generating alpha: michael a. gayed, cfa @pensionpartners predicting volatility & corrections

GENERATING ALPHA:

Michael A. Gayed, CFA@pensionpartners

PREDICTING VOLATILITY & CORRECTIONS

PENSION PARTNERS, LLCAbout Us

BUT ENOUGH ABOUT US…

Investment manager of mutual funds and separate accounts

Absolute return and equity sector rotation strategies

Quantitative, objective investment process utilizing the principles of intermarket analysis

Open, transparent communication through various writings, media appearances, and social media

For more information, contact us at solutions@pensionpartners.com

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INTRODUCTIONA VERY BRIEF Look at Asset Allocation

THE PROBLEM IS…

Single most important determinant of returns

Asset allocation policy drives 90% of portfolio variability (Brinson, Hood, Beebower)

On average, accounts for all of total return (Ibbotson & Kaplan)

Average performance across all investments must equate to the market (Sharpe)

Efficient Market Hypothesis (EMH) – no strategy can consistently outperform buy and hold

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INTRODUCTIONA VERY BRIEF Look at Asset Allocation

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Numerous studies put into question EMH

If markets are not fully efficient, tactical managers can take advantage of anomalies How?

Momentum Gradual Diffusion of Information

VolatilityClustering Seasonality

Inefficient Markets

INTRODUCTIONDEFINING Intermarket Analysis

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• Branch of technical analysis

• Study of asset class and sector relationships

• Relative movement across and within markets can be predictive of on-coming booms, busts, volatility, and economic changes

Ways of using intermarket analysis?

WHY WE’RE HEREA Look at Signals and Strategies

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OUR AGENDAWhat We Will Be Covering Today

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Part I: Part II: Part III:

• Power of Utilities sector

• Volatility timing & seasonality

• Implementation & implications

• Using Treasuries as signal

• Dynamic asset class rebalancing

• Practical ways to allocate

Beta Rotation Tactical Risk Rotation Examples in Recent History

CONCLUSION

BETA ROTATIONPART I

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A look at theoretical performance…

BETA ROTATIONPower of Utilities sector

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One of the best early predictors of the stock market (Edson Gould)

Why? Highly sensitive to interest rate expectations and economic fluctuations

Backtesting to 1926, a simple strategy of rotating either fully into Utilities of fully into the stock market based on rolling 4 week

return significantly outperforms a buy and hold of both

BETA ROTATIONA simple buy and rotate approach

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$1,000

$10,000

$100,000

$1,000,000

$10,000,000

$100,000,000

$1,000,000,000$877,671,986

$34,282,186

$17,820,871

Growth of $10,000: July 1926 - July 2013

Beta Rotation Strategy Market Utilities

BETA ROTATIONA simple buy and rotate approach

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Annualized Returns by Decade

Time Period BRS Market Utilities Outperformance vs. Market # Weeks

July 1926-1929 26.6% 15.3% 28.3% 11.3% 178

1930-1939 3.7% 0.1% -6.4% 3.6% 521

1940-1949 12.6% 9.6% 8.8% 3.0% 522

1950-1959 19.9% 18.0% 14.8% 1.9% 521

1960-1969 10.3% 8.4% 6.5% 2.0% 522

1970-1979 12.9% 6.0% 6.9% 6.9% 522

1980-1989 22.4% 16.7% 18.1% 5.7% 522

1990-1999 19.8% 17.9% 8.6% 1.9% 522

2000-2009 6.0% -0.3% 8.6% 6.3% 521

2010-July 2013 17.3% 14.9% 13.2% 2.4% 187

All Years 13.9% 9.8% 9.0% 4.2% 4538

BETA ROTATIONA simple buy and rotate approach

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1929193219341937193919421944194719491952195419571959196219641967196919721974197719791982198419871989199219941997199920022004200720092012

-100%

-50%

0%

50%

100%

150%

200%

Rolling 3-Year Outperformance (Beta Rotation Strategy - Market)

BETA ROTATIONA simple buy and rotate approach

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But that’s not all…

Annualized Return Divided by Annualized VolatilityTime Period BRS Market BRS-Market

1926-1929 1.16 0.84 0.32

1930-1939 0.11 0.00 0.11

1940-1949 0.36 0.28 0.09

1950-1959 2.39 1.79 0.60

1960-1969 1.05 0.75 0.30

1970-1979 0.89 0.37 0.52

1980-1989 1.67 1.07 0.60

1990-1999 1.70 1.36 0.33

2000-2009 0.30 -0.02 0.32

2010-2013 1.19 0.88 0.31

All Years 0.80 0.56 0.24

BETA ROTATIONViolating Timing

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Real strength of Utilities is as a signal on volatility

Table 5: Annualized Volatility

Time Period Vol of Market when BRS is in Utilities

Vol of Market when BRS is in Market Differential

July 1926 - 1935 26.1% 31.0% -4.9%

1936-1962 14.6% 14.8% -0.1%

1963-1978 16.4% 11.2% 5.2%

1979-1992 16.0% 13.7% 2.3%

1993 - July 2013 20.3% 15.1% 5.2%

1963 - July 2013 18.0% 13.6% 4.4%

1936 - July 2013 16.8% 14.0% 2.8%

All Years 18.1% 16.6% 1.5%

BETA ROTATIONVolatility timing

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But what about seasonality?

Utilities Strength vs. High VIX/VIX Spikes (Jan 1990 - July 2013)

Criteria # Weeks % of Time BRS in Utilities

% of Time in Utilities Overall Differential

Top 1% of VIX Values (Above 49.3) 12 83.3% 48.5% 34.8%

Top 5% of VIX Values (Above 34.7) 61 58.1% 48.5% 9.6%

Top 10% of VIX Values (Above 29.3) 123 61.0% 48.5% 12.5%

Top 1% of VIX Weekly % Changes (>40.0%) 12 58.3% 48.5% 9.8%

Top 5% of VIX Weekly % Changes (>21.7%) 61 61.3% 48.5% 12.8%

Top 10% of VIX Weekly % Changes (>15.5%) 123 53.7% 48.5% 5.2%

Tail event conditions ARE predictable

BETA ROTATIONSell in May, Rotate Away?

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But that’s not all…

Table 8: Sell in May and Rotate Away?Time Period Utilities Market BRS % of Time in Utilities

Jan 1.4% 1.2% 1.9% 58.1%Feb 0.0% 0.6% 0.8% 49.3%Mar 0.4% 0.8% 1.0% 40.3%Apr 1.0% 1.3% 1.5% 45.8%May 0.4% 0.3% 0.4% 44.4%Jun 1.6% 1.0% 1.4% 53.4%Jul 0.9% 0.8% 1.2% 55.3%

Aug 1.0% 1.1% 1.4% 52.5%Sep -0.5% -0.7% 0.0% 46.6%Oct 0.6% 0.6% 0.9% 56.6%Nov 0.6% 1.0% 1.2% 50.7%Dec 1.9% 1.9% 1.7% 43.0%

Nov-Apr 5.5% 6.9% 8.4% 47.8%May-Oct 4.0% 3.3% 5.3% 51.5%Overall 9.7% 10.4% 14.2% 49.7%

BETA ROTATIONSell in May, Rotate Away?

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BETA ROTATIONImplementation

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More importantly…

Possible to execute with Exchange Traded Funds

BETA ROTATIONImplications on equities

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As fiduciaries, nearly all asset allocators hold equities for clients

Identifying high risk periods of increased volatility minimizes emotional response

Reducing beta exposure, leverage, and positioning more conservatively might enhance equity returns

But what about outside of equities?

TACTICAL RISK ROTATIONPART II

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TACTICAL RISK ROTATION

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Using Treasuries as signal

A look at theoretical performance…

Utilities useful for within equity allocation

Treasuries helpful for bond/stock asset allocation

Backtesting to 1977, a simple strategy that overweights bonds relative to stocks and vice-versa when long duration Treasuries

on month-over-month basis outperforms intermediate produces stronger risk-adjusted returns

Total return long duration Treasuries relative to intermediate provides clues on economy and risk

TACTICAL RISK ROTATION

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All-In Strategy – 100% Treasuries or 100% Stocks

TACTICAL RISK ROTATION

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All-In Strategy – 100% Treasuries or 100% Stocks

TACTICAL RISK ROTATION

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All-In Strategy – 100% Treasuries or 100% Stocks

TACTICAL RISK ROTATION

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All-In Strategy – 100% Treasuries or 100% Stocks

TACTICAL RISK ROTATION

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All-In Strategy – 100% Treasuries or 100% Stocks

TACTICAL RISK ROTATION

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All-In Strategy – 100% Treasuries or 100% Stocks

TACTICAL RISK ROTATION

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All-In Strategy – 100% Treasuries or 100% Stocks

Instead of 100% to Treasuries…

TACTICAL RISK ROTATION

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Dynamic Risk Rebalancing

What’s the easiest way of doing this?

Rule:

Overweight bonds when total return long duration outperforms intermediate duration in prior month

TACTICAL RISK ROTATION

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Practical ways to implement

Numerous bond and stock mutual funds/ETFs can be used to over/underweight

The question of when to deviate from target weights can be answered by tracking total return behavior of Treasury ETFs

Identifying periods where bonds are likely to outperform stocks can minimize portfolio drawdowns

Helps answer when to buy, when to sell.

EXAMPLES IN RECENT HISTORYPART III

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EXAMPLES IN RECENT HISTORY

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2010: Flash Crash

EXAMPLES IN RECENT HISTORY

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2011: Summer Crash

EXAMPLES IN RECENT HISTORY

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2012: Two Mini-Corrections

EXAMPLES IN RECENT HISTORY

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2013: False Positives

EXAMPLES IN RECENT HISTORY

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2014: A defensive sector posture defines January-April

Utilities top performing sector YTD

Broad averages did NOT correct, nor did volatility meaningfully

increase

BUT high beta/high momentum names did crack following

leadership

Positioning into defensive/low beta sectors ended up

outperforming aggressive/high beta ones

1 2 3 4

EXAMPLES IN RECENT HISTORY

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2014: No Large-Cap Correction, But…

EXAMPLES IN RECENT HISTORY

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2014: Small-Cap Correction

CONCLUSION

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Intermarket analysis can enhance asset allocation

Within equities, tracking behavior of Utilities can be an early predictor of on-coming volatility

Treasury total return behavior on a month-over-month basis can guide portfolio tilts when addressing fixed income/stock weightings

To generate alpha, follow Utilities and Treasuries.

Intermarket analysis which tracks relationships that lead can result in better risk management, and long-term alpha

QUESTIONS?

Happy to answer any questions you may have

THANK YOU FOR LISTENING

http://www.pensionpartners.com/ solutions@pensionpartners.com