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Quantocracy’s Daily Wrap for 11/15/2017

This is a summary of links featured on Quantocracy on Wednesday, 11/15/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Weekly Mean Reversion Rotation Strategy on S&P500 Stocks [Alvarez Quant Trading]

    A reader emailed me about testing a weekly mean reversion rotation strategy on S&P500 stocks. My first thought was, why had I not done this type of test before? The very first strategy that I worked on with Larry Connors was this type of strategy. The strategy I will be testing today is a simpler version and different universe but how well will it hold up? Basic Rules Testing period is from

Quantocracy’s Daily Wrap for 11/14/2017

This is a summary of links featured on Quantocracy on Tuesday, 11/14/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Comparing Some Strategies from Easy Volatility Investing, and the Table.Drawdowns Command [QuantStrat TradeR]

    This post will be about comparing strategies from the paper Easy Volatility Investing, along with a demonstration of Rs table.Drawdowns command. First off, before going further, while I think the execution assumptions found in EVI dont lend the strategies well to actual live trading (although their risk/reward tradeoffs also leave a lot of room for improvement), I think these
  • Ensemble Methods for E-Mini S&P 500 Futures Long/Short Strategy [Golden Compass]

    Ensemble methods are learning algorithms that construct a set of classifiers and then classify new data points by taking a (weighted) vote of their predictions. This is with the intention that ensembles will achieve better prediction accuracy than individual classifiers. In machine learning research, most research papers focus on evaluating the performance of single algorithms. In recent years,
  • Better Small Cap Premium [Quantpedia]

    We find that when measured in terms of dollar-turnover, and once beta-neutralised and Low-Vol neutralised, the Size Effect is alive and well. With a long term t-stat of 5.1, the Cold-Minus-Hot (CMH) anomaly is certainly not less significant than other well-known factors such as Value or Quality. As compared to market-cap based SMB, CMH portfolios are much less anti-correlated to the Low-Vol
  • How to Balance Short and Long term Goals in Asset Allocation [Alpha Architect]

    Peng Wang and Jon Spinney A version of this paper can be found here Want to read our summaries of academic finance papers? Check out our Academic Research Insight category. What are the research questions? Investors following a purely quantitative approach to asset allocation are often left with unintuitive portfolios with high turnover. On the other hand, those who pursue ad-hoc approaches face
  • Investing Outside the U.S. – Purgatory for Pessimists [Factor Investor]

    The current equity bull market has not been kind to non-U.S. allocations. At a recent conference I attended, the term TINA: there is no alternative came up more than once in the context of allocating investor portfolios. It captures the collective sentiment that equities, despite a massive bull run and rising valuations, are one of few viable asset classes to park capital. Expected returns
  • Can asset bubbles be mathematically quantified before they burst? [Alpha Architect]

    The subject of asset bubbles and market crashes has fascinated me for more than 20 years. As an options market maker for Susquehanna International Group (SIG), extreme price movements were a daily source of concern. I sat next to Jeff Yass for years and watched him manage option positions in thousands of different stocks. Almost daily he would be celebrating a big win in a stock that had an
  • Hedge Fund Factor Exposure and Alternatives [Factor Research]

    Equity hedge fund returns have been disappointing over the last 14 years An exposure analysis shows no structural factor exposure, but frequent factor rotation Multi-factor long-short products are an interesting alternative, depending on the fee level INTRODUCTION Hedge fund assets reached an all-time high in 2017 with $3.3 trillion under management. Although returns were muted in recent years,

Quantocracy’s Daily Wrap for 11/13/2017

This is a summary of links featured on Quantocracy on Monday, 11/13/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • A Case Against Overweighting International Equity [Flirting with Models]

    Weve read a number of outlooks and commentaries lately from firms arguing for investors to take a tactical tilt away from U.S. equities and towards International equities. The logic behind this tilt is largely driven by relative valuations: international equities appear significantly cheaper than U.S. equities based on most valuation metrics. In this commentary, we discuss why such a
  • Podcast: Building Mean Reversion trading strategies with @AlvarezQuant – Part 3 [Better System Trader]

    And were back for the final episode in this 3-part series on building Mean Reversion strategies with Cesar Alvarez from Alvarez Quant Trading. In the 1st 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. In the 2nd episode we
  • Market returns in odd and even weeks [UK Stock Market Almanac]

    A couple of years ago the Almanac wrote about a strange characteristic of the UK equity market which was the difference in performance in odd and even weeks. The original article is here (see the original article for the definition of odd/even weeks etc.) To recap briefly, the FTSE 100 Index saw much stronger returns in odd weeks than even weeks. Lets see whats happened recently and if this
  • Matrix Iterations for Adaptive Asset Allocation [TrendXplorer]

    Adaptive Asset Allocation (AAA) is based on the Nobel Prize winning portfolio theory of Markowitz (1952) AAA combines assets momentum, volatilities, and cross-correlations for building diversified investment portfolios In a tactical application AAA exploits momentum for crash detection and results in consistent returns at mitigated risk levels Actually, their encounter was coincidental. The

Quantocracy’s Daily Wrap for 11/10/2017

This is a summary of links featured on Quantocracy on Friday, 11/10/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How To Get Funding For Your Trading Strategy [Quant Insti]

    So, its been some time since youve been thinking of making more money out of your successful trading strategy. And why should you not? After all, youve worked hard for it and there is only a small % of people who are successful in this business. The idea is to add more funds to your trading strategy and get more profits. How To Get Funding For Your Trading Strategy?Click To Tweet So how
  • Factor Investors Beware: Positive SMB May Not Mean You Own Small-Caps [Alpha Architect]

    Regression analysis is used all the time to assess how a portfolio loads on certain factors. The most common factor loadings examined are the market, size, value, and momentum factors. This can be an informative exercise, and there are nice tools online, such as portfolio visualizer, which allow investors to examine factor loadings on funds. Note: We have an article (with an excel file),
  • Research Review | 10 November 2017 | Factor Strategies [Capital Spectator]

    Investing in a Multi-Asset Multi-Factor World Alexandar Cherkezov (Invesco), et al. August 31, 2017 In this article, we advance the use of factor investing across multiple asset classes. It turns out that style factors well established in the equity domain such as value, momentum or quality do extend to other asset classes as well. Even more so, multi-asset multi-factors significantly

Quantocracy’s Daily Wrap for 11/09/2017

This is a summary of links featured on Quantocracy on Thursday, 11/09/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Overnight Risk [Qusma]

    Why are overnight periods riskier? For one, you cant use stops to limit your risk. But more importantly, the distribution of overnight returns has far more extreme negative returns than the intraday or close-to-close periods. Lets take a look at some stats on close-to-open, open-to-close, and close-to-close returns for SPY: Some definitions: Skew: negative skew means longer tails on the

Quantocracy’s Daily Wrap for 11/08/2017

This is a summary of links featured on Quantocracy on Wednesday, 11/08/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • PDF: Two Centuries of Value and Momentum 1800-2014

  • 800 Years of Risk-Free Rate [Quantpedia]

    This paper presents a new dataset for the annual risk-free rate in both nominal and real terms going back to the 13th century. On this basis, we establish for the first time a long-term comparative investigation of bond bull markets. It is shown that the global risk-free rate in July 2016 reached its lowest nominal level ever recorded. The current bond bull market in US Treasuries which
  • Risk Parity in Python [Quant Dare]

    Once we are familiar with the theory surrounding Risk Parity, its time to put the strategy into practice and try out the algorithm for ourselves. We discover how it works, analyse the strategy and create our own portfolios. Thanks to the posts written by T.Fuertes and mplanaslasa we already know what the Risk Parity strategy is, its formulation and even how it differs from the Inverse
  • State of Trend Following in October [Au Tra Sy]

    Last month saw a strong upwards performance from the State of Trend Following index, single-handedly reversing half the negative performance for the year, which still stands close to double-digit territory. Please check below for more details. Detailed Results The figures for the month are: October return: 8.72% YTD return: -8.02% Below is the chart displaying individual system results throughout

Quantocracy’s Daily Wrap for 11/07/2017

This is a summary of links featured on Quantocracy on Tuesday, 11/07/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Timing TAA Strategies Based on Relative Strength: A Suboptimal Approach [Allocate Smartly]

    We track a wide range of tactical asset allocation strategies in near real-time (41 and counting), which members can combine into their own custom portfolios. We provide members with a wealth of data to understand how each strategy fits into a coherent trading plan, but we dont tell members the absolute best ones to trade or how to combine them. Thats because there isnt a single
  • Earning Money in Cryptocurrency Markets by Spotting Statistical Arbitrage Opportunities [Quant at Risk]

    When you come in contact with cryptocurrencies, e.g. Bitcoin (BTC), you quickly realise that there is no single price of BTC at any given moment. The reason is that Bitcoin is traded on different markets. It can be worth more on Coinbase exchange and less on Kraken exchange. In particular, the Coindesk Bitcoin Price Index (XBP) aims to unify the BTC price into a single number based on four markets
  • Replicating Indexes In R (Part III): Socially Responsible Investing [Capital Spectator]

    In previous installments of replicating indexes I profiled the style-analysis methodology and presented an example using a hedge fund index. Now lets turn to a strategy of replicating the S&P 500 Index with a handful of stocks that are considered socially responsible investments (SRI). Whats the rationale? A growing number of investors require that their equity portfolios match certain

Quantocracy’s Daily Wrap for 11/06/2017

This is a summary of links featured on Quantocracy on Monday, 11/06/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Cointegration, Correlation and Log Returns [Quantoisseur]

    The differences between correlation and cointegration can often be confusing. While there are some helpful explanations online, I wasnt satisfied with the visual examples. When looking at a plot of an actual pair of symbols where the correlation and cointegration test results differ, it can be difficult to pinpoint which portions of the time series are responsible for these separate properties.
  • Are we misidentifying seasonal patterns as genuine earnings news? [Alpha Architect]

    Changes in earnings are comprised of the expected earnings number plus any seasonal component of earnings. If the seasonal component is expected then it should not affect prices in an efficient market. However, unusual returns have been documented surrounding earnings announcements at the seasonal juncture in time. It is possible investors discount the complexity of seasonality even though it is a
  • It s Long/Short Portfolios All The Way Down [Flirting with Models]

    Long/short portfolios are helpful tools for quantifying the value-add of portfolio changes, especially for active strategies. In the context of fees, we can isolate the implicit fee of the managers active decisions (active share) relative to a benchmark and ask ourselves whether we think that hurdle is attainable. Bar-belling low fee beta with high active share, higher fee managers may actually
  • Integrated Value, Growth and Quality Portfolios [Factor Research]

    Integrated Value, Growth & Quality portfolios generated attractive returns year-to-date 2017 Sorting stocks on several characteristics results in relatively smooth performance Mitigates the issue of factor timing, but not of factor selection INTRODUCTION Year-to-date 2017 is shaping up as a terrible year for the consensus trade of the beginning of the year Value, which was based on animal

Quantocracy’s Daily Wrap for 11/02/2017

This is a summary of links featured on Quantocracy on Thursday, 11/02/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Application of Machine Learning Techniques to Trading [Auquan]

    Auquan recently concluded another version of QuantQuest, and this time, we had a lot of people attempt Machine Learning with our problems. It was good learning for both us and them (hopefully!). This post is inspired by our observations of some common caveats and pitfalls during the competition when trying to apply ML techniques to trading problems. IF you havent read our previous posts, we
  • The Herd Effect in Financial Markets [Quant Dare]

    Often in financial markets, as in our daily life, we imitate the decisions of predecessors, instead of analysing available information and making our own decisions. This decision imitation could lead to collective hysteria, and investment calls may be influenced by these panicked situations. Imagine that youre looking for a place to have dinner, and find a street with two restaurants. Both look
  • Trend Following Strong in October [Wisdom Trading]

    October 2017 Trend Following: UP +7.12% / YTD: -15.39% Below is the full State of Trend Following report as of last month, which saw our trend following index post a strong positive performance. Performance is hypothetical. Chart for October: Wisdom State of Trend Following – October 2017 And the 12-month chart: Wisdom State of Trend Following 12 months – October 2017 Below are the summary stats:

Quantocracy’s Daily Wrap for 11/01/2017

This is a summary of links featured on Quantocracy on Wednesday, 11/01/2017. 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 wide range 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. Learn more about what we do or let AllocateSmartly help you follow these strategies in
  • The ABCs of creating a mean reversion strategy Part 2 [Alvarez Quant Trading]

    This post is the continuation of the steps for creating a mean reversion strategy from the first part of The ABCs of creating a mean reversion strategy Part 1. You can also listen to part 2 of my interview on Better System Trader here. A quick recap of the topics covered in part 1. I covered trading universe, indicators to measure daily mean reversion, combining multiple mean reversion
  • What Will We Talk About at the Evidence-Based Investing Conference This Year? [Alpha Architect]

    ack and I will be attending the Evidence-Based Investing Conference tomorrow in NYC. Were excited to participate and be part of the crowd. Be sure to give us a holler love to discuss whatever is on your mind! Author rendering of the scene at EBI Historically, the conversations at EBI can end up covering fun topics. For example, Over the summer, Jack spoke at the West Coast version and