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Quantocracy’s Daily Wrap for 12/22/2017

This is a summary of links featured on Quantocracy on Friday, 12/22/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Stock Misplacement in Sized-Based Indices [Alpha Architect]

    There has been much discussion of the small-cap premium recently. Has its popularity cannibalized its utility? Are large firms preventing a level playing field? Will the small-cap premium exist going forward? This article does not address these concerns directly, but it does identify and analyze another potential issue that could diminish the utility of small cap exposures. In particular, I

Quantocracy’s Daily Wrap for 12/21/2017

This is a summary of links featured on Quantocracy on Thursday, 12/21/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • (Don t Get) Contangled Up In Noise [QuantStrat TradeR]

    This post will be about investigating the efficacy of contango as a volatility trading signal. For those that trade volatility (like me), a term you may see thats somewhat ubiquitous is the term contango. What does this term mean? Well, simple: it just means the ratio of the second month of VIX futures over the first. The idea being is that when the second month of futures is more than
  • The Returns to Value Strategies When Valuation Spreads Are Wide (Deep Value) [Alpha Architect]

    The academic research has generally found valuations, such as the earnings yield (E/P) (or the CAPE 10 earnings yield) and valuation spreads, have predictive value in terms of future returns. The higher the earnings yield, the higher the expected return, and the larger the spread in valuations between growth and value stocks, the larger the future value premium is likely to be in the future.(1)
  • Carry Trade Across Fixed and Floating Currency Regimes [Quantpedia]

    Carry trade returns vary across fixed and floating currency regimes. Over the last century, outsized carry returns occur exclusively in the floating regime, being zero in the fixed regime. The absence of skewness in floating carry returns rules out a skewness-based explanation for this result. Fixed-to-floating regime shifts deliver negative return shocks to the floating carry strategy, even when

Quantocracy’s Daily Wrap for 12/20/2017

This is a summary of links featured on Quantocracy on Wednesday, 12/20/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Forecasting S&P 500 using Machine Learning [Quant Dare]

    Is it possible to foresee the future movements of a stock? Lets use Machine Learning techniques to predict the direction of one of the most important stock indexes, the S&P 500. Pregaming The Standard & Poors 500 (S&P500) is a stock market index based on the capitalization of the 500 largest American companies. It is an index widely traded through index funds and ETFs, which
  • Book Review – Market Timing with Moving Averages [Alpha Architect]

    Trend-following is something Ive struggled with for years always felt like voodoo magic and data-mining. That said, I finally came around to appreciating the practice after a ton of research replication efforts, independent research. At the time I was investigating the topic there really werent any references or books that gave me the depth of understanding that I was looking for. What I
  • Cryptocurrencies vs. Other Asset Classes [CXO Advisory]

    Are cryptocurrencies potentially useful portfolio diversifiers? In their November 2017 paper entitled Exploring the Dynamic Relationships between Cryptocurrencies and Other Financial Assets, Shaen Corbet, Andrew Meegan, Charles Larkin, Brian Lucey and Larisa Yarovaya apply a battery of tests to analyze relationships: (1) among three cryptocurrencies; and, (2) between the cryptocurrencies and

Quantocracy’s Daily Wrap for 12/19/2017

This is a summary of links featured on Quantocracy on Tuesday, 12/19/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Pairs Trading using Data-Driven Techniques: Simple Trading Strategies Part 3 [Auquan]

    Pairs trading is a nice example of a strategy based on mathematical analysis. Well demonstrate how to leverage data to create and automate a pairs trading strategy. Underlying Principle Lets say you have a pair of securities X and Y that have some underlying economic link, for example two companies that manufacture the same product like Pepsi and Coca Cola. You expect the ratio or difference
  • Industry Herding by Short Sellers Signals that Conditions are Changing [Alpha Architect]

    Does the industry concentration exhibited in short sellers holdings convey new material information about the industry? Are the excess returns obtained from industry shorting combined with firm-specific shorting strategies explained by risk? Is the industry shorting signal correlated with economic trends in the associated industry? What are the Academic Insights? YES. The results reported here

Quantocracy’s Daily Wrap for 12/18/2017

This is a summary of links featured on Quantocracy on Monday, 12/18/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Value 2.0 [Flirting with Models]

    Traditional value strategies simply sort the investment universe based on one or more valuation metrics (e.g. book-to-market, price-to-earnings, etc.) and purchase the securities that look the cheapest. However, this process is often prone to structural sector bets, which are uncompensated sources of risk within a strategy. By comparing the value of stocks within each sector along with the value
  • Factor Returns: Year-End Calendar Effects [Factor Research]

    Value & Size generate abnormally large positive returns in January, Momentum negative returns Abnormal returns are limited to the last week of December and first week of January Difficult to harvest these returns efficiently due to illiquidity of markets at these times INTRODUCTION At this time of the year investors tend to receive market outlooks for 2018 from a variety of service providers.
  • Machine Learning Classification Strategy In Python [Quant Insti]

    In this blog, we will step by step implement a machine learning classification algorithm on S&P500 using Support Vector Classifier (SVC). SVCs are supervised learning classification models. A set of training data is provided to the machine learning classification algorithm, each belonging to one of the categories. For instance, the categories can be to either buy or sell a stock. The

Quantocracy’s Daily Wrap for 12/16/2017

This is a summary of links featured on Quantocracy on Saturday, 12/16/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Podcast: When a quant trader enters the world of sports betting with Andreas Koukorinis [Chat With Traders]

    Andreas Koukorinis lives in London and in 2013 he co-founded Stratagem Technologiesa tech startup using AI and machine learning to trade sports as a financial product. These sports predominately include; football, tennis and basketball. But for Andreas, his roots are in trading instruments and markets that most of us are more accustomed to. Hes worked for the likes of Morgan Stanley and
  • Pricing Arithmetic Asian Options using Moment Matching [Top of The Bell Curve]

    Asian options are path-dependent options whose payoff depends on the average value of the underlying asset during a specific set of dates across the life of the option. Because the payoff of the Asian options depends on the average value of the underlying asset, volatility in the average value is lower than that of the plain vanilla options. Thus Asian options tend are less expensive than the
  • Are Recent S&P 500 Returns Excessive Relative To History? [Capital Spectator]

    The US stock market has been on a tear lately. Has the party gone too far? A rising chorus of analysts say that caution is advised, citing several valuation metrics. The Shiller PE Ratio, for instance, is currently at its second-highest level since the late-1800s. Valuations appear stretched, but history reminds that this form of excess can endure. And with the US economy posting ongoing signs of

Quantocracy’s Daily Wrap for 12/13/2017

This is a summary of links featured on Quantocracy on Wednesday, 12/13/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Time Series Analysis for Financial Data VI ARCH and GARCH models [Auquan]

    In this mini series on Time Series modelling for Financial Data, so far weve used AR, MA and a combination of these models on asset prices to try and model how our asset behaves. Weve found that we were able to model certain time periods well with these models and failed at other times. This was because of volatility clustering or heteroskedasticity. In this post, we will discuss conditional
  • Hierarchical clustering of Exchange-Traded Funds [Quant Dare]

    Clustering has already been discussed in plenty of detail, but today I would like to focus on a relatively simple but extremely modular clustering technique, hierarchical clustering, and how it could be applied to ETFs. Well also be able to review the python tools available to help us with this. Clustering Suitability First of all, ETFs are well suited for clustering, as they are each trying to
  • Iron Condor Results Summary – Part 6 – IC Returns vs Initial Conditions Correlation [DTR Trading]

    In the last article, we looked at correlations between Iron Condor returns and Iron Condor structures / trade management. Specifically, we started with the following list of areas to investigate: Correlation between Iron Condor strategy structure / management and result metrics Which result metrics most influence equity curve shape Correlation between result metrics Correlation between initial

Quantocracy’s Daily Wrap for 12/12/2017

This is a summary of links featured on Quantocracy on Tuesday, 12/12/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How is big data impacting the finance world? [Mathematical Investor]

    Big data is already a frequently-heard buzzword, both in the business analytics arena, but also in the field of high-performance scientific computing. Basically, big data encompasses the collection, processing, indexing and utilization of large-scale datasets. Some concrete examples include temperature and sunlight data downloaded from satellites monitoring of the Earths
  • Free Bitcoin/Bitcoin Futures Quotes & Charts [Six Figure Investing]

    Finding quotes and historical data for Bitcoin and Bitcoin futures can be an adventure. Below Ive assembled links to the online resources that Ive been able to find. In many cases, data is available from multiple sources. I did not attempt to list all of them. BTC Quotes Yahoo Finance (BTC-USD) Does not identify which exchange (s) it is using Shows market cap, supply, volume statistics
  • FX Momentum Explained via Dispersion Risk [Quantpedia]

    This paper studies the relation between global foreign exchange (FX) return dispersion risk and the cross-section of currency momentum returns. We find robust empirical evidence that FX return dispersion is a priced risk factor and that it contains information beyond traditional factors. Currencies with high past returns (winners) load positively on dispersion innovations, whereas currencies with
  • Beware of the Surprise Departure of Independent Directors! [Alpha Architect]

    What are the research questions? What are the general circumstances associated with independent director departures? Is it possible to identify situations whereby the departure is unexpected and not due to retirements, director outside commitments or firings by the firm? Are the unexpected or surprise departures followed by negative stock market return performance? Are the unexpected departures

Quantocracy’s Daily Wrap for 12/11/2017

This is a summary of links featured on Quantocracy on Monday, 12/11/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • No Silver Bullets: 8 Ideas for Financial Planning in a Low-Return Environment [Flirting with Models]

    Most institutions are forecasting lower expected returns for traditional asset classes compared to historical realized levels. Rules based upon historically realized numbers like the 4% withdrawal rule may fail going forward. Should we simply accept lower withdrawal rates in our financial plan? Is there a silver bullet to over-coming this return gap problem? In this presentation, we offer
  • Mean-Reversion on Equity Index Level [Factor Research]

    Mean-Reversion on index level became profitable post the 1970s, before that Momentum dominated The structural shift from Momentum to Mean-Reversion is consistent across markets Likely explained by the evolution of financial markets INTRODUCTION Investors and traders basically only have two options when it comes to investing: speculate on Momentum or Mean-Reversion. Naturally these options can be
  • The Most Wonderful Week Of The Year [Quantifiable Edges]

    Over several time horizons op-ex week in December has been the most bullish week of the year for the SPX. The positive seasonality actually has persisted for up to 3 weeks. Ive shown the study below in the blog many times since 2008. It looks back to 1984, which was the first year that SPX options traded. The table is updated again this year. 2017-12-11 The stats here remain extremely strong.
  • Time Warp Edit Distance [Dekalog Blog]

    Part of my normal routine is to indulge in online research for use useful ideas, and I recently came across An Empirical Evaluation of Similarity Measures for Time Series Classification, and one standout from this paper is the Time Warp Edit Distance where, from the conclusion, "…the TWED measure originally proposed by Marteau (2009) seems to consistently outperform all the considered

Quantocracy’s Daily Wrap for 12/10/2017

This is a summary of links featured on Quantocracy on Sunday, 12/10/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Momentum and Market Anomalies [Alpha Architect]

    Momentum is the tendency for assets that have performed well (poorly) in the recent past to continue to perform well (poorly) in the future, at least for a short period of time. Initial research on momentum was published by Narasimhan Jegadeesh and Sheridan Titman, authors of the 1993 study, Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The type of
  • Research Review | 8 December 2017 | Momentum Investing [Capital Spectator]

    Implementing Momentum: What Have We Learned? Adrienne Ross (AQR Capital Management), et al. December 2017 An abundance of academic evidence and theory exists on the efficacy and intuition behind momentum investing, yet a limited number of studies discuss the feasibility of running momentum portfolios in practice. And no study to date has directly analyzed implementation costs for a live momentum
  • November 2017 Trend Following [Wisdom Trading]

    November 2017 Trend Following: DOWN -0.61% / YTD: -15.45% Please find below the latest edition of the Wisdom State of Trend Following as of last month. Performance is hypothetical. Chart for November: Wisdom State of Trend Following – November 2017 And the 12-month chart: Wisdom State of Trend Following 12 months – November 2017 Below are the summary stats: Horizon Return Ann. Vol. Last month
  • State of Trend Following in November [Au Tra Sy]

    November was down for the index, sitting just below the negative double-digit line before year-end. It looks like the State of TF will end in the red in 2017, unless a strong bitcoin-inspired December rally lifts the index back in the black. Please check below for more details. Detailed Results The figures for the month are: November return: -4.09% YTD return: -11.26% Below is the chart displaying