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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

Quantocracy’s Daily Wrap for 10/16/2017

This is a summary of links featured on Quantocracy on Monday, 10/16/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Hedging Market Crashes with Factor Exposure [Factor Research]

    None of the factors consistently generated positive performance during recent market crashes However, almost any factor exposure would have increased the risk-return ratio of an equity-centric portfolio Low Volatility and Mean-Reversion would have been most beneficial, Momentum least INTRODUCTION A long time ago in a galaxy far, far awaymarkets declined. On our world, supported by an empire of
  • Sleuthing Out Allocations [Flirting with Models]

    Determining the allocations of an investment strategy is often the first step in scenario analysis, sensitivity analysis, and stress testing. For a single fund or ETF, the allocations can be found on the providers website or in marketing materials. However, when analyzing a larger group of funds or using third-party software tools, simplifying assumptions are frequently employed. Balancing
  • Podcast: Factor Replication with Lu Zhang [Alpha Architect]

    Here is a link to our podcast on Behind the Markets Wes and Jeremy speak with Lu Zhang, The John W. Galbreath Chair, Professor of Finance, at the Fisher College of Business at The Ohio State University, and co-author of the paper, Replicating Anomalies. The team dig into the 3-year research project and dissect some of the results. Prof. Zhang tell the audience what he considers to be the
  • October Opex Week Historically Bullish [Quantifiable Edges]

    Option expiration week is often a pretty good week for the market. October is one of those months where it has been especially good over the years. This can be seen in the study below. 2017-10-16 I decided to exclude 2008 because action that week was such an incredible outlier that it greatly skewed all the stats. (The week started with an 11.5% gain on Monday of 2008.) Even without 2008, results
  • Tips To Start Your Own Business In Algorithmic Trading [Quant Insti]

    You are doing well at work but have always felt that need to cater to the aspiration of doing something more, building something of your own? You are passionate about the chosen field of work. You have already explored different organizations and their work processes extensively. Entrepreneurship seems to be the only logical step ahead. The only concern is how? The basic questions that you need to
  • How to Predict FX Carry Profitability [Quantpedia]

    In this paper, we study the effectiveness of carry trade strategies during and after the financial crisis using a flexible approach to modeling currency returns. We decompose the currency returns into multiplicative sign and absolute return components, which exhibit much greater predictability than raw returns. We allow the two components to respond to currency-specific risk factors and use the

Quantocracy’s Daily Wrap for 10/13/2017

This is a summary of links featured on Quantocracy on Friday, 10/13/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Replicating Anomalies [Alpha Architect]

    Academic research is amazing and incredibly useful for helping us better understand the complex world in which we live. In fact, academic research has literally rewired my brain at times. However, research isnt perfect and the search for truth is messy. Data-mining. Overfitting. P-hacking. Weve recently covered the subject here, here, and here. Whats the bottom line? Disregard everything
  • Are U.S. Equity Momentum ETFs Working? [CXO Advisory]

    Are U.S. stock and sector momentum strategies, as implemented by exchange-traded funds (ETF), attractive? To investigate, we consider five momentum-oriented U.S. equity ETFs with assets over $100 million, all currently available (in order of decreasing assets): iShares Edge MSCI USA Momentum Factor (MTUM) holds U.S. large-capitalization and mid-capitalization stocks with relatively high
  • Research Review | 13 October 2017 | Expected Return [Capital Spectator]

    The Most Dangerous (and Ubiquitous) Shortcut in Financial Planning John West and Amie Ko (Research Affiliates) September 2017 Using historical returns to forecast the future is one of the most common shortcuts in financial planning. Investment advisors who use only past returns to forecast future returns may well be creating unrealistic expectations and poor investment outcomes for their clients.