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Quantocracy’s Daily Wrap for 11/05/2016

This is a summary of links featured on Quantocracy on Saturday, 11/05/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • New Book Added: 150 Most Frequently Asked Questions on Quant Interviews [Amazon]

    Topics: Mathematics, calculus, differential equations, Covariance and correlation matrices. Linear algebra, Financial instruments: options, bonds, swaps, forwards, futures, C++, algorithms, data structures, Monte Carlo simulations. Numerical methods, Probability. Stochastic calculus, Brainteasers The use of quantitative methods and programming skills in all areas of finance, from trading to risk
  • October brings another down month to Trend Following [Wisdom Trading]

    Election year is shaping up to be a bad year for trend following. October saw the State of Trend Following index post another successive down month. The current drawdown is still within the limits of the max value from the historical back-test run, but the Year-To-Date performance is now well into double-digit territory. It will be interesting to see if this bad patch is correlated with the
  • Bottom-Up Works Best With Multiple Factors [Larry Swedroe]

    CAPM was the first formal asset pricing model. Market beta was its sole factor. With the 1992 publication of their paper, The Cross-Section of Expected Stock Returns, Eugene Fama and Kenneth French introduced a new-and-improved three-factor model, adding size and value to market beta as factors that not only provided premiums, but helped further explain the differences in returns of
  • Research Review | 4 Nov 2016 | Risk Factors & Return Premia [Capital Spectator]

    Measuring Factor Exposures: Uses and Abuses Ronen Israel and Adrienne Ross (AQR Capital Management) September 19, 2016 A growing number of investors have come to view their portfolios (especially equity portfolios) as a collection of exposures to risk factors. The most prevalent and widely harvested of these risk factors is the market (equity risk premium); but there are also others, such as value
  • Principal Component Analysis [Quant Dare]

    Principal Component Analysis (PCA) is a technique used to reduce the dimensionality of a data set, finding the causes of variability and sorting them by importance. >How? If you have a set of observations (features, measurements, etc.) that can be projected on a plane (X, Y) such as: DataSet representation You can display the previous graph from X* and Y* axes, which remain orthogonal. New axes

Quantocracy’s Daily Wrap for 11/04/2016

This is a summary of links featured on Quantocracy on Friday, 11/04/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • New Book Added: Financial Signal Processing and Machine Learning [Amazon]

    The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available. Financial Signal Processing and Machine Learning unifies a number of recent advances made in signal processing and machine learning for the design and management of investment portfolios and financial engineering. This book bridges the
  • Antonacci’s Composite Dual Momentum [Allocate Smartly]

    This is a test of Gary Antonaccis Composite Dual Momentum strategy from his seminal paper: Risk Premia Harvesting Through Dual Momentum. The model uses Antonaccis unique approach to measuring momentum, which considers both absolute (aka time-series) and relative (aka cross-sectional) momentum, to trade a much larger basket of asset classes than his more well-known GEM strategy. Results
  • Podcast: How to think about strategies like a quant w/ Derek Wong [Chat With Traders]

    On this episode, I have our very first guest from China; Derek Wonghe is the Director of Systematic Trading and Options at a private fund in Shanghai. Initially though, Derek got his start in the agricultural pits at the CBOT, then following on from this, hes worked at various quant shops in Chicago, South Korea, and now days, mainland China. After discussing Dereks backstory, we talk;

Quantocracy’s Daily Wrap for 11/03/2016

This is a summary of links featured on Quantocracy on Thursday, 11/03/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Risk of Low Volatility Strategies [Investing Research]

    Most factor-based, otherwise known as Smart Beta, ETF strategies are based on a single concept like value or momentum. Over the last two years, the largest flows have been to ETFs investing in low volatility stocks. The most popular being the iShares Edge MSCI Min Vol USA ETF (USMV), which as of September 30th had grown to $14.4bn USD, more than doubling over the last 12 months. With product
  • A Reversal-Based Trading Strategy Around Earnings Announcements [Quantpedia]

    This study documents that earnings announcements serve as a reality check on short-term, fear and greed driven price development: stocks with extreme abnormal returns in the week before an earnings announcement experience strong price reversal around the announcement. A trading strategy that exploits this reversal is profitable in 40 of the last 42 years and earns abnormal returns in excess of
  • Financial Time-Series Segmentation Based On Turning Points in Python [Quant at Risk]

    A determination of peaks and troughs for any financial time-series seems to be always in high demand, especially in algorithmic trading. A number of numerical methods can be found in the literature. The main problem exists when a smart differentiation between a local trend and global sentiment needs to be translated into computer language. In this short post, we fully refer to the

Quantocracy’s Daily Wrap for 11/02/2016

This is a summary of links featured on Quantocracy on Wednesday, 11/02/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Risk Parity and The Four Faces of Risk [GestaltU]

    Benjamin Graham famously said that "In the short run, the market is a voting machine but in the long run, it is a weighing machine." But this is not quite correct. Rather, in the short term, the market is a machine where investors "vote" about what the market will "weigh" in the future. Of course, when Benjamin Graham referred to "weighing," he was actually
  • Value Investing using Enterprise Multiples – Is the Premium Due to Risk and/or Mispricing? [Alpha Architect]

    At Alpha Architect, we are big fans of Value investing (and Momentum). In the past, Wes and I examined which valuation measure had the largest spread between Value and Growth firms. The evidence showed (updated results here) that Enterprise Multiples had the largest spread between Value and Growth firms. We define Enterprise Multiples as the Total Enterprise Value (TEV) of the firm divided by
  • Low Priced Stocks No Bargain [Larry Swedroe]

    As I wrote about last week, the absolute level of a firms stock price is arbitrary, as it can be easily manipulated by the firm through altering the number of shares outstanding (for example, by splitting the stock). Despite this obvious fact, the research into investor behavior has found a strong preference among individuals for low-priced stocks. For instance, the research shows that

Quantocracy’s Daily Wrap for 11/01/2016

This is a summary of links featured on Quantocracy on Tuesday, 11/01/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Tactical Asset Allocation in October [Allocate Smartly]

    This is a summary of the recent performance of a number of excellent tactical asset allocation strategies. These strategies are sourced from books, academic papers, and other publications. While we dont (yet) include every published TAA model, these strategies are broadly representative of the TAA space. Read more about our backtests or let AllocateSmartly help you follow these strategies in

Quantocracy’s Daily Wrap for 10/31/2016

This is a summary of links featured on Quantocracy on Monday, 10/31/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Rising Correlations and Tactical Asset Allocation [Flirting with Models]

    The power of strategic asset allocation is best harnessed when future asset class behavior is relatively certain and diversification opportunities abound. Uncertainty around rising rates and the current monetary policy environment may call both of these criteria into question. Holding all else equal, tactical asset allocation (TAA) is most likely to add value in environments where
  • Demystifying the Hurst Exponent Part 1 [Robot Wealth]

    This is the first post in a two-part series about the Hurst Exponent. Tom and I worked on this series together, but the awesome code presented throughout is all his. Thanks Tom! Mean-reverting time series have long been a fruitful playground for quantitative traders. In fact, some of the biggest names in quant trading allegedly made their fortunes exploiting mean reversion of financial time series
  • The Rebalance Bonus for Value and Momentum Porfolios [Alpha Architect]

    A sophisticated DFA-focused advisor asked us to conduct some research on the following question: Are there additional portfolio diversification benefits to combining concentrated portfolios of value and momentum stocks relative to combining less concentrated portfolios of value and momentum stocks? In concrete terms, is combining a value fund with 300+ holdings (e.g., DFA Large Cap Value, DFLVX)

Quantocracy’s Daily Wrap for 10/30/2016

This is a summary of links featured on Quantocracy on Sunday, 10/30/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Foundations of Successful Trading with Howard Bandy [Better System Trader]

    There are a number of different aspects to trading that we really need to get a handle on to increase our odds of success. Some aspects we often put a lot of thought and analysis into, and others we may not consider so carefully or at all, which could be impacting our trading results without us even realizing. Todays guest, Dr Howard Bandy, is here to discuss the foundations of trading, and some