UTAH SCHOOL AND INSTITUTIONAL TRUST FUNDS BOARD … · Ammar Dalal Derivative Operations Analyst Deanna Pulley Derivative Operations Associate Roslyn Skanes Derivative Operations

UTAH SCHOOL AND INSTITUTIONAL TRUST FUNDS

BOARD PRESENTATION

FOR ONE-ON-ONE USE ONLY

Presented to: Utah SITFO Board

Presented by: Ryan Labs Asset Management

Presented on: March 26, 2019

This presentation is intended for institutional investors and/or Qualified Eligible Persons. It includes important Disclosures that are an integral part of this presentation on the final pages of this Appendix. These materials have not been reviewed by or approved by the National Futures Association. All simulations are gross of fees.

PREAMBLE

2

Certain performance returns reflected in this presentation are based on simulated and

hypothetical performance results that do not reflect the actual performance of any client

account. The performance of the “Historical Model” is back tested, which means that it

reflects the retroactive application of the investment program to historical data for

periods during which the investment program did not exist. The performance of the

“Production Model” reflects the application of the investment program for the period

following its development.

Important disclosures regarding the simulated and hypothetical performance returns

contained herein, including the inherent limitations of simulated and hypothetical

returns, are provided at the end of this presentation. Please consider these important

disclosures when reviewing the contents of this presentation.

This material is intended for one-on-one presentation to qualified eligible persons only.

There can be no assurance that the program discussed herein will achieve profits or

avoid incurring substantial losses, or that the investment program will achieve its stated

goals.

This presentation is intended for institutional investors and/or Qualified Eligible Persons. It includes important Disclosures that are an integral part of this presentation on the final pages of this Appendix. These materials have not been reviewed by or approved by the National Futures Association. All simulations and live returns are gross of fees.


Providing a diverse range of insurance, wealth

and asset management solutions

$763BAssets under management

.

26Countries with

SLF offices

$24BMarket capitalization

Our strategy is

focused on four key

pillars of growthCanada U.S. Asia A leader in global asset management1 2 3 4

PART of the SUN LIFE FINANCIAL GLOBAL ORGANIZATION

3This presentation is intended for institutional investors and/or Qualified Eligible Persons. It includes important Disclosures that are an integral part of this presentation on the final pages of this Appendix. These materials have not been reviewed by or approved by the National Futures Association. All simulations and live returns are gross of fees.


SUN LIFE INVESTMENT MANAGEMENT

Solutions across traditional and alternative asset classes

Public fixed income

Global investment grade bonds – high yield bonds and

loans, structured products, municipals, derivatives

Private fixed income

Corporate Finance, Project Finance, Private Real Estate

Finance, Middle Market Finance, Private Securitization

Finance

Real estate

Commercial mortgages, real estate equity

$160BAsset management

business

800+Institutional client

base



STABILITY

Stability of a leading, global

financial services organization

with over $759 billion in AUM;

operating through a balanced

and diversified model focused

on asset management

INFRASTRUCTURE

Leverage key operational

infrastructure and investment

capabilities across the Sun Life

Investment Management

companies

ALIGNMENT OF INTERESTS

Benefit of seed capital for new

market ventures; potential

opportunities to co-invest

alongside Sun Life

BENEFIT OF PARTNERSHIP


A full disclosure presentation is an integral part of this report, and is attached in the appendix. Returns shown are total returns gross of fees.

Short/Intermediate

Core

Long

Assets Under Management (US$)*

$9.2

billion

Corporate Public

Union/Taft-Hartley Foundations/Endowments

Healthcare Insurance

Special Purpose

Client Accounts*

169

INTEGRATED ASSET MANAGEMENT

CONSISTENT RETURNS over market

cycles with high information ratios

Run over $2.65B billion in Treasury

securities including over $800 million in

STRIPS

Core strategy has OUTPERFORMED

Bloomberg Barclays US Aggregate Index

over the last consecutive 17 years

RYA N L A B S A S S E T M A N A G E M E N TF I R M O V E RV I E W


*Assets under management and number of client accounts are as of 3/8/2019.

A full disclosure presentation is an integral part of this report, and is attached in the appendix. Returns shown are total returns gross of fees. 7

SUN L IFE PROVIDES OVERLAY CAPABIL IT IES

48%30%

19%

2% 1%

Corporate Securitized Treasury

Agency Municipals Cash

Total AUM: $8.33B

54%

34%

10%

2%

Interest Rate Hedges Foreign Exchange Hedges

Equity Hedges Credit Hedges

Overlay positions

Total Notional: $48B*

42 total investment professionals

10 overlay professionals

*12/31/2018 RL AUM and 9/30/2018 Sun Life AUM with notional values in USD based on 9/30/2018 CAD/USD rate. Includes only portions of Sun Life Investment operations



RYAN LABS ASSET MANAGEMENT TEAMExecutive Committee

Richard Familetti, CFA, President & Chief Investment Officer (2009 | 1986)

Thomas Keresztes, Chief Operations Officer & Chief Compliance Officer (2015 | 1987)

Chris Adair, Senior Managing Director - Head of Sales, Client Service & Strategy (2005 | 1992)

(Ryan Labs Start | Industry Start)

Tail Hedging and Overlay Strategies

Brett Pacific, CFA, Senior Managing Director, Portfolio Manager (2004 | 1993)

Peng Zhou, PhD., FSA, CFA, Managing Director, Portfolio Manager (2003 | 2003)

John Bichajian, CFA, Director (2009 | 2003)

Rawan El-Khatib, Director (2008 | 2008)

Kyle Chang, CFA, Director (2014 | 2012)

Operations, Research, & Indexes

Thomas Keresztes, Chief Operations Officer & Chief Compliance Officer (2015 | 1987)

Terry Lombardo, Director (2000 | 2000)

Theresa Arata, Director (2012 | 1985)

Dhruv Trivedi, Director (2017 | 2004)

Thomas Watson, Director (2017 | 2012)

James Lizotte, CFA, Associate Director (2014 | 2014)

Alex Zambelli, Associate Director (2015 | 2015)

Jean Mimy, Analyst (1999 | 1988)

Leveraged Finance Group

Mark Pelletier, CFA, Senior Managing Director, Portfolio Manager (2018 | 1988)

Michael Cerullo, Managing Director, Portfolio Manager (2018 | 1988)

Christian Toro, CFA, CPA, Managing Director, Portfolio Manager (2018 | 1997)

Dana Dratch, CFA, Managing Director, Portfolio Manager (2018 | 1995)

Juan Estela, Managing Director, Portfolio Manager (2018 | 1999)

Shelly-Ann Glover, Director (2018 | 2000)

Client Service & Strategy

Chris Adair, Senior Managing Director - Head of Sales, Client Service & Strategy (2005 | 1992)

Bradley D. Jacob, Managing Director (2008 | 2003)

Mark Monroe, Managing Director (2012 | 1997)

John Linder, CFA, CPA, Managing Director (2018 | 1996)

Robert Shrekgast, Director (2018 | 1993)

Melissa Spadafora, Director (2016 | 2012)

Pawel Krasowski, Associate Director (2015 | 2015)

Joshua Hassell, Associate (2018 | 2018)

Mark Stefaniak, Analyst (2017 | 2017)

Vincent Spoleti, Analyst (2018 | 2018)

Asset Management

Richard Familetti, CFA, President & Chief Investment Officer (2009 | 1986)

Michael P. Donelan, CFA, Managing Director, Portfolio Manager (2003 | 1988)

Matthew Salzillo, Managing Director, Portfolio Manager (2004 | 2004)

Philip Mendonca, Managing Director, Portfolio Manager (2003 | 2003)

Daniel J. Lucey, CFA, Managing Director, Portfolio Manager (2009 | 2003)

Raghava Vudata, Director (2008 | 2008)

Annette Serrao, CFA, Director (2010 | 2010)

Shera Abella, Director (2017 | 2008)

Kenneth Szal, Director (2009 | 2009)

Marina Mestres, Analyst (2016 | 2016)

Alyssa Barchetta, Analyst (2018 | 2018)



M I D D L E O F F I C E B A C K O F F I C E

Brett Pacific, CFA

Derivatives and Quantitative

Strategies and LLC

Senior Managing Director

Derivative Trading

Glenn Barry, CFA, FRM

Head Derivative Trader,

Managing Director

Interest Rate Equity FX

Beth Lee

Derivative Trader

Senior Director

Andrew Poston, CFA, FRM

Derivative Trader

Director

Peng Zhou, PhD, FSA, CFA

Portfolio Manager,

Managing Director

John Bichajian, CFA

Portfolio Manager,

Senior Director

Rawan El-KhatibPortfolio Manager,

Director

Shekhar Shastri, CFA

Valuations Manager,

Managing Director

Martin Chmiel

Derivative Operations

Manager

Aleksandar Popic

Derivative Collateral

Manager

Derivative Valuation Derivative Operations Derivative Collateral

Duan Wang, PhD

Quant

Associate Director

Johan NacoQuant

Senior Analyst

Tihomir Lukic


Senior Associate

Chris Raposo


Senior Associate

Boris Korenak

Derivative Collateral

Analyst

Jas Dhamrat


Senior Associate

Ammar Dalal


Analyst

Deanna Pulley


Associate

Roslyn SkanesDerivative Operations and

Collateral Director

Matthew BoehnerDerivative Analyst

OVERLAY TEAM OVERVIEW

F R O N T O F F I C E



Synthetic Beta

Equity

Currency

Duration

O V E R L A Y

S O L U T I O N S

Return

Enhancement

Credit

Cash equalization

Protective equity

O V E R L A Y

S O L U T I O N S

Tail Risk

Equity

Interest rate

Defensive risk premia

O V E R L A Y

S O L U T I O N S

OVERLAY OVERVIEW



Active

dialogue with

top dealers in

each market

Execute on

large number

of derivative

exchanges

Connect via

leading

electronic

platforms

ROBUST PLATFORM



PORTFOLIOS ARE DOMINATED BY GROWTH RISK -

TREASURIES OFFSET THE WORST EQUITY SELLOFFS

12


ALL INSTITUTIONAL PORTFOLIOS ARE

GROWTH RISK DOMINATED

1. Equities typically represent the largest source of growth risk

2. For the typical portfolio weighting of 60/40 between equities and bonds

1. US equities have an annualized volatility of 15%, bonds have an annualized

volatility of 4%

2. Over time, 96% of risk (volatility) can be attributed to equity movements*

because equities are so much more volatile than the bond allocation

3. The determinant of portfolio movement is the equity allocation

40%

60%

Bonds Equity

Asset Allocation Risk Contribution

*Prepared for illustrative purposes only from portfoliovisualizer.com. Data since Jan 1987, rebalancing quarterly.Uses VTSMX (Vanguard US Stock Market ETF) and VBMFX (Vanguard Total Bond ETF) data as representative equity and bond returns.

4%

96%

Bonds Equity



0.9

1.0

1.1

1.2

1.3

1.4

Po

rtfo

lio V

alu

e

S&P 500

S&P 500 withDrawdowns Eliminated

0.8

0.9

1.0

1.1

1.2

1.3

1.4

Po

rtfo

lio V

alu

e

S&P 500

S&P 500 with Drawdowns Eliminated0.4

0.6

0.8

1.0

1.2

1.4

Po

rtfo

lio V

alu

e

S&P 500

S&P 500 with Drawdowns Eliminated

14

EQUITY DRAWDOWNS DAMAGE PORTFOLIOS

1. Equities are a significant portion of most portfolios

2. Large drawdowns do occur, interfering with portfolio objectives

3. Offsetting large drawdowns allows portfolios to compound at higher rates

3

Offsetting Large Equity Market Declines is Beneficial

(April 2007 – December 2018)

Dec 2007 – June 2009 Dec 2010 – June 2012 Dec 2015 – June 2017

6.30

2.17


This presentation is intended for institutional investors and/or Qualified Eligible Persons. It includes important Disclosures that are an integral part of this presentation on the final pages of this Appendix. These materials have not been reviewed by or approved by the National Futures Association. All simulations are gross of fees. 15

SOLUTIONS TO ADDRESS THIS PROBLEM

1. Adding additional, sizable, offsetting risk exposures to the portfolio

2. In order to offset equity risk, such an allocation must be:

Liquid ✓

Scalable ✓

Impactful (volatile like equities) ✓

Transparent ✓

Cost Effective ✓

Positive Expected Return ✓

NEGATIVELY CORRELATED TO EQUITIES WHEN EQUITIES DRAW DOWN

✓



THIRD PARTY VALIDATION OF FLIGHT TO QUALITY

ATTRIBUTES OF TREASURIES


When Diversification Fails Sébastien Page, CFA, and Robert A. Panariello, CFA

Financial Analyst Journal (Vol. 74, No. 3), Third Quarter 2018, Page 19

During large stock market selloffs:

STOCKS PRICES

TREASURY PRICES

= Negative Correlation

LESS CONCERNED WITH CORRELATIONS WHEN STOCKS ARE DOING WELL

As Equity Selloffs Get Worse, Treasury Returns Become More Positive


FLIGHTS TO QUALITY, TRIGGERED BY EQUITY

SELLOFFS, ARE LIKELY TO RECUR PERIODICALLY

17


FLIGHT TO QUALITY / LIQUIDITY PREMIUM

(SHORT DURATION EVENT) STOCKS RATES

• In times of economic distress, investors tend to rebalance portfolios, selling risk assets and

buying more liquid/less risky assets (Treasuries rally)

• Premium increases during large risk asset sell-offs (typically short duration event lasting

several days) and price correlation becomes more negative as volatility increase

Israel, R., & Maloney, T. (2014). Understanding Style Premia. The Journal of Investing, 23(4).

Performance of US Treasuries is inverse to the change in Treasury Yield. Data since 1979. Source: Bloomberg.

-0.20

-0.10

0.00

0.10

0.20

0.30

0.40

0.50

0.60

-10.00% -8.00% -6.00% -4.00% -2.00% 0.00% 2.00% 4.00%

Co

rrel

atio

n

Equity Return

Correlation Between Equity Returns and Treasury Yield

Rolling 5-Day Correlation

Rolling 30-Day Correlation



FLIGHT TO QUALITY / LIQUIDITY PREMIUM RELATIONSHIP

Recent Evidence STOCKS RATES Relationship Intact


When Equites Selloff, Treasury Rates Decline => Treasuries Rally

-0.60

-0.40

-0.20

0.00

0.20

0.40

0.60

0.80

1.00

-5% -4% -3% -2% -1% 0% 1% 2% 3% 4% 5%

Intr

ad

ay C

orr

ela

tio

ns

Daily Equity Returns

All Days Sept 1, 2018 through March 8, 2019

Equity Treasury Correlation vs Equity Returns


TRACK RECORD OF $2.65B WITHIN TREASURIES

THROUGH ALL PORTFOLIOS


Cell

Sample Long Duration Portfolio (3/8/2019) Custom Liability Benchmark Difference

Weight

(%)MDur

MTD

Return

QTD

Return

YTD

Return

Cumm

Return

Weight

(%)MDur

MTD

Return

QTD

Return

YTD

Return

Cumm

Return

Weight

(%)MDur

MTD

Return

QTD

Return

YTD

Return

Cumm

Return

Cash 0.72 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.72 0.00 0.00 0.00 0.00 0.00

Treasury 33.78 0.47 2.02 0.79 0.79 5.39 30.07 0.55 2.03 0.51 0.51 4.77 3.71 -0.08 -0.01 0.29 0.29 0.63

Agency 1.41 0.02 0.82 3.99 3.99 2.97 0.00 0.00 0.00 0.00 0.00 0.00 1.41 0.02 0.82 3.99 3.99 2.97

Local Authority 0.70 0.07 1.46 3.08 3.08 3.08 0.00 0.00 0.00 0.00 0.00 0.00 0.70 0.07 1.46 3.08 3.08 3.08

Sovereign 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Supranational 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Industrial 25.26 0.02 0.66 3.38 3.38 3.68 42.90 0.03 0.65 2.69 2.69 3.51 -17.64 -0.01 0.02 0.69 0.69 0.16

Utility 11.34 0.21 0.89 2.60 2.60 2.81 12.15 0.13 0.87 2.25 2.25 2.95 -0.81 0.08 0.03 0.35 0.35 -0.14

Finance 16.75 0.04 0.43 3.25 3.25 3.95 14.89 0.04 0.51 2.92 2.92 3.36 1.87 0.00 -0.08 0.34 0.34 0.59

MBS Pass Thru 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Asset Backed 2.47 0.03 0.21 0.79 0.79 3.86 0.00 0.00 0.00 0.00 0.00 0.00 2.47 0.03 0.21 0.79 0.79 3.86

CMBS 6.35 0.06 0.68 2.18 2.18 5.76 0.00 0.00 0.00 0.00 0.00 0.00 6.35 0.06 0.68 2.18 2.18 5.76

Covered 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

CMO 1.21 0.08 0.62 1.24 1.24 2.62 0.00 0.00 0.00 0.00 0.00 0.00 1.21 0.08 0.62 1.24 1.24 2.62

Other 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

TOTAL 100.00 0.20 1.10 2.24 2.24 4.38 100.00 0.20 1.06 2.02 2.02 3.84 0.00 0.00 0.03 0.22 0.22 0.54

Notes: Based on a Representative Account

% Weight = Percent of Total Portfolio Weight

Daily Return = Total Return For the Day

MTD Return = Total Return Since End Of Previous Month

QTD Return = Total Return Since End of Last Calendar Quarter

YTD Return = Total Return Since End Of Previous Year

Cumm Ret = Cumulative Total Return Since 3/8/2018

• Ryan Labs manages $2.65B in US

Treasury securities as of 3/8/2019


TRACK RECORD OF >$800MM WITHIN STRIPS

THROUGH ALL PORTFOLIOS

21

Cell

Sample Long Duration Portfolio

Structure by Industry (3/8/2019)

Weight

(%)

Market

Value

Coupon

(%)

YTW

(%)

MDur

(%)

Cash 0.73 1,723,686 - - -

Treasury 33.88 80,262,950 0.38 3.06 23.05

Agency 1.41 3,344,595 3.61 3.90 9.24

Local Authority 0.70 1,667,681 6.70 4.29 13.02

Sovereign - - - - -

Supranational - - - - -

Industrial 25.22 59,743,324 3.87 3.72 9.24

Utility 11.34 26,861,938 4.02 3.78 10.21

Finance 16.72 39,607,925 3.80 3.57 6.39

MBS Pass Thru - - - - -

Asset Backed 2.47 5,845,369 3.50 3.51 2.11

CMBS 6.34 15,020,355 3.46 4.46 8.14

Covered - - - - -

CMO 1.21 2,855,053 3.29 3.58 11.73

Other - - - - -

TOTAL 100.00 236,932,877 2.64 3.50 13.29

CUSIP Issuer Maturity Price YTW Market

Value

Weight

(%)

912833Y46 19YR US Coupon STRIP 5/15/2037 58.69 2.91 1,349,824 0.57

912833Z52 19YR US Coupon STRIP 8/15/2037 58.14 2.96 1,947,824 0.82

912833Z60 19YR US Coupon STRIP 2/15/2038 57.15 2.98 4,000,640 1.69

912834AT5 20YR US Coupon STRIP 8/15/2038 56.38 2.97 1,014,822 0.43

912834AU2 20YR US Coupon STRIP 2/15/2039 55.40 2.98 3,711,666 1.57

912834FB9 21YR US Coupon STRIP 2/15/2040 53.31 3.03 2,638,598 1.11

912834JB5 22YR US Coupon STRIP 8/15/2040 52.18 3.06 2,400,464 1.01

912834JP4 22YR US Coupon STRIP 2/15/2041 51.31 3.06 3,181,158 1.34

912834KV9 23YR US Coupon STRIP 11/15/2041 49.81 3.10 1,095,864 0.46

912834LB2 23YR US Coupon STRIP 2/15/2042 49.31 3.11 3,624,212 1.53

912834LX4 24YR US Coupon STRIP 11/15/2042 48.06 3.12 4,806,300 2.03

912834MZ8 25YR US Coupon STRIP 11/15/2043 46.47 3.13 2,602,264 1.10

912834NF1 25YR US Coupon STRIP 2/15/2044 46.06 3.13 2,302,950 0.97

912834PB8 26YR US Coupon STRIP 11/15/2044 45.05 3.13 2,004,770 0.85

912834PH5 26YR US Coupon STRIP 2/15/2045 44.73 3.13 1,051,179 0.44

912834KB3 27YR US Coupon STRIP 5/15/2045 44.45 3.12 10,224,190 4.32

912834PT9 27YR US Coupon STRIP 11/15/2045 43.71 3.12 4,808,210 2.03

912834PZ5 27YR US Coupon STRIP 2/15/2046 43.41 3.12 5,773,530 2.44

912834QH4 28YR US Coupon STRIP 5/15/2046 43.14 3.12 1,639,206 0.69

912834RB6 28YR US Coupon STRIP 2/15/2047 42.17 3.11 2,951,760 1.25

912834RR1 29YR US Coupon STRIP 8/15/2047 41.34 3.13 4,995,456 2.11

TOTAL 47.43 3.10 67,573,027 29.15

US STRIPS

within

representative

portfolio

• Across 169 portfolios and $9.2B in

AUM, Ryan Labs manages $800MM

in STRIPS as of 3/8/2019


The securities identified and described do not represent all of the securities purchased, sold or recommended for client accounts. The reader

should not assume that an investment in the securities identified was or will be profitable.


DEFENSIVE RISK PREMIUM DYNAMIC CAPTURE -

PROCESS OVERVIEW

22


DYNAMIC HEDGING PROCESS

STEP I

Risk signalSTEP II

Equity signalSTEP III

Treasury signalSTEP IV

Scaling ratio

Hedge off

yes yes yes

no no no



-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%

8 9 10 11 12 13 14 15 16 17 18 19 21 23 25 27 29

Retu

rn

Implied Equity Volatility (VIX)

Equity and Treasury Return vs Risk Sentiment Level

Avg. 3D Annualized SPX Return

Avg. 3D Annualized Treasury Return (Detrend)

Avg. 3D Annualized Treasury Return

RELATIONSHIP DRIVING THE RISK SIGNAL WE CHOSE:

FLIGHT TO QUALITY / LIQUIDITY PREMIUM VS VIX

As risk sentiment (VIX Index) increases above 16

• Equity return becomes more negative

• Treasury return becomes more positive

• Avoid hedging when market is generally optimistic

24

Source: Bloomberg. Data since 1/1/1990.



• Potential active periods require elevated risk sentiment, trending higher

25

Source: Bloomberg. Presented for illustrative purposes only. Data since 1/1/2007.

STEP I - RISK SIGNAL TEST



DESIGN OF EQUITY AND TREASURY SIGNALS

STEPS II & III

Run Daily Univariate

Regressions

Select two indicators

with highest

confidence

• Capturing wide cross-section of market risk premia

• 26 Indicators

• Recent trailing data

• Select strongest two indicators

• Models responds to current market conditions

Run Daily

Multivariate

Regression

• Is the confidence threshold met?

• If yes, signal is on



DRP IS TRIGGERED WHEN ALL THREE SIGNALS ARE “ON”

27

Past performance is no guarantee of future results. Please see additional disclosures at the end of this presentation regarding model and back tested performance.

*The “DRP Production” period reflects the application of the DRP overlay trading program in a paper portfolio for the period following the program’s development and prior to Ryan Labs’ management of client assets in the program (January 1,

2016 to June 30, 2016). The “DRP Live” period reflects the period in which client assets were managed in the DRP overlay trading program (July 1, 2016 to present). Small modifications to the DRP overlay trading program model were

implemented taking effect July 1, 2018, and these small modifications have been incorporated in the “Hypothetical” period reflecting the application of the DRP overlay trading program over periods during which the DRP overlay trading program

did not exist (April 30, 2007 – December 31, 2015). THESE RESULTS ARE BASED ON SIMULATED OR HYPOTHETICAL PERFORMANCE RESULTS THAT HAVE CERTAIN INHERENT LIMITATIONS. UNLIKE THE RESULTS SHOWN IN

AN ACTUAL PERFORMANCE RECORD, THESE RESULTS DO NOT REPRESENT ACTUAL TRADING. ALSO, BECAUSE THESE TRADES HAVE NOT ACTUALLY BEEN EXECUTED, THESE RESULTS MAY HAVE UNDER-OR OVER-

COMPENSATED FOR THE IMPACT, IF ANY, OF CERTAIN MARKET FACTORS, SUCH AS LACK OF LIQUIDITY. SIMULATED OR HYPOTHETICAL TRADING PROGRAMS IN GENERAL ARE ALSO SUBJECT TO THE FACT THAT THEY

ARE DESIGNED WITH THE BENEFIT OF HINDSIGHT. NO REPRESENTATION IS BEING MADE THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFITS OR LOSSES SIMILAR TO THESE BEING SHOWN.

STEP I

Risk signal

STEP IV

Scaling ratio

Hedge off

yes

no

STEP II

Equity signalyes

no

STEP III

Treasury signalyes

no

Indicators CategoryIndicator

Contribution2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Equity Volatility 5% 51% 21% 17% 26% 15% 17% 10% 45% 8% 8% 10%

High Yield Bonds 30% 4% 28% 18% 13% 16% 20% 23% 12% 22% 7% 33%

Emerging Market 5% 8% 24% 30% 12% 20% 6% 4% 6% 7% 23% 7%

Volatility Skewness 12% 15% 6% 19% 8% 11% 9% 7% 31% 3% 4% 20%

Volatility Term Structure 10% 2% 5% 2% 5% 12% 10% 4% 0% 2% 1% 0%

Cross Currency Basis 12% 4% 4% 3% 1% 9% 8% 37% 2% 19% 2% 12%

Commodity 16% 7% 3% 4% 12% 12% 7% 3% 1% 24% 48% 8%

Currency 10% 1% 4% 5% 22% 4% 23% 7% 2% 9% 0% 10%

Relative Value 1% 7% 5% 2% 2% 2% 1% 4% 0% 7% 7% 2%

# of days when Indicators over

threshold61 84 58 64 66 64 40 92 53 81 38 30

# of Days when DRP is Active 47 58 20 33 47 0 4 41 36 35 0 15

# of days of Gain/Loss 24/23 35/23 8/12 17/16 25/22 0/0 2/2 23/18 19/17 18/17 0/0 5/10

Yearly Performance (Hypothetical) 1.1% 62.8% -0.9% 5.1% 13.8% 0.0% 0.0% 1.4% 0.4% 7.4% 0.0% -4.0%


STEP IV – SCALING RATIO – BASED ON RISK

• Magnitude of potential sell-off determines scaling ratio

• Assess both level and trend of volatility

• Higher risk level increases scaling ratio

• Higher scaling ratio during extreme risk regimes

• Scaling ratio capped

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Normalized VIX

Leverage Ratio

Hedge Ratio Cap in "Extreme" Risk Period

Hedge Ratio Cap in "Elevated" Risk Period

RISK BASED



HISTORIC MODEL SIMULATION (HYPOTHETICAL)• From 4/2007 to 12/2018, hedge is on roughly 7% of the time

Hypothetical4/30/2007 – 6/30/2016

DRP Live7/1/2016 - Present

Return Since Apr 2007 Dec 2010

S&P 500 + DRP 14.12% 14.12%

S&P 500 6.86% 11.32%

DRP 6.36% 2.28%

DRP Vol 13.39% 5.96%

DRP

Production1/1/2016 –6/30/2016

Past performance is no guarantee of future results. Please see additional disclosures at the end of this presentation regarding model and backtested performance.

*The information presented assumes the DRP overlay trading program’s hypothetical, production model, and live performance record and an underlay of investments whose performance tracks the S&P 500 Index for the periods shown. It is for illustrative

purposes only.

The “DRP Production” period reflects the application of the DRP overlay trading program in a paper portfolio for the period following the program’s development and prior to Ryan Labs’ management of client assets in the program (January 1, 2016 to June 30,

2016). The “DRP Live” period reflects the period in which client assets were managed in the DRP overlay trading program (July 1, 2016 to present). Small modifications to the DRP overlay trading program model were implemented taking effect July 1, 2018, and

these small modifications have been incorporated in the “Hypothetical” period reflecting the application of the DRP overlay trading program over periods during which the DRP overlay trading program did not exist (April 30, 2007 – December 31, 2015).

THESE RESULTS ARE BASED ON SIMULATED OR HYPOTHETICAL PERFORMANCE RESULTS THAT HAVE CERTAIN INHERENT LIMITATIONS. UNLIKE THE RESULTS SHOWN IN AN ACTUAL PERFORMANCE RECORD, THESE RESULTS DO NOT

REPRESENT ACTUAL TRADING. ALSO, BECAUSE THESE TRADES HAVE NOT ACTUALLY BEEN EXECUTED, THESE RESULTS MAY HAVE UNDER-OR OVER-COMPENSATED FOR THE IMPACT, IF ANY, OF CERTAIN MARKET FACTORS, SUCH AS

LACK OF LIQUIDITY. SIMULATED OR HYPOTHETICAL TRADING PROGRAMS IN GENERAL ARE ALSO SUBJECT TO THE FACT THAT THEY ARE DESIGNED WITH THE BENEFIT OF HINDSIGHT. NO REPRESENTATION IS BEING MADE THAT ANY

ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFITS OR LOSSES SIMILAR TO THESE BEING SHOWN.



6.32%

47.08%

15.11%8.97%

19.62%

5.38% 4.18% 3.85%7.33% 9.11%

2.08% 2.70%

-3.72%-10%

0%

10%

20%

30%

40%

50%

12/07 12/08 12/09 12/10 12/11 12/12 12/13 12/14 12/15 06/16 12/16 12/17 12/18

Excess Return

1.07%

62.80%

-0.86%

5.09%

13.82%

0.00%0.03%

1.40%0.38%

7.61%

0.00% 0.00%

-3.93%-5.24%

15.72%

-15.97%

-3.87% -5.80% -5.38% -4.14% -2.45%-6.95%

-1.50% -2.08% -2.70% -0.21%

-20%

-10%

0%

10%

20%

30%

40%

50%

60%

70%

12/07 12/08 12/09 12/10 12/11 12/12 12/13 12/14 12/15 06/16 12/16 12/17 12/18

Yearly Performance (April 2007 - December 2018)

DRP (Hypothetical)

CBOE S&P W/ 5% OTM PUTS - S&P Total Return

30

DRP VS. ALWAYS ON PUTS (HYPOTHETICAL)

CBOE PPUT - SPTR is a CBOE benchmark that tracks the S&P Total Return with constantly rolling 5% out of the money puts. The Index represents an always-on hedge for 5% downside movements in US equities. We have subtracted out the total return of the

S&P 500 to represent just the hedged portion of the Index. Past performance is no guarantee of future results. Please see additional disclosures at the end of this presentation regarding model and backtested performance.

*The “DRP Production” period reflects the application of the DRP overlay trading program in a paper portfolio for the period following the program’s development and prior to Ryan Labs’ management of client assets in the program (January 1, 2016 to June 30,

2016). The “DRP Live” period reflects the period in which client assets were managed in the DRP overlay trading program (July 1, 2016 to present). Small modifications to the DRP overlay trading program model were implemented taking effect July 1, 2018, and

these small modifications have been incorporated in the “Hypothetical” period reflecting the application of the DRP overlay trading program over periods during which the DRP overlay trading program did not exist (April 30, 2007 – December 31, 2015).

THESE RESULTS ARE BASED ON SIMULATED OR HYPOTHETICAL PERFORMANCE RESULTS THAT HAVE CERTAIN INHERENT LIMITATIONS. UNLIKE THE RESULTS SHOWN IN AN ACTUAL PERFORMANCE RECORD, THESE RESULTS DO NOT

REPRESENT ACTUAL TRADING. ALSO, BECAUSE THESE TRADES HAVE NOT ACTUALLY BEEN EXECUTED, THESE RESULTS MAY HAVE UNDER-OR OVER-COMPENSATED FOR THE IMPACT, IF ANY, OF CERTAIN MARKET FACTORS, SUCH AS

LACK OF LIQUIDITY. SIMULATED OR HYPOTHETICAL TRADING PROGRAMS IN GENERAL ARE ALSO SUBJECT TO THE FACT THAT THEY ARE DESIGNED WITH THE BENEFIT OF HINDSIGHT. NO REPRESENTATION IS BEING MADE THAT ANY

ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFITS OR LOSSES SIMILAR TO THESE BEING SHOWN.

DRP

Since

Apr

2007

Dec

2010

DRP 6.36% 2.28%

PPUT-SPTR -3.71% -3.92%

Excess 10.08% 6.20%

Hypothetical4/30/2007 – 12/31/2015

DRP Live7/1/2016 - PresentDRP

Production1/1/2016 –

6/30/2016

*



STRIPS UNDERLAY with

DEFENSIVE RISK PREMIA OVERLY

31


STRIPS WITH DEFENSIVE RISK PREMIA

Defensive

Risk PremiaSTRIPS

YTW(%): 3.06

Duration: 25.33

Substantial

Additional

Rate Exposure

1.25 x 19.63 = 24.53 Years Duration

1.50 x 19.63 = 29.44 Years DurationFutures Duration

Proposed

Scaling


As of 3/8/2019

Range of 0.00 to 1.50


12.5%

144.9%

-36.3%

15.8%

74.1%

3.3%

-20.5%

46.8%

-3.7%

30.7%

-16.9%

13.5%

-7.6%

-1.2%10.4%

54.5%

-35.7%

10.7%

56.2%

3.3%

-20.5%

44.9%

-4.0%

21.9%

-16.9%

13.5%

-4.2% -0.7%

-50%

-25%

0%

25%

50%

75%

100%

125%

150%

12/07 12/08 12/09 12/10 12/11 12/12 12/13 12/14 12/15 06/16 12/16 12/17 12/18 03/19

Yearly Performance (April 30, 2007 - March 7, 2019)

Bloomberg Barclays 20 - 30 Year Equal Par STRIPS Index + Ryan Labs Defensive Risk Premia

Bloomberg Barclays 20 – 30 Year Equal Par STRIPS Index

33

STRIPS + DRP YEARLY PERFORMANCE COMPARISON


Past performance is no guarantee of future results. Please see additional disclosures at the end of this presentation regarding model and back tested performance. The information presented assumes the DRP

overlay trading program’s production model and live performance record and an underlay of investments whose performance tracks the Bloomberg Barclays 20 – 30 Year Equal Par STRIPS Index for the periods

shown. It is for illustrative purposes only. The “DRP Production” period reflects the application of the DRP overlay trading program in a paper portfolio for the period following the program’s development and prior

to Ryan Labs’ management of client assets in the program (January 1, 2016 to June 30, 2016). The “DRP Live” period reflects the period in which client assets were managed in the DRP overlay trading program

(July 1, 2016 to present). Small modifications to the DRP overlay trading program model were implemented taking effect July 1, 2018. THESE RESULTS ARE BASED ON SIMULATED OR HYPOTHETICAL

PERFORMANCE RESULTS THAT HAVE CERTAIN INHERENT LIMITATIONS. UNLIKE THE RESULTS SHOWN IN AN ACTUAL PERFORMANCE RECORD, THESE RESULTS DO NOT REPRESENT

ACTUAL TRADING. ALSO, BECAUSE THESE TRADES HAVE NOT ACTUALLY BEEN EXECUTED, THESE RESULTS MAY HAVE UNDER-OR OVER-COMPENSATED FOR THE IMPACT, IF ANY, OF

CERTAIN MARKET FACTORS, SUCH AS LACK OF LIQUIDITY. SIMULATED OR HYPOTHETICAL TRADING PROGRAMS IN GENERAL ARE ALSO SUBJECT TO THE FACT THAT THEY ARE DESIGNED

WITH THE BENEFIT OF HINDSIGHT. NO REPRESENTATION IS BEING MADE THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFITS OR LOSSES SIMILAR TO THESE BEING SHOWN.

(Hypothetical)

2.12%

90.42%

-0.56%

5.17%

17.86%

0.00% 0.02% 1.82% 0.28%8.79%

0.00% 0.00%

-3.44% -0.53%-20%

0%

20%

40%

60%

80%

100%

12/07 12/08 12/09 12/10 12/11 12/12 12/13 12/14 12/15 06/16 12/16 12/17 12/18 03/19

Excess Return


DISCLOSURESPast performance is not a guarantee or a reliable indicator of future results. Swaps are a type of derivative; swaps are increasingly subject to central clearing and

exchange-trading. Swaps that are not centrally cleared and exchange-traded may be less liquid than exchange-traded instruments. Derivatives may involve

certain costs and risks such as liquidity, interest rate, market, credit, management and the risk that a position could not be closed when most advantageous.

Investing in derivatives involves leverage and could lose more than the amount invested. Currency rates may fluctuate significantly over short periods of time and

may reduce the returns of a portfolio.

The overlay strategies are only available to Eligible Contract Participants as defined in Commodity Exchange Act Section 1 (a) (18) in ECP’s conjunction with the

bond mandate described herein. This presentation only contains summary information regarding the overlay investment management approaches and is not a

complete description of the investment objectives, portfolio management and research that supports these approaches. There is no guarantee that these

investment strategies will work under all market conditions or are suitable for all investors and each investor should evaluate their ability to invest long-term,

especially during periods of downturn in the market. No representation is being made that any account, product, or strategy will or is likely to achieve profits,

losses, or results similar to those shown. Hypothetical or simulated performance results have several inherent limitations. Unlike an actual performance record,

simulated results do not represent actual performance and are generally prepared with the benefit of hindsight. There are frequently sharp differences between

simulated performance results and the actual results subsequently achieved by any particular account, product, or strategy. In addition, since trades have not

actually been executed, simulated results cannot account for the impact of certain market risks such as lack of liquidity. There are numerous other factors related

to the markets in general or the implementation of any specific investment strategy, which cannot be fully accounted for in the preparation of simulated results

and all of which can adversely affect actual results.

Models Used - This presentation provide performance for a “Production Model” and a “Historical Model.” The performance of the “Historical Model” is back

tested, it reflects the application of the investment program over periods during which the investment program did not exist. The performance of the “Production

Model” reflects the application of the investment program for the period following its development. Neither the “Production Model” nor the “Historical Model”

reflects the performance of any client account. Small modifications to the DRP overlay trading program model were implemented taking effect July 1, 2018 (during

the live trading period), and these small modifications have been incorporated in the “Historical Model”.

The performance of the Historical Model and Production Model contains two components: (i) a underlay of investments whose performance tracks the S&P 500

and (ii) application of the Defensive Risk Premia (“DRP”) tactical hedging overlay. The tactical hedging positions will typically consist of treasury futures. The

size of the tactical hedge is continuously adjusted in response to Ryan Lab’s review of market risk indicators, which seek to determine whether volatility is

increasing risk exposure. If Ryan Labs determines that certain equities and treasures risk indicators identify a likely sell-off, it will increase hedge ratio,

potentially up to 150% of the assets of the underlay. There is no guarantee that Ryan Labs will accurately identify or respond to risk indicators.



DISCLOSURESBacktested Returns - Hypothetical back tested returns have many inherent limitations. Unlike actual performance, hypothetical back tested returns do not

represent actual investment decisions for client accounts. Since investment decisions were not made, performance results may under- or over-compensate for

the effect, if any, of certain market factors, such as lack of liquidity and cash held as collateral for futures trading, and may not reflect the impact that certain

economic factors may have had on the decision-making process. Although Ryan Labs developed the hypothetical back tested performance herein according to

certain defined rules and standards, all back tested performance is developed with the benefit of hindsight. Other periods selected (if data had been available)

may have different results, including losses. There can be no assurance that Ryan Labs will achieve profits or avoid incurring substantial losses.

Ryan Labs cannot assure that the hypothetical back tested performance results will be similar to Ryan Labs’ management of the model or that the results shown

in the hypothetical back tested performance would be similar to what Ryan Labs’ performance would have been had it actually been managing the model in this

manner for the period presented. Ryan Labs believes that the back tested performance shown is reasonably representative of its expected management of the

model and is sufficiently relevant for consideration by potential clients.

Model Returns - The performance presented reflects model performance an investor may have obtained had it invested in the manner shown and does not

represent performance that any investor actually attained. The model performance presented is based upon the assumptions discussed above. Certain of the

assumptions have been made for modeling purposes and are unlikely to be realized. No representation or warranty is made as to the reasonableness of the

assumptions made or that all assumptions used in achieving the returns have been stated or fully considered. Model returns have many inherent limitations and

may not reflect the impact that material economic and market factors may have had on the decision-making process if client funds were actually managed in the

manner shown. Actual performance may differ substantially from the model performance presented. Changes in the assumptions may have a material impact on

the model returns presented. The period presented was primarily a period of rising returns. Other periods selected may have different results, including losses.

There can be no assurance that Ryan Labs will achieve profits or avoid incurring substantial losses.

Where indicated, returns are gross of advisory fees, net of transaction costs, and include the reinvestment of dividends. If the expenses were reflected, the

performance shown would be lower. Actual fees are described in Part 2A of Ryan Labs’ Form ADV and will vary depending on, among other things, the applicable

fee schedule and account size. For example, if $100,000 were invested and experienced a 10% annual return compounded monthly for 10 years, its ending value,

without giving effect to the deduction of advisory fees, would be $270,704 with annualized compounded return of 10.47%. If an advisory fee of 0.95% of the

average market value of the account were deducted monthly for the 10-year period, the annualized compounded return would be 9.43% and the ending dollar

value would be $246,355.

General discussions contained within this presentation regarding the market or market conditions represent the view of either the source cited or Ryan Labs.

Nothing contained herein is intended to predict the performance of any investment. There can be no assurance that actual outcomes will match the assumptions

or that actual returns will match any expected returns. The information contained herein is as of the date hereof, unless otherwise indicated, is subject to change,

and Ryan Labs assumes no obligation to update the information herein.



DISCLOSURESThe information in this presentation may contain projections or other forward-looking statements regarding future events, targets or expectations regarding the

strategies described herein, and is only current as of the date indicated. There is no assurance that such events or targets will be achieved, and may be

significantly different from that shown here. The information in this presentation, including statements concerning financial market trends, is based on current

market conditions, which will fluctuate and may be superseded by subsequent market events or for other reason.

The indices referenced herein are broad-based securities market indices and used for illustrative purposes only. They have been selected as they are well known

and are easily recognizable. Broad-based securities indices are unmanaged and are not subject to fees and expenses typically associated with managed accounts

or investment funds. Investments cannot be made directly into an index. The performance of the indices represents unmanaged, passive buy-and-hold strategies,

investment characteristics and risk/return profiles that differ materially from managed accounts or investment funds, and in investment in a managed account or

investment fun is not comparable to an investment in such indices or in the securities that comprise the indices. Past performance is no guarantee of future

results. Investments of the managed account or investment fund may be illiquid, making, at times, fair market valuation impossible or impracticable. As a result,

valuation of the managed account or investment fund may be volatile, reducing the utility of comparison to any index whose underlying securities are priced

according to market value, such as the indices. Investors should be aware that the managed account or investment fund may incur losses both when major

indices are rising and when they are falling.

The S&P 500 Index (“S&P 500”) is comprised of a representative sample of 500 large-cap companies. The index is an unmanaged, float-weighted index with each

stock’s weight in the index in proportion to its float, as determined by Standard & Poors. The S&P 500 is one of the most widely used benchmarks of U.S. equity

performance.

The Barclays Capital Aggregate Bond Index is a broad base index which represents the performance of investment grade bonds being traded in United States.

This material contains opinions and such opinions are subject to change without notice. Information contained herein has been obtained from sources believed to

be reliable, but not guaranteed. No part of this material may be reproduced in any form, or referred to in any other publication, without express written permission.

Front office personnel are supervised by Ryan Labs; middle and back office personnel are supervised by Sun Life. Notional assets under management, where

shown, represent gross notional value of the overlay strategy managed by the indicated entity, and may significantly exceed the net exposure of the overlay

strategies. The indicated entity may not be responsible for securities portfolios associated with the overlay strategy.

The hypothetical examples shown are intended to illustrate the process and generic benefits of utilizing an overlay strategy and are not intended to represent the

returns of any actual Ryan Labs overlay strategy, or the hypothetical performance of any proposed Ryan Labs overlay strategy. The results are not reflective of

any portfolio because important factors such as risk constraints, trading costs, universe breadth, market capitalization, portfolio turnover, incremental market

impact, number of holdings, sector/country/industry weighting, and external analyst coverage which could materially influence an actual portfolio have not been

considered.



DISCLOSURESThese Disclosures that are an integral part of the presentation, which is only intended for institutional investors and/or Qualified Eligible Persons.

PURSUANT TO AN EXEMPTION FROM THE COMMODITY FUTURES TRADING COMMISSION IN CONNECTION WITH ACCOUNTS OF QUALIFIED ELIGIBLE PERSONS, THIS

DOCUMENT IS NOT REQUIRED TO BE, AND HAS NOT BEEN, FILED WITH THE COMMISSION. THE COMMODITY FUTURES TRADING COMMISSION DOES NOT PASS UPON

THE MERITS OF PARTICIPATING IN A TRADING PROGRAM OR UPON THE ADEQUACY OR ACCURACY OF COMMODITY TRADING ADVISOR DISCLOSURE.

CONSEQUENTLY, THE COMMODITY FUTURES TRADING COMMISSION HAS NOT REVIEWED OR APPROVED THIS TRADING PROGRAM OR THIS BROCHURE OR ACCOUNT

DOCUMENT.

The information contained herein employs proprietary projections of expected returns. The relative relationships and forecasts contained herein are based upon proprietary

research and are developed through analysis of historical data and capital markets theory. Any opinions and estimates offered constitute our judgment and are subject to

change without notice, as are statements of financial market trends, which are based on current or recent market conditions.

HYPOTHETICAL PERFORMANCE RESULTS HAVE MANY INHERENT LIMITATIONS, SOME OF WHICH ARE DESCRIBED BELOW. NO REPRESENTATION IS BEING MADE

THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFITS OR LOSSES SIMILAR TO THOSE SHOWN. IN FACT, THERE ARE FREQUENTLY SHARP DIFFERENCES

BETWEEN HYPOTHETICAL PERFORMANCE RESULTS AND THE ACTUAL RESULTS SUBSEQUENTLY ACHIEVED BY ANY PARTICULAR TRADING PROGRAM.

ONE OF THE LIMITATIONS OF BACKTESTED HYPOTHETICAL PERFORMANCE DERIVED FROM THE RETROACTIVE APPLICATION OF A MODEL IS THAT THEY ARE

GENERALLY PREPARED WITH THE BENEFIT OF HINDSIGHT. IN ADDITION, HYPOTHETICAL TRADING DOES NOT INVOLVE FINANCIAL RISK, AND NO HYPOTHETICAL

TRADING RECORD CAN COMPLETELY ACCOUNT FOR THE IMPACT OF FINANCIAL RISK IN ACTUAL TRADING. FOR EXAMPLE, THE ABILITY TO WITHSTAND LOSSES OR

TO ADHERE TO A PARTICULAR TRADING PROGRAM IN SPITE OF TRADING LOSSES ARE MATERIAL POINTS WHICH CAN ALSO ADVERSELY AFFECT ACTUAL TRADING

RESULTS. THERE ARE NUMEROUS OTHER FACTORS RELATED TO THE MARKETS IN GENERAL OR TO THE IMPLEMENTATION OF ANY SPECIFIC TRADING PROGRAM

WHICH CANNOT BE FULLY ACCOUNTED FOR IN THE PREPARATION OF HYPOTHETICAL PERFORMANCE RESULTS AND ALL OF WHICH CAN ADVERSELY AFFECT

ACTUAL TRADING RESULTS. RYAN LABS HAS LITTLE OR NO EXPERIENCE IN TRADING ACTUAL ACCOUNTS FOR ITSELF OR FOR CUSTOMERS. BECAUSE THERE ARE

LITTLE OR NO ACTUAL TRADING RESULTS TO COMPARE TO THE HYPOTHETICAL RESULTS, CUSTOMERS SHOULD BE PARTICULARLY WARY OF PLACING UNDUE

RELIANCE ON THESE HYPOTHETICAL PERFORMANCE RESULTS.

THESE RESULTS ARE BASED ON SIMULATED OR HYPOTHETICAL PERFORMANCE RESULTS THAT HAVE CERTAIN INHERENT LIMITATIONS. UNLIKE THE RESULTS

SHOWN IN AN ACTUAL PERFORMANCE RECORD, THESE RESULTS DO NOT REPRESENT ACTUAL TRADING. ALSO, BECAUSE THESE TRADES HAVE NOT ACTUALLY

BEEN EXECUTED, THESE RESULTS MAY HAVE UNDER-OR OVER-COMPENSATED FOR THE IMPACT, IF ANY, OF CERTAIN MARKET FACTORS, SUCH AS LACK OF

LIQUIDITY. SIMULATED OR HYPOTHETICAL TRADING PROGRAMS IN GENERAL ARE ALSO SUBJECT TO THE FACT THAT THEY ARE DESIGNED WITH THE BENEFIT OF

HINDSIGHT. NO REPRESENTATION IS BEING MADE THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFITS OR LOSSES SIMILAR TO THESE BEING SHOWN.

PERFORMANCE RESULTS ARE GROSS OF INVESTMENT MANAGEMENT FEES. THE DEDUCTION OF AN ADVISORY OR OTHER FEES, COMMISSIONS AND EXPENSES

REDUCES AN INVESTOR’S RETURN. ACTUAL ACCOUNT PERFORMANCE WILL VARY DEPENDING ON INDIVIDUAL PORTFOLIO SECURITY SELECTION AND THE

APPLICABLE FEE SCHEDULE.

PAST PERFORMANCE IS NOT INDICATIVE OF FUTURE RESULTS.

MARKET PARTICIPATION PRESENTS THE POTENTIAL FOR LOSS AS WELL AS PROFIT.



DISCLOSURES1. Hedge Ratio

The DRP daily process, based on a volatility matrix, determines a daily Hedge Ratio that is based on a $1 portfolio value. When the Hedge Ratio

equals zero = 0, it means that no hedging position is required in Treasury futures. When the Hedge Ratio is greater than zero > 0, it means that a

hedge position of Treasury futures is required in the amount of holding Treasury future of value = $1 * hedge ratio. An example is shown as

below:

Beginning Portfolio Value = $200MM

Hedge ratio = 0.8

Hold Treasury Futures of Value = $200MM * 0.8 = $160MM

The hedge ratio varies every day. From May 2007 to December 2018, the minimum MIN Hedge Ratio was equal to 0.002, while the maximum

Hedge Ratio was 1.50, and the mean Hedge Ratio was 0.73. A hedge ratio greater than 1.0 implies more notional is being hedged than the

underlying portfolio value indicative of a more volatility environment.

2. Gearing

The use of derivative strategies allow investors to start mandates unfunded (only posting collateral however mark to market can generate daily

cash flow loses). On a standalone basis a derivative strategy has an expected return per unit of volatility and clients can choose their desired

level of volatility for the strategy. When ported onto an underlying asset, the same can be true to measure the derivative strategy relative to the

underlying asset in units of expected (historical) TE.

An example is shown below:


Gearing = 50%

Hedge ratio = 1.25

Hold Treasury Future of Value = $200MM*1.25*50% = $125MM


Expected TE: 1000

TE Target 750

Gearing = 75%

Hedge ratio = 1.75

Hold Treasury Future of Value = $200MM*1.75*75% = $262.5MM

Gearing is determined by client/consultant. It can be changed as requested.



DISCLOSURES

3. Negative Semi-Variance

Negative Semi-Variance to S&P 500 is an average of the squared deviations of portfolio return to S&P 500 return when S&P 500 total return

is negative. Formula as below:

𝑁𝑒𝑔𝑎𝑡𝑖𝑣𝑒 𝑆𝑒𝑚𝑖𝑣𝑎𝑟𝑖𝑎𝑛𝑐𝑒 𝑡𝑜 𝑆&𝑃 500 =1

𝑛

1

𝑛

𝑅𝑃 − 𝑅𝑆𝑃∗ 2

𝑅𝑃 = 𝑇𝑜𝑡𝑎𝑙 𝑅𝑒𝑡𝑢𝑟𝑛 𝑜𝑓 𝑈𝑛𝑑𝑒𝑟𝑙𝑦𝑖𝑛𝑔 𝐵𝑜𝑛𝑑𝑠 + 𝐷𝑅𝑃;𝑅𝑆𝑃∗ = 𝑇𝑜𝑡𝑎𝑙 𝑅𝑒𝑡𝑢𝑟𝑛 𝑜𝑓 𝑆&𝑃 500 𝑤ℎ𝑒𝑛 𝑡𝑜𝑡𝑎𝑙 𝑟𝑒𝑡𝑢𝑟𝑛 𝑖𝑠 𝑛𝑒𝑔𝑎𝑡𝑖𝑣𝑒


Documents

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