Factor Trends in 2020

Share This Post

The Tactical Model (TM1) is a global stock selection and position timing model developed by ExtractAlpha.  TM1 improves upon simple price reversal strategies in several ways:

  • By intelligently controlling for risk factors
  • By conditioning reversals on volume effects
  • By taking into account uncorrelated mid-horizon alpha strategies, including factor trendsliquidity trends, and seasonality, in 3 separate components


In this research note we examine the performance of these technical factors alongside simple price reversal, with a particular focus on the large outperformance of factor momentum during the first half 2020, during which high-scoring Factor Momentum stocks have outperformed low-scoring stocks by 67% through mid-June.

We measure a signal’s ability to forecast returns by tracking the gross (pre-transaction cost) cumulative return (not compounded) to a portfolio which goes long the top decile of U.S. stocks and short the bottom decile of U.S. stocks each day according to that strategy, with daily rebalancing and equal weighting, subject to a minimum market cap of US$100m, minimum ADV of US$1m, and minimum price of US$4.  Using this methodology, we look at the Tactical Model and each of its four subcomponents, alongside Basic Reversal – which is just the 5-day cumulative return of each stock, with the sign inverted.

Here we see a large reversal drawdown in mid-March as news of the coronavirus spread, which we discussed at some length in a March 2020 research note, followed by a strong rebound.  The Tactical Model’s smarter variant of Reversal, being less crowded and more sophisticated than basic reversal, experienced less of a drawdown and a similar bounceback.

The Liquidity shock and Seasonality components have not done much that’s interesting this year to date.  Factor Momentum, however, has been very interesting, and a very valuable diversifier for reversal strategies.  The basic idea behind Factor Momentum is as follows:

  • If we decompose a stock’s return into an idiosyncratic portion and a portion which is explained by common risk factors, then the idiosyncratic portion of that return will usually reverse.
  • These stock-specific moves may be largely liquidity driven rather than informational or fundamental, and as such may be temporary.  
  • This is why in our Reversal Component we use residual returns rather than total returns, with these residual returns having the effects of the common factors removed.  
  • We further refine our identification of these idiosyncratic moves as liquidity-driven by focusing on large idiosyncratic return moves which are accompanied by relatively light volume.
  • The common factor component of returns, however, tends to trend over short horizons of about one day in the U.S. (and a bit longer in other markets).  
  • When large institutions move money into a particular style, they tend to do so over multiple days, so if we identify a factor move on day 1, we are likely to see it again in day 2. 
  • This is the concept we capture in the Factor Momentum component of the Tactical Model, which scores each stock according to the moves in factors it is exposed to, using the ExtractAlpha Risk Model to measure those moves and exposures.


In 2020, we have seen some very dramatic factor moves, and ones which persisted across time.  The Factor Momentum component was well positioned to capture these moves and has resulted in significant outperformance of the Tactical Model on a risk-adjusted basis year to date.

We can measure factor moves in two ways: by plotting long-short decile returns, just as we do with the TM1 cumulative return charts above; or by looking at the Factor Returns which are derived from a cross-sectional regression in our Risk Model, which tells us the degree to which each factor explains the cross-section of returns, after controlling for the other factors.  It is this latter formulation which we use in our Factor Momentum component, but the former one tells the story of this year to date’s factor moves more clearly and is shown below.

As we can see, there has been a massive outperformance of high-volatility stocks this year, and for many other factors we see a fairly linear trend in one direction up to mid-March, followed by a trend in the opposite direction thereafter.

By plotting day-over-day autocorrelations of the factors individually this year, smoothed out to a trailing 252 trading day number, we can see that the average autocorrelation was fairly high at 0.1 going into March. All factors except Size increased in autocorrelation after that point, indicating an increasingly factor-driven market.  Size is an interesting exception, and its low autocorrelation is the result of some rapid oscillations in size returns in mid-March, with large and small stocks outperforming by turns.

In fact, by some measures we’ve hit a 20-year high in factor autocorrelations recently.  Below we plot the factor autocorrelations in two ways: time series, in which we take the trailing one-year autocorrelation for each factor and then average across the factors, and cross sectional, where we do a cross-sectional correlation of the relative performance of the factors each day and then average it out over the last year.  Notably, time series autocorrelation hit an all-time high on March 18.

 All of this implies that in these market conditions Factor Momentum should perform especially well, and indeed looking at the long-horizon performance of the component, we do see returns which reflect the autocorrelation chart above:


In a macro-driven, uncertain environment such as we find ourselves in in 2020, we should expect that trending factor moves should continue to provide the right conditions for Factor Momentum, and the Tactical Model in general, to outperform

More To Explore

Alternative Data for Cannabis

The cannabis industry is experiencing a massive growth spurt, creating an exciting opportunity for investors. However, with the industry’s rapid expansion, investors are finding it

Chloe Miao

Chloe joined ExtractAlpha in 2023. Prior to joining, she was an associate director at Value Search Asia Limited. She earned her Masters of Arts in Global Communications from the Chinese University of Hong Kong.

Matija Ratkovic

Matija is a specialist in software sales and customer success, bringing experience from various industries. His career, before sales, includes tech support, software development, and managerial roles. He earned his BSc and Specialist Degree in Electrical Engineering at the University of Montenegro.

Jack Kim

Jack joined ExtractAlpha in 2022. Previously, he spent 20+ years supporting pre- and after-sales activities to drive sales in the Asia Pacific market. He has worked in many different industries including, technology, financial services, and manufacturing, where he developed excellent customer relationship management skills. He received his Bachelor of Business in Operations Management from the University of Technology Sydney.

Perry Stupp

Perry brings more than 20 years of Enterprise Software development, sales and customer engagement experience focused on Fortune 1000 customers. Prior to joining ExtractAlpha as a Technical Consultant, Perry was the founder, President and Chief Customer Officer at Solution Labs Inc. a data analytics company that specialized in the analysis of very large-scale computing infrastructures in place at some of the largest corporate data centers in the world.

Perry Stupp

Perry brings more than 20 years of Enterprise Software development, sales and customer engagement experience focused on Fortune 1000 customers. Prior to joining ExtractAlpha as a Technical Consultant, Perry was the founder, President and Chief Customer Officer at Solution Labs Inc. a data analytics company that specialized in the analysis of very large-scale computing infrastructures in place at some of the largest corporate data centers in the world.

Janette Ho

Janette has 22+ years of leadership and management experience in FinTech and analytics sales and business development in the Asia Pacific region. In addition to expertise in quantitative models, she has worked on risk management, portfolio attribution, fund accounting, and custodian services. Janette is currently head of relationship management at Moody’s Analytics in the Asia-Pacific region, and was formerly Managing Director at State Street, head of sales for APAC Asset Management at Thomson Reuters, and head of Asia for StarMine. She is also a board member at Human Financial, a FinTech firm focused on the Australian superannuation industry.

Leigh Drogen

Leigh founded Estimize in 2011. Prior to Estimize, Leigh ran Surfview Capital, a New York based quantitative investment management firm trading medium frequency momentum strategies. He was also an early member of the team at StockTwits where he worked on product and business development.  Leigh is now the CEO of StarKiller Capital, an institutional investment management firm in the digital asset space.

Andrew Barry

Andrew is the CEO of Human Financial, a technology innovator that is pioneering consumer-led solutions for the superannuation industry. Andrew was previously CEO of Alpha Beta, a global quant hedge fund business. Prior to Alpha Beta he held senior roles in a number of hedge funds globally.

Natallia Brui

Natallia has 7+ years experience as an IT professional. She currently manages our Estimize platform. Natallia earned a BS in Computer & Information Science in Baruch College and BS in Economics from BSEU in Belarus. She has a background in finance, cybersecurity and data analytics.

June Cook

June has a background in B2B sales, market research, and analytics. She has 10 years of sales experience in healthcare, private equity M&A, and the tech industry. She holds a B.B.A. from Temple University and an M.S. in Management and Leadership from Western Governors University.

Steven Barrett

Steve worked as a trader at hedge funds and prop desks in Hong Kong and London for 15+ years. He also held roles in management consultancy, internal audit and business management. He holds a BA in Business Studies from Oxford Brookes University and an MBA from Hong Kong University of Science & Technology.

Jenny Zhou, PhD

Jenny joined ExtractAlpha in 2023. Prior to that, she worked as a quantitative researcher for Chorus, a hedge fund under AXA Investment Managers. Jenny received her PhD in finance from the University of Hong Kong in 2023. Her research covers ESG, natural language processing, and market microstructure. Jenny received her Bachelor degree in Finance from The Chinese University of Hong Kong in 2019. Her research has been published in the Journal of Financial Markets.

Kristen Gavazzi

Kristen joined ExtractAlpha in 2021 as a Sales Director. As a past employee of StarMine, Kristen has extensive experience in analyst performance analytics and helped to build out the sell-side solution, StarMine Monitor. She received her BS in Business Management from Cornell University.

Triloke Rajbhandary

Triloke has 10+ years experience in designing and developing software systems in the financial services industry. He joined ExtractAlpha in 2016. Prior to that, he worked as a senior software engineer at HSBC Global Technologies. He holds a Master of Applied Science degree from Ryerson University specializing in signal processing.

Jackie Cheng, PhD

Jackie joined ExtractAlpha in 2018 as a quantitative researcher. He received his PhD in the field of optoelectronic physics from The University of Hong Kong in 2017. He published 17 journal papers and holds a US patent, and has 500 citations with an h-index of 13. Prior to joining ExtractAlpha, he worked with a Shenzhen-based CTA researching trading strategies on Chinese futures. Jackie received his Bachelor’s degree in engineering from Zhejiang University in 2013.

Yunan Liu, PhD

Yunan joined ExtractAlpha in 2019 as a quantitative researcher. Prior to that, he worked as a research analyst at ICBC, covering the macro economy and the Asian bond market. Yunan received his PhD in Economics & Finance from The University of Hong Kong in 2018. His research fields cover Empirical Asset Pricing, Mergers & Acquisitions, and Intellectual Property. His research outputs have been presented at major conferences such as AFA, FMA and FMA (Asia). Yunan received his Masters degree in Operations Research from London School of Economics in 2013 and his Bachelor degree in International Business from Nottingham University in 2012.

Willett Bird, CFA

Prior to joining ExtractAlpha in 2022, Willett was a sales director for Vidrio Financial. Willett was based in Hong Kong for nearly two decades where he oversaw FIS Global’s Asset Management and Commercial Banking efforts. Willett worked at FactSet, where he built the Asian Portfolio and Quantitative Analytics team and oversaw FactSet’s Southeast Asian operations. Willett completed his undergraduate studies at Georgetown University and finished a joint degree MBA from the Northwestern Kellogg School and the Hong Kong University of Science and Technology in 2010. Willett also holds the Chartered Financial Analyst (CFA) designation.

Julie Craig

Julie Craig is a senior marketing executive with decades of experience marketing high tech, fintech, and financial services offerings. She joined ExtractAlpha in 2022. She was formerly with AlphaSense, where she led marketing at a startup now valued at $1.7B. Prior to that, she was with Interactive Data where she led marketing initiatives and a multi-million dollar budget for an award-winning product line for individual and institutional investors.

Jeff Geisenheimer

Jeff is the CFO and COO of ExtractAlpha and directs our financial, strategic, and general management operations. He previously held the role of CFO at Estimize and two publicly traded firms, Multex and Market Guide. Jeff also served as CFO at private-equity backed companies, including Coleman Research, Ford Models, Instant Information, and Moneyline Telerate. He’s also held roles as advisor, partner, and board member at Total Reliance, CreditRiskMonitor, Mochidoki, and Resurge.

Vinesh Jha

Vinesh founded ExtractAlpha in 2013 with the mission of bringing analytical rigor to the analysis and marketing of new datasets for the capital markets. Since ExtractAlpha’s merger with Estimize in early 2021, he has served as the CEO of both entities. From 1999 to 2005, Vinesh was the Director of Quantitative Research at StarMine in San Francisco, where he developed industry leading metrics of sell side analyst performance as well as successful commercial alpha signals and products based on analyst, fundamental, and other data sources. Subsequently, he developed systematic trading strategies for proprietary trading desks at Merrill Lynch and Morgan Stanley in New York. Most recently he was Executive Director at PDT Partners, a spinoff of Morgan Stanley’s premiere quant prop trading group, where in addition to research, he also applied his experience in the communication of complex quantitative concepts to investor relations. Vinesh holds an undergraduate degree from the University of Chicago and a graduate degree from the University of Cambridge, both in mathematics.

Subscribe to the ExtractAlpha monthly newsletter