Composite Macro ETF Weekly Analytics (8/30/2015)

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COMPOSITE ETF CUMULATIVE RETURN MOMENTUM

These charts show the sum (cumulative) of the daily returns of each composite ETF over the specified period. The daily return is calculated as the log of the percent change between daily adjusted close prices.

These charts help determine asset class return momentum. This is important because momentum is arguably the strongest and most persistent market anomaly. Poorly performing asset classes are likely to continue under performing while outperforming asset classes are likely to continue their relative strength. 

last 63 trading days

Source: Yahoo Finance

last 21 trading days

Source: Yahoo Finance

last 10 trading days

Source: Yahoo Finance

last 5 trading days

Source: Yahoo Finance

COMPOSITE ETF CUMULATIVE RETURN (BEST VS WORST VS BENCHMARK)

These charts visualize the cumulative return performance of the best and worst performing asset classes over the specified period. These best and worst asset classes are then compared to a benchmark ETF composite represented by the Large Cap category. 

These charts help give investors an idea of how an actual investment in the represented asset classes would have performed over the period in percentage terms. This also helps visualize the relative strength or weakness of various asset classes as compared to the most common Large Cap benchmarks.

LAST 63 TRADING DAYS

Source: Yahoo Finance

last 21 trading days

Source: Yahoo Finance

last 10 trading days

Source: Yahoo Finance

COMPOSITE ETF Z-SCORES OF AVERAGE rolling RISK ADJUSTED RETURNS

These charts show the z-scored average of the composite ETF's rolling risk adjusted returns.  Risk adjusted returns are used to improve the robustness of the chart and the information presented. 

By examining the standardized values we can see how each asset class performed relative to the group. This adds further clarity to the relative strength (weakness) of asset class return performance. 

last 63 trading days; rolling period = 10 days

Source: Yahoo Finance

last 21 trading days; rolling Period = 5 days

Source: Yahoo Finance

last 10 trading days; rolling period = 5 days

Source: Yahoo Finance

COMPOSITE ETF Risk-adjusted return correlations heatmap clusterplots

These charts visualize the correlations of the asset class returns over the specified period. Red indicates highly correlated returns while blue indicates negatively correlated returns. 

By examining a clustered heatmap investors are able to quickly determine the intensity and grouping of asset return correlations. Generally speaking, investors should seek to diversify their portfolios by holding uncorrelated assets. Better diversification among asset classes helps to lower overall portfolio volatility with the implication of improving a portfolio's long term performance. 

last 63 trading days

Source: Yahoo Finance

last 21 trading days

Source: Yahoo Finance

last 10 trading days

Source: Yahoo Finance

Was David Woo Right; Was the Selloff Exacerbated by Risk Parity Strategies?

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Today after the close Bloomberg TV had David Woo, Managing Director and Head of Global Rates and Currencies Research at Bank of America/Merrill Lynch, on to provide some insight regarding recent market action. More specifically, he addressed how Chinese and American markets are linked.

He dropped a lot of gems during his segment but one point really struck a chord with me. He said that the recent selloff has likely been exacerbated by "Risk Parity Guys". 

If you're unfamiliar with 'risk parity' here are some good working definitions:

“Risk parity (or risk premia parity) is an approach to investment portfolio management which focuses on allocation of risk, usually defined as volatility, rather than allocation of capital.”
— https://en.wikipedia.org/wiki/Risk_parity
“A portfolio allocation strategy based on targeting risk levels across the various components of an investment portfolio. The risk parity approach to asset allocation allows investors to target specific levels of risk and to divide that risk equally across the entire investment portfolio in order to achieve optimal portfolio diversification for each individual investor. ”
— http://www.investopedia.com/terms/r/risk-parity.asp

Essentially, this says that risk parity strategies approach portfolio allocation based on the underlying asset's risk/volatility as opposed to traditional portfolio allocation which allocates capital based on holding some specified amount of each asset class. 

David Woo went on to elaborate that traditional asset class correlations began to break down during this selloff, implying that traditional methods of diversification were no longer viable and as a result any fund/fund manager which allocates capital on the basis of 'risk parity' or similar strategies would be forced to reduce risk across all asset classes. 

I thought this was a brilliant insight and immediately wanted to see if I could find some evidence that would support his analysis. 

To do this I used my Composite ETF model to plot rolling correlations of the 'Bonds' ETF composite vs the ETF composite of each asset class. The reason I use rolling correlation is because of the inherent link between asset correlations and volatility. Specifically, as correlations across assets/asset classes rise diversification decreases and volatility/tail risk increases.  I've selected some of the more interesting plots that lend credence to his statement.

bonds vs asia-pac equity

Data Source: Yahoo Finance

bonds vs consumer discretionary

Data Source: Yahoo Finance

bonds vs consumer staples

Data Source: Yahoo Finance

bonds vs europe equity

Data Source: Yahoo Finance

bonds vs financials

Data Source: Yahoo Finance

bonds vs global equity

Data Source: Yahoo Finance

bonds vs industrials

Data Source: Yahoo Finance

bonds vs large cap

Data Source: Yahoo Finance

bonds vs materials

Data Source: Yahoo Finance

bonds vs mid cap

Data Source: Yahoo Finance

bonds vs precious metals

Data Source: Yahoo Finance

bonds vs real estate

Data Source: Yahoo Finance

bonds vs small cap

Data Source: Yahoo Finance

bonds vs telecom

Data Source: Yahoo Finance

After reviewing some of the evidence I would say David Woo is on to something.  To be fair however, rising correlations among this many asset classes over a short time period is likely to cause multiple types of fund strategies to reduce risk exposures quickly. 

If you haven't seen his segment I'd recommend trying to find it. Either way I'll be on the lookout for his analysis going forward. 

European Sovereign Debt Crisis Redux, What's the Playbook?

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I wrote this post originally  as a guest feature on RectitudeMarket.com. Check out the website for great investment ideas and original analysis.

Now that Greece has officially rejected austerity it’s time to examine our 2011 playbook to get some clues as to what might happen. More importantly depending on your timeframe there should be plenty of strategic and tactical strategies for profit due to the increase in volatility.

Let’s compare EUR/USD, Treasury yields, EU yield spreads, and other Developed Markets from 2011 to 2015 for insights on portfolio positioning.

EUR/USD Annualized Rolling Mean Returns suggest a possible structural change

Examining the chart it is easy to see that since 2014 the rolling returns have declined dramatically. In fact it is at a level only seen twice on the chart. First, in 2001 and again in 2009. Both of those periods were tail ends of global recessions. The fact that we are not in a global recession currently(yet?)  suggests potential major trend changes are continuing. 

2011 and 2015 time periods of interest are shaded gray

EUR/USD 252 day rolling volatility is spiking

Simply observing the chart the low-to-high is unparalled since 2008 although much lower on an absolute basis. This is indicative of investor indecision and whipsaws.

2011 and 2015 time periods of interest are shaded gray

Developed Markets' Rolling Mean Returns show decoupling

During periods of global financial streess the commodity countries appear to show acute weakness. EWA and EWC are seriously underperforming their developed market, non-EU peers. QQQ appears to show the most resilience in the face of Eurozone stress in both 2011, and 2015. 

2011 and 2015 time periods of interest are shaded gray

Treasury Yields are likely to fall in a flight to safety trade then continue rising

During the 2011 crisis you can see treasury yields collapse on a lagged basis before continuining to rise. It is likely that yields will follow the same playbook by compressing until more market participants feel certainty regarding potential contagion risk. Barring a total collapse in investor faith in the EU I doubt yields stay compressed for very long given what appears to be a structural shift in rates. 

2011 and 2015 time periods of interest are shaded gray

Treasury Yield volatility is rising yet remains muted when compared to 2011

All 3 maturities remain below their 2011 and subsequent 2012 peaks. They could test those highs but the chart shows a general downtrend in rolling volatility. 

2011 and 2015 time periods of interest are shaded gray

Long term lagged Eurozone interest rate spreads do not show contagion risk like 2011

Examining the long term rates pulled from the ECB’s website we can look at the yield spreads over German Bunds to get an indication of the potential contagion risk this time around. The entire year of 2011 is shaded given the bulk of the crisis happened within that time period. Compared to 2011, Italy, Spain, and Portugal are not yet seeing the same ‘stress’ in 2015. 

2011 and 2015 time periods of interest are shaded gray

Conclusions

1.       Expect increasing volatility across the board as market uncertainty heightens regarding potential contagion risk.

2.       Create your shopping list for ‘overvalued’ ETF’s and individual equities as the potential flight to safety trade will likely create reasonable longer term buying opportunities in quality names.

3.       Barring a complete debacle in the Eurozone US markets are likely to outperform other developed market peers.

4.       Pay particular attention to the EU yield spreads over ‘safe’ German Bonds. If the peripheral spreads start to blow out again as they did in 2011, all bets are off and safety of investment capital becomes critically important if it hasn’t already. 

COMPOSITE SECTOR ETF VALUATION UPDATED [5.24.2015]

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Check out my updated IPython Notebook where I take a look at changes and trends in ETF valuations using the Implied Cost of Capital model. To learn more about the model and the methodology used see here and here. 

Composite Sector ETF Valuation updated [5.24.2015]

Composite Sector ETF Valuation updated [5.10.2015]

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Check out my updated IPython Notebook where I take a look at changes and trends in ETF valuations using the Implied Cost of Capital model. To learn more about the model and the methodology used see here and here. 

Composite Sector ETF Valuation updated [5.10.2015]