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Quantocracy’s Daily Wrap for 10/31/2017

This is a summary of links featured on Quantocracy on Tuesday, 10/31/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Do Portfolio Factors or Characteristics Drive Expected Returns? [Alpha Architect]

    This article examines a somewhat over-looked, but important, discussion that raged among academic researchers in the late 1990s and early 2000s. The topic: factors versus characteristics. What do you mean, Factors versus characteristics? We often highlight that the value premium can be explained by either risk and/or mispricing. A core aspect of the risk argument is that a
  • Trading Using Decision Tree Classifier Part 1 [Quant Insti]

    The strategy in this blog will cover no normal technical indicators, but some of my own creation. Also, we will see the difference between strategy performance on test and train data along with respect to the changes in the size of the train data and the prediction length. Unlike in my previous blogs, in here I will use a dynamic time frame to fetch data for the past few days. But before we begin,

Quantocracy’s Daily Wrap for 10/30/2017

This is a summary of links featured on Quantocracy on Monday, 10/30/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Alternative Data: The Next Frontier of Quant? [Flirting with Models]

    The world is awash with new data. Satellite imagery, shipping manifests, agricultural sensors, and more can provide untapped insights. To understand how investors might benefit, we decompose investment strategies into three pieces: systematic rules, idiosyncratic decisions, and randomness. We explore how new and unique data might help investors enhance decision making in each of these categories.
  • Resist the Siren Call of High Dividend Yields [Factor Research]

    Buying high yielding and selling low yielding stocks has been an attractive strategy since 2000 However, it has been a highly unattractive strategy over the last century Investors should resist the Siren call of high yielding stocks and focus on other factors INTRODUCTION The search for yield has led investors and savers to consider quite adventurous investments in recent years. One contender for
  • Launching My Subscription Service [QuantStrat TradeR]

    After gauging interest from my readers, Ive decided to open up a subscription service. Ill copy and paste the FAQs, or my best attempt at trying to answer as many questions as possible ahead of time, and may answer more in the future. Im choosing to use Patreon just to outsource all of the technicalities of handling subscriptions and creating a centralized source to post
  • Information In Volatility Structure [Tr8dr]

    In the prior post Information In Volatility Structure [1] applied the SABR model to fit noisy raw option price data of approximatelty 700 million prices across a 10 year history of 2700 stocks. The point was to examine a hypothesis: does supply / demand imbalance in the options market express in terms of abnormal vol skew? can abnormal vol skew point to forward market behavior? First Application I
  • Broken Wing Butterfly Price and Volatility – CDN [DTR Trading]

    In the last two posts (here, and here), we looked at how implied volatility (IV) and price of the option strikes in two broken wing butterfly (BWB) strategies changed with time. In this post, we'll look at another BWB strategy, the centered delta neutral (CDN) BWB. In this strategy, the short put options are at-the-money (ATM), the lower long is at least 100 points below the market, and the
  • Autumn Readings about Factor Investing [Quantpedia]

    Factor returns, net of changes in valuation levels, are much lower than recent performance suggests. Value-add can be structural, and thus reliably repeatable, or situationala product of rising valuationslikely neither sustainable nor repeatable. Many investors are performance chasers who in pushing prices higher create valuation levels that inflate past performance, reduce potential future
  • Academic Research Insight: Sin Stocks May Earn a “Boycott” Risk Premium [Alpha Architect]

    In this study, a two-factor risk model is developed assuming differing preferences for sin or no-sin stocks for two groups of investors. Social screens are built into the model by assuming a small percentage of investors are self-restricting, declining to invest in sin stocks. Since each group of investors is facing a different set of investment opportunities, the derivation of a
  • Podcast: Building Mean Reversion trading strategies with @AlvarezQuant – Part 2 [Better System Trader]

    And were back for the 2nd episode in this 3-part series on building Mean Reversion strategies with Cesar Alvarez from Alvarez Quant Trading. In the first episode we discussed the goal of Mean Reversion trading, how to select a trading universe, a number of effective techniques to measuring Mean Reversion and how to combine indicators to identify better quality trades. If you havent listened

Quantocracy’s Daily Wrap for 10/27/2017

This is a summary of links featured on Quantocracy on Friday, 10/27/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • HillClimber.ai: A New Machine Learning Mashup from Long-Time Quantocracy Contributor @JacquesQuant

    HillClimber.ai is a curated machine learning mashup inspired by the quantitative finance blog aggregator Quantocracy. A special shout-out to Mike for all the help he provided in setting up this website. This mashup is very new and I would welcome all feedback from the community. There are many good blogs that I am sure to have missed. To request a blog / feed please send an email to
  • Replicating Indexes In R With Style Analysis (Part II): Global Macro [Capital Spectator]

    Imitation, Oscar Wilde famously observed, is the sincerest form of flattery that mediocrity can pay to greatness. The observation echoes the objective for using Professor Bill Sharpes style analysis to replicate investment indexes that, for one reason or another, cant be purchased directly. If we can obtain an indexs returns, theres a pretty good chance that we can reverse
  • Updating Historical Data Using Oanda’s API and R [Dekalog Blog]

    Following on from my previous post about downloading historical data, this post shows how previously downloaded data may be updated and appended with new, more recent data without having to re-download all the old data all over again. The main function to do this, HisPricesDates, downloads data between given dates as function inputs and is shown below. HisPricesDates = function( Granularity,

Quantocracy’s Daily Wrap for 10/26/2017

This is a summary of links featured on Quantocracy on Thursday, 10/26/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Want to Learn More About Factor Investing? Read This. [Alpha Architect]

    Replicating Anomalies is arguably a must read for anyone who thinks about factor investing and is looking to improve their understanding of the space. Lu Zhang, and his colleagues, Kewei Hou and Chen Xue, spent nearly 3 years carefully compiling and replicating 447 anomalies identified in the academic literature Thats a lot of programming and late nights burning the midnight oil
  • How universities are failing finance students [Mathematical Investor]

    One of us (Marcos Lopez de Prado) has been interviewed on the topic of educational training in the finance field by Institutional Investor. A brief synopsis of this interview is below. The full article is HERE. How Universities Are Failing Finance Students With investment shops fighting over mathematicians and engineers, a Guggenheim executive argues that finance degrees and departments face
  • Takeaways from a Non-PHD who Powered Through a 144-page Factor Investing Paper [Alpha Architect]

    Wes recently challenged me with a unique proposition: Hey Ryan, read through this Replicating Anomalies paper and tell me what you think. Its a bit long, but Im curious to hear your thoughts. Well, by a bit long, Wes really meant 144 pages of equations and reams of quantitative data on various factor analysis. Regardless, I jumped on the challenge grenade and decided to share a few

Quantocracy’s Daily Wrap for 10/25/2017

This is a summary of links featured on Quantocracy on Wednesday, 10/25/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Meta Strategy: A Smart Approach to Combining TAA Strategies [Allocate Smartly]

    Were very excited for the launch of an awesome new feature for our members: Meta Strategy. We track a wide range of published tactical asset allocation strategies in near real-time (40 and counting), which members can then combine into their own custom portfolios. Our platform helps members better understand how each strategy fits into a coherent trading plan, but weve never given members
  • ReSolve’s Buffett Bet Portfolio Based on Risk Parity and Factors [Invest Resolve]

    Note: This is not an official bet. Were not interested in documenting all the potential details that would be involved, and we dont have $1million to wager. Moreover, licensed firms are not allowed to make public fund recommendations, so the details of an official bet would have to be private and that wont work for our purposes. Were interested in taking a stand on how investors should
  • Are Equity Multifactor ETFs Working? [CXO Advisory]

    Are equity multifactor strategies, as implemented by exchange-traded funds (ETF), attractive? To investigate, we consider seven ETFs, all currently available (in order of decreasing assets): Goldman Sachs ActiveBeta U.S. Large Cap Equity (GSLC) holds large U.S. stocks based on good value, strong momentum, high quality and low volatility. iShares Edge MSCI Multifactor USA (LRGF) holds large

Quantocracy’s Daily Wrap for 10/24/2017

This is a summary of links featured on Quantocracy on Tuesday, 10/24/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Return of Free Data and Possible Volatility Trading Subscription [QuantStrat TradeR]

    This post will be about pulling free data from AlphaVantage, and gauging interest for a volatility trading subscription service. So first off, ever since the yahoos at Yahoo decided to turn off their free data, the world of free daily data has been in somewhat of a dark age. Well, thanks to http://blog.fosstrading.com/2017/10/getsymbols-and-alpha-vantage.html#gpluscommentsJosh Ulrich, Paul Teetor,
  • Stick to the Fundamentals and Discover Your Industry Peers [Alpha Architect]

    When performing multiple-based valuations, which rely on the assumption that perfect substitutes should sell for the same price, it is very important to identify companies that are truly comparable. Most analysts use industry classifications. Lee et al. (2015) note that industry classifications are at best crude guidelines for identifying comparable companies. Knudsen et al. study an alternate

Quantocracy’s Daily Wrap for 10/23/2017

This is a summary of links featured on Quantocracy on Monday, 10/23/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Would You Invest in A Coin Flip? [Flirting with Models]

    For active strategies, investors often focus on the potential outperformance the strategy can create. Beyond the potential for outperformance, active strategies also introduce tracking error: extra volatility that comes from active decisions. While most view tracking error as a negative, if derived from a unique source, it can actually be a beneficial source of internal diversification within the
  • Tail Risk in Term Structure Based Strategies in Commodities [Quantpedia]

    In this paper I document that carry trades in commodity markets are subject to potential large and infrequent losses, that is, tail risk. Also, I show that shocks to carry trades and volatility have persistent tail-specific effects which last from four to twelve weeks ahead. The main empirical results are consistent with existing theoretical models in which carry traders are subject to limited
  • A Potential Winner: Buying Lottery Stocks with Low Short Interest [Alpha Architect]

    Kelley Bergsma & Jitendra Tayal A version of this paper can be found here Want to read our short summaries of academic finance papers? Check out our Academic Research Insight category. What are the research questions Using data from CRSP and Compustat from 1989 to 2015 the research team constructed portfolios based on lottery characteristics (example here) and analyze the impact of relative
  • Factor Returns: Small vs Large Caps [Factor Research]

    A frequent criticism of factor investing is that factor returns are stronger in small caps Our research highlights that this is not uniformly true across factors Value and Size benefit most from including small caps INTRODUCTION Factor investing can be challenged in many ways. Nearly all of the research is based on backtesting of financial data, not on realized returns. The few factor products

Quantocracy’s Daily Wrap for 10/19/2017

This is a summary of links featured on Quantocracy on Thursday, 10/19/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Interview with Dr Thomas Starke of @AAAQuants [Chat With Traders]

    Dr Thomas Starke is a Physics PhD who once designed microchips, worked as an engineer for Rolls Royce and lectured at University of Oxford, before applying his know-how of modelling to financial markets As a trader, Thomas has contracted to various funds and up until recently, he was a Quantitative Developer at a well-regarded Sydney prop trading firm. Thomas was great to chat withnot only

Quantocracy’s Daily Wrap for 10/18/2017

This is a summary of links featured on Quantocracy on Wednesday, 10/18/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The ABCs of creating a mean reversion strategy Part 1 [Alvarez Quant Trading]

    I was recently interviewed on Better System Trader, click here for part one of the interview, about the steps for creating a stock mean reversion strategy. I will be covering and expanding on the topics from the interview. These steps, for the most part, would apply to any strategy one is creating. The focus will be a long stock mean reversion strategy using daily bars. What is Mean Reversion
  • QSTrader: A Major Update On Our Progress [Quant Start]

    I spoke at the Open Data Science London conference last weekend on the topic of becoming a quant. Part of the talk was aimed at educating practising data scientists on the fact that quantitative finance firms do actually contribute to, and create, many open source projects. One such project is QSTrader, which I haven't discussed for some time on the site. In today's post I am pleased to
  • Trend-Following: A Deep Dive Into A Unique Risk Premium [Alpha Architect]

    Trend-following strategies have historically been laughed at via the modern academic finance research community. Having first-hand knowledge of that community, we can verify that academic researchers are humans like the rest of us (we checked, academics arent robots), and they suffer from group think and confirmation bias. Anything related to momentum and/or trend-following was written off as

Quantocracy’s Daily Wrap for 10/17/2017

This is a summary of links featured on Quantocracy on Tuesday, 10/17/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Academic Research Insight: Sentiment Feedback Strength Trading Strategy [Alpha Architect]

    What are the research questions? Based on the evidence that tweets are faster than news in revealing new market information, but that news is regarded a more reliable source of information, the authors propose a superior trading strategy based on the sentiment feedback strength between the news and the tweets. By studying a total of 1,271,308 tweet messages from a selective group of users among