vix webinar presentation slides final - s&p dow jones indices · please see the last slides for...

How Are Institutional Investors Using VIX®?

WebinarThursday, September 22, 2016

Copyright © 2016 by S&P Global. All rights reserved.

This webinar is accepted for 1-hour CFA® , CFP® and, CIMA® credit.

Email [email protected] if you have not already indicated that you would like to receive credit for this webinar. For CFA credit, please provide your CFA ID number. Credit is not available for replays of this webinar.

CE Credits

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S&P Dow Jones Indices emphasizes to participants that Matt Moran, John Burkhartzmeyer, David Pedack, and Mike Edleson are guest speakers and are not affiliated with S&P Dow Jones Indices and that S&P Dow Jones Indices is not providing endorsements as to the opinions expressed which are those of the guest speaker for this webinar. S&P Dow Jones Indices offers no guarantees or warranties as to the accuracy and reliability of opinions expressed.

Guest speakers are not affiliated with S&P Dow Jones Indices and S&P Dow Jones Indices does not sponsor, endorse, sell, or promote any product based on an S&P Dow Jones index nor does it make any representation regarding the advisability of investing in the products.

Disclaimer

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Roby Muntoni

Global Head Asset Owners ChannelS&P Dow Jones IndicesRoby Muntoni is Global Head of the Asset Owners Channel for S&P Dow Jones Indices (S&P DJI). The Asset Owners Channel focuses on developing and managing relationships with asset owners to promote S&P DJI’s indices and services, across asset classes. Prior to joining S&P DJI in 2009, Roby was a Managing Director at Bear Stearns Asset Management and Vice President at Bank of New York’s Asset Management, leading product development efforts for the institutional market. Previously, Roby directed Index Operations at financial data provider Mergent Inc. (formerly a division of Moody’s), responsible for launching the Dividend Achievers family of indices, which were acquired by NASDAQ. Roby holds a bachelor’s in communications from Queens University, Charlotte, and an MBA from the University of North Carolina Charlotte.

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More to Read and Watch

VIX on S&P DJI’s Indexology® MicrositeThe Volatility of Active

Management

Look out for complimentary copies of these publications in our “Thank You” email. Sign up to receive future index-related research, commentary, and educational publications at www.spdji.com and www.cboe.com/VIX

Indexology Blog: Dividend Volatility and Correlations

Pursue Powerful OutcomesWith VIX Options and Futures

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Matthew Moran

Vice President, Business DevelopmentChicago Board Options ExchangeMr. Matthew Moran is vice president of business development for the Chicago Board Options Exchange (CBOE), where he is responsible for many of the exchange's educational efforts for pension funds, mutual funds, and other institutional investors. Previously, he was trust counsel at Harris Bank and vice president at Chicago Mercantile Exchange. He is an associate editor of two Institutional Investor publications -- The Journal of Trading and The Journal of Index Investing. Mr. Moran holds JD and MBA degrees from the University of Illinois.

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Vinit Srivastava

Senior Director, Strategy and Volatility IndicesS&P Dow Jones IndicesVinit Srivastava is Senior Director, Strategy and Volatility Indices, at S&P Dow Jones Indices, focusing on alternative beta strategies including factor-based indices, dividends and volatility, as well as quantitative, thematic, and asset-allocation strategies. In his role, Vinit works closely with the sales, marketing, and Global Research & Design departments to bring new ideas to market.Prior to his current role, Vinit worked for Oracle USA, Inc. in engineering and product management roles for seven years. At McGraw-Hill Financial, Vinit worked on Business Strategy and Corporate Strategy assignments prior to taking his role at S&P Dow Jones Indices.Vinit holds an MBA from the Darden School of Business at the University of Virginia, a master’s in Mechanical Engineering from Carnegie Mellon University, and a B. Tech in Mechanical Engineering from IIT Kharagpur, India.

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Mike Edleson, CFA

Chief Risk OfficerUniversity of ChicagoMike Edleson is responsible for the risk management of the University’s endowment. He joined the University’s Office of Investment in 2010.From 2003 to 2010, Mike ran risk management globally for four divisions of Morgan Stanley as managing director, including equities and MSSB (brokerage). Previously, he worked as chief economist and senior vice president of NASDAQ and NASD, and served on the boards of directors of several organizations and companies. Mike was a finance professor at Harvard Business School for over six years, following four years on the faculty at West Point; he was an Army engineer officer and served nearly 30 years in uniform, active and reserve. Mike is a financial author and inventor, and has been co-editor or associate editor of two finance journals. He is on the board of directors of Myriad Funds, Financial Management Association Int'l, and serves on the investment committee for West Point. Mike earned a BS, summa cum laude, from West Point, an MS and PhD in economics from MIT, and is a CFA Charterholder.

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David Pedack, CFA

Portfolio Manager, Equity DerviativesRussell InvestmentsDavid Pedack is a portfolio manager in the equity derivatives group at Russell Investments. David manages options and volatility overlays for the Russell Multi Strategy Volatility Fund, Strategic Call Overwriting Fund , Enhanced Income Fund and a variety of separate accounts. He is responsible for trading, implementation, and ongoing derivatives research for the Russell funds and third-party clients. Prior to becoming a portfolio manager in Russell Investments’ equity derivatives group, David was a quantitative analyst at the firm.

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John Burkhartzmeyer

Senior Derivatives Trader, State of Wisconsin Investment Board (SWIB)John has been a derivatives trader for over 20 years and is a part of SWIB’s Multi-Asset group. He is responsible for SWIB’s derivative trading and is member of the firm’s strategy team. Prior to, he spent time on the sell side with both Collins Stewart and Pali Capital, serving as an Institutional Derivatives Trader and Strategist. John started out as Designated Primary Market Maker with Mercury Trading on the Chicago Board Options Exchange (CBOE) in 1993, and after leaving the trading floor, he joined Knight Financial Products as a Risk Manager, where he helped oversee floor-based trading operations. John has previously held memberships on the CBOE, International Securities Exchange (ISE), Philadelphia Stock Exchange (PHLX), and Pacific Stock Exchange (PSE), and earned a B.A degree from Gustavus Adolphus College.

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CBOE 11

An Introduction to the VIX® Index, VIX Futures and VIX Options

Matthew MoranVice President, Business DevelopmentChicago Board Options Exchange

September 22, 2016

CBOE 12

Volatility ConceptsImplied Volatility is a forward-looking annualized volatility figure derived from the current market price of options. The VIX Index is a measure of 30-calendar-day implied or expected volatility.

Historic Volatility is a measure of actual price changes during a specific time period in the past. Typically, historic volatility is measured as the annualized standard deviation of daily returns during a specific past period.

CBOE 13

CBOE Volatility Index (VIX)

Since 1993 a premier barometer of investor sentiment and market volatility.Measures the market's expectation of 30-day volatility implicit in the prices of near-term S&P 500 (SPX) options. The SPX options used in the VIX calculation are –

O-T-M puts and calls covering the entire range of strike prices (the “ volatility skew”)SPX options with more than 23 days and less than 37 days to expiration to provide a 30-calendar-day volatility measure

Launch of VIX futures in 2004 and VIX options in 2006, with settlement date on Wednesday (30 days before SPX expiration)The VIX Index is not investablewww.cboe.com/VIX

CBOE 14

VIX Index Since 1990

For all the VIX daily closing values since Jan. 1990 –(1) The average

value was 19.8, and

(2) The medianvalue was 17.9.

The years with the highest average daily closes were 2008 (32.7) and 2009 (31.5)

Average Daily Closing Values of VIX in Recent Years2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 201512.8 12.8 17.5 32.7 31.5 22.5 24.2 17.8 14.2 14.2 16.7

The VIX Index often spiked upward when S&P 500 (SPX) fell

CBOE 15

Key Reasons for High Interest in VIX

1. High Volatility of Volatility. Since 2002 the average historic volatility of VIX has been more than 100.

2. Negative Correlations. Since 2002 SPX and VIX have had a negative correlation of weekly returns, and the correlation was even more negative in 2008.

30‐Day Historic Volatility (average from 2002 through July 2016)

VIX S&P 500 Emerging Mkts. Stocks

30-yr U.S. Treasury Bonds Commodities

102.9 17.0 17.2 14.1 22.6 Sources: Bloomberg and CBOE.

Correlations of Weekly Returns of SPX vs. Other Indexes

VIX Emerging Mkts. Stocks

30-yr U.S. Treasury Bonds Commodities

2002 through Aug. 2016 -0.70 0.71 -0.42 0.31

In Year 2008 -0.83 0.78 -0.30 0.39 Sources: Bloomberg and CBOE.

Past performance is not predictive of future returns. Indexes are not investable. In the tables above, the indexes used for the asset classes are the MSCI Emerging Markets Index (in US$), the Citigroup 30-Year Treasury Bond Index, and the S&P GSCI Index (for commodities). Please see the last slides for important disclosures.

CBOE 16

Reason #3 - Convexity

Dates with Biggest % Changes in SPX & VIX (Jan. 1990 ‐ Sep. 12, 2016)

Biggest % changes in S&P 500 (SPX) Biggest % changes in VIX Index

SPX VIX SPX VIX15-Oct-2008 -9.0% 25.6% 27-Feb-2007 -3.5% 64.2%1-Dec-2008 -8.9% 23.9% 15-Nov-1991 -3.7% 51.7%

29-Sep-2008 -8.8% 34.5% 23-Jul-1990 -1.7% 51.5%9-Oct-2008 -7.6% 11.1% 8-Aug-2011 -6.7% 50.0%27-Oct-1997 -6.9% 34.3% 24-Jun-2016 -3.6% 49.3%31-Aug-1998 -6.8% 11.8% 21-Aug-2015 -3.2% 46.4%20-Nov-2008 -6.7% 8.9% 24-Aug-2015 -3.9% 45.3%8-Aug-2011 -6.7% 50.0% 15-Apr-2013 -2.3% 43.2%

19-Nov-2008 -6.1% 9.8% 4-Feb-1994 -2.3% 41.9%22-Oct-2008 -6.1% 31.1% 3-Aug-1990 -1.9% 40.7%

9-Sep-2016 -2.5% 39.9%21-Nov-2008 6.3% -10.1% 4-Aug-2011 -4.8% 35.4%10-Mar-2009 6.4% -10.7% 18-Aug-2011 -4.5% 35.1%24-Nov-2008 6.5% -11.0%13-Nov-2008 6.9% -10.0%23-Mar-2009 7.1% -5.8% 15-Jun-2006 2.1% -25.9%28-Oct-2008 10.8% -16.4% 9-Aug-2011 4.7% -27.0%13-Oct-2008 11.6% -21.4% 10-May-2010 4.4% -29.6% Sources: Bloomberg and CBOE. www.cboe.com/VIX

3. Convexity. As the SPX declines, the VIX Index can explode on the upside. VIX shot up by more than 40% on ten different days since 1990.

Past performance is not predictive of future returns. Please see the last slides for important disclosures.

CBOE 17

Reason #4 – Volatility Risk Premium

Average of End‐of‐Day Values Per Year1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

VIX Index 25.6 24.4 23.3 25.7 27.3 22.0 15.5 12.8 12.8 17.5 32.7 31.5 22.5 24.2 17.8 14.2 14.2 16.7

Subsequent 30-trading-day realized

volatility of SPX19.1 18.7 22.1 20.2 25.7 15.7 11.2 10.4 9.6 16.6 36.7 24.2 16.7 21.6 12.9 11.2 11.5 15.4

Sources: Bloomberg and CBOE

4. Richly Priced Index Options. Per the figures below, the SPX options have been “richly” priced in 17 of 18 years since 1998.

CBOE 18

VIX Futures and Options

Key Specifications

VIX Futures Pricing Based on Forward Value of VIX.

VIX futures trade more than 23 hours per day and VIX options trade more than 13 hours per day.

Expiration & settlement are usually on Wednesday.

VIX Futures VIX OptionsExchange CBOE Futures Exchange (CFE) Chicago Board Options Exchange (CBOE)

Year of Introduction 2004 2006

Ticker VX and VX01 through VX53 VIXMultiplier $1,000 $100

Extended Trading Hours CT (Chicago time)

On the Monday trading day - 5:00 p.m. (Sunday) to 8:30 a.m. On the Tuesday through Friday trading days -- 3:30 p.m. (previous day) to 8:30 a.m.

2:00 a.m. to 8:15 a.m.

Regular Trading Hours CT (Chicago time)

Last Trading DateTrading hours for expiring VX futures contracts end at 8:00 a.m. Chicago time on the Final Settlement Date.

The last trading day (usually a Tuesday) is the business day prior to the Expiration Date of each contract expiration.

Expiration and Settlement

Settlement Value

Number of Contract Expirations

Up to six near-term expiration weeks, nine near-term serial months and five months on the February quarterly cycle for the VX futures contract.

Up to six 6 weekly expirations and up to 12 standard (monthly) expirations in VIX options may be listed.

Options Exercise Style Not applicable European - VIX options generally may be

exercised only on the Expiration Date. Please visit www.cboe.com/VIX for more details.

Usually on a Wednesday morning (30 days before a Friday settlement for SPX options)

The exercise-settlement value for VIX futures and options (Ticker: VRO) shall be a Special Opening Quotation (SOQ) of VIX calculated from the sequence of opening prices during regular trading hours for SPX of the options used to calculate the index on the settlement date.

8:30 a.m. to 3:15 p.m.

VIX Futures and VEQTOR September 22, 2016

Vinit SrivastavaSenior DirectorStrategy Indices

Copyright © 2016 by S&P Global. All rights reserved.

VIX and the S&P 500• VIX is also referred to as the “investor fear gauge” as it hit its highest levels during periods of

market turbulence historically.

Source: S&P Dow Jones Indices LLC. Data as of June 30, 2016. Past performance is no guarantee of future results. It is not possible to invest directly in an index. Charts are provided forillustrative purposes and reflect hypothetical historical performance. Please see the Performance Disclosure at the end of this document for more information regarding the inherent limitations associated with back-tested performance. Permission to reprint or distribute any content from this presentation requires the prior written approval of S&P Dow Jones Indices. Not for distribution to the public. Copyright © 2016 by S&P Global. All rights reserved.

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S&P 500 Versus VIXCorrelation (Jan. 1990 – Aug. 2016): - 0.71

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S&P 500 Versus VIXCorrelation (Aug. 2011 – Aug. 2016): - 0.81

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VIX Spot (RHS)

Vertical Axes represent index levels (both LHS and RHS)

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VIX Futures IndicesIn January 2009, Standard & Poor’s launched the S&P 500 VIX Futures Index Series.

• The S&P 500 VIX Short-Term Futures Index™ measures the return from a rolling long position in the first and second month VIX futures contracts. The index maintains a constant one-month maturity.

- Rolls continuously throughout each month from the shorter-term into the longer-term VIX futures contract.

• The S&P 500 VIX Mid-Term Futures Index™ measures the return from a rolling long position in the fourth, fifth, sixth and seventh month VIX futures contracts. The index maintains a constant five-month maturity.

- Rolls continuously throughout each month from the shortest-term contract into the longest-term contract while maintaining positions in the other two contracts.

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Permission to reprint or distribute any content from this presentation requires the prior written approval of S&P Dow Jones Indices. Not for distribution to the public. Copyright © 2016 by S&P Global. All rights reserved.

Tracking the VIX Spot

Source: S&P Dow Jones Indices LLC. Statistics are calculated using daily returns. Data as of Aug. 31, 2016. Past performance is no guarantee of future results. It is not possible to invest directly in an index. Chart is provided for illustrative purposes and reflects hypothetical historical performance. Please see the Performance Disclosure at the end of this document for more information regarding the inherent limitations associated with back-tested performance. Permission to reprint or distribute any content from this presentation requires the prior written approval of S&P Dow Jones Indices. Not for distribution to the public. Copyright © 2016 by S&P Global. All rights reserved.

The S&P 500 VIX Futures Index Series does not track the VIX spot perfectly• Futures are less sensitive than the spot to the market movement• Sensitivity declines with longer dated contracts

Rolling 21-Trading-Day Beta With VIX Spot (Vertical Axis)

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S&P 500 VIX Short-Term Futures Index S&P 500 VIX Mid-Term Futures Index

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Volatility Versus Equity

Source: S&P Dow Jones Indices LLC. Statistics are calculated using daily returns. Data as of Aug. 31, 2016. Permission to reprint or distribute any content from this presentation requires the prior written approval of S&P Dow Jones Indices. Not for distribution to the public. Copyright © 2016 by S&P Global. All rights reserved.

20 Worst 1-Day Performance for S&P 500 Since Dec. 2005DATE S&P 500 VIX SPOT S&P 500 VIX SHORT-

TERM FUTURES INDEXS&P 500 VIX MID-TERM FUTURES INDEX

Oct. 2008 -9.03% 25.61% 14.03% 8.39%Dec. 2008 -8.93% 23.93% 12.76% 10.54%Sep. 2008 -8.79% 34.48% 14.00% 8.31%Oct. 2008 -7.62% 11.11% 9.97% 5.04%Nov. 2008 -6.71% 8.89% 5.28% 4.93%Aug. 2011 -6.66% 50.00% 19.06% 7.21%Nov. 2008 -6.12% 9.79% 9.79% 6.53%Oct. 2008 -6.10% 31.14% 10.34% 6.61%Oct. 2008 -5.74% 3.13% 9.60% 0.75%Jan. 2009 -5.28% 22.86% 12.82% 6.04%Nov. 2008 -5.27% 14.31% 6.52% 5.89%Nov. 2008 -5.19% 8.17% 7.72% 2.85%Nov. 2008 -5.03% 16.72% 11.76% 4.73%Feb. 2009 -4.91% 6.94% 6.30% 2.12%Aug. 2011 -4.78% 35.41% 21.35% 8.50%Sep. 2008 -4.71% 23.54% 6.00% 3.12%Sep. 2008 -4.71% 19.54% 5.72% 3.20%Mar. 2009 -4.66% 13.59% 6.56% 2.10%Feb. 2009 -4.56% 13.35% 4.34% 2.57%Aug. 2011 -4.46% 35.12% 19.23% 10.74%CORRELATION WITH S&P 500 (DEC. 2005 – AUG. 2016)

- -74.57% -75.25% -74.49%CORRELATION WITH VIX SPOT (DEC. 2005 – AUG. 2016)

- - 88.77% 79.64%

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VIX Term StructureTerm structure decay results in the index declining when the futures curve is in contango.

In the S&P 500 VIX Short-Term Futures Index, a positive roll cost occurs on 76% of days, with an average daily loss of 0.18%.

In the S&P 500 VIX Mid-Term Futures Index, a positive roll cost occurs on 64% of days, with a lower average daily loss of 0.07%.

Source: Liu & Dash, Volatility ETFs & ETNs, Journal of Trading, Winter 2012.

Source: S&P Dow Jones Indices LLC. Statistics are calculated using daily returns. Data as of Aug. 31, 2016. Past performance is no guarantee of future results. It is not possible to invest directly in an index. Chart is provided for illustrative purposes and reflects hypothetical historical performance. Please see the Performance Disclosure at the end of this document for more information regarding the inherent limitations associated with back-tested performance. Permission to reprint or distribute any content from this presentation requires the prior written approval of S&P Dow Jones Indices. Not for distribution to the public. Copyright © 2016 by S&P Global. All rights reserved.

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HEDGING VOLATILITY EXPOSURE THROUGH S&P 500 DYNAMIC VEQTOR INDEX (VEQTOR)

Allocates the majority of weightings to the S&P 500 (TR) when volatility is low.

EquityS&P 500

Allocates part of the weightings to the S&P 500 VIX Short-Term Futures Total Return Index to provide a “volatility hedge” when volatility is high.

VolatilityVIX Futures

Shifts 100% weighting to an interest-bearing cash investment when the index loses more than 2% in a week (stop loss).

CashO/N LIBOR

• Implied equity volatility has historically had a strongly negative correlation to equity market returns and is considered a useful tool to hedge against the potential downside of the broad equity market.

• The S&P 500 Dynamic VEQTOR Index dynamically allocates between equity, volatility and cash in order to hedge equity portfolio tail risk.

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S&P 500 Dynamic VEQTOR Index

Source: S&P Dow Jones Indices LLC. Data as of June 30, 2016. Monthly total return in USD is used in calculation. Past performance is no guarantee of future results. It is not possible to invest directly in an index. Charts are provided for illustrative purposes and reflect hypothetical historical performance. Please see the Performance Disclosure at the end of this document for more information regarding the inherent limitations associated with back-tested performance. Permission to reprint or distribute any content from this presentation requires the prior written approval of S&P Dow Jones Indices. Not for distribution to the public. Copyright © 2016 by S&P Global. All rights reserved.

Performance

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Wealth Curves

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S&P 500 VIX Short-Term Futures

S&P 500 Dynamic VEQTOR

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VIX was launched in 1993. The S&P 500 Dynamic VEQTOR Index was launched on Nov. 18, 2009. The S&P 500 VIX Short-Term Futures Index was launched on May 10, 2010. The S&P 500 VIX Mid-Term Futures Index was launched on Jan. 22, 2009. All information presented prior to an index’s Launch Date is hypothetical (back-tested), not actual performance. The back-test calculations are based on the same methodology that was in effect on the index Launch Date. Complete index methodology details are available at www.spdji.com.

S&P Dow Jones Indices defines various dates to assist our clients in providing transparency. The First Value Date is the first day for which there is a calculated value (either live or back-tested) for a given index. The Base Date is the date at which the Index is set at a fixed value for calculation purposes. The Launch Date designates the date upon which the values of an index are first considered live: index values provided for any date or time period prior to the index’s Launch Date are considered back-tested. S&P Dow Jones Indices defines the Launch Date as the date by which the values of an index are known to have been released to the public, for example via the company’s public website or its datafeed to external parties. For Dow Jones-branded indices introduced prior to May 31, 2013, the Launch Date (which prior to May 31, 2013, was termed “Date of introduction”) is set at a date upon which no further changes were permitted to be made to the index methodology, but that may have been prior to the Index’s public release date.

Past performance of the Index is not an indication of future results. Prospective application of the methodology used to construct the Index may not result in performance commensurate with the back-test returns shown. The back-test period does not necessarily correspond to the entire available history of the Index. Please refer to the methodology paper for the Index, available at www.spdji.com for more details about the index, including the manner in which it is rebalanced, the timing of such rebalancing, criteria for additions and deletions, as well as all index calculations.

Another limitation of using back-tested information is that the back-tested calculation is generally prepared with the benefit of hindsight. Back-tested information reflects the application of the index methodology and selection of index constituents in hindsight. No hypothetical record can completely account for the impact of financial risk in actual trading. For example, there are numerous factors related to the equities, fixed income, or commodities markets in general which cannot be, and have not been accounted for in the preparation of the index information set forth, all of which can affect actual performance.

The Index returns shown do not represent the results of actual trading of investable assets/securities. S&P Dow Jones Indices LLC maintains the Index and calculates the Index levels and performance shown or discussed, but does not manage actual assets. Index returns do not reflect payment of any sales charges or fees an investor may pay to purchase the securities underlying the Index or investment funds that are intended to track the performance of the Index. The imposition of these fees and charges would cause actual and back-tested performance of the securities/fund to be lower than the Index performance shown. As a simple example, if an index returned 10% on a US $100,000 investment for a 12-month period (or US $10,000) and an actual asset-based fee of 1.5% was imposed at the end of the period on the investment plus accrued interest (or US $1,650), the net return would be 8.35% (or US $8,350) for the year. Over a three year period, an annual 1.5% fee taken at year end with an assumed 10% return per year would result in a cumulative gross return of 33.10%, a total fee of US $5,375, and a cumulative net return of 27.2% (or US $27,200).

Performance Disclosure

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Copyright © 2016 by S&P Dow Jones Indices LLC, a part of S&P Global. All rights reserved. Standard & Poor’s ®, S&P 500 ® and S&P ® are registered trademarks of Standard & Poor’s Financial Services LLC (“S&P”), a subsidiary of S&P Global. Dow Jones ® is a registered trademark of Dow Jones Trademark Holdings LLC (“Dow Jones”). Trademarks have been licensed to S&P Dow Jones Indices LLC. Redistribution, reproduction and/or photocopying in whole or in part are prohibited without written permission. This document does not constitute an offer of services in jurisdictions where S&P Dow Jones Indices LLC, Dow Jones, S&P or their respective affiliates (collectively “S&P Dow Jones Indices”) do not have the necessary licenses. All information provided by S&P Dow Jones Indices is impersonal and not tailored to the needs of any person, entity or group of persons. S&P Dow Jones Indices receives compensation in connection with licensing its indices to third parties. Past performance of an index is not a guarantee of future results.

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CBOE 29

Panel Discussion: VIX Institutional Usage

Moderator: • Matthew Moran, Vice President, Business Development, CBOE

Panelists:• Mike Edleson, CFA, Chief Risk Officer at the University of Chicago

• David Pedack, CFA, Portfolio Manager, Equity Derviatives, Russell Investments

• John Burkhartzmeyer, Senior Derivatives Trader, State of Wisconsin Investment Board

CBOE 30

Panel Discussion: VIX Institutional Usage

Sample Questions:

• Can long positions in VIX-related products be used to diversify and hedge left tail risk?

• Can short positions in VIX-related products be used to enhance long-term risk-adjusted returns?

CBOE 31

Sample VIX Strategies*

Investors who are Bullish on VIX, and Bearish on stocks might consider –Long VIX Call OptionsLong VIX Call SpreadsShort VIX Put Credit SpreadsLong VIX Futures

Investors who are Bearish on VIX, and Bullish on stocks might consider –Long VIX Put OptionsLong VIX Put SpreadsShort VIX Call Credit SpreadsShort VIX Futures

Caution – sometimes VIX and stock prices move in the same direction.

Please visit www.cboe.com/VIX for more information about prices and strategies.

CBOE 32

VIX Spot Index and VIX Futures in 2008

% change over 101-trading-day period below - VIX spot 210%; VIX Nov fut 184%; VIX Dec fut 169%

0102030405060708090

30-Jun-08 30-Aug-08 30-Oct-08

(June 30 - Nov. 19, 2008) Source: Bloomberg

VIX Spot

VIX Futures Oct '08

VIX Futures Nov '08

VIX Futures Dec '08

VIX generally was in –> Contango in Aug. 2008 (spot lower than futures)> Backwardation in Oct. 2008 (spot higher than futures)


CBOE 33

VIX Index and Futures In August 2015Weekly futures and options – more precision and responsiveness

The addition of weekly expirations to standard monthly expirations offers volatility exposures that more precisely track the performance of the VIX Index.


Wrong‐Way Risk & Endowment Investing

It’s a Conspiracy against LinearityMarketsProductsStrategiesStructural (Brittle)Agency issues

Your Beta / Exposure isn’t what you think it is, when it matters most

‐50

‐40

‐30

‐20

‐10

0

10

‐50 ‐40 ‐30 ‐20 ‐10 0 10

Right‐Way

Linear

Wrong‐Way

β= .75 always

β> .75,increasingwith losses

Lossesaccelerating

Lossesslowingβ< .75,

risk flattening with losses

Overall Market Return (%)

Portfolio

Loss (%

)

0

10

20

30

40

50

60

70

80

90

500 700 900 1100 1300 1500

Level of V

IX

SPX TR Index Level

Past 13 years, weekly observations

Relationship of Volatility and Market Level

Aug‐Oct 2008

‐0.1

0.0

0.1

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1.0

EM Equity Credit Real Estate Commodities

Rolling

1y corrletio

n with

S&P500

(Mon

thly Returns)

Correlations Spiked During Financial Crisis

Before Crisis

Average correlation measure with Equities for 18 months before and after Sept 2008

Credit spiked

hard,

a few quarters earlier

thruNov'07

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‐60.0% ‐40.0% ‐20.0% 0.0% 20.0% 40.0% 60.0%

Estim

ated

Beta (40d, previou

s 2 yrs price data)

Return on GEF Index in previous 2yrs

2y GEF Beta v 2y Return on GEF Index(assuming current portfolio)

end Aug 2008 ‐ Sep 2010 since Sep 2010

before May 2004 Jun 2004 ‐ Aug 2008

Sep ‐ Nov 2008

‐8%

‐6%

‐4%

‐2%

0%

2%

4%

6%

‐25% ‐20% ‐15% ‐10% ‐5% 0% 5% 10% 15%

Figure 6 Non‐l inearity and negative convexity in hedge fund returns, 2003‐13

Full sample

Drops 'Outlier'

S&P 500 Return

CS Agg HFI Return

Outlier ?

Investment Return

w/Performance Fee

‐30%

‐20%

‐10%

0%

10%

20%

‐20% ‐10% 0% 10%

Credit's Negative Convexity to Equity Markets, 1990‐2011

High Yield Distressed

Corp High Yield

SPX Monthly

Risk steeper to the downside

Vols Spike Correlations Spike Betas Spike Carry in Products Non‐Linear Fees

Negative Convexity in HF Returns

ANDRebalancing as a Short PutIlliquidity & LeveragePush for Returns

Wrong‐Way Risk‐Return Profile

ALL ENDOWMENTS HAVE NEGATIVELY CONVEX RETURNS / WRONG‐WAY RISK PROFILE

Our beta for up markets is 175% of our beta for down markets

Case Study: Why Portfolio Protection?Mike Edleson, CRO, University of Chicago

34

Behavioral & Cultural Issues

• Committee Behavior & Governance Breakdown• “Buy High, Sell Low”• Is Staff confident enough to invest when returns

are the highest (but markets are scariest)?

In a world of similar track records, the response to a crisis can make‐or‐break an endowment

Tail protection, economically and behaviorally, helps work against our most destructive human tendencies.

‐15%

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30%

‐150

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Total Capital Raised v Cohort Return(since 1990)

Private Capital Raised $B Performance (Cohort IRR) %

351

Expected returns generally highest after a crisis‐ Publics (but we must sell then)‐ Privates (but we stop investing then)‐ Most E&F simply stopped private investments and

didn’t restart until 2011 / later..

“Everybody’s got plans…until they get hit.” – Mike Tyson

A Tail Hedge program is like a mouth guard. Keeps the brain from getting too rattled during a crisis so we can keep our head in the game.

“We Planned & Positioned for this”“We have the cash, the risk capacity, and the confidence to take advantage of the opportunities being offered by the market”{

BONUSIn practice, strategic hedging of our negative convexity risk‐return profile makes us keenlyaware of “fake alpha” carry returns in our investments…this leads us to focus on the best, highest “true alpha” among them.

Risk Culture extends to convexity as well.Case Study: Why Portfolio Protection?Mike Edleson, CRO, University of Chicago

35

5% Spending Rule (5.5% here)–40% Scenario ▼

9.2% payout70‐75% Privatesfor a few years

Is a 9‐10% payout with 25‐30% in “liquid(?)” assets sustainable?Liquidity Needs: $1.2 – 1.4B in replay of crisis (while $7 →$4.7B)Predictable Cash Flow to meet Important LT Strategic OperationsDoes our “long term” investment horizon really excuse all sins?

Meeting the Needs of the University

Not just returns +%Reduces crisis betaCash in a CrisisReduces leverageBuys time, prevents disasterSurvival of the “Enterprise”

Enterprise Risk PerspectiveGifts not only smaller, but not gifted (high β)Debt shoots up, Enterprise more leveredHospital & Grants revenue potentially degraded

At this exact point, our liquidity disappears, and our investment risk skyrockets. Is this OK?

Tail Protectio

n

Tail Risk vs. The Higher Purpose Implementing a Protection Program

Protection Payoff

BUCK

Balancing Bang for the Buck and Basis

Various Hypothetical Strategies' Economics Shown

BANG

Expected Cost

Too Linear?

Ineffective

Too Expensive?

Basis Risk Too High?

Can Size Down

SWEETSPOT

What Risk Drivers? What portion of tail? …true “crisis”?Governance Support / FatigueSizing A Protection Program• Capital/Budget/Bleed/Cost• To Linearize return profile• To truncate most painful losses• To outperform peers in crisis• To provide $X of needed liquidity• To support %C of portfolio in carry/illiquids• To not impair long‐run entp. performance

Who does it (managers?)Strategic or Tactical?MonetizationRobustness

NOTE on COSTA small strategic portfolio protection program costs far less than most think. Nearly every‐one gets the math wrong on this.

Our actual experience, implemented over 4+ years, has been a (very) slight positive impact on portfolio return.

Case Study: Why Portfolio Protection?Mike Edleson, CRO, University of Chicago

36

CBOE 37

Four Benchmark Indexes


The S&P 500® VIX® Short-Term Futures Inverse Daily Index is designed to measure the performance of the inverse of the S&P 500 VIX Short-Term Futures Index, which utilizes prices of the next two near-term VIX futures contracts to replicate a position that rolls the nearest month VIX futures to the next month on a daily basis in equal fractional amounts.

Annual Returns2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 thru Aug. 31

-48.8% -71.0% 116.0% 144.8% -45.4% 162.6% 108.1% -7.9% -15.8% 46.3% S&P 500 VIX Short-Term Futures Inverse Daily Index

17.2% 21.3% 23.4% 1.6% 17.4% 3.5% 14.3% 5.8% -9.0% -2.0% S&P 500 Dynamic VEQTOR Index

5.5% -37.0% 26.5% 15.1% 2.1% 16.0% 32.4% 13.7% 1.4% 7.8% S&P 500

53.9% 83.9% -23.6% -13.2% -7.6% -52.9% -43.8% -16.5% -14.2% -11.8% S&P 500 VIX Mid-term Futures Index

Sources: Bloomberg and CBOE. Total return indexes (pre-tax with reinvested dividends).

What % allocation to any VIX-based strategy might have the potential to improve portfolio performance?

During what time periods did the indexes have positive and negative returns?

CBOE 38

More Gauges for Robust Analysis

SKEW Index is derived from the price of S&P 500 tail risk, and is calculated from the prices of SPX O-T-M options. www.cboe.com/SKEW

VVIX Index is an indicator of the expected volatility of the 30-day forward price of the VIX. www.cboe.com/VVIX

VIX Index is an indicator of the expected volatility of the 30-day forward price of the SPX Index.www.cboe.com/VIX

VXMT Index is an indicator of the expected volatility of the 6-month forward price of the SPX Index.www.cboe.com/VXMT

The averages shown below are for time period in charts

In recent years has VIX Index been lower than average and SKEW Index higher than average?If so, why?

Since Jan. 2008 VIX has been in contango on 82% of the days, and in backwardation on 18% of the days (using the 3-mo. futures prices)

CBOE 39

Term Structure for VIX Futures

How do investors implement VIX term structure trades?

Risk Premia Investing – Implied Volatility

p.40

Implied volatility – Risk Premia

Russell believes implied volatility is a risk premia based return source. Depending on client’s needs we offer many fully funded ways of capturing this premium:

Fully Funded Mandates• Call Overwriting• Put Writing• VIX Carry• Multi Strategy Volatility

Implied volatility – Hedging Solutions

Russell also offers overlay capabilities for non-funded tactical strategies:

• Equity Replacement• For example, risk reversals (sell put, buy call, costless) and

similar solutions.• Tactical Hedging and Downside Protection

• For example, put spread collars (buy spread put, sell call, costless) and similar solutions.

• Lower volatility strategy solutions • Diversification of return source• Alternative risk premia source

Source: Russell Investments. For Illustrative purposes.

Volatility StrategiesVolatility strategies capture various forms of volatility risk premium (VRP). Building a diversified approach is a more thoughtful way to capture VRP: Equity Implied Volatility versus Realized Volatility

The spread between option implied volatility and subsequent realized volatility. Historically the volatility implied by the price of options exceeds the actual volatility that occurs.

Volatility (VIX) Term Structure

The level of volatility across tenor (time to expiration) for a specific options type or futures curve. The volatility can either decrease typically in a contango term structure (VIX futures) as time to expiration approaches or increase as with a backwardated vol of vol (VIX options) term structure as time to expiration approaches.

Volatility of Implied Volatility (VVIX) versus Realized Volatility

The volatility of VIX options. Similar to a long observed and explainable difference between implied and realized volatility, there is an observable spread of implied versus realized volatility of volatility.

p.41

p.42

Implied Volatility Versus Realized Volatility

S&P 500 1M Realized

CBOE VIX Index

Volatility Risk Premium

Implied volatility exceeds realized volatility >80% of the time since 1990 therefore options can harvest the insurance premium known as VRP

This is Equity Implied versus Realized VRP

Strategy: Delta hedged index options (i.e. option straddles or strangles)

Source: Russell Investments. For Illustrative purposes.

p.43

Volatility Term Structure

This is Term Structure Premium

Source: Russell Investments. For Illustrative purposes. Generic contango and backwardation type curves.

Future implied volatility exceeds near dated implied volatility this is known as

volatility roll down or term structure premium

Strategy: Short futures to receive “roll down”, possibly hedge with longer dated futures

p.44Source: Implied volatility represented by VIX = CBOE Market Volatility Index. VVIX = CBOE Volatility of Volatility Index.

Implied Vol of VIX Versus Realized

VIX 1M Realized

CBOE VVIX Index Volatility Risk Premium

This is Volatility of Volatility Risk Premium

Strategy: Sell delta hedged VIX call options

CBOE 45

Volatility Skew – June 24 & Sept. 16 Implied Volatility

Is implied volatility generally higher for index options that can be used for left tail protection for portfolios (O-T-M SPX puts and O-T-M VIX calls)?

What types of trades can benefit from the fact that implied volatilities for VIX and SPX options vary at different levels of moneyness?

CBOE 46

Seasonality of Volatility

Have some periods during the years been consistently more volatile than other periods?

What types of trades can benefit from differing volatility levels throughout the year?

CBOE 47

VIX Index, Futures and Options Since 2008

Could the panelists comment on 1. liquidity, 2. capacity, & 3. execution – during different volatility regimes?

CBOE 48

VIX Futures Open Interest

VIX futures open interest rose since then (often when the VIX Index was at below-average levels) and hit a record 543,192on Sept. 8, 2016.

In late January 2009 the VIX futures open interest was 9,100 contracts.

Does the amount of long-VIX and short-VIX customer interest change with the levels of the VIX Index?

CBOE 49

VIX ETPs – Assets & Net Exposure

CBOE 50

White Paper ‐ Impact of Adding Long VIX Futures or Options to a Traditional Portfolio During the 5-Month Period (Aug. 2008 – Dec. 2008)

Improved portfolio performance in late 2008 with the addition of long VIX futures or long VIX calls to a “traditional” portfolio of stocks, bonds, and alternatives

-15.9%

-19.7%

97.2%

20.8%

-4.0%

3% 25%-OTM VIX Call Options

3% ATM VIX Call Options

10% VIX Futures

2.5% VIX Futures

0% VIX Futures or Options

From: VIX Futures and Options: A Case Study of Portfolio Diversification During the 2008 Financial Crisis." The Journal of Alternative Investments (Fall 2009)

CBOE 51

To Learn More …

More info at www.cboe.com/VIX --• VIX White Paper (with Methodology)• Term Structure• Price Charts• VIX Index and Futures Prices• Futures and Options Volume• Strategies• Bibliography

Thank you for joining us…

Contact Us Want More?John BurkhartzmeyerState of Wisconsin Investment [email protected]

Please click on the widget at the bottom of your screen to complete the survey. Your feedback is important to us.

Please click on the resources widget for more content and to visit our websites

Mike Edleson, CFAUniversity of [email protected]

David Pedack, CFARussell [email protected]

Matthew MoranChicago Board Options [email protected]

Vinit SrivastavaS&P Dow Jones [email protected]

52

CBOE 53

Important Disclosures

Options involve risk and are not suitable for all investors. Prior to buying or selling an option, a person must receive a copy of Characteristics and Risks of Standardized Options (the “ODD”). The ODD and supporting documentation for any claims, comparisons, recommendations, statistics or other technical data in these materials are available by calling 1-888-OPTIONS, or contacting CBOE at www.cboe.com/Contact. The information in these materials is provided solely for general education and information purposes and therefore should not be considered complete, precise, or current. Many of the matters discussed are subject to detailed rules, regulations, and statutory provisions which should be referred to for additional detail and are subject to changes that may not be reflected in these materials. No statement within this material should be construed as a recommendation to buy or sell a security or to provide investment advice. Past performance does not guarantee future results. These materials contain comparisons, assertions, and conclusions regarding the performance of indexes based on backtesting, i.e., calculations of how the indexes might have performed in the past if they had existed. Backtested performance information is purely hypothetical and is provided in this document solely for informational purposes. The methodology of the Indexes is owned by Chicago Board Options Exchange, Incorporated (CBOE) may be covered by one or more patents or pending patent applications. S&P®, and S&P 500® are registered trademarks of Standard & Poor's Financial Services, LLC and are licensed for use by Chicago Board Options Exchange, Incorporated (CBOE) and CBOE Futures Exchange, LLC (CFE). CBOE's financial products based on S&P indices are not sponsored, endorsed, sold or promoted by S&P and S&P makes no representation regarding the advisability of investing in such products. CBOE Volatility Index®, VIX®, CBOE® and Chicago Board Options Exchange® are registered trademarks and BXM, BXD, BXN and BXY are servicemarks of CBOE. CBOE slides are copyright © 2016 Chicago Board Options Exchange, Incorporated. All Rights Reserved.

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