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Quantocracy’s Daily Wrap for 06/12/2021

This is a summary of links featured on Quantocracy on Saturday, 06/12/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Honest Guide to Getting a Quant Job in Finance: (1) So, you want to be a Quant?! [Quant at Risk]

    They say that a journey of thousand miles commences with a single step. So, here you are, firm in your own resolutions or hesitating where to go. Graduated from a university or standing and trembling about next move in your life. Fired from one job or looking for another opportunity to seize. Battling against the wind, the haze, the misfortune that fell unexpectedly upon you, suddenly from
  • Combining Value and Profitability Factors: the International Evidence [Alpha Architect]

    My October 29, 2020, article for Alpha Architect examined the research on the profitability factor. I then reviewed the findings of the June 2020 study On the Conjoint Nature of Value and Profitability, which analyzed how combining the profitability factor with the value factor tilting the portfolios exposure to the two factorsimpacted the risk and return of a long-only U.S.

Quantocracy’s Daily Wrap for 06/10/2021

This is a summary of links featured on Quantocracy on Thursday, 06/10/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Concepts of Entropy in Finance: Transfer entropy [Quant Dare]

    The concept of entropy has many useful applications in finance such as measuring risk, uncertainty, or noise in a signal. In this post we will focus on transfer entropy, a useful tool for causal inference between financial time series. What is entropy? Entropy in general represents the uncertainty, ambiguity, and disorder of a stochastic process. The concept of entropy has been introduced in many

Quantocracy’s Daily Wrap for 06/07/2021

This is a summary of links featured on Quantocracy on Monday, 06/07/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Optimising my way out of a small fund problem – part one [Investment Idiocy]

    This is part one of a series of posts about using optimisation to get the best possible portfolio given a relatively small amount of capital. In this short post I present the idea, and discuss some issues that I need to resolve. It's a bit of a stream of conciousness! It's less of a blog post, and more my random jottings on the subject converted from scribbles to electronic prose.
  • Still Using Book to Market for a Value Metric? Read This. [Alpha Architect]

    Book to Market (B/M) has been a prominent indicator used to construct "value" tilted portfolios. The love affair with B/M started with Graham and Dodd (1934), but became the gold standard after Fama and French (1992). Historically, B/M was a reasonable ratio to express the value factor and it worked incredibly well when investors were hunting for value in steel mills, railroads, and
  • Liquid Alt Juggernauts: Worth their Salt? [Factor Research]

    Liquid alternative mutual funds only captured 10% of the market share from hedge funds The alpha generated since 2013 was essentially zero Long-short equity funds can be replicated simply via market beta + cash INTRODUCTION One of the most perplexing questions in the investment industry is why liquid alternatives have not been able to disrupt the hedge fund industry in the same way as ETFs have

Quantocracy’s Daily Wrap for 06/04/2021

This is a summary of links featured on Quantocracy on Friday, 06/04/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • This Time is Different? Consider Quantifying Subjective Priors [Alpha Architect]

    This time is different. –John Templeton "This time is different," is a sentiment that leads many investors to stray from using data analysis in their investment decision process and more towards discretionary judgment. The logic as to why data analysis techniques may not apply to different situations is often framed in the following way: These particular set of conditions have

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