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Tactically Conservative ... Bullish on Life!

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Merlyn.AI represents a paradigm shift in ETF design. While most ETFs focus on a specific slice of the market, such as a particular sector, factor, theme, or asset class, Merlyn.AI sponsors ETFs designed to be complete, self-contained, tactical portfolio management systems in a tax-efficient ETF wrapper. Each month each ETF evaluates over 400 US ETFs across broad and divergent markets and select a portfolio that seeks to provide the five things investors want most (right). Superior investment decisions require superior signal processing methods that can reduce market noise and clarify the momentum signal. Merlyn.AI employs the most proficient signal processing methods available, many of which come from the same cross-disciplinary sciences that enable today's WiFi, USB, iPhones, and remotely controlled rovers on Mars. For more on this topic, please see: Index Overview


The SectorSurfer Momentum Index                (100/0 Equities/Bonds Allocation) 

The MAI SectorSurfer Momentum Index begins with a 100/0 equities/bonds allocation typical of a classic aggressive portfolio. Each of its six underlying momentum strategies selects one ETF, its momentum leader, for the portfolio to hold. During Bull markets, the Index allocates 70% to four domestic economic sector ETFs and 30% to two geopolitical sector ETFs (regions and countries). When a Bear market  is signaled the Index automatically allocates 100% to a portfolio of bonds, treasuries and other defensive ETFs. The Index employs Temporal Portfolio Theory, including owning only momentum leaders and the methods of tactical risk avoidance — risk is not a one-dimensional problem cured by a single dose of diversification. The Index additionally employs the below methods seeking to improve risk and return performance: 

• Advanced signal processing that clarifies the momentum signal and seeks to improve fund selection reliability;
• Bull/Bear Indicators StormGuard-Armor and SwanGuard, to determine the market's Bull vs. Bear status;
Adaptive Tuning that seeks to eliminate hindsight bias when tuning the momentum filters; 
Fuzzy Logic to better assess the 14 conditions that determine the Bull vs. Bear status; and
Genetic Algorithms that seek to eliminate hindsight selection bias by evolving candidate sets monthly.
 

Index Details

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The Best-of-Breed Core Momentum Index                    (100/0 Equities/Bonds Allocation) 

The MAI Best-of-Breed Core Momentum Index begins with a 100/0 equities/bonds allocation typical of a classic aggressive portfolio. Each of its three underlying momentum strategies selects one ETF, its momentum leader, for the portfolio to hold. Selected ETFs must have > $10B of AUM (assets under management). During Bull markets, the Index allocates 35% to an economic sector strategy selection, 35% to a factor-mix strategy selection, and 30% to a global regions strategy selection. When a Bear market  is signaled the Index automatically allocates 100% to a portfolio of bonds, treasuries and other defensive ETFs. The Index employs Temporal Portfolio Theory, including owning only momentum leaders and the methods of tactical risk avoidance — risk is not a one-dimensional problem cured by a single dose of diversification. The Index additionally employs the below methods seeking to improve risk and return performance:

• Advanced signal processing that clarifies the momentum signal and seeks to improve fund selection reliability;
• Bull/Bear Indicators StormGuard-Armor and SwanGuard, to determine the market's Bull vs. Bear status;
Adaptive Tuning that seeks to eliminate hindsight bias when tuning the momentum filters; 
Fuzzy Logic to better assess the 14 conditions that determine the Bull vs. Bear status; and
Genetic Algorithms that seek to eliminate hindsight selection bias by evolving candidate sets monthly.
 

Index Details   

New

The Bull-Rider Bear-Fighter Index                           (80/20 Equities/Bonds Allocation) 

The MAI Bull-Rider Bear-Fighter Index begins with an 80/20 equities/bonds allocation typical of a classic growth portfolio. Each of eight underlying momentum strategies selects one ETF (its momentum leader) for the portfolio to hold. During bull markets, the Index allocates 35% to sectors, 15% to countries, 10% to global regions, 10% to factors, 10% to style-mix, and 20% to bonds, treasuries, gold and the like. When a Bear market  is signaled the Index automatically allocates 100% to a portfolio of bonds, treasuries and other defensive ETFs. The Index employs Temporal Portfolio Theory, including owning only momentum leaders and the methods of tactical risk avoidance — risk is not a one-dimensional problem cured by a single dose of diversification. The Index additionally employs the below methods seeking to improve risk and return performance:

• Advanced signal processing that clarifies the momentum signal and seeks to improve fund selection reliability;
• Bull/Bear Indicators StormGuard-Armor and SwanGuard, to determine the market's Bull vs. Bear status;
Adaptive Tuning that seeks to eliminate hindsight bias when tuning the momentum filters; 
Fuzzy Logic to better assess the 14 conditions that determine the Bull vs. Bear status; and
Genetic Algorithms that seek to eliminate hindsight selection bias by evolving candidate sets monthly.
 

Index Details

 



The Tactical Growth and Income Index                           (30/70 Equities/Bonds Allocation) 

The MAI Tactical Growth and Income Index begins with a 30/70 equities/bonds allocation typical of a classic conservative portfolio.  Each of eight underlying momentum strategies selects one ETF (its momentum leader) for the portfolio to hold.  During bull markets, the Index allocates 15% to sectors, 5% to countries, 5% to global regions, 5% to dividends, and 70% to bonds, treasuries, gold, and the like. When a Bear market  is signaled the Index automatically allocates 100% to a portfolio of bonds, treasuries and other defensive ETFs. The Index employs Temporal Portfolio Theory, including owning only momentum leaders and the methods of tactical risk avoidance — risk is not a one-dimensional problem cured by a single dose of diversification. The Index additionally employs the below methods seeking to improve risk and return performance:

• Advanced signal processing that clarifies the momentum signal and seeks to improve fund selection reliability;
• Bull/Bear Indicators StormGuard-Armor and SwanGuard, to determine the market's Bull vs. Bear status;
Adaptive Tuning that seeks to eliminate hindsight bias when tuning the momentum filters; 
Fuzzy Logic to better assess the 14 conditions that determine the Bull vs. Bear status; and
Genetic Algorithms that seek to eliminate hindsight selection bias by evolving candidate sets monthly.
 

Index Details

 




About Merlyn.AI
Merlyn.AI Corporation (MAI) is a Palo Alto-based exchange traded fund sponsor launched in January 2019 by two long-time friends, David Epstein and Scott Juds. MAI is exclusively licensed to create and market ETFs based on the Merlyn.AI technology developed by Seattle-based SumGrowth Strategies, LLC. Merlyn.AI is the result of more than three decades of research and development by MAI Co-Founder, Chairman and CEO Scott Juds, who discovered momentum in market data using advanced signal processing in early 1992.

Scott Juds - Co-Founder, Chairman & CEO of Merlyn.AI CorpScott Juds, Co-Founder, Chairman and CEO is also the Founder and CEO of Seattle-based SumGrowth Strategies (a decade-old company with two automated platforms - AlphaDroid for advisors and SectorSurfer for individual investors). He was formerly the Founder and President of piTech Engineering of Seattle, Co-Founder and VP of Engineering for IDX Inc. of AR, and VP of Advanced Engineering for EATON Corporation's Opcon division. Mr. Juds has been granted over 40 U.S. and foreign patents, holds an MSEE from Stanford University, and a BSEE from the University of Wisconsin – Madison. He won the prestigious NAAIM Wagner Award in 2016 with his paper "Investment Performance Improvement Utilizing Automated Polymorphic Momentum" and currently serves as a NAAIM panel judge for the annual contest. Mr. Juds is the creator of Temporal Portfolio Theory (Modern Portfolio Theory extended with advanced signal processing), and the author of both "Conquering the Seven Faces of Risk" (FinTech Press 2017) and "Photoelectric Sensors and Controls" (Marcel Dekker 1988).
  

Valery-Talma - Chief Operationg Officer of Merlyn.AI CorpValéry Talma, COO and Director, has a strong background in venture capital, corporate finance, mergers & acquisitions, investment banking, and international finance. Mr. Talma has been Deputy General Manager of Gulf Bank in Kuwait, Founder & Managing Director of Peninsula Insights in the United Arab Emirates, Managing Director - Head of Investment Banking Advisory of HSBC in Saudi Arabia, Managing Director - Middle East & Africa Investment Banking of Credit Agricole CIB in DIFC, Dubai, and UAE, and Vice President of UBS in Paris and London. Mr. Talma holds a BA in Economics and Business (Magna Cum Laude) from the University of California, Los Angeles, and holds a Master of Science in Business Administration and Management from HEC Paris. Recently he has taken multiple Continuing Studies courses in Computer Science – Artificial Intelligence at Stanford University.

Lisa Noble, Vice President of Marketing, Merlyn.AI CorpLisa Noble, Vice President of Marketing and Communications.  With a BS and MS in Electronics and Communications Engineering from Rice University Lisa started her career designing signal processing software and hardware for spread spectrum communication systems at ESL/TRW, and later co-founded Spectral Innovations, a developer of digital signal processing technology. After continuing her education with a JD from Stanford Law School, she held positions as a patent attorney at Fenwick and West, Associate General Counsel and Intellectual Property Attorney at DIVA Systems, and Director of Intellectual Property at Liberate Technologies. More recently, she founded Lisa Noble Photography with publications including Cosmopolitan, Oprah Magazine, Huffington Post, Showtime, Travel Channel and The Colbert Show.

Warren Hyland - Co-Founder of Merlyn.AI CorpPhil Scanlon, Vice President of Sales, is a FINRA Series 7 and Series  63 licensed financial services professional with expertise in wholesale distribution, channel management, ETF model portfolios, retirement planning and SMAs. Phil has held positions as Client Relations Manager for ING, Business Development Specialist for Fidelity Investments, Financial Advisor for VALIC, Regional Sales Director for SIP America, Wholesaler for Terra Capital Partners, Regional Investment Consultant for S&P Global, and Vice President of Sales for iSelect Fund. Phil holds an MBA in Finance from Fordham Gabelli School of Business and a BSC in Finance from Santa Clara University.  
 

Sue Guzman, COO Merlyn.AI CorpSue Guzman, Director. With an MS-Engineering Management degree from Stanford University and BSEE from UW-Madison, Ms. Guzman has three decades of successful corporate leadership experience in Blue Chip firms (Hewlett Packard and National Instruments), as well as new companies, such as fiber optics startup kSaria. These experiences led to her selection as CEO and General Manager (ret.) of Celerity Systems/Aeroflex Inc., a major supplier of broadband test and measurement products based in Cupertino, CA.  Aside from her duties at MAI, she is President of Canine Companions for Independence (South Bay), a nonprofit that trains highly skilled assistance dogs for placement with children and adults with disabilities— for free.

Warren Hyland - Co-Founder of Merlyn.AI CorpWarren Hyland, Co-Founder and Director, is a strong business development and technology licensing professional, skilled in startups, turn-arounds, sensing technology, waste management, biofuels, mining, and renewable energy — and sailing the warm beautiful seas. Mr. Hyland is CEO of the Inventor Mentor Group, Manager of the Wizards Chest, LLC, Manager of the Legacy Fund, LLC, Co-Founder of Luminaerospace, and past Director of Novita Technologies. Mr. Hyland holds a BaSc Engineering from the University of Toronto.

 
 

 

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