performance can be excessive government spending, taxation, and regulation, and “regime uncertainty” stemming from secretive or unpredictable policies.  These are difficult to quantify, but are usually accompanied by two more easily measured indicators: currency weakness, and rising economic anxiety (i.e., market stress).  These two indicators are the primary market signals the model relies on.  The price of gold serves to measure a currency’s value, and credit spreads measure economic anxiety.Ranson 1_Page_03

Ranson described four economic scenarios arrayed in quadrants defined by the change in the rates of economic growth and inflation (exhibit 3). Accelerating growth occupies the two lower quadrants and declining growth the top two, while accelerating inflation resides in the two right-hand quadrants and decelerating inflation on the left side. The scenarios (quadrants) determine the best performing assets.  Haven assets (bonds and gold) do best in the two upper scenarios when economic growth declines.  Risk assets (equities and commodities) stand out in the lower half of the array when economies accelerate.  When viewed laterally, financial assets (Ranson called them “soft” assets) that struggle against inflation reside on the left side of the array and those that do better against rising inflation (“hard” assets) reside on the right side.  Hard assets include gold, other commodities, real estate, and foreign equities.  (All foreign equities fit into this category because the model assumes they would perform comparatively well when an investor’s home currency is weak.) Putting the model together, shows gold as the preferred asset in the upper right quadrant (decelerating growth with rising inflation) and bonds preferred in the upper left quadrant (both growth and inflation decelerating). Domestic equities shine in the lower left quadrant (rising growth and decelerating inflation) while commodities and real estate are best in the lower right quadrant when both growth and inflation rise.Ranson 1_Page_04

Ranson presented statistics to support his model (exhibit 4). Separating the past 45 years of available data for the United States, he showed that when the rate of GDP growth accelerated from the prior year, the returns on equities and commodities always improved, while returns on treasury bonds and gold worsened.  When the rate of GDP growth slowed from the prior year, the reverse relationships held: returns on equities and commodities fell, and those for bonds and gold improved.Ranson 1_Page_05

Looking at inflation rates revealed similarly intuitive results (exhibit 6). When the CPI accelerated in a year, financial assets (both stocks and bonds) exhibited weaker returns, and gold and commodities did better than in the prior year.  When the CPI decelerated, financial assets enjoyed improved returns, while gold and commodities worsened.

Putting it all together (exhibit 11), Ranson presented an Asset-Allocation Compass with north pointing to heightened business risk, increasing investment anxiety, weakening economic growth and widening credit spreads. South points to the exact opposite conditions. East points to a weakening, or unstable, currency (measured by the price of gold) and west to a strengthening currency. He then filled in the best asset classes for eight points around the compass. His four primary asset classes occupied the diagonal compass points, corresponding to their positioning in the quadrant array:

  • Gold in the northeast
  • High quality bonds in the northwest
  • Domestic equities in the southwest
  • Hard assets in the southeast

Ranson 1_Page_12

Ranson assigned the primary points of the compass to sub-groups of the primary classes. The most intuitive one was Treasury Inflation Protected Securities (TIPS) pointing west (declining inflation, strengthening currency). Pointing south toward strengthening growth were risk assets: B-rated junk bonds, MLPs, and developed market foreign equities. Pointing east (rising inflation and a falling currency) were commercial real estate and C-rated junk bonds, assets exhibiting little influence from changing spreads and more from the price of gold. The distinction between B and C-rated junk bonds may be surprising but Ranson’s research has shown that while they are correlated to each other, C’s are much better correlated to the gold price while B’s correlate more to credit spreads.

The compass had nothing listed for north (weakening growth and heightened risk perceptions). Ranson noted that he was not aware of an asset class that would fit well in this slot but, like a gap in the periodic table of the elements, he could describe the attributes he expected it to exhibit. It would have to respond positively to widening credit spreads, and be little effected by the price of gold (or value of the dollar).

In response to a question following his presentation, Ranson pointed out that the correlations his model depends on often take several years to manifest themselves, so the model works best for patient investors with very long investment horizons.

Vault Series: Melissa Brown, CFA, Axioma


Managing risk, specifically equity market risk, was the topic of CFA Society Chicago’s new Vault Series on January 11. The series brings noted investment experts to Chicago on a bi-monthly basis to share their thoughts and insights on the investment scene. The name comes from the common-area conference room in the Society’s new home at 33 North LaSalle Street, a space that was, indeed, once the safe deposit vault for a bank. The latest flat screen video monitors hang over the bare steel safe deposit boxes still line the walls. The day’s speaker was Melissa Brown, CFA, Senior Director of Applied Research at Axioma, a provider of risk management and portfolio analysis models and tools serving asset managers and institutional investors. Brown provides perspective and insight on market risks as measured and quantified by Axioma’s data and analytics.

Brown began by noting there are many types and measures of risks (e.g., Value at Risk, standard deviation, credit risk, liquidity risk, etc.) but Axioma defines it as the expected volatility of a market (they focus on equity markets) over a defined investment horizon. It is a function of volatility and correlations, both of which they see as being persistent over time, and therefore possible to forecast from the past. Currently, Axioma sees benchmark risks as low, but volatility is unlikely to decline further. In 2016, volatility declined in most equity markets around the world, despite a jump in mid-year following the “Brexit” vote. This was more pronounced in U. S. markets than other countries, and also in developed markets more than emerging markets. The level of volatility at the end of the year was not materially different from levels in 2000.

Axioma decomposes risk by looking at five components:

  • Portfolio holdings (generally are they more or less risky?)
  • Characteristics of the holdings (sector, industry, cap size, etc.)
  • Security-specific risks (which rose in 2016)
  • Factor volatility (an important component in Q4)
  • Correlations

The last one, correlations, is very low now and is the reason market volatility is low despite the relatively high volatility of individual securities.  Sector also plays an important role here. In the U. S. in 2016 there was a wide dispersion of risks and returns by sector. Consumer discretionary, Technology, Energy, and Materials all did well with declining risk. Finance, real estate, telecom, and utilities had very mixed results, but also with generally lower risk (except for finance). The dispersion of sector returns peaked in November at levels near records for Axioma’s database. Brown pointed out that the low correlations could provide an opportunity for active management to outperform passive.

Taking an international view, Brown noted that as of the end of the year, risk in developed markets is highly concentrated (see Italy, Greece, and Iceland) while in emerging markets, risk is more widely (and evenly) scattered. This situation developed during the fourth quarter and reflects the strength of the dollar, which is more of a challenge for emerging markets than for developed. Switzerland just nudged out the U. S. for the lowest risk by country at year end. Mexico holds the distinction as the riskiest country, again reflecting the weakness of the peso since the U. S. election.