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Quantocracy’s Daily Wrap for 04/04/2018

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

  • When Breaking up is Easy To Do [Factor Investor]

    This post is a bit of an experiment. My good friend Steven Wood and I started discussing some collaborations a few months ago. We hope that it ups the quality of our research and also brings some new insights into each of our philosophies. Below is his recent post, for which I helped provide some research on the performance of spin-offs, which was popularized by Joel Greenblatt in the mid
  • Stitching data for a more ‘balanced’ backtest [Better System Trader]

    When traders set in-sample and out-of-sample periods for their backtests, its common just to pick some dates that split the data into a pre-defined percentage or range. The trouble with this approach is that it often doesnt take into account the type of market environments that exist in those periods. For example, your in-sample period may be very bearish, and if your out-of-sample period is
  • Isolation forest: the art of cutting off from the world [Quant Dare]

    We have talked about outliers several times in this blog. Examples include how to detect them or how to transform the data to remove them. Here we have another technique to detect outliers in our big data set: the isolation forest algorithm. The idea behind the isolation forest method The name of this technique is based on its main idea. The algorithm isolates each point in the data and splits
  • On The Diversification Dangers of DIY Tactical Asset Allocation [Allocate Smartly]

    We wanted to take a moment to highlight two must read posts from Newfound Research. Newfound is a thought leader in the TAA space and we highly recommend following them now. The Diversification Dangers of DIY Tactical and Diversifying the What, How, and When of Trend Following Newfound outlines three ways in which TAA investors often fail to diversify: WHAT they trade: failing to diversify
  • What is Bitcoin’s Fair Value? [Quantpedia]

    We develop a strong diagnostic for bubbles and crashes in bitcoin, by analyzing the coincidence (and its absence) of fundamental and technical indicators. Using a generalized Metcalfes law based on network properties, a fundamental value is quantified and shown to be heavily exceeded, on at least four occasions, by bubbles that grow and burst. In these bubbles, we detect a universal

Quantocracy’s Daily Wrap for 04/03/2018

This is a summary of links featured on Quantocracy on Tuesday, 04/03/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Timing Country Exposure with Value: A Valuation Measure Horserace [Alpha Architect]

    Buy cheap. This is a motto many live by, not only in their daily lives but also in their investment philosophy. Historically, buying cheap stocks was a good idea (i.e., the so-called value premium). But how might valuation matter when it comes to country allocations? In other words, given valuations, how much money should I allocate to U.S. equity and how much should I allocate to
  • How to Perform Investment Sentiment Analysis on Twitter [Alpha Architect]

    What are the research questions? By studying tweets on thirty companies in the Dow Jones Index, the authors ask the following research question: Is it possible to develop a system for the detection and discovery of the popularity of special events on Twitter that may influence the financial markets? What are the Academic Insights? The system devised by the authors is composed of five steps:

Quantocracy’s Daily Wrap for 04/02/2018

This is a summary of links featured on Quantocracy on Monday, 04/02/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The most important plot in finance [Mathematical Investor]

    In this post we look at the one plot that proves that technical analysis (TA) is useless. TECHNICAL ANALYSIS AND HOROSCOPES As volatility has made a come back in recent months, investors have sought advice to asset managers. In many instances, such advice consists in technical indicators. Charles Schwab represents TA as an indispensable tool for active traders (examples: here and here). Merrill
  • Diversifying the What, How, and When of Trend Following [Flirting with Models]

    Nave and simple long/flat trend following approaches have demonstrated considerable consistency and success in U.S. equities. While there are many benefits to simplicity, an overly simplistic implementation can leave investors naked to unintended risks in the short run. We explore how investors can think about introducing greater diversification across the three axes of what, how, and when in
  • Factor Olympics Q1 2018 [Factor Research]

    2018 started negative for the majority of factors Momentum, Quality and Growth showed the strongest performance Low Volatility, Dividend Yield and Value generated negative returns INTRODUCTION We present the performance of seven well-known factors on an annual basis for the last 10 years and the first quarter 2018. It is worth mentioning that not all factors have strong academic support, e.g.

Quantocracy’s Daily Wrap for 04/01/2018

This is a summary of links featured on Quantocracy on Sunday, 04/01/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Tactical Asset Allocation in March [Allocate Smartly]

    This is a summary of the recent performance of a wide range of excellent tactical asset allocation strategies. 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 follow these strategies in
  • A Simple System For Hedging Long Portfolios [Relative Value Arbitrage]

    In this post, we are going to examine a trading system with the goal of using it as a hedge for long equity exposure. To this end, we test a simple, short-only momentum system. The rules are as follows, Short at the close when Close of today Cover at the close when Close of today > lowest Close of the last 10 days The Table below presents results for SPY from 1993 to the present. We performed

Quantocracy’s Daily Wrap for 03/30/2018

This is a summary of links featured on Quantocracy on Friday, 03/30/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Research Review | 30 March 2018 | Portfolio Analysis [Capital Spectator]

    Factor Momentum Robert D. Arnott (Research Affiliates), et al. January 31, 2018 Past industry returns predict the cross section of industry returns, and this predictability is at its strongest at the one-month horizon (Moskowitz and Grinblatt 1999). We show that the cross section of factor returns shares this property, and that industry momentum stems from factor momentum. Factor momentum is

Quantocracy’s Daily Wrap for 03/29/2018

This is a summary of links featured on Quantocracy on Thursday, 03/29/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Trading rules that keep you trading [Alvarez Quant Trading]

    I have written the difficulty in trading and testing short strategies. I had stopped trading my short strategy because it was too hard to trade psychologically for me. About nine months ago, I revisited my short strategy to see how it had been doing since I stopped and of course it has been doing just fine even during these very bullish times. As strategy developers we often add rules to improve
  • Holy Bullish Thursday!! [Quantifiable Edges]

    Stock market performance leading up to and around many holidays has often been bullish. This is something I have written about several times over the years. Holy Thursday is one such day that has done quite well. I have shown Holy Thursday stats a few times in the past. The chart and statistics below are all updated through last year. 2018-03-28 Despite the last 2 years losing some ground, the
  • Newfound 2018 March Madness: Final Four Update [Flirting with Models]

    We outlined the full set of rules for the Newfound 2018 March Madness Brackets here. After two more rounds, we are down to the Final Four in our Newfound 2018 March Madness Bracket Challenge, and while the right hand side of the bracket looks predictable with two number 1 seeds facing off (Kansas and the current tournament favorite, Villanova) the left hand side has 11 seed Loyola facing off

Quantocracy’s Daily Wrap for 03/28/2018

This is a summary of links featured on Quantocracy on Wednesday, 03/28/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • R Quantifying Trend Days [Flare 9x]

    In this post I will be using R and data.table to extract all trend up / down days. The following method was used to quantify a trend day: 1. Trend up = Close price closes within 25% of the days high 2. Trend down = Close prices closes within 25% of the days low 3. Exclusive of gaps, if open is above yesterdays high or low exclude 4. Daily return must be over / below .75 / -.75% Other methods come
  • How Algo Trading Reacts to Market Stress [Quantpedia]

    A key issue raised by the rapid growth of computerised algorithmic trading is how it responds in extreme situations. Using data on foreign exchange orders and transactions that includes identification of algorithmic trading, we find that this type of trading contributed to the deterioration of market quality following the removal of the cap on the Swiss franc on 15 January 2015, which was an event

Quantocracy’s Daily Wrap for 03/27/2018

This is a summary of links featured on Quantocracy on Tuesday, 03/27/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Risk-Based Explanations for the Momentum Premium [Alpha Architect]

    Most of the literature on the momentum factor has focused on behavioral explanations, generally either investor underreaction or overreaction. For example, in his paper Explanations for the Momentum Premium, Yale University professor Tobias Moskowitz points out: Underreaction results from information traveling slowly into prices. That causes momentum. For example, there is ample evidence

Quantocracy’s Daily Wrap for 03/26/2018

This is a summary of links featured on Quantocracy on Monday, 03/26/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Protect & Participate: Managing Drawdowns with Trend Following [Flirting with Models]

    Trend following is an investment strategy that buys assets exhibiting strong absolute performance and sells assets exhibiting negative absolute performance. Despite its simplistic description, trend following has exhibited considerable empirical robustness as a strategy, having been found to work in equity indices, bonds, commodities, and currencies. A particularly interesting feature about trend
  • Factor Exposure Analysis: Dow Jones [Factor Research]

    Factor exposure should be considered a source of returns as well as of risk Factor biases can be measured top-down or bottom-up The results of the two approaches do not necessarily reconcile INTRODUCTION Factor investing has become immensely popular in recent years and assets in smart beta products surpassed $1 trillion in 2017. However, factor exposure should be regarded as much as a source of

Quantocracy’s Daily Wrap for 03/23/2018

This is a summary of links featured on Quantocracy on Friday, 03/23/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Tax Efficient Tactical Asset Allocation [Allocate Smartly]

    New to Tactical Asset Allocation? Learn more: What is TAA? In our previous post, we looked at the tax impact of TAA for investors trading in taxable accounts. Using our database of more than 40 published TAA models we concluded that, while TAA as a whole has been relatively tax efficient, the particular strategies that you choose mattersa lot. Individual strategies range from very to not
  • Two Centuries of Momentum [Flirting with Models]

    A momentum-based investing approach can be confusing to investors who are often told that chasing performance is a massive mistake and timing the market is impossible. Yet as a systematized strategy, momentum sits upon nearly a quarter century of positive academic evidence and a century of successful empirical results. Our firm, Newfound Research, was founded in August 2008 to offer
  • What s Cheap? A Factor Perspective [Factor Investor]

    There are a hundred ways to evaluate whether an investment is cheap–discounted cash flows, competitor multiples, mean reversion, multiple of projected earnings–the list goes on…and on. To each his own on what is the "best" valuation methodology, but suffice it to say that the persistent tug of our own behavioral biases suggests that objective measures (as opposed to subjective) are