Profiting with synthetic annuities option strategies to increase yield and control portfolio risk

Profiting with Synthetic Annuities This page intentionally left blank Profiting with Synthetic Annuities Option Strategies to Increase Yield and Control Portfolio Risk Michael Lovelady Vice President, Publisher: Tim Moore Associate Publisher and Director of Marketing: Amy Neidlinger Executive Editor: Jim Boyd Editorial Assistant: Pamela Boland Operations Specialist: Jodi Kemper Marketing Manager: Megan Graue Cover Designer: Alan Clements Managing Editor: Kristy Hart Senior Project Editor: Lori Lyons Copy Editor: Krista Hansing Editorial Services Proofreader: Sheri Cain Indexer: Brad Herriman Compositor: Nonie Ratcliff Graphics: Laura Robbins, Tammy Graham Manufacturing Buyer: Dan Uhrig © 2012 by Michael Lovelady Pearson Education, Inc Publishing as FT Press Upper Saddle River, New Jersey 07458 This book is sold with the understanding that neither the author nor the publisher is engaged in rendering legal, accounting, or other professional services or advice by publishing this book Each individual situation is unique Thus, if legal or financial advice or other expert assistance is required in a specific situation, the services of a competent professional should be sought to ensure that the situation has been evaluated carefully and appropriately The author and the publisher disclaim any liability, loss, or risk resulting directly or indirectly, from the use or application of any of the contents of this book FT Press offers excellent discounts on this book when ordered in quantity for bulk purchases or special sales For more information, please contact U.S Corporate and Government Sales, 1-800-382-3419, corpsales@pearsontechgroup.com For sales outside the U.S., please contact International Sales at international@pearson.com Company and product names mentioned herein are the trademarks or registered trademarks of their respective owners Certain screenshots, including Options Analysis Workspace and Theoretical Positions, were created with TradeStation ©TradeStation Technologies, Inc All rights reserved All rights reserved No part of this book may be reproduced, in any form or by any means, without permission in writing from the publisher Printed in the United States of America First Printing June 2012 ISBN-10: 0-13-292911-2 ISBN-13: 978-0-13-292911-0 Pearson Education LTD Pearson Education Australia PTY, Limited Pearson Education Singapore, Pte Ltd Pearson Education Asia, Ltd Pearson Education Canada, Ltd Pearson Educatión de Mexico, S.A de C.V Pearson Education—Japan Pearson Education Malaysia, Pte Ltd Library of Congress Cataloging-in-Publication Data Lovelady, Michael Lynn, 1957Profiting with synthetic annuities : option strategies to increase yield and control portfolio risk / Michael Lynn Lovelady 1st ed p cm ISBN 978-0-13-292911-0 (hardcover : alk paper) Options (Finance) Annuities Risk management I Title HG6024.A3L68 2012 368.3’7 dc23 2012009307 Contents Preface viii Chapter Introduction Chapter Synthetic Annuity Design 25 Chapter Tracking Performance 53 Chapter Covered Synthetic Annuities 69 Chapter Managing a Covered Synthetic Annuity 99 Chapter Generalized Synthetic Annuities 127 Chapter Managing a Generalized SynA 151 Chapter Synthetic Annuities for High-Yielding Stocks 169 Chapter Synthetic Annuities for the Bond Market 183 Chapter 10 Synthetic Annuities for the Volatility Market 207 Index 225 Acknowledgments I would like to express my sincere gratitude to several people who made this book possible At Pearson/FT Press, my editor Jim Boyd, who believed in the material and understood better than me what the scope of the book should be; Michael Thomsett, who gave the project invaluable guidance and direction from beginning to end; Lori Lyons, for her dedicated and patient production management; Krista Hansing, for copyedits; and all those who helped with marketing, illustration, and production I would also like to thank Don DePamphilis at Loyola Marymount University for giving me the idea to write the book and being a mentor; Cooper Stinson, a gifted writer who reviewed early manuscripts and asked all the right questions; Leslie Soo Hoo, for much needed help in reading and revising drafts; and Abbie Reaves, for editing Also, my friends and family who gave me encouragement and inspiration, and forgave me for missing tee times: my parents, Abigail, Alice, Billie, Brennan, Colby, Connor, Ethan, Eva, Frank, Hannah, Joanna, Lindsey, Matty, Noah, Nolan, Petra, Sally, Steve-O, and Tony Above all, for life itself, the Triune God of Creation—I always remember About the Author Michael Lovelady, CFA, ASA, EA, is the investment strategist and portfolio manager for Oceans Capital Group LLC Michael designs and implements reduced-volatility and theta-generating hedge fund investment strategies He developed the “synthetic annuity” (SynA) and uses it extensively in portfolio management Prior to founding Oceans 4, Michael worked as a consulting actuary for Towers Watson and PricewaterhouseCoopers Much of his work was related to design issues at a time when many employers were moving away from traditional defined benefit plans Michael worked with clients to consider and implement alternatives ranging from defined contribution to hybrid DB/DC plans His experience with retirement income strategies, from both the liability and asset sides, has given him a unique perspective Michael has also been involved in teaching and creating new methods for making quantitative investing more accessible to students, trustees, and others without math or finance backgrounds He developed the investment profile—a graphical representation of investments and the basis of a simplified option pricing model, and visually intuitive presentations of structured securities Michael has served various organizations, including Hughes Aircraft, Boeing, Global Santa Fe, Dresser Industries, the Screen Actors Guild, The Walt Disney Company, Hilton Hotels, CSC, and the Depository Trust Company He is a CFA charterholder, an Associate of the Society of Actuaries, and an ERISA Enrolled Actuary He currently lives in Los Angeles Preface Profiting with Synthetic Annuities is about the use of options in investing and portfolio management This book is written for experienced investors who are considering option strategies, for experienced option traders, and for institutional investors interested in alternative strategies Synthetic annuities are structured securities that use options and management rules to customize the risk/return profile of investments Options are used to create a synthetic risk-smoothing mechanism and annuity-like cash flows The management rules are designed to mitigate risk and maximize income over the long term Together, the options structure and management rules address several emerging issues in investment management: • The explicit use of hedging, insurance, and risk allocations in risk management instead of reliance on traditional portfolio models • The desire for greater yields not related to market direction • A recognition of behavioral influences on investor performance • The growing importance of volatility-reducing quantitative methods, particularly those related to stock options • The desire of many investors for annuity-like income streams Unlike many books on options and options strategies that deal mainly with tactical trading, Profiting with Synthetic Annuities is about the strategic use of options as integral components of investment portfolios Synthetic annuities treat options as permanent components of an investment position The goal is to create a hybrid architecture that balances the long-term investor perspective of mean-variance portfolios and the risk discipline of quantitative-based strategies ix In terms of presentation, Profiting with Synthetic Annuities uses a unique visual representation of structured securities As a result, few formulas appear in the book; instead, graphical interpretations communicate the ideas and compare alternative investments 216 s If the VIX moves below 15, you also might want to start accumulating long OTM calls with a portion of the net option proceeds You still want to maintain a net credit, but a few long calls in a market crash can be extremely profitable Because these are relatively expensive (the put–call skew pointed that out earlier), you can use a spread to decrease the cost You can also use the time volume discount in the spread by buying longer-dated options and selling shorter-dated options The long call options help flatten delta exposure in difficult markets With only short puts, delta fairly quickly begins to disappear as the VXX spikes up Long calls, even if they are far OTM, begin to kick in as the VXX goes up and as the IV on the VXX goes up Both the absolute price increase and the expanding IV contribute rapidly to the rising long option price In this configuration, you are using the SynA framework to finance long calls from a portion of the proceeds from selling puts This makes sense especially if you believe that you are close to a natural bottom in the VIX As the VIX settles in around a support level of 10 to 15, the cost of the call options goes down doubly because of lower absolute levels of the VXX and lower IV priced into the VXX call options If the VIX goes below 10, consider even starting to take slightly net negative theta positions in anticipation of a directional move up Keep in mind that similar to the relationship between bond rates and the TBT/TLT, the ETFs that track volatility suffer from tracking error The VXX is not an easy instrument to trade because of the large amount of slippage and its sensitivity to intraday and interday volatility Depending on the shape of the futures curve—particularly in times of high contango—there may be higher levels of negative roll yield as well Theta on the SynA helps counteract this to some degree, which is one advantage of the SynA, compared to holding long-term positions in VIX-related instruments that use futures As with the TBT, you can also leverage theta by selling call spreads With a VIX-related instrument used as a portfolio hedge, Chapter 10 • SynthetiC annuitieS for the Volatility Market 217 make sure the spread is fairly tight in case of a spike You can adjust the theta on the call spreads in addition to the theta on the short puts to counteract even high levels of negative roll yield If you are using advanced applications, begin to look for put–call arbitrage opportunities as the puts are priced at relatively low IVs At some points, you might have a directional preference in the movement of the underlying security and can place limit orders to take advantage of arbitrage by placing the first leg of the arbitrage trade in the direction of your preference and placing a limit order in the other direction For example, if your maximum portfolio gain happens when the underlying goes up without regard to the arb trade, sell the underlying If the underlying goes up, you will make money If it goes down, complete the synthetic long side of the arb trade Building a SynA When the VIX Is Greater Than 40 By late 2011, the VIX had gone above 50 for the first time since 2008 Betting against a larger spike is difficult, but the VIX cannot sustain these levels without some sort of systemic problem As systemic problems unfold, the uncertainty about the size of the problem and how widely it will spread causes demand for protection, pushing put prices higher Although this is an emotionally difficult period for building a SynA, it can be extremely profitable—as long as you are prepared for things to get much worse and you have the dry powder to make it to the other side You not want to get caught in a margin squeeze, especially since it will happen at the same time your portfolio is under the most stress With that said, let’s look at how to structure a SynA when the VIX is high My approach usually is to begin to sell call option spreads on one of the volatility measures, such as the VXX, and use a portion of the money to buy put options Do this a little at a time, because the ride 218 s could get wild before it starts to calm down In other words, this is the fourth type of SynA covered in Chapter 6, “Generalized Synthetic Annuities.” It is based on a view that prices will fall over the mid- to longer term and that the risk is a price spike This could also be set up as the third type of SynA, with a short position in the underlying such as the VXX, short puts to generate theta, and long calls to protect against a spike As pointed out in earlier chapters, the two setups are mathematically equivalent Stress Testing Fundamentally, I view the low-range VIX SynA as good rainy-day planning, whereas the high-range VIX SynA is more of a trade, but one that is well priced If you stress test your portfolio, the low-range SynA will move up in value as the market moves down The short puts will quickly drop in value, and the long calls will begin to climb in value So both components of the SynA help offset portfolio losses The opposite is true for the high-range SynA If volatility continues to rise, which means that equities are probably falling, the SynA will move in the same direction as the rest of the portfolio: down So if it provides no diversification, why would you it? It is simply based on price The premiums on OTM call options can be tempting, especially if you can ride out the spikes or, better yet, take advantage of further spikes to add to the position You just have to keep in mind that volatility normally does not reach 40 unless the market sees the potential of something catastrophic Although the price movement in the high-range SynA is not diversifying, it is indirectly helpful in other ways Option Prices and Other Portfolio Effects The effects of volatility on a portfolio are not symmetric In rising markets, volatility is normally falling In falling markets, volatility Chapter 10 • SynthetiC annuitieS for the Volatility Market 219 is normally rising This not only makes volatility a great diversifier, it also means that volatility affects hedging and trading decisions In very stable markets where the VIX is under 15, puts are relatively inexpensive and the premiums from selling call options are relatively low In other words, it is cheaper time to buy options During these periods, capital gains are usually strong, so you might want to shift your emphasis from theta-generated income to price gains and low-cost put protection—That is, theta is lower and delta exposure is higher The opposite is true during periods when the market is under stress During these periods, it makes sense to emphasize more theta income and lower delta exposures Put option prices are higher, but offset by the ability to finance them with higher-priced call option premiums In this case, theta is higher and delta lower In general, the higher the volatility, the more expensive options are Because SynA’s are generally net short options, the higher the volatility, the more you will receive from selling options and the more theta the SynA is capable of generating A rule of thumb is to divide the VIX by 10, and that is the monthly gross income from theta You can see how this scales from the lowrange SynA to the high-range SynA When the VIX is 40, the potential exists for 4% monthly income on a SynA built on the S&P 500 Index SynA’s built on individual securities, in which implied volatilities are higher than on the index, have more income potential Of course, the price movements predicted by the higher volatility make the potential returns harder to achieve Still, two things are working in your favor The first is that if you previously implemented the low-range SynA, the high-range SynA short calls are not risky; they are just the completion of a well-timed call spread It is well timed because the long call leg of the low-range SynA was purchased during a time of low volatility (and, therefore, low prices), and you sold the short leg at much higher levels during a 220 s time of high volatility and high prices The second is that the higher overall levels of volatility work to increase the effectiveness of the other SynA’s in the portfolio as call options are sold at higher prices I look at the level and direction of volatility as one of a few indicators that affect a broad range of portfolio management decisions, such as the level and direction of inflation and the equity index yield versus Treasury rates Volatility dictates both the rate at which you can extract virtual dividends and the relative cost of put protection For instance, in low volatility environments, you may want to consider financing a portion of position-level put protection from the low-range SynA rather than through the normal number of short call options, which may be priced too low to justify the upside limitation Or you could simply decide to sell fewer options in favor of contingent sales if and when you need to for cost-basis adjustments The point is that extremely low volatility usually happens during periods when the market is stable or rising and call premiums are depressed as they price in low implied volatility Example of a VXX SynA As the European debt crisis evolved through the summer and fall of 2011, the VIX and related volatility measures such as the VXX remained high Until November, it was unclear as to how far Germany and France were prepared to go to support the southern countries Also unclear was whether the ECB recognized the full extent of the problem When Timothy Geithner got involved, there was talk of some creative backstops that might be used to help with rolling over short-term debt During critical periods, a metric often emerges as the canary in the coal mine In this one, it was the rate on Italian sovereign debt Chapter 10 • SynthetiC annuitieS for the Volatility Market 221 When the Italian sovereign debt rate peaked and started down, I began to build a high-range volatility SnyA As the ECB began to put forward potential solutions and later credit facilities, it calmed the markets and I added to the position as the VIX started to fall There appears to be a lag effect for volatility Instead of falling quickly, the VIX is a little skeptical and likes to tail off, even when it looks like the crisis has passed Figure 10.2 shows the SynA in December, a few days before options expiration The SynA consisted of short calls only The VXX had already fallen from higher than 50 to around 41, and implied volatility on the VXX had fallen from 150% to around 100% The position delta was ($183.92), and theta was $191.15 This shows the power of high volatility to produce high theta-to-delta ratios Because this SynA consisted of short calls only, you might be asking what makes it a SynA and not just a string of short call options The distinguishing factor of all SynA’s is a commitment to risk control, to something when the maximum position drawdown is exceeded The risk control on this SynA was contingent short puts, which turned out not to be necessary because of the gradual decline in the VXX When the options expired, I did not roll out the SynA because the VIX had settled in the midrange between 20 and 40, a range that can be unstable In summary, converting a relatively underutilized asset that is perfectly behaved in market crashes into a yield-producing security adds a powerful new tool in portfolio construction This chapter discussed the opportunities for low-range, negatively correlated SynA’s and high-range, mega-theta SynA’s The problems with tracking error and slippage in the underlying instruments need to be addressed, but there appear to be exciting opportunities of adding volatility exposures to portfolio architecture 222 s Source: TradeStation Technologies, Inc Figure 10.2 Volatility SynA on PowerShares ETF VXX as of December 14, 2011 Chapter 10 • SynthetiC annuitieS for the Volatility Market 223 Endnotes Grant, Maria, CFA, Gregory, Krag, and Lui, Jason Goldman Sachs United States: Option Research, “Volatility as an Asset Class” 2007 Bernstein, Peter Capital Ideas Evolving 2007: John Wiley & Sons, Inc., Hoboken, New Jersey, p 100 and 165 Grant, Maria, CFA, Gregory, Krag, and Lui, Jason Goldman Sachs United States: Option Research, “Volatility as an Asset Class” 2007 Cherney, Nick, Lloyd, William, Kawaller, Geremy “Portfolio Applications for VIX-Based Instruments.” Journal of Indexes Copyright IndexUniverse.com 2011 This page intentionally left blank Index Symbols 401(k) plans, A adjustments automatic, 99 reverting, 101-103 security price interaction, 100-101 trading, 103 CSynA’s automatic, 99-103 cost basis, 104-106 delta, 106-116 tactical, 120-124 generalized SynA’s cost basis, 151-152 delta, 152-153 leverage, 153-158 allocated capital, 171 alpha, 19-21 opportunities, 17-18 “Alpha Orbits,” 184 alternative SynA’s, 144 negative delta, 149 positive delta, 148 Apple, 47, 50 approval level, options, 127 Asian currency crisis (1998), asset allocation models, 16 assets, volatility, 209-210 B behavioral finance, Benklifa, Michael, 132 Bernstein, Peter, 11 beta, 20-21 Black, Fisher, 210 Black Monday (1987), Black-Scholes option pricing formula, 29-31 bonds, 183 adding yield, 191-192 low yields, 183 payback periods, 196 prices, 195 cycles, 183-184 inflation, 194-195 risks, 185-190 stress testing, 192 Buffett, Warren, Bullard, James, 199, 201-204 BuyWrite Index (BXM), 94-97 C calculations, CSynA payback periods, 79-83 Callan Associates, BXM study, 96 call options call/put pairs, selling, 156-158 covered, 27, 72-73 CSynA’s, 83 put-call parity, 146-148 call/put pairs, selling, 156-158 Capital Asset Pricing Model (CAPM), 10-11 Capital Ideas Evolving, 11 CAPM (Capital Asset Pricing Model), 10-11 Cherney, Nick, 212 Chesapeake Energy SynA payoff chart, 158-160 concentrated stocks, 37-47 contango, 212 contingent CSynA’s, 85 225 226 Index cost basis adjustments, 54 CSynA’s, 104-106 generalized SynA’s, 151-152 tracking template, 56-57 cost basis rule, 151 covered call options, 69-73 versus SynAs, 27 covered percentage parameter (CSynA), 93 covered synthetic annuities (CSynA’s) See CSynA’s (covered synthetic annuities) Cramer, Jim, 169 CSynA’s (covered synthetic annuities), 69, 99, 127 automatic adjustments, 99 reverting, 101-103 security price interaction, 100-101 trading, 103 building, 73-76, 79 call options, 83 contingent, 85 cost basis adjustments, 104-106 covered calls, 70-73 December roll forward, 124-126 Deere & Company, 73-88 delta adjustments, 106-108 defensive, 109 offensive, 109-112 put protection, 112-116 deltas long-term targets, 87-88 versus theta, 85-87 dividends, 87 monthly roll forward, 116-118, 120 natural curve, 141-142 payback period, 79-83 volatility, 124-126 standard, 88-89, 93 BXM (BuyWrite Index), 94-97 covered percentage, 93 fundamental/technical valuation, 90-91 lower delta adjustments, 93 maximum drawdown, 92 micro-efficient parameter, 91-92 minimum value, 91 momentum parameter, 91-92 parameters, 94-95 price-related delta, 92 reverting parameter, 91-92 upper delta adjustments, 93 stock-only, 85 strike prices, 83 tactical adjustments, 120-124 variation, 135 cycles, bond prices, 183-184 D DB (defined benefit) plans, 1-2 DC (defined contribution) plans, 1-2 December roll forward, CSynA’s, 124-126 Deere & Company CSynA example, 73-88 generalized SynA, 136-138 defensive delta adjustments, CSynA’s, 109 defined benefit (DB) plans, 1-2 defined contribution (DC) plans, 1-2 delta, 62-63 call options, 70-72 CSynA’s, 76-78, 85-87, 106-108 defensive, 109 long-term targets, 87-88 offensive, 109-112 put protection, 112-116 generalized SynA’s, 152-153 SynA’s, 171 targets, price-based, 161 diversification, portfolios, 207-212 dividends, CSynA’s, 87 ex-dividend dates, generalized SynA’s, 166 yields, 173-174 dot.com bubble crash (2000-2002), 7-8 downside protection, 14-16 drawdown limits, 14 E–F earnings reports, generalized SynA’s, 165 echo crash (1997), Efficient Market Hypothesis (EMH), 17 Ennis, Richard, 11, 13 Enron, 17 equity risk premiums, 14 ETFs (exchange traded funds), 186 ex-dividend dates, generalized SynA’s, 166 Fidelity Magellan Fund, 169 fundamental/technical valuation high parameter (CSynA), 90-91 fundamental/technical valuation low parameter (CSynA), 90-91 G–H gamma, 62-63 CSynA’s, 78 generalized SynA, 138-140 GDAA (global dynamic asset allocation), generalized SynAs, 127-133, 140-141 Deere & Company, 136-138 gamma, 138-140 managing, 151 adjustment leverage, 153-158 cost basis adjustments, 151-152 delta adjustments, 152-153 earnings reports, 165 ex-dividend dates, 166 intrinsic value, 163-165 iron condor overlay, 162-163 mean reversion, 163-166 price-based delta targets, 161 price preferences, 158-161 theta-to-delta ratios, 167-168 trending triggers, 166 theta, 138-140 targets, 132-135 global dynamic asset allocation (GDAA), global financial crisis (2008-2009), global tactical asset allocation (GTAA), Greeks, 53, 63 Gross, Bill, 194 growth stocks, 169 GTAA (global tactical asset allocation), hedging, 19-20, 185 high-yielding stocks, 170 Hokenson, Richard, 199 hybrid 401(k) plans, I idiosyncratic risk, 17 implied volatility (VXX), 214 implied volatility (IV), investment profiles, 29-31 227 inflation, bond prices, 194-195 International Paper (IP), 169-171, 176-177, 180-182 Internet bubble crash (2000-2002), 7-8 intrinsic value, generalized SynA’s, 163-165 Intuitive Surgical (ISRG), 111 Investment Management after the Global Financial Crisis, 13 investment profiles, 25, 28-29 adjusting for behavioral finance, 34, 37 assigning probabilities, 29-31 options, 32 probability distributions, 25, 29 reshaping, 128-141 stock-only position, 29 versus payoff curves, 25-26 investment thesis, strategy complements, 195-198 IP (International Paper), 169-172, 176-177, 180-182 IRAs (Individual Retirement Accounts), iron condors, 162-163 J–K–L Kawaller, Geremy, 212 Leibowitz, Martin, 12, 184, 196 Leland O’Brien and Rubinstein (LOR), Level options, 69 leverage adjustments, generalized SynA’s, 153-158 theta, 182 Lloyd, William, 212 Long Term Capital Management (LTCM), long-term management, SynA’s, 174-176 LOR (Leland O’Brien and Rubinstein), lower delta adjustments parameter (CSynA), 93 LTCM (Long Term Capital Management), Lynch, Peter, 169 228 Index M macro-inefficiency, 196 Mad Money, 169 managing CSynA’s, monthly roll forward, 116-120 generalized SynA’s, 151 adjustment leverage, 153-158 cost basis adjustments, 151-152 delta adjustments, 152-153 earnings reports, 165 ex-dividend dates, 166 intrinsic value, 163-165 iron condor overlay, 162-163 mean reversion, 163-166 price-based delta targets, 161 price preferences, 158-161 theta-to-delta ratios, 167-168 trending triggers, 166 SynA’s, long-term, 174-176 managing CSynA’s automatic adjustments, 99 reverting, 101-103 security price interaction, 100-101 trading, 101-103 cost basis adjustments, 104-106 December roll forward, 124-126 delta adjustments, 106-108 defensive, 109 offensive, 109-112 put protection, 112-116 tactical adjustments, 120-124 markets, turbulent, 47-52 market volatility, investor returns, 9-10 Markowitz, Harry, 11 maximum drawdown parameter (CSynA), 92 mean reversion, generalized SynA’s, 163-166 mean-variance-optimized (MVO) portfolios, 5, 11 micro-efficient parameter (CSynA), 91-92 minimum value parameter (CSynA), 91 modern portfolio theory (MPT), 2-7, 10, 13 momentum parameter (CSynA), 91-92 monthly roll forward, CSynA’s, 116-120 MPT (modern portfolio theory), 2-7, 10, 13 MVO (mean-variance-optimized) portfolios, 5, 11 N–O negative delta SynA’s, 142-144 alternative form, 149 net options credit, 56 net options premium, 56 non-diversified risk, 17 offensive delta adjustments, CSynA’s, 109-112 options approval level, 127 call, covered, 72-73 investment profiles, 32 Level 1, 69 prices, volatility, 218-220 security price, 70 selling, 105 Options Analysis Workspace (TradeStation), 58-66 P parameters (CSynA’s), 89, 94-95 covered percentage, 93 fundamental/technical valuation high, 90-91 fundamental/technical valuation low, 90-91 lower delta adjustments, 93 maximum drawdown, 92 micro-efficient, 91-92 minimum value, 91 momentum, 91-92 price-related delta, 92 reverting, 91-92 upper delta adjustments, 93 “Parsimonious Asset Allocation,” 11 payback period bonds, 196 CSynA’s, 79-83 volatility, 124-126 tracking template, 57-58 payoff chart, Chesapeake Energy SynA, 158-160 payoff curves versus investment profiles, 25-26 performance, tracking, 53-54, 66 tracking template, 54-58 TradeStation, 58-66 “Portfolio Applications for VIX-Based Instruments,” 212 portfolios diversification, volatility market, 207-212 global dynamic asset allocation (GDAA), global tactical asset allocation (GTAA), insurance, 5-6 mean-variance-optimized (MVO), 5, 11 modern portfolio theory (MPT), 2-7, 10, 13 volatility effects, 218-220 positions strategic versus tactical, 149-150 theoretical, 54-63 positive delta SynA’s, alternative form, 148 price-related delta parameter (CSynA), 92 prices bonds, 195 cycles, 183-184 inflation, 194-195 options, volatility, 218-220 probability distribution, investment profiles, 25, 29 Profiting with Iron Condors, 133 projected payback period, tracking template, 57-58 protective puts, 69 put/call pairs, selling, 156-158 put-call parity, 146-148 put protection, financing, 112-116 puts call/put pairs, selling, 156-158 put-call parity, 146-148 Q-R “Qualified Commitment to DB Plans, A,” 22 “Race to Zero, The,” 199 random variables, 29 ratios, theta-to-delta, generalized SynA’s, 167-168 records, 64-66 retirement accounts, 20-21 returns, volatility, 9-10 reverse SynA’s, 142-144 reverting parameter (CSynA), 91-92 229 risk allocations, 4, 20 bonds, 185-190 budgeting, 4, 20 idiosyncratic, 17 management, 19-20 measurements, non-diversified, 17 reducing, 21-22 tolerance, CSynA, 92 rolling out/up, 110 S Scholes, Myron, 210 securities prices automatic adjustments, 100-101 options, 70 structured, 25 selling call/put pairs, 156-158 “Seven Faces of the Peril,” 199-204 Sharpe, Bill, 11 Siegel, Lawrence, 8-9 stability, generalized SynA’s, 138-140 standard CSynA’s, 88-89, 93 BXM (BuyWrite Index), 94-97 covered percentage, 93 fundamental/technical valuation, 90-91 lower delta adjustments, 93 maximum drawdown, 92 minimum value, 91 parameters, 91-95 price-related delta, 92 upper delta adjustments, 93 stochastic math, 29 stock-only CSynA’s, 85 stock-only positions versus SynAs, 40-42 stocks concentrated, 37-47 growth, 169 high-yielding, 170 strategic positions, versus tactical, 149-150 strategies, investment thesis, 195-198 stress testing bonds, 192 volatility SynA’s, 218 strike prices, CSynA’s, 83 structured securities, 25 230 Index synthetic annuities (SynA’s), 4-5, 26-28 aggressive approach, 28 alternative, 144 negative delta, 149 positive delta, 148 as hedging instrument, 185 creating, 27-28 generalized, 127-141 Deere & Company, 136-138 gamma, 138-140 managing, 151-168 theta, 138-140 theta targets, 132-135 managing, long-term, 174-176 reverse, 142-144 turbulent markets, 47-52 utility curve, applying, 44-45 versus covered call positions, 27 versus stock-only positions, 40-42 VIX, 214-218 volatility-squared, 212-214 high VIX, 217-218 low VIX, 214-217 stress testing, 218 VXX, 220-221 T tactical adjustments, CSynA’s, 120-124 tactical positions versus strategic, 149-150 TBT (technical barriers to trade), 186-194 theoretical positions, 54, 60-63 theta, 63, 78, 85-87 generalized SynA, 132-140 leveraging, 182 theta-to-delta ratios, generalized SynA’s, 167-168 tracking performance, 53-54, 66 tracking template, 54 cost basis, 56 example, 58 projected payback period, 57 trade triggers, 56 TradeStation, 58-66 tracking template, 54 cost basis, 56 example, 58 projected payback period, 57 trade triggers, 56 TradeStation, 58-66 trade triggers, tracking template, 56-58 trading accounts, 20-21 transactions, records, 64-66 trending triggers, generalized SynA’s, 166 turbulent markets, 47, 50-52 U–V upper delta adjustments parameter (CSynA), 93 utility curve, 34, 37, 42 SynA, applying to, 44-45 utility functions, 34, 37 variables, random, 29 VIX over 40, building volatility SynA’s, 217-218 under 20, building volatility SynA’s, 214-217 volatility, implied volatility (IV), 29-31 investor returns, 9-10 option prices, 218-220 payback periods, CSynA’s, 124-126 portfolios, 218-220 diversification, 207-212 volatility market, 207 volatility risk premiums (VRPs), 210-211 volatility-squared SynA’s, 212-214 high VIX, 217-218 low VIX, 214-217 stress testing, 218 VRPs (volatility risk premiums), 210-211 VXX SynA’s, 220-221 volatility, 212-218 W–Z Whaley, Robert, 96 “Why Are Put Options So Expensive?,” 135 Worldcom, 17 yields, 173-174 bonds, 183 adding, 191-192 stress testing, 192 generalized SynA’s, 138-140 increasing, 19 .. .Profiting with Synthetic Annuities This page intentionally left blank Profiting with Synthetic Annuities Option Strategies to Increase Yield and Control Portfolio Risk Michael Lovelady... 195 7Profiting with synthetic annuities : option strategies to increase yield and control portfolio risk / Michael Lynn Lovelady 1st ed p cm ISBN 978-0-13-292911-0 (hardcover : alk paper) Options... related to stock options • The desire of many investors for annuity-like income streams Unlike many books on options and options strategies that deal mainly with tactical trading, Profiting with Synthetic