Quantocracy

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Quantocracy’s Daily Wrap for 06/17/2020

This is a summary of links featured on Quantocracy on Wednesday, 06/17/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Trend-following, volatility targeting and Ensembles for Bitcoin [Beat Passive]

    Today well incrementally build a strategy using trend-following, volatility targeting, and ensemble models and well use Bitcoin as our use-case. Why bitcoin? Because its a maddening asset-class thats extremely volatile over short periods of time and seemed like a fun place to test these concepts. You might be thinking: an investing strategy for bitcoin is such a cop out, of course
  • What is the difference between Extra Trees and Random Forest? [Quant Dare]

    Extra Trees and Random Forest are two very similar ensemble methods and often a doubt arises as to whether to use one or the other. What is really the difference between them? In previous posts, Random forest: many are better than one, we have seen how to create a Random Forest from decision trees and how they improve their performance. Furthermore, if you want more information about simple
  • ReSolve Riffs on Gold vs Treasury as Disaster Protection [Invest Resolve]

    This is ReSolves Riffs live on Youtube every Friday afternoon to debate the most relevant investment topics of the day. The recent pandemic-led selloff has once again highlighted the importance of having ballast in portfolios to deal with extreme equity volatility and ultimately protect investors from disastrous outcomes. This week we discussed: Whether bonds can continue to

Quantocracy’s Daily Wrap for 06/16/2020

This is a summary of links featured on Quantocracy on Tuesday, 06/16/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Free Online Event from AI & Data Science in Trading: June 22-26

    AI & Data Science in Trading Digital Week brings together experts in the use of AI and advanced data analytic techniques within asset management, primarily for finding alpha, managing risk and optimizing portfolios. Join us for a week long online event from wherever you are in the world. Use this time to continue to learn, network and utilize AI to optimize your investment workflow. During
  • Trading Costs Wipe Out the Overnight Return Anomaly [Alpha Architect]

    At least once a year, the press and Twittersphere propagate the mistaken idea that investors can earn excess returns by buying the S&P 500 at the close of the market, then selling it at the open the next day. The logic is that by exposing themselves to only overnight returns, investors can seek to harness some form of information surprises by the way of earnings announcements or idiosyncratic
  • Defensive & Diversifying Strategies: What Worked in 2020? [Factor Research]

    Defensive smart beta strategies like Low Volatility did not offer much capital protection in 2020 Long-short multi-factor investing generated negative returns, but still offered diversification benefits Managed futures finally found their redemption given positive & uncorrelated returns INTRODUCTION The best defense is a good offense is frequently quoted in the military (George

Quantocracy’s Daily Wrap for 06/15/2020

This is a summary of links featured on Quantocracy on Monday, 06/15/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Order Flow Correlation May Imply Momentum Factor Crowding [Alpha Architect]

    This study is one of several studies reviewed here and here, attempting to measure factor crowding. This article specifically examines the presence of factor crowding by estimating the correlation between market order flow with the magnitude of the factor signal to trade. They hypothesize that factor crowding can be identified via the correlations associated with supply-demand imbalances where

Quantocracy’s Daily Wrap for 06/13/2020

This is a summary of links featured on Quantocracy on Saturday, 06/13/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Portfolio simulations [OSM]

    In our last post, we compared the three most common methods used to set return expectations prior to building a portfolio. Of the threehistorical averages, discounted cash flow models, and risk premia modelsno single method dominated the others on average annual returns over one, three, and five-year periods. Accuracy improved as the time frame increased. Additionally, aggregating all three

Quantocracy’s Daily Wrap for 06/12/2020

This is a summary of links featured on Quantocracy on Friday, 06/12/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Monster Factor Correlation Chart [Alpha Architect]

    We recently added a monster correlation matrix to our factor library data sheet that maps out the correlation of all the factors against every other factor. Here is a sample output that highlights the difference in the correlations between value factors and different quality factors. Note the big difference between book to market, which has a negative correlation to quality, and the other metrics
  • Research Review | 12 June 2020 | Forecasting [Capital Spectator]

    Breaking Bad Trends Ashish Garg (Research Affiliates), et al. May 7, 2020 We document and quantify the negative impact of trend breaks (i.e., turning points in the trajectory of asset prices) on the performance of standard trend-following strategies across several assets and asset classes. The frequency of trend breaks has increased in recent years, which can help explain the lower performance of

Quantocracy’s Daily Wrap for 06/11/2020

This is a summary of links featured on Quantocracy on Thursday, 06/11/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • 5 Surprising Things We Learned from a Factor Investing Expert [Alpha Architect]

    Lu Zhang and his colleagues made some waves with their new paper, Replicating Anomalies. (now published in the RFS congrats!). We have a summary of the paper here. Lu Zhang, and his colleagues, Kewei Hou and Chen Xue, spent nearly 3 years carefully compiling and replicating 447 anomalies identified in the academic literature. The paper is so dense Ryan even created a blog post that
  • How to extend ETF prices with mutual fund data using SQL [Robot Wealth]

    On Zero to Robot Master Bootcamp, we teach how to build a portfolio of three automated systematic trading strategies. One of them is a long term Risk Premia Harvesting strategy which trades asset class ETFs. ETFs are useful instruments for analysing long term (tradeable) performance of various asset classes but many have been introduced only relatively recently and have limited data available.
  • Counterpoint: ETF Activity May Make the Stock Market MORE Efficient [Alpha Architect]

    The Securities and Exchange Commission (SEC) has called for more research and discussion on the impacts of ETFs. In a previous post, we covered why ETFs have not screwed up correlations, liquidity, and alpha opportunities. However, here is another post from Wes that outlines arguments that ETFs may screw up stock market efficiency. In short, how ETFs affect stock market efficiency is an ongoing

Quantocracy’s Daily Wrap for 06/08/2020

This is a summary of links featured on Quantocracy on Monday, 06/08/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • 8 week algo trading course taught by full-time pro traders [Robot Wealth]

    Learn to research, build & trade three systematic trading strategies, from scratch, in 8 weeks. Join Bootcamp Today as featured by: The Financial Hacker In 8 weeks on the Zero to Robot Master Bootcamp, you will learn how to run a portfolio of three automated systematic trading strategies. These are the strategies that you will learn to build and trade on Zero to Robot Master bootcamp. Teach me
  • Tail Hedging [Flirting with Models]

    The March 2020 equity market sell-off has caused many investors to re-investigate the potential benefits of tail risk hedging programs. Academic support for these programs is quite limited, and many research papers conclude that the cost of implementation for nave put strategies out-weighs the potential payoff benefits. However, many of these studies only consider strategies that hold options to
  • Musings on Low Volatility [Factor Research]

    The Low Volatility strategy failed to protect investors in March and April 2020 Industrials & materials generated positive and technology & real estate negative relative performance Low Vol strategies do not deliver ESG benefits INTRODUCTION Low volatility (Low Vol) strategies have gained popularity over the past decade with retail and institutional investors alike. Although initially,

Quantocracy’s Daily Wrap for 06/07/2020

This is a summary of links featured on Quantocracy on Sunday, 06/07/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Curated list of libraries, packages and resources for Quants [Milton FMR]

    Numerical Libraries & Data Structures numpy NumPy is the fundamental package for scientific computing with Python. scipy SciPy (pronounced Sigh Pie) is a Python-based ecosystem of open-source software for mathematics, science, and engineering. pandas pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools
  • Downloading FX Pairs via Oanda API to Calculate Currency Strength Indicator [Dekalog Blog]

    In the past I have posted a series of blog posts about a Currency Strength Indicator (here, here, here and here). This blog post gives an Octave function to use Oanda's API to download all the 10 minute OHLC data required to calculate the above strength indicators on the 10 minute time frame. ## Copyright (C) 2020 dekalog ## ## This program is free software: you can redistribute it and/or

Quantocracy’s Daily Wrap for 06/05/2020

This is a summary of links featured on Quantocracy on Friday, 06/05/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Fat Tails Everywhere? Profiling Extreme Returns: Part II [Capital Spectator]

    Its long been established that stock market returns arent normally distributed and that fat tails (extreme returns that are unexpected for a normal distribution) apply. This has implications, of course, for portfolio design and management. The first question: What are the choices for managing tail risk for equity exposures? There are many answers, each with a different set of pros and cons.
  • Excess Returns Podcast: Systematic Value Investing [Alpha Architect]

    Recently I was invited to talk with Justin and Jack on the Excess Returns Podcast. I thank them for the opportunity and enjoyed the conversation! Below are some of the topics we discussed: Struggles in value and its long-term potential going forward. What would it take to convince you that value investing doesnt work anymore? Impact of the shutdown on earnings and how to look at analyzing

Quantocracy’s Daily Wrap for 06/04/2020

This is a summary of links featured on Quantocracy on Thursday, 06/04/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Why Aren’t Call Options More Expensive Than Put Options? [Robot Wealth]

    Why arent calls more expensive than puts for an asset which is more likely to go up than down? We have an asset trading at $100 for which the distribution of future returns is a known fact. It has annual returns described by a normal distribution with mean 5% and standard deviation 10%. This is, therefore, an asset with positive drift. It is more likely to go up than down. Because we are
  • Do Interest Rates Explain Value s Underperformance? [Alpha Architect]

    From January 2017 through March 2020, the value premium, defined by HML (the return of high book-to-market stocks minus the return of low book-to-market stocks experienced a drawdown of 42 percent. 1 If we extend the period back to January 2007, the drawdown of about 51 percent is the largest ever. There have been many attempts to explain the reason for the dramatic underperformance; weve even