Quantocracy

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Quantocracy’s Daily Wrap for 09/10/2019

This is a summary of links featured on Quantocracy on Tuesday, 09/10/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Can you apply factors to trade performance? [Robot Wealth]

    When tinkering with trading ideas, have you ever wondered whether a certain variable might be correlated with the success of the trade? For instance, maybe you wonder if your strategy tends to do better when volatility is high? In this case, you can get very binary feedback by, say, running backtests with and without a volatility filter. But this can mask interesting insights that might surface if

Quantocracy’s Daily Wrap for 09/09/2019

This is a summary of links featured on Quantocracy on Monday, 09/09/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Bagging in Financial Machine Learning: Sequential Bootstrapping [Hudson and Thames]

    To understand the Sequential Bootstrapping algorithm and why it is so crucial in financial machine learning, first we need to recall what bagging and bootstrapping is and how ensemble machine learning models (Random Forest, ExtraTrees, GradientBoosted Trees) work. It all starts from a Decision Tree algorithm. As we all know Decision Tree is an extremely useful machine learning algorithm which
  • CTAs in Perspective [Spring Valley]

    CTAs, mostly trend followers, have historically delivered meaningful diversification to both traditional and alternative asset classes. However, CTAs have struggled over the last ten years. There have been various explanations such as low volatility, increased correlations, and suppressed interest rates. By understanding the drivers behind trend following, we isolate the impact each variable has
  • Build Your Own Long/Short [Flirting with Models]

    We exploit the idea that long-only strategies are long/short portfolios all the way down, we demonstrate how to isolate the active bets of portfolio managers. Using the example of a momentum / low-volatility barbell portfolio, we construct a simple long/short portfolio using ETFs and S&P 500 futures. Recognizing that not all investors will have access to S&P 500 futures, we argue

Quantocracy’s Daily Wrap for 09/07/2019

This is a summary of links featured on Quantocracy on Saturday, 09/07/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Stock Market Trends (h/t @PyQuantNews) [Frank Ceballos]

    Purpose: The purpose of this article is to introduce the reader to some of the tools used to spot stock market trends. Materials and Methods: We will utilize a data set consisting of five years of daily stock market data for Analog Devices. The time period we consider starts on January 1, 2013 and ends on December 31, 2017. We will start analyzing the data using line plots, then introduce
  • The low-risk effect: evidence and reason [SR SV]

    The low-risk effect refers to the empirical finding that within an asset classes higher-beta securities fail to outperform lower-beta securities. As a result, betting against beta, i.e. leveraged portfolios of longs in low-risk securities versus shorts in high-risk securities, have been profitable in the past. The empirical evidence for the low-risk effect indeed is reported as strong and

Quantocracy’s Daily Wrap for 09/06/2019

This is a summary of links featured on Quantocracy on Friday, 09/06/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Interview with Marcos Lopez de Prado [Mathematical Investor]

    Marcos Lopez de Prado, who was named Quant of the Year for 2019 by the Journal of Portfolio Management, and who has recently formed his own investment firm True Positive Technologies, was recently interviewed by KNect365, an organization that sponsors numerous conferences and other exchanges between professionals in various fields, including finance, life sciences, technology, law,

Quantocracy’s Daily Wrap for 09/05/2019

This is a summary of links featured on Quantocracy on Thursday, 09/05/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • March for the Fallen 2019: Detailed Logistics Outline and What to Expect [Alpha Architect]

    Action Item: Please let us know your trip details so we can support you as much as possible. We are a little over 3 weeks away from March for the Fallen (#MFTF). NOTE: There is a monster training event occurring simultaneously to MFTF this year so be prepared to dodge humvees and watch out for stray artillery shells. Im joking. But seriously, we are anticipating potential logistical issues so
  • Neural Network In Python: Introduction, Structure and Trading Strategies [Quant Insti]

    You are probably wondering how a technical topic like Neural Network Tutorial is hosted on an algorithmic trading website. Neural network studies were started in an effort to map the human brain and understand how humans take decisions but algorithm tries to remove human emotions altogether from the trading aspect. What we sometimes fail to realise is that the human brain is quite possibly the
  • Preliminary Test Results of Time Series Embedding [Dekalog Blog]

    Following on from my post yesterday, this post presents some preliminary results from the test I was running while writing yesterday's post. However, before I get to these results I would like to talk a bit about the hypothesis being tested. I had an inkling that the dominant cycle period might having some bearing on tau, the time delay for the time series embedding implied by Taken's
  • An Analysis of Benjamin Graham s Net Current Asset Values: A Performance Update [Alpha Architect]

    The study examined the performance of securities that were trading at no more than two-thirds of its Net Current Asset Value (NAV) during the 1970-82 period in the US Net nets, on a gross basis, more than tripled the returns of the market (as measured by the S&P 500 TR) Net nets, on a net basis (i.e. after commissions and potential taxes) more than doubled the returns of the market (as

Quantocracy’s Daily Wrap for 09/04/2019

This is a summary of links featured on Quantocracy on Wednesday, 09/04/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • DIY Ray Dalio ETF: How to build your own Hedge Fund strategy with risk parity portfolios [Open Quants]

    Earlier this month, Bloomberg published a news article about the launch of a new Risk Parity ETF in the US. The RPAR Risk Parity ETF plans to allocate across asset classes based on risk. The fund would be the first in the U.S. to follow this quantitative approach, allotting more money to securities with lower volatility according to Bloomberg. [The RPAR Risk Parity ETF is] kind of like Bridgewater
  • Understanding Variance Explained in PCA [Eran Raviv]

    Principal component analysis (PCA) is one of the earliest multivariate techniques. Yet not only it survived but it is arguably the most common way of reducing the dimension of multivariate data, with countless applications in almost all sciences. Mathematically, PCA is performed via linear algebra functions called eigen decomposition or singular value decomposition. By now almost nobody cares how
  • How a College Student Built a Slackbot to Execute Trades In a Day, Part 1 [Alpaca]

    Chinese tariffs. Tesla to 420. Trump tweets. With so much unpredictability in the markets these days, one short look away from the market could take a toll on your portfolio. Unfortunately, the market does not wait for people to get off work to become volatile. In fact, much of the volatility can happen during the workday, while people are busy in meetings or trying to get work done. Luckily for

Quantocracy’s Daily Wrap for 09/03/2019

This is a summary of links featured on Quantocracy on Tuesday, 09/03/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Sector Momentum [Flirting with Models]

    We explore top N sector rotation strategies based upon momentum signals. We find that too much concentration (i.e. N is too small) leads to poor performance, whereas performance does not appear to materially degrade for larger N. We find that short- to long-term signals all appear to generate higher total returns than the S&P 500 and there may be room to benefit from diversification by
  • Crisis proof your portfolio: part 2/2 [Alpha Architect]

    This is part 2 (part one is here) of an excellent article that examines the feasibility and effectiveness of protecting equity portfolios using traditional passive means and more contemporary active strategies. It is jam-packed with information and analysis that is best consumed in two parts; however, a good summary of the article by Larry Swedroe can be found here. The focus in part 1 is the
  • A Quant’s Approach to Drawdown: The Cold Blood Index [Robot Wealth]

    In part 1 of this series, we talked about how a market-savvy systematic trader would approach a period of drawdown in a trading strategy. Specifically, theyd: do the best job possible of designing and building their trading strategy to be robust to a range of future market conditions chill out and let the strategy do its thing, understanding that drawdowns are business-as-usual go and look for
  • Python & Data Science Tutorial Analyzing a Random Dataset [Quantoisseur]

  • An Updated Look At SPX Performance After Labor Day [Quantifiable Edges]

    A couple of years ago on the blog I showed a study suggesting that Labor Day week performance has been somewhat dependent on whether the market has rallied over the 20 trading days leading up to it. I decided to update that study today. Below is a look at post-Labor Day performance when the previous 20 days have seen gains versus losses. First lets look at rises into the holiday (unlike now).
  • Improving the Odds of Value: II [Factor Research]

    Value investors earn a premium for holding undesirable stocks The yield curve may identify periods where the premium is more attractive Since 1971, the performance of the Value factor was negative when the yield curve was flattening INTRODUCTION Imagine a portfolio of companies that are plagued by declining sales, negative earnings, too much leverage, rating downgrades, CEOs that prefer golf over

Quantocracy’s Daily Wrap for 09/01/2019

This is a summary of links featured on Quantocracy on Sunday, 09/01/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Tactical Asset Allocation in August [Allocate Smartly]

    This is a summary of the recent performance of a wide range of excellent Tactical Asset Allocation (TAA) strategies, net of transaction costs. These strategies are sourced from books, academic papers, and other publications. While we dont (yet) include every published TAA model, these strategies are broadly representative of the TAA space. Learn more about what we do or let AllocateSmartly help

Quantocracy’s Daily Wrap for 08/30/2019

This is a summary of links featured on Quantocracy on Friday, 08/30/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Is Pairs Trading Still Viable? [Quant Rocket]

    Classic pairs trading strategies have suffered deteriorating returns over time. Can a research pipeline that facilitates the identification and selection of ETF pairs make pairs trading viable again? This post investigates such a pipeline. The problem: pairs wander away Source: Ernie Chan, Algorithmic Trading: Winning Strategies and Their Rationale, Wiley, May 28, 2013, chapter 4. Pairs trading is

Quantocracy’s Daily Wrap for 08/29/2019

This is a summary of links featured on Quantocracy on Thursday, 08/29/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Free Financial, Fundamental and Macroeconomic Data with R examples [Open Quants]

    In this Article, we will show how to obtain free financial data including: End-of-day and real-time pricing; Company financials; Macroeconomic data. Data sources utilized in this Article include: U.S. Securities and Exchange Commission (SEC); Quandl; IEX; Alpha Vantage. We also provide code to reproduce results as part of our Open Source Live Book Initiative.
  • Can We Explain the Low Volatility Anomaly? [Alpha Architect]

    One of the big problems for the first formal asset pricing model developed by financial economists, the CAPM, was that it predicts a positive relation between risk and return. But empirical studies have found the actual relation to be flat, or even negative. Over the last 50 years, the most defensive (low-volatility, low-risk) stocks have delivered both higher returns and higher