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Quantocracy’s Daily Wrap for 12/04/2018

This is a summary of links featured on Quantocracy on Tuesday, 12/04/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How to Use Trend Following within a Portfolio [Alpha Architect]

    A question we have been receiving recently is the following: How should I use trend following within a portfolio? Generally, the questions are related to our Global Value, Momentum, and Trend Index, which allocates to the (1) Value, (2) Momentum, and (3) Trend factors. A big difference between the Global Value Momentum Trend (GVMT) portfolio and many other smart-beta products is the

Quantocracy’s Daily Wrap for 12/03/2018

This is a summary of links featured on Quantocracy on Monday, 12/03/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • GARCH and a rudimentary application to Vol Trading [QuantStrat TradeR]

    This post will review Kris Boudts datacamp course, along with introducing some concepts from it, discuss GARCH, present an application of it to volatility trading strategies, and a somewhat more general review of datacamp. So, recently, Kris Boudt, one of the highest-ranking individuals pn the open-source R/Finance totem pole (contrary to popular belief, I am not the be-all end-all of coding R
  • The relationship between ATR and standard deviation [Investment Idiocy]

    Let's begin this post with a gross generalisation: Professional traders tend to measure risk and target risk using standard deviation. Amateur traders tend to use a funky little number called the ATR: 'Average True Range'. Both try and achieve the same aim: summarise the typical movement in the price of something using a single number. However they are calculated differently. Can we
  • Maximizing Diversification [Flirting with Models]

    Diversification within a portfolio can be quantified using the diversification ratio, which measures how much the volatility is reduced relative to a scenario where all assets are perfectly correlated. By maximizing the diversification ratio, we can construct the most diversified portfolio for a given investment universe. We construct the most diversified portfolio using data from 1973 and look at
  • Measuring Factor Exposures: Uses and Abuses [Alpha Architect]

    What are the research questions? USES: Can investors really separate alpha from beta? What are the ins-and-outs of understanding the exposures in a portfolio and their contribution to alpha? ABUSES: Are there differences in the way strategies are constructed in academic articles vs. the way practitioners actually implement those strategies that are consequential for investors?
  • Private Equity: The Emperor Has No Clothes [Factor Research]

    This research note was originally published by the CFA Institutes Enterprising Investor blog. Here is the link. SUMMARY Private equity returns can be replicated with small cap equities Small, cheap and levered stocks would have achieved higher returns since 1988 Valuation and debt multiples are at all-time-highs, lowering expected returns FROM BUST TO BOOM The private equity industry had an
  • Free Data and the Collapse of Trading Costs [CXO Advisory]

    How have costs of U.S. stock trading data evolved in recent years? In his October 2018 paper entitled Retail Investors Get a Sweet Deal: The Cost of a SIP of Stock Market Data, James Angel examines costs of U.S. stock market data. He also describes the production of these data and their consolidation/distribution via Securities Information Processors (SIP). Using data for U.S. trading costs

Quantocracy’s Daily Wrap for 12/01/2018

This is a summary of links featured on Quantocracy on Saturday, 12/01/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Tactical Asset Allocation in November [Allocate Smartly]

    This is a summary of the recent performance of a wide range of excellent tactical asset allocation 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 you
  • Listen to the whole quant album [Cuemacro]

    Its 50 years since the Beatles released the White Album. To celebrate it has been reissued with new mixes of the original tracks. I have to admit, its rarer these days to listen to an album the whole way through. Instead, I invariably listen to playlists on iTunes which select tracks from all manner of different artists and albums and mix them together. iTunes and Spotify have revolutionized
  • Understanding the correlation of equity and bond returns [SR SV]

    The correlation of equity and high grade sovereign bond returns is a powerful driver of portfolio construction and the term premia of interest rates. This correlation has turned from positive in the 1970s-1990s to negative in the 2000s-2010s, on the back of similar shifts in the correlation between inflation and economic growth and between inflation and real interest rates. The structural

Quantocracy’s Daily Wrap for 11/30/2018

This is a summary of links featured on Quantocracy on Friday, 11/30/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Research Review | 30 November 2018 | Risk Factors [Capital Spectator]

    Factor Investing: Get Your Exposures Right! Franois Soup (BNP Paribas Asset Management), et al. October 26, 2018 This paper is devoted to the question of optimal portfolio construction for equity factor investing. The first part of the paper focusses on how to make sure that a given equity portfolio has the targeted factor exposures, even before imposing any constraints. We show that such

Quantocracy’s Daily Wrap for 11/28/2018

This is a summary of links featured on Quantocracy on Wednesday, 11/28/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Stiffness Indicator Analysis [Alvarez Quant Trading]

    A reader pointed me the November 2018 issue of Technical Analysis of Stocks & Commodities to an article about a trend following indicator on S&P500 stocks. I liked the concept of the indicator and the article had backteted results and AmiBroker code. How could I resist not looking into this? Little did I realize this would lead to Backtesting is Hard and How much does not having
  • Deep Reinforcement Trading [Quant Dare]

    Deep Reinforcement Learning applications in finance are still largely unknown. Nonetheless, recent developments in other fields have pushed researchers towards exciting new horizons. I believe that there is a huge potential for Reinforcement Learning in finance. As investment guru Ray Dalio, founder of Bridgewaters, defends in his book Life and Work Principles, investment is an iterative process.
  • When SPX Closes Higher On Bad Breadth [Quantifiable Edges]

    While the SPX closes higher on Tuesday, NYSE breadth was weak both from an % Up Issues and % Up Volume standpoint. This triggered the study below from the Quantifinder. I also discussed it in last nights subscriber letter. 2018-11-28-1 Here we see numbers suggesting a substantial bearish edge over the next 1-4 days. Below is the full list of instances and their 4-day returns. 2018-11-28-2

Quantocracy’s Daily Wrap for 11/27/2018

This is a summary of links featured on Quantocracy on Tuesday, 11/27/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Create own Recession Indicator using Mixture Models [Eran Raviv]

    Broadly speaking, we can classify financial markets conditions into two categories: Bull and Bear. The first is a todo bien market, tranquil and generally upward sloping. The second describes a market with a downturn trend, usually more volatile. It is thought that those bull\bear terms originate from the way those animals supposedly attack. Bull thrusts its horns up while a bear swipe its

Quantocracy’s Daily Wrap for 11/26/2018

This is a summary of links featured on Quantocracy on Monday, 11/26/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Tactical Statistical Arbitrage [Factor Research]

    SUMMARY Statistical arbitrage behaves similarly across markets Volatility is the main performance driver Attractive strategy for diversifying an equity portfolio INTRODUCTION Strategies like Value or Momentum are like staples that deserve a permanent allocation in investors portfolios. In contrast, other strategies are more like sunscreen, which is mainly used tactically to minimize the risk of
  • A Proxy for the Unobservable Global Market Portfolio [Alpha Architect]

    What are the Research Questions? The authors propose an estimation of the capital stock that involves all identifiable and measurable financial and nonfinancial assets in the world economy. This portfolio seeks to represent the so-called Global Market Portfolio, that all MBA students learn to know and love when studying the CAPM. (discussion here). As a selection rule, they include assets

Quantocracy’s Daily Wrap for 11/25/2018

This is a summary of links featured on Quantocracy on Sunday, 11/25/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Maximising the potential of portfolios with Adam Butler of @InvestReSolve [Better System Trader]

    With so much focus often on the actual trading strategies or investments, portfolio construction can sometimes become an afterthought or not even considered. However, as were going to hear about today, portfolio construction and optimization has the potential for huge increases in wealth But there are a number of aspects we need to carefully consider if we want to maximise the potential
  • CDS term premia and exchange rates [SR SV]

    The term structure of sovereign credit default swaps (CDS) is indicative of country-specific financial shocks, because rising country risk affects short-dated maturities more than longer-dated ones. This feature allows disentangling global and local risk factors in sovereign CDS markets. The latter align with the performance of other local asset markets. In particular, recent empirical research

Quantocracy’s Daily Wrap for 11/23/2018

This is a summary of links featured on Quantocracy on Friday, 11/23/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Is trend following dead? [Investment Idiocy]

    I get asked this question at least once a week. As those of you that have met me IRL ('in real life') will know I have limited patience and I'm easily bored. I'm definitely bored of answering this question. This post is the last time I'll answer it. There are broadly two ways to answer this question: Looking at fundamental reasons why trend following is less likely to work
  • Investment Strategy Development Coursework [CXO Advisory]

    In a series of five presentation slide sets (Lectures 1-8 of 10) on Advances in Financial Machine Learning, Marcos Lopez de Prado provides part of Cornell Universitys ORIE 5256 graduate course at the School of Engineering (Special Topics in Financial Engineering V). The course description includes: Machine learning (ML) is changing virtually every aspect of our lives. As it

Quantocracy’s Daily Wrap for 11/22/2018

This is a summary of links featured on Quantocracy on Thursday, 11/22/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Queue Position Simulation [Systematic Edge]

    First off, Happy Thanksgiving! If time permits in the coming months Id like to explore more on how I look at High Frequency (HF) data. Hopefully along the way I can spark some new discussion and improve on my thought process. HFT strategy simulation is no easy task. I am referring to this as an simulation because its purely an approximation of how a strategy would have performed given a
  • Decision Tree For Trading Using Python [Quant Insti]

    Decision Trees, are a Machine Supervised Learning method used in Classification and Regression problems, also known as CART. Remember that a Classification problem tries to classify unknown elements into a class or category; the output always are categorical variables (i.e. yes/no, up/down, red/blue/yellow, etc.) A Regression problem tries to forecast a number such as the return for the next day.
  • Estimating the probability of something that never happened [Quant Dare]

    Have you ever needed to estimate the probability of a rare event? So rare that you havent been able to encounter it in real data? Well, what if I told you that there exists a way to calculate a statistically correct approximation. Oh, and you wont even need a calculator! Recently I have just heard of the statistical Rule of three. No, this is not the mathematical Rule of three