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Quantocracy’s Daily Wrap for 05/31/2017

This is a summary of links featured on Quantocracy on Wednesday, 05/31/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Watch presentations from R/Finance 2017 [Revolutions]

    It was another great year for the R/Finance conference, held earlier this month in Chicago. This is normally a fairly private affair: with attendance capped at around 300 people every year, it's a somewhat exclusive gathering of the best and brightest minds from industry and academia in financial data analysis with R. But for the first time this year (and with thanks to sponsorship from
  • A single value to measure equity market correlation [Quant Bear]

    There exists a vast amount of studies that show an increase in correlation between global equity indices during bear markets and propose ways to measure/forecast this correlation (see for example Campbell, Koedjik and Kofman or Capiello, Engle and Sheppard, and many, many more). These studies differ greatly in their methodologies and complexities but they more or less all show the same significant
  • Can A Simple Market Timing Indicator Be Beat? [Alvarez Quant Trading]

    As long time readers of my blog know, I often use a market timing indicator in my strategies. My favorite one, and a simple one, is using the 200 day moving average on either the SPY or S&P 500 Index. I recently ran into these posts, Using Market Breadth To Gauge Market Health (Part 5) and Matts Breadth Indicator. Matts Breadth Indicator (MBI) intrigued me because I had not seen
  • Portfolio Rebalancing Research: Momentum and Tolerance Bands [Alpha Architect]

    If you are looking for research on stock selection, youre in luck the research is everywhere and has arguably been overdone. Get started with Moon Cycles & Stock Market Returns and The Congressional Calendar & Stock Market Returns to get a sense for how esoteric the research has gotten. Hundreds of these papers have been covered on the Alpha Architect blog and you could spend a
  • What are the Different Types of Quant Funds? [Quant Start]

    This is the third in a series of posts written by Frank Smietana, an expert guest contributor to QuantStart. In this detailed post Frank examines the different algorithmic trading strategies carried out by quantitative hedge funds. Click for parts one and two. – Mike. Institutional asset managers specialize in a particular asset class, style, sector, or geography, based on their expertise or
  • Why Bitcoin is the Ultimate Safe Haven Asset [Signal Plot]

    In 2008, in the middle of the global financial crisis, Satoshi Nakamoto published a white paper describing the bitcoin protocol. The bitcoin blockchain then came into existence on January 3, 2009 when Nakamoto created the genesis block the first block of the blockchain. All subsequent blocks contain data from the previous block as an input, thus forming an unbroken chain representing all
  • SPX Dips After Persistent Move To A New High What s the Next Move? [Quantifiable Edges]

    One compelling study that triggered tonight suggested the recent persistent upmove is unlikely to abruptly end. (This is a theme we have seen many times over the years.) It considers what happens after SPX moves up at least 5 days in a row to a 50-day high, and then pulls back. (This is the current setup.) 2017-05-31 We see here a decent edge that becomes stronger and more consistent as you look

Quantocracy’s Daily Wrap for 05/30/2017

This is a summary of links featured on Quantocracy on Tuesday, 05/30/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Beta Convexity [Jonathan Kinlay]

    Around a quarter of a century ago I wrote a paper entitled Equity Convexity which to my disappointment was rejected as incomprehensible by the finance professor who reviewed it. But perhaps I should not have expected more: novel theories are rarely well received first time around. I remain convinced the idea has merit and may perhaps revisit it in these pages at some point in future.
  • Get Fed Day Research & Tools While Helping Fight Multiple Sclerosis [Quantifiable Edges]

    Quantifiable Edges is now offering our Fed Day research and tools to anyone that makes any size donation to the MS Society! Keep reading for details. One bit of research that Quantifiable Edges has become known for are the many studies I have published on Fed Days. In fact, you could say I wrote the book on Fed Days. And the pdf version of that book sells for $25. But between now and June 24th I
  • Academic Research Insight: Factor Investing Over the Long Run [Alpha Architect]

    Title: FACTOR BASED INVESTING: THE LONG TERM EVIDENCE Authors: ELROY DIMSON, PAUL MARSH, AND MIKE STAUNTON Publication: THE JOURNAL OF PORTFOLIO MANAGEMENT, 2017, SPECIAL ISSUE (version here) What are the research questions? Is there out-of-sample (OOS) evidence for factor investing? What are the Academic Insights? By studying a data set including 23 countries and over a long time frame (1926 for

Quantocracy’s Daily Wrap for 05/29/2017

This is a summary of links featured on Quantocracy on Monday, 05/29/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Big Little Details [Flirting with Models]

    Limited attention drives us to focus on the big details of investment strategies. Small details can have an outsized impact on performance, especially if they can compound upon one another. To quote Aaron Brown, Head of Risk at AQR: It takes a lot of compounding to turn a mistake into a disaster. There will never be any shortage of mistakes []. So its the compounding you have to prevent,
  • Know what you don t know with data [Cuemacro]

    Lets say you had to identify a city youd never heard of on a map. Lets take a city chosen at random, Stockton and you wanted to identify which country it is in. You have with you a list of every single town in the world, alongside its country. A simple brute force way to find the country, is literally to go through every town on the list till you get to Stockton. You can obviously use

Quantocracy’s Daily Wrap for 05/28/2017

This is a summary of links featured on Quantocracy on Sunday, 05/28/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Evaluating Trading Strategies with Random Portfolios [Geodesic Edge]

    Active asset management has been under attack during the past several months. Hedge funds have been shutting down left and right, labeled as overpriced and underperforming, and are losing capital to low cost passive mutual funds and ETFs. Active mutual funds have been losing ground as well to their passive counterparts. Warren Buffet has even gone so far as to refer to hedge fund managers who have

Quantocracy’s Daily Wrap for 05/26/2017

This is a summary of links featured on Quantocracy on Friday, 05/26/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • March for the Fallen: Get Fit with Alpha Architect [Alpha Architect]

    As a former US Marine, Memorial Day is every day, however, Memorial Day is special because the time is set aside to reflect on those who paid the ultimate sacrifice. Enjoy and stay safe out there! In addition to enjoying the long Memorial Day weekend, we offer a unique opportunity to honor the fallen and hang with good people trying to do good things for society. One such event is March for the
  • Testing the Hierarchical Risk Parity algorithm [QuantStrat TradeR]

    This post will be a modified backtest of the Adaptive Asset Allocation backtest from AllocateSmartly, using the Hierarchical Risk Parity algorithm from last post, because Adam Butler was eager to see my results. On a whole, as Adam Butler had told me he had seen, HRP does not generate outperformance when applied to a small, carefully-constructed, diversified-by-selection universe of asset classes,
  • Research Review | 26 May 2017 | Smart Beta [Capital Spectator]

    How much higher can smart beta adoption climb? Now in its fourth year, FTSE Russells latest annual survey of global institutional asset owners indicates that smart beta adoption is at an all time high and that investors continue to find new applications for its use. The survey, Smart beta: 2017 global survey findings from asset owners, reveals that the percentage of asset owners reporting an
  • An Analysis of Momentum Behaviour in the Long-Term [Quantpedia]

    Motivated by behavioral theories, we test whether recent past performance of the momentum strategy (Past Momentum Performance–PMP) negatively predicts the performance of stale momentum portfolios. Following periods of top-quintile PMP, momentum portfolios exhibit strong reversals 2-5 years after formation, whereas, following periods of bottom-quintile PMP, stale momentum portfolios earn positive

Quantocracy’s Daily Wrap for 05/25/2017

This is a summary of links featured on Quantocracy on Thursday, 05/25/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Vix Spx Seasonality By Month, Even Keel [Voodoo Markets]

    While seeing some sell in may headlines a while ago, thought id pull up the monthly mean returns for spx and vix. I wanted to see them on an even keel, so that each month starts at 0%, to better gauge their monthly behaviour 1 2 3 4 5 6 7 8 9 import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns import quandl import calendar %matplotlib inline
  • Yes. Demographics and Economic Growth Matter for Equity Returns [EconomPic]

    Quick note… for those not already listening, my buddy Patrick OShaughnessy has one of the (if not the) best investing podcasts out there with his podcast Invest Like the Best. Each week he sits down with some of the best capital allocators, investment thinkers, etc… in the world and really allows his guests to share deep insights. I highly recommend it to anyone reading this who isn't

Quantocracy’s Daily Wrap for 05/24/2017

This is a summary of links featured on Quantocracy on Wednesday, 05/24/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How Many Assets Are Needed To Test a K-Factor Model? [Alex Chinco]

    Imagine youre a financial economist who thinks that some risk factor,{\color{white}i}f_t, explains the cross-section of expected returns. And, you decide to test your hunch. First, you regress the realized returns of N different assets on{\color{white}i}f_t to estimate each assets exposure to the risk factor, \tilde{b}_n: \begin{equation*} r_{n,t} = \tilde{a}_n + \tilde{b}_n \cdot f_t +
  • The Value Premium: Risk or Mispricing? [Alpha Architect]

    One of the great debates in finance is whether the source of the value premium is risk-based or a behavioral anomaly. In our book, Your Complete Guide to Factor-Based Investing, my co-author Andrew Berkin and I present the evidence showing that there are good arguments on both sides. Thus, its likely the answer isnt black or white. For example, we show that the academic research

Quantocracy’s Daily Wrap for 05/23/2017

This is a summary of links featured on Quantocracy on Tuesday, 05/23/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Case for Tactical Alpha, Part 3: The Greatest Trick Wall Street Ever Pulled [Invest Resolve]

    The investment industry has investors convinced that the only path to better performance is through stock selection. As a result, most investors approach the challenges of portfolio construction exactly backward and miss out on the most important opportunities to produce differentiated performance. The purpose of this series is to challenge the conventions that lead to misguided asset allocation
  • Academic Research Insight: The Social Media Factor [Alpha Architect]

    are to Editors Note: The Academic Research Insight will be a weekly short-form research summary on research that is directly related to investing. Elisabetta Basilico (a PhD and a CFA!) will be driving the effort, which will supplement our long-form summaries, in-house research, and general research commentary. We look forward to empowering investors through education! Title: THE SIXTH
  • An Example of Python Trading Strategy in Quantiacs Platform [Quant Insti]

    Algorithmic trading has seen great traction in recent years and the numbers of students, engineering graduates, and finance professionals looking to explore this lucrative domain has been growing exponentially with each passing year. Are you among the ones looking to learn quant skills and also make money with your trading ideas? Let us explore the Quantiacs platform which allows one to create,

Quantocracy’s Daily Wrap for 05/22/2017

This is a summary of links featured on Quantocracy on Monday, 05/22/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Rough Path Theory and Signatures Applied To Quantitative Finance – Part 2 [Quant Start]

    his is the second in a new advanced series of posts written by Imanol Prez, a PhD researcher in Mathematics at Oxford University, and a new expert guest contributor to QuantStart. In this post Imanol continues the theoretical discussion of Rough Paths and Signatures and begins applying them within a machine learning framework, utilising scikit-learn. – Mike. In the last article the signature of
  • The time has come: setting up a DB with MySQL and R [Quant Bear]

    The recent decision by Yahoo to screw with their API for financial data (and in the process disabling all packages/functions in various programing languages obtaining EOD (end-of-day) data, at least temporarily) shows us two important things: Nothing is free and reliable forever Its a good idea to have a database set up So for everyone in the why do i need a DB/I dont know how to set it
  • The Marcos Lopez de Prado Hierarchical Risk Parity Algorithm [QuantStrat TradeR]

    This post will be about replicating the Marcos Lopez de Prado algorithm from his paper building diversified portfolios that outperform out of sample. This algorithm is one that attempts to make a tradeoff between the classic mean-variance optimization algorithm that takes into account a covariance structure, but is unstable, and an inverse volatility algorithm that ignores covariance, but is more
  • Can We Improve Sector Rotation? [Flirting with Models]

    Momentum-based sector rotation is a popular investment strategy. Recent academic studies have shown that alternative implementations of standard momentum including risk-adjusted momentum, residual momentum, and frog-in-the-pan momentum can significantly improve the risk-adjusted and total return potential of stock-based momentum systems. We explore whether these approaches create

Quantocracy’s Daily Wrap for 05/20/2017

This is a summary of links featured on Quantocracy on Saturday, 05/20/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How to Scrape and Parse 600 ETF Options in 10 mins with Python and Asyncio [Black Arbs]

    This is Part 1 of a new series I'm doing in semi real-time to build a functional options data dashboard using Python. There are many underlying motivations to attempt this, and several challenges to implementing a tool like this from scratch. Where to get the data? Is it affordable? Easily accessible? API? How to parse the results? How to aggregate and organize the data for analysis? How to
  • Solved: Errors Downloading Stock Price Data from Yahoo Finance [Robot Wealth]

    Recently, Yahoo Finance a popular source of free end-of-day price data made some changes to their server which wreaked a little havoc on anyone relying on it for their algos or simulations. Specifically, Yahoo Finance switched from HTTP to HTTPS and changed the data download URLs. No doubt this is a huge source of frustration, as many backtesting and trading scripts that relied on such
  • Yahoo is dead, long live Yahoo! [Trading with Python]

    On 18 May 2017 the ichart data api of yahoo finance went down, without any notice. And it does not seem like it is coming back. This has left many (including me) with broken code and without a descent free end-of-day data source. Something needs to be done. Now. Apparently Yahoo! does not want us to download free data automatically, but it is still possible to download it by hand, clicking the
  • An Example of Trading Model Design by Richard Olsen (Founder of @OANDA) [Quantpedia]

    We introduce a new approach to algorithmic investment management that yields profitable automated trading strategies. This trading model design is the result of a path of investigation that was chosen nearly three decades ago. Back then, a paradigm change was proposed for the way time is defined in financial markets, based on intrinsic events. This definition lead to the uncovering of a large set