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Quantocracy’s Daily Wrap for 06/02/2021

This is a summary of links featured on Quantocracy on Wednesday, 06/02/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Linking Attribution Factors [Quant Dare]

    In the business of performance measurement, a recurrent task is the breakdown of a stream of returns into meaningful contributions from different factors, in order to identify the driving financial forces or sources of risk. Eventually, these daily contributions have to be aggregated to explain the complete period performance or the divergence between two different streams of returns. This step is
  • The Case against EM Equities [Factor Research]

    EM equities are highly correlated to US stocks & high yield bonds, limiting diversification benefits They outperform primarily when the USD is depreciating, making it a currency play The largest MSCI EM index members will experience 50% population declines INTRODUCTION Seeing latex slowly dripping out of rubber trees into wooden bowls on a plantation in Malaysia was a fascinating experience as
  • Get Green or Die Trying? [Alpha Architect]

    In 2015, 197 nations signed onto the Paris Agreement and committed to limiting global warming to less than 2 degrees C above preindustrial levels. Although the arguments are compelling, the drive to manage carbon risk presents quite a challenge for individual investors and portfolio managers. Although ESG investing spans the gamut of environmental issues, the specific case of carbon risk is

Quantocracy’s Daily Wrap for 05/31/2021

This is a summary of links featured on Quantocracy on Monday, 05/31/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Explanatory Power of Factor Momentum [Alpha Architect]

    Momentum is the tendency for assets that have performed well (poorly) in the recent past to continue to perform well (poorly) in the future, at least for a short period of time. 1 In 1997, Mark Carhart, in his study On Persistence in Mutual Fund Performance, was the first to use a momentum factor, together with the three FamaFrench factors (market beta, size, and value), to explain mutual
  • Factor momentum: a brief introduction [SR SV]

    Standard equity factors are autocorrelated. Hence, it is not surprising that factor strategies have also displayed momentum: past returns have historically predicted future returns. Indeed, factor momentum seems to explain all return momentum in individual stocks and across industries. Momentum has been concentrated on a subset of factors, most notably those related to betting against beta,

Quantocracy’s Daily Wrap for 05/27/2021

This is a summary of links featured on Quantocracy on Thursday, 05/27/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Fit forecast weights by instrument, by group or fit across all markets? Or all three? [Investment Idiocy]

    I've long been a critic of the sort of people who think that one should run a different trading system for each instrument that you trade. It is the sort of thing that makes intuitive sense; surely the S&P 500 is a completely different animal to the Corn future? And that's probably true for high frequency traders, but not at the sort of timescales that I tend to trade over (holding
  • Different methods for mitigating overfitting on Neural Networks [Quant Dare]

    Using Machine Learning and Deep Learning models to solve scientific problems of greater or lesser complexity is a challenge. Referring to neural networks, on the one hand, simple networks with too little capacity will not learn the problem well producing a model that underfits the data. On the other hand, complex networks with too much capacity will learn it too well leading to a model that
  • Update on Recent Matrix Profile Work [Dekalog Blog]

    Since my previous post, on Matrix Profile (MP), I have been doing a lot of online reading about MP and going back to various source papers and code that are available at the UCR Matrix Profile page. I have been doing this because, despite my initial enthusiasm, the R tsmp package didn't turn out to be suitable for what I wanted to do, or perhaps more correctly I couldn't hack it to get

Quantocracy’s Daily Wrap for 05/25/2021

This is a summary of links featured on Quantocracy on Tuesday, 05/25/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Value and Momentum Investing: Combine or Separate? [Alpha Architect]

    When it comes to Value and Momentum investing we often get asked the following set of questions: Should I use value and momentum, in one screen, to form a single portfolio of stocks? ("Blended", "combined", or "integrated") Or should I focus on the value and momentum factor separately, and then combine the factor portfolios? ("Pure", "Separated",
  • Estimating Fair Value For The 10-Year Treasury Yield, Part II [Capital Spectator]

    Earlier this month, I reviewed a model that estimates a theoretical level for the worlds most-important interest rate: the 10-year Treasury yield. In todays follow-up, lets consider a second model for additional context. The goal in this series is to select several models with an eye on combining the estimates. A long line of literature demonstrates, rather convincingly, that one of the
  • Portfolio Construction in Venture Capital [Factor Research]

    A few winners generate most of the venture capital returns Given this asymmetrical return distribution, portfolios should be constructed equally Missing the winners is simply too risky INTRODUCTION 2020 turned out to be a record year for the venture capital industry, despite the global pandemic. More than 12,000 investments were made into early to late-stage start-ups at a combined value of $166

Quantocracy’s Daily Wrap for 05/24/2021

This is a summary of links featured on Quantocracy on Monday, 05/24/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Machine Learning Based Statistical Arbitrage [Jonathan Kinlay]

    Applying Machine Learning in Statistical Arbitrage In this series of posts I want to focus on applications of machine learning in stat arb and pairs trading, including genetic algorithms, deep neural networks and reinforcement learning. Pair Selection Lets begin with the subject of pairs selection, to set the scene. The way this is typically handled is by looking at historical correlations and

Quantocracy’s Daily Wrap for 05/21/2021

This is a summary of links featured on Quantocracy on Friday, 05/21/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Free ticket to Algo Trading Summit Online Conference July 15th – Includes many Quantocracy contributors!

    The online conference for quants and algo-traders. Hear from the best and brightest minds in algo-trading. Join like-minded pros and gain hands-on, actionable information from the best and brightest minds in algo-trading
  • Trees and networks [OSM]

    Its been over a month since our last post and for that we must apologize. We endeavor to be more prolific, but sometimes work and life get in the way. On the work front, lets just say we wont have to spend as much time selling encyclopedias door-to-door, which should free up more time to dedicate to writing value-added blog posts. On the life front, we had the chance to hike several
  • Pairs Trading – A Real-World Profitable Strategy [Milton FMR]

    Pairs trading is popular due to its simple approach and effectiveness. At the heart of the strategy is how the prices of two assets diverge and converge over time. Pairs trading algorithms profit from betting on the fact that spread deviations return to their mean. One of the more notable hedge funds that implemented a pairs trading strategy was Long Term Capital Management. The company was
  • Bitcoin Elasticity and Volatility [Mark Best]

    So the crypto markets on May 19th were fun!? If you have been a part of these markets for any time, this volatility is not that surprising. That said it is still pretty amazing that the price can drop 30% in a single day. This is maybe more surprising since it is to the backdrop of an increase in institutional investors and a narrative of this time its different. I was asked a question
  • Predictability of the Value Premium Across Asset Classes [Alpha Architect]

    The value spread is the difference between the value signal in the long versus the short portfolio. This isnt the first time we have hit on this topic. Wes and I have done several posts on the subject: Timing Value and Momentum with Valuation-Spreads The Returns to Value Strategies When Valuation Spreads Are Wide (Deep Value) The Forecasting Power of Value, Profitability, and Investment Spreads

Quantocracy’s Daily Wrap for 05/20/2021

This is a summary of links featured on Quantocracy on Thursday, 05/20/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Are Ben Graham s Disciples Value and Quality Factor Investors? [Alpha Architect]

    I examine the performance records of performance of Ben Graham's well-known disciples: Walter Schloss, Tom Knapp, Warren Buffett, Bill Ruane, Charlie Munger, Rick Guerin, and Stan Perlmeter. The research question I seek to address is the following: Do the academic "value" and "quality" factors explain the performance of these legendary investors? Surprisingly, the evidence

Quantocracy’s Daily Wrap for 05/18/2021

This is a summary of links featured on Quantocracy on Tuesday, 05/18/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • More Robust Strategies [Financial Hacker]

    The previous article dealt with John Ehlers AM and FM demodulating technology for separating signal and noise in price curves. In the S&C June issue he described a practical example. Applying his FM demodulator makes a strategy noticeably more robust at least with parameter optimization. The simple example strategy is basically a short-term trend follower. The price curve is
  • ESG Performance Breakdown by E, S, and G [Alpha Architect]

    The relationship among ESG ratings from third-party providers has historically produced conflicting results. Differences in sourced information and weighting schemes have produced low correlations between ratings and as a result, have handicapped the efforts to understand the relationship between ESG ratings and performance. Consequently, the credibility and willingness to use and invest utilizing

Quantocracy’s Daily Wrap for 05/17/2021

This is a summary of links featured on Quantocracy on Monday, 05/17/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Idea Streams #3 Seeking Diversification Amidst Global Market Correlations [Quant Connect]

    The CSI 300 is a capitalization-weighted stock market index that tracks the top 300 stocks listed on the two main stock exchanges in mainland China. In April 2020, South China Morning Post reported that the 120-day correlation between the CSI 300 Index and the S&P 500 index recently rose to its highest level since Bloomberg began compiling the data in 2002. The rise in correlation can be
  • Max Sortino Added to the Portfolio Optimizer (And Whether That Matters) [Allocate Smartly]

    We track more than 60 Tactical Asset Allocation strategies, which members can combine together into custom portfolios. To make creating those portfolios easier, we provide an optimizer showing the best performing combinations of strategies based on the members investment objective, such as maximizing the Sharpe Ratio (risk-adjusted return) or minimizing volatility. By popular demand, weve
  • $SPX Loves Tax Day [Quantifiable Edges]

    In the 4/12/19 blog I showed a study about US tax day (normally April 15th). The reason tax day may be important is that it is the last day that people can make IRA contributions to count for the previous tax year. This can create a last-minute rush and you will often have an inflow of funds heading into the market right around and on the day taxes are due. Fund managers will often put this money
  • Managed Futures: Fast & Furious vs Slow & Steady [Factor Research]

    Managed futures strategies aim to exploit short- or long-term trends Short-term trend followers are often seen as offering better stock market crash protection characteristics Our analysis highlights that the differences are marginal INTRODUCTION Aesops famous story of the race between the tortoise and the hare was put up to a test in 2016 when researchers made them compete with each other in
  • Research Review | 14 May 2021 | Stock Returns [Capital Spectator]

    Long-Horizon Stock Returns Are Positively Skewed Adam Farago and Erik Hjalmarsson (University of Gothenburg) April 28, 2021 At long horizons, multiplicative compounding induces strong-to-extreme positive skewness into stock returns; the magnitude of the effect is primarily determined by single-period volatility. Consequently, at horizons greater than five years, returns individual or
  • The macro forces behind equity-bond price correlation [SR SV]

    Since the late 1990s, the negative price correlation of equity and high-grade bonds has reduced the volatility of balanced portfolios and boosted Sharpe ratios of leveraged long-long equity-bond strategies. However, this correlation is not structurally stable. Over the past 150 years, equity-bond correlation has changed repeatedly. A structural economic model helps to explain and predict

Quantocracy’s Daily Wrap for 05/13/2021

This is a summary of links featured on Quantocracy on Thursday, 05/13/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Learning Candlestick Patterns [Tr8dr]

    In the previous posts I described an Reinforcement Learning approach to Learning the Exit part 1, part 2. My initial conclusions there have been: reward smoothing (with the labeler) leads to more robust results than a reward on position exit without smoothing the learning process struggled and had more volatility from epoch to epoch obtained the best results with smoothed reward obtained
  • The Rust Programming Language [Mark Best]

    I love programming! There is something really satisfying about solving a complicated problem concisely. That said I see programming languages as a tool to solve a problem rather than purely coding for coding sake. I have used a lot of programming languages over the last 20 years namely Java, R, Matlab, Python, C++ and now Rust. It is pretty common to read articles about language wars and which one
  • Fixed income when you re between a rock and a hard place – Part 2 [Alpha Architect]

    In Part 1, we defined fixed income factors. But factors alone will not solve each investors problem. Below, we extend the discussion by walking through a case study that shows how an asset allocator might use factors to solve a common problem: how to invest in a low yield environment given the practical constraints faced by many investors. Or, how can factors help investors stuck between a rock