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Quantocracy’s Daily Wrap for 06/21/2018

This is a summary of links featured on Quantocracy on Thursday, 06/21/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • CAPE of Good Hope? P/E Divergence as a Performance Signal [EconomPic]

    Lawrence Hamtil recently shared a Vanguard paper with me that was surprising given it indicated the trailing twelve month price-to-earnings ratio "TTM P/E" was nearly as strong a predictor of forward 10-year equity returns as the cyclically adjusted price-to-earnings "CAPE" ratio going back to 1926. My assumption had been that the CAPE ratio (which uses smoothed 10-year real

Quantocracy’s Daily Wrap for 06/20/2018

This is a summary of links featured on Quantocracy on Wednesday, 06/20/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Curse of dimensionality part 3: Higher-Order Comoments [Eran Raviv]

    Higher moments such as Skewness and Kurtosis are not as explored as they should be. These moments are crucial for managing portfolio risk. At least as important as volatility, if not more. Skewness relates to asymmetry risk and Kurtosis relates to tail risk. Despite their great importance, those higher moments enjoy only a small portion of attention compared with their lower more friendly moments:

Quantocracy’s Daily Wrap for 06/19/2018

This is a summary of links featured on Quantocracy on Tuesday, 06/19/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • A Simple Momentum Strategy [Jonathan Kinlay]

    Momentum trading strategies span a diverse range of trading ideas. Often they will use indicators to determine the recent underlying trend and try to gauge the strength of the trend using measures of the rate of change in the price of the asset. One very simple momentum concept, a strategy in S&P500 E-Mini futures, is described in the following blog post: The basic idea is to buy the
  • Are Currently Used Significance Levels for Investment Strategies Too Strict? [Quantpedia]

    Most papers in the financial literature estimate the p-value associated with an investment strategy, without reporting the power of the test used to make that discovery. This is a mistake, because a particularly low false positive rate (Type I error) may be achieved at the expense of missing a large proportion of the investment opportunities (Type II error). In this paper we provide analytic

Quantocracy’s Daily Wrap for 06/18/2018

This is a summary of links featured on Quantocracy on Monday, 06/18/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • My R Book On Portfolio Analytics Has Been Published [Capital Spectator]

    Quantitative Investment Portfolio Analytics In R: An Introduction To R For Modeling Portfolio Risk and Return rolled off the presses earlier today for the first time. The book is currently available as a softback title. Stay tuned for details on an upcoming Kindle version. Meantime, after nearly four years of writing in my spare time, Im thrilled (and relieved) to announce that my third
  • Sector vs Country Momentum [Factor Research]

    The Momentum strategy can be applied to stocks, sectors and countries Sector and country Momentum portfolios generate positive excess returns However, cross sector & country and single stock Momentum portfolios generate higher risk-return ratios INTRODUCTION When a graduate joins the M&A division of an investment bank in Europe he or she often has to decide between a country or sector
  • A Smarter CAPE Ratio to Better Forecast Expected Stock Returns [Alpha Architect]

    What are the research questions? The authors propose and test an enhanced Shiller model that incorporates macroeconomic conditions, by modeling real bond yields and volatility, equity volatility and inflation, in a 2 step approach to forecasting equity returns. The underlying thesis is that the level of mean reversion in the CAPE ratio varies with the state of the economy and is not a fixed
  • Inferring the Statistics of Buffett’s Alpha [Flirting with Models]

    Buffetts alpha over the past 38 years has been an astounding 10% annualized, making him a prime example of investment discipline and skill. Through a statistical lens, the probability of having a track record this solid is extremely small. However, given enough investors mimicking Buffetts style, one should emerge with a track record close to Buffetts. Unfortunately, real world
  • Weak Week After June Opex [Quantifiable Edges]

    I noted a few years ago here on the blog that the week after June options expiration has done especially poorly in recent years. The table below is updated and shows all such weeks dating back to 1999. 2018-06-18 Those are some pretty weak numbers. Below is a 5-day profit curve. 2018-06-18-2 As you can see, it has been quite a streak of bearishness. Twelve out of the last fourteen years have

Quantocracy’s Daily Wrap for 06/16/2018

This is a summary of links featured on Quantocracy on Saturday, 06/16/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • FX carry strategies (part 2): Hedging [SR SV]

    There is often a strong case for hedging FX carry trades against unrelated global market factors. It is usually not difficult to hedge currency positions at least partly against global directional risk and against moves in the EURUSD exchange rate. The benefits of these hedges are [1] more idiosyncratic and diversifiable currency trades and, [2] a more realistic assessment of the actual

Quantocracy’s Daily Wrap for 06/15/2018

This is a summary of links featured on Quantocracy on Friday, 06/15/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Download Intraday Stock Data with IEX and Parquet [Black Arbs]

    IEX is a relatively new exchange (founded in 2012). For our purposes, what makes them different from other exchanges is they provide a robust FREE API to query their stock exchange data. As a result we can leverage the pandas-datareader framework to query IEX data quite simply. WHY PARQUET? Apache Parquet is a columnar storage format available to any project in the Hadoop ecosystem, regardless
  • Are Investors Becoming Better at Fund Picking? [Quantpedia]

    This study analyzes how the determinants of mutual fund investor cash flows have changed over time, and the associated impact on investor returns. Using data from 1992-2016 we find that investor return-chasing behavior essentially disappeared starting in 2011. Investor flows have become more sensitive to expenses, past risk and alpha. Investors are paying more attention to fund characteristics

Quantocracy’s Daily Wrap for 06/14/2018

This is a summary of links featured on Quantocracy on Thursday, 06/14/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • False Promises: Going Passive is Not Momentum Investing [Factor Investor]

    There is some popular marketing spin going around that indexingconstructing portfolios based on market-cap weightsis effective because it allows an investor to own more of companies that have been successful and appreciated, while moving away from losers that have been unsuccessful and declined. This sounds logical, but it is empirically wrong. The strategy suggested above is tantamount to a
  • The 52 Week High and the Q-Factor Investment Model [Alpha Architect]

    In the past, we have examined the following two topics: (1) stock performance & the 52-week high and (2) the investment CAPM. When examining the performance of stocks relative to their respective 52-week high (highlighted by us here), the authors (George and Hwang) find the following: When coupled with a stocks current price, a readily available piece of informationthe 52-week high
  • A New Book For Portfolio Analysis Using R [Capital Spectator]

    Later this month Ill be publishing my third book: Quantitative Investment Portfolio Analytics In R: An Introduction To R For Modeling Portfolio Risk and Return. Although there are already many R books on the market, this one serves a particular niche: a short guide for recovering Excel addicts running relatively sophisticated analytics on investment portfolios and bumping up against the limits
  • State of Trend Following in May [Au Tra Sy]

    Positive May return for the State of Trend Following, with a YTD performance slightly negative. Please check below for more details. Detailed Results The figures for the month are: May return: 1.48% YTD return: -2.38% Below is the chart displaying individual system results throughout May: StateTF May And in tabular format: System May Return YTD Return BBO-20 4% 13.65% Donchian-20 5.88% 16.98%

Quantocracy’s Daily Wrap for 06/13/2018

This is a summary of links featured on Quantocracy on Wednesday, 06/13/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Help Fight MS and Receive Research & More From Quantifiable Edges [Quantifiable Edges]

    Last year Quantifiable Edges readers helped me raise over $4000 for Multiple Sclerosis (MS), and this year I am upping the incentive for people to donate! I am happy for any size donation, but I have created 2 donation levels this year so that people are incented to give more: Thank You Level: One bit of research that Quantifiable Edges has become known for are the many studies I have published on
  • RSI2 (Relative Strength Index) Analysis [Alvarez Quant Trading]

    From my time with working with Larry Connors, I have become known for using the 2-Period RSI (RSI2) (Relative Strength Index) in my trading. I have written lots of blog posts that use it and I often use it in my personal strategies. One thing I like to do with indicators that I use frequently is a thorough analysis of them. Often, I find characteristics that I did not expect. Do you know about the
  • Hedge Fund Return Predictability [Rayner Gobran]

    This is the sixth in my Hedge Fund Hacks series. In this post, I hammer home how little we know about the expected returns of a hedge fund or a managed futures strategy because we have so little data. You will learn just how large the uncertainty is and what you can do about it. Glimpses Through the Fog I remember hiking with my wife in North Wales in the Spring of 2003. Wales tends to be cloudy
  • New video explains the danger of selection bias in finance [Mathematical Investor]

    A new video has been produced by the Mathematicians Against Fraudulent Financial and Investment Advice (MAFFIA) group. It explains, in simple terms, how many of the financial strategies and funds available today are based on a statistically dubious foundation, typically rooted in selection bias effects, because the finance world, unlike other fields such as the pharmaceutical industry, has not yet

Quantocracy’s Daily Wrap for 06/12/2018

This is a summary of links featured on Quantocracy on Tuesday, 06/12/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Fun with the Cryptocompare API [Robot Wealth]

    Cryptocompare is a platform providing data and insights on pretty much everything in the crypto-sphere, from market data for cryptocurrencies to comparisons of the various crytpo-exchanges, to recommendations for where to spend your crypto assets. The user-experience is quite pleasant, as you can see from the screenshot of their real-time coin comparison table: cryptcurrency prices As nice as the
  • Labeling and Meta-Labeling Returns for ML Prediction [Black Arbs]

    This post focuses on Chapter 3 in the new book Advances in Financial Machine Learning by Marcos Lopez De Prado. In this chapter De Prado demonstrates a workflow for improved return labeling for the purposes of supervised classification models. He introduces multiple concepts but focuses on the Triple-Barrier Labeling method, which incorporates profit-taking, stop-loss, and holding period
  • Estimating the Hurst Exponent Using R/S Range [Flare 9x]

    In this post we will estimate the Hurst exponent using the R/S method. The Hurst exponent determines the long range memory of a time series (more below). If a series has no memory ie if each point in time is independent from previous points in time then its said to be more of a random process. Examples of random processes are markov processes, Brownian motion and white noise. A series which trends

Quantocracy’s Daily Wrap for 06/11/2018

This is a summary of links featured on Quantocracy on Monday, 06/11/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Commodities for the Long Run [Alpha Architect]

    The paper investigates this issue by answering the following research questions: Are commodities returns positive on average? How do they vary in different economic states (backwardation/contango; expansion/recession periods; unexpected inflation) ? How have they contributed to a broad portfolio? What are the Academic Insights? By studying a novel dataset consisting of daily futures prices going
  • Better Returns From Seasonal Investing In The S&P 500 (1950-2018) [iMarketSignals]

    From 1950 to 2018 the S&P 500 performed best from November to April, and significantly worse from May to October during most years. From 1950-2018 the real annualized return for the S&P 500 was 6.71%. Had one only invested from November to April each year the return would have been 6.60%, almost the same. Investing in a money-market fund from May to October each year and the remaining time
  • The Siren of Statistics [Highly Evolved Vol]

    A siren was a mythological being who lured sailors with their enchanting music to shipwreck on the rocky coasts of their island. Their songs were almost impossible to resist. But more generally a siren is a bad thing that we are attracted to, either physically or psychologically. For investors, an example of a sirens song is simplicity. Many investors are prone to looking for just a few
  • Factor Fimbulwinter [Flirting with Models]

    Value investing continues to experience a trough of sorrow. In particular, the traditional price-to-book factor has failed to establish new highs since December 2006 and sits in a 25% drawdown. While price-to-book has been the academic measure of choice for 25+ years, many practitioners have begun to question its value (pun intended). We have also witnessed the turning of the tides against the
  • Skewness as a Factor [Factor Research]

    Skewness is a feature of stocks with high firm-risks Stocks with positive or negative skewness outperform the market Can partially be explained by the Size factor INTRODUCTION Many investors started their investment career at an early age, typically buying a stock that showed an enticing performance chart, was featured somewhere or recommended by a family member. Moving to a professional