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Quantocracy’s Daily Wrap for 12/24/2018

This is a summary of links featured on Quantocracy on Monday, 12/24/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Asset Allocation Roundup [Allocate Smartly]

    Six recent asset allocation articles (tactical or otherwise) that you might have missed: 1. Trend Following on Steroids (Wouter Keller via Alpha Architect) Wouter Keller details his latest tactical model: Defensive Asset Allocation. We track a number of strategies from Dr. Keller and his partner-in-quant JW Keuning (including this one). Its worth noting that their strategies are, overall,
  • Dart-Throwing Monkeys and Process Diversification [Flirting with Models]

    This weeks commentary is a short addendum to last weeks piece, attempting to serve as a (very) brief and simplified summary of process diversification. Volatility is only one way of measuring risk; dispersion in terminal wealth is another. Using simulations of dart-throwing monkeys, we plot the dispersion in terminal wealth for different levels of portfolio and manager diversification. We
  • Research Compendium 2018 [Factor Research]

    In 2018 we published more than 50 research notes and 4 white papers on mainly factor investing, but also on other topics like zombie stocks, replicating private equity returns, statistical arbitrage, and mutual fund performance chasing. We would like to thank you for reading and always appreciate feedback, especially if critical. The Research Compendium 2018 contains all of our research published

Quantocracy’s Daily Wrap for 12/23/2018

This is a summary of links featured on Quantocracy on Sunday, 12/23/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Hundreds of quant papers/libraries from #QuantLinkADay in 2018 [Cuemacro]

    I tweet quite a bit! It can involve random subjects such as burgers. However, the main objective of my Twitter account is to tweet about all thinks quant related, whether its trading strategies or the market or coding (in particular Python). To make sure I actually did this, several years ago, I started my #QuantLinkADay daily tweets, where I post at least one daily link to something quant
  • The little girl study and the horrid Crash of 87 [Quantifiable Edges]

    Every once in a while I come across a study that reminds me an awful lot of Longfellows The little girl. 2018-12-23-2 After the strong and persistent selling over the last few days I decided to examine other times like now where the SPX dropped at least 1.5% for 3 days in a row. The study below looks back to late 1987 and shows all 10 occurrences over the time period, along with their

Quantocracy’s Daily Wrap for 12/22/2018

This is a summary of links featured on Quantocracy on Saturday, 12/22/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Bear is Here [Quintuitive]

    October and December have been devastating for stocks. It wasnt until Friday though that we officially reached the depths of a bear market. There are different theories, the most common is 20% pullback in an index. As readers of this blog are aware, I follow a slightly different definition, based on Jack Schanneps work. Based on this definition, a bear market is official when two of the
  • The macro information inefficiency of financial markets [SR SV]

    There are reason and evidence for financial markets failing to be efficient with respect to macro trends. The main reason is cost: tradable economic research is expensive and investment firms will only invest in such research if their fees on expected incremental portfolio returns exceed their expenses. This requires them to concentrate scarce research budgets on areas where they see

Quantocracy’s Daily Wrap for 12/21/2018

This is a summary of links featured on Quantocracy on Friday, 12/21/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • ReSolve 12 Days of Christmas [Invest ReSolve]

    This holiday season, ReSolve is offering a gift in podcast-form: a 12-episode mini-series, where we will explore, from first principles, timeless investment wisdom that will help you maximize your long-term success. From universe selection to portfolio construction, our aim is to offer you a comprehensive framework for a more thoughtful investment approach, for yourselves and your clients.
  • Machine Learning Classification Methods and Factor Investing [Alpha Architect]

    In the last post in our machine learning series, we showed how nonlinear regression algos might improve regression forecasting relative to plain vanilla linear regression (i.e., when underlying reality is nonlinear with complex interactions). In this piece, well first review machine learning for classification, a problem which may be less familiar to investors, but fundamental to machine

Quantocracy’s Daily Wrap for 12/20/2018

This is a summary of links featured on Quantocracy on Thursday, 12/20/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Position Sizing for Practitioners Part 3: A Portfolio Approach [Quant Fiction]

    Diversification is the Only Free Lunch Im sure everyone has heard this old adage at some point in their trading career. Most people probably shrug it off and go back to watching The Big Short and dreaming of putting on that one career-making trade. Or maybe theyre still trying to figure out how to pick every single top and bottom on one instrument, thinking all they need is that one
  • What to do when you find the Holy Grail [Alvarez Quant Trading]

    As I have mentioned in several interviews, I am always looking for new strategies. One area that fascinates me is stock options. Because it is difficult to get good data and to do backtests, I believe that there are good edges here to be found. A few weeks ago, I found myself with lots of time and having read presentations on options, I went into a testing frenzy. After lots of work, I found a

Quantocracy’s Daily Wrap for 12/19/2018

This is a summary of links featured on Quantocracy on Wednesday, 12/19/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Cash or Bonds at Low Yields and a Flat Yield Curve? [EconomPic]

    While there have been a few cyclical periods of rising rates over the past 40 years, we've largely been in one large downtrend… meaning that it has consistently paid to own bonds vs cash / take duration risk for nearly my / many investment lives. Now that we've moved away from a zero interest rate policy on cash in the U.S. and the yield curve is essentially flat, this post is an
  • Algorithmic Trading Regulations – European Union [Quant Insti]

    A game of cat and mouse. Technological development more often than not stays ahead of regulators. Each new technological advance or disruption carries risks for the stability of things and advantages for those who are at the forefront. Regulators try to set rules and good practices that limit possible abuses and bring transparency to the participants. In this post, we will review the European
  • Data Science is Revolutionizing Investment Practice [Alpha Architect]

    What are the Research Questions? This editorial introduces data science to the wider investment community and highlights some of the advantages (and potential pitfalls as discussed yesterday) it can bring to everyday investment practice. The paper answers two apparently simple questions: What is data science? How can data science help advance investing practice? What are the Academic Insights?

Quantocracy’s Daily Wrap for 12/18/2018

This is a summary of links featured on Quantocracy on Tuesday, 12/18/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Overlooked Half of the Global Stock Market [Quant Rocket]

    The US stock market is the largest and most liquid stock market in the world and tends to get all the attention. Many brokers and trading platforms are US-only, and many traders focus exclusively on the US market. This post compares the number of stock listings in each of 17 countries to quantify what traders miss out on by ignoring the rest of the world. The Countries I compare 17 countries which

Quantocracy’s Daily Wrap for 12/17/2018

This is a summary of links featured on Quantocracy on Monday, 12/17/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • What do portfolios and teacups have in common? [Flirting with Models]

    Portfolio risk is often measured as the variance of returns over time. Another form of risk is the variance of terminal wealth that can arise from small variations in strategy inputs or asset returns. Strategies or portfolios that are more sensitive to small changes in inputs are inherently fragile. Fragile strategy design makes it difficult to rely upon backtests or historical results in
  • Factor Investing Made In China [Factor Research]

    This research note was originally published by the CAIA Associations AllAboutAlpha blog. Here is the link. SUMMARY Common equity factors generated attractive risk-adjusted returns in the Chinese stock market Factor performance in China often mirrors global factor performance Indicates common factor drivers that permeate even emerging and isolated markets INTRODUCTION Economic news like changes
  • A Protocol to Prevent “Quants Gone Wild” [Alpha Architect]

    What are the Research Questions? Data mining in finance has long been a concern for academic researchers. Campbell Harvey, one of the authors on this paper, is leading the effort to ensure the integrity of empirical finance research. For example, see here for a post on his address to the AFA. The concerns associated with data mining arent going away. A monster increase in affordable computing
  • Weekly Recap: Value Performance & ETFs’ impact on correlations & liquidity [Alpha Architect]

    This week Ryan and I discuss two posts. First, we examine a guest post by Matthew Bartolini of State Street Global Advisors, discussing the underperformance of Value and its outlook for 2019. Second, we examine a guest post by Elisabetta on a recent JPM paper examining the effects that ETFs have had on Correlations, Liquidity, and Alpha Opportunities. Paper Links: After a Lost Decade, Will Value

Quantocracy’s Daily Wrap for 12/15/2018

This is a summary of links featured on Quantocracy on Saturday, 12/15/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Modern backtesting with integrity [SR SV]

    Machine learning offers powerful tools for backtesting trading strategies. However, its computational power and convenience can also be corrosive for financial investment due to its tendency to find temporary patterns while data samples for cross validation are limited. Machine learning produces valid backtests only when applied with sound principles. These should include [1] formulating a logical

Quantocracy’s Daily Wrap for 12/14/2018

This is a summary of links featured on Quantocracy on Friday, 12/14/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Portfolio construction through handcrafting: implementation [Investment Idiocy]

    This post is all about handcrafting; a method for doing portfolio construction which human beings can do without computing power, or at least with a spreadsheet. The method aims to achieve the following goals: Humans can trust it: intuitive and transparent method which produces robust weights Can be easily implemented by a human in a spreadsheet Can be back tested Grounded in solid theoretical
  • The Most Wonderful Week of the Year 2018 edition [Quantifiable Edges]

    Over several time horizons op-ex week in December has been the most bullish week of the year for the SPX. The positive seasonality actually has persisted for up to 3 weeks. Ive shown the study below in the blog many times since 2008. It looks back to 1984, which was the first year that SPX options traded. The table is updated again this year. 2018-12-14-1 The stats are extremely strong. This
  • Estimating the Bid-Ask Spread [Dekalog Blog]

    Below I provide a vectorised Octave function to estimate the bid-ask spread from high, low and close prices according to "A Simple Way to Estimate Bid-Ask Spreads from Daily High and Low Prices," (Corwin and Schultz, 2012). The paper can be downloaded from one of the author's homepage at https://www3.nd.edu/~scorwin/, where one can also find a spreadsheet which shows the
  • Random Walk Simulation Of Stock Prices Using Geometric Brownian Motion [Quant Insti]

    In this blog on random walk simulation, we will learn how to simulate stock prices. Future stock prices are very hard to predict and are dependent on the past trend and volatility. While simulating the stock prices one has to give reasonable weightage to these two parameters. The random walk model helps incorporate these two features of a stock and simulate the stock prices in a very clear and
  • Does the Sunspot Cycle Predict Grain Prices? [CXO Advisory]

    As a follow-up to Sunspot Cycle and Stock Market Returns a reader asked: Sunspot activity does have a direct relationship to weather. Could one speculate on the agriculture market using the sunspot cycle? To investigate, we relate sunspot activity to the fairly long U.S. Producer Price Index (PPI) for grains. Using monthly averages of daily sunspot counts and monthly PPI for grains
  • Sunspot Cycle and Stock Market Returns [CXO Advisory]

    A reader asked whether Charles Nenner, self-described as the talk of Wall Street since accurately predicting some of the biggest moves in the Markets over the past few years, accurately forecasts equity and commodity markets. We consider the following: In his July 2007 discussion of the Nenner Methodology at the Bloomberg Studio, Charles Nenner cites sunspot activity as a specific key