Quantocracy

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Quantocracy’s Daily Wrap for 08/27/2019

This is a summary of links featured on Quantocracy on Tuesday, 08/27/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Tech Dividends [Reproducible Finance]

    In a previous post, we explored the dividend history of stocks included in the SP500. Today well extend that anlaysis to cover the Nasdaq because, well, because in the previous post I said I would do that. Well also explore a different source for dividend data, do some string cleaning and check out ways to customize a tooltip in plotly. Bonus feature: well get into some animation too. We
  • The Single Futures Roll [Hudson and Thames]

    Building trading strategies on futures contracts has the unique problem that a given contract has expiration date, example the 3 month contract on wheat. In order to build a continuous time series across the different contracts we stitch them together, most commonly using an auto roll or some other function. However a problem occurs when we do this, which is: come the expiry date, there is usually

Quantocracy’s Daily Wrap for 08/26/2019

This is a summary of links featured on Quantocracy on Monday, 08/26/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Es-CAPE Velocity: Value-Driven Sector Rotation [Flirting with Models]

    Systematic value strategies have struggled in the post-2008 environment, so one that has performed well catches our eye. The Barclays Shiller CAPE sector rotation strategy a value-based sector rotation strategy has out-performed the S&P 500 by 267 basis points annualized since it launched in 2012. The strategy applies a unique Relative CAPE metric to account for structural differences
  • Social Media, News Based Sentiment, and Market Timing [Alpha Architect]

    With a growing availability of filtered (news) and unfiltered (social media) information, the author investigates the following question: Do news or social media contain any information that is of relevance for investment decision making and if so are the two sources are complementary or overlapping? What are the Academic Insights? By using an extensive sample of directly comparable news- and

Quantocracy’s Daily Wrap for 08/25/2019

This is a summary of links featured on Quantocracy on Sunday, 08/25/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Analyzing global fixed income markets with tensors [SR SV]

    Roughly speaking, a tensor is an array (generalization of a matrix) of numbers that transform according to certain rules when the arrays coordinates change. Fixed-income returns across countries can be seen as residing on tensor-like multidimensional data structures. Hence a tensor-valued approach allows identifying common factors behind international yield curves in the same way as principal
  • Wide Range N-Day Pattern | Trading Strategy (Setup) [Oxford Capital]

    Developer: Toby Crabel (Narrow Range N-Day Pattern; Note: Wide Range N-Day Pattern applies a reverse logic of Narrow Range N-Day Pattern). Source: Crabel, T. (1990). Day Trading with Short Term Price Patterns and Opening Range Breakout. Greenville: Traders Press, Inc. Concept: Volatility cycles (expansion-contraction) with different look back periods. Research Goal: Performance verification of

Quantocracy’s Daily Wrap for 08/22/2019

This is a summary of links featured on Quantocracy on Thursday, 08/22/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

Quantocracy’s Daily Wrap for 08/20/2019

This is a summary of links featured on Quantocracy on Tuesday, 08/20/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Quint Switching Filtered: Not as Simple as It Appears to Be [Allocate Smartly]

    This is a test of the Quint Switching Filtered strategy from Lewis Glenn. On the surface this is a run-of-the-mill tactical asset allocation strategy based on short-term momentum, not unlike several strategies that we track. But digging a little deeper, well highlight qualities that make this strategy unique both for the better and the worse. Results from 1970 net of transaction costs
  • A new way to sentiment-tag financial news [Vered Zimmerman]

    Over the past few years, financial-news sentiment analysis has taken off as a commercial natural language processing (NLP) application. Like any other type of sentiment analysis, there are two main approaches: one, more traditional, is by using sentiment-labelled word lists (which we will also refer to as dictionaries). The other, is using sentiment classifiers based on language models trained on
  • Crisis Proof Your Portfolio: part 1/2 [Alpha Architect]

    This is a unique article in that it directly assesses the feasibility and effectiveness of protecting equity portfolios using traditional passive means and more contemporary active strategies. It is jam-packed with information and analysis that is best consumed in two parts; however, a good summary of the article by Larry Swedroe can be found here. The focus in part 1 is the usefulness of

Quantocracy’s Daily Wrap for 08/19/2019

This is a summary of links featured on Quantocracy on Monday, 08/19/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Risk Parity Part I: Chasing Diversifiers [Two Centuries Investments]

    The rise and fall (?) of Risk Parity is a great case study of the frameworks I have been writing about so far. We start with the concept of Chasing Diversifiers. Chasing Diversifiers (link) Although Risk Parity is as close as you get to a pure risk diversification play, just like other diversifiers, the benefits of Risk Parity were sold and bought when both the forward looking consensus
  • Using PMI to Trade Cyclicals vs Defensives [Flirting with Models]

    After stumbling across a set of old research notes from 2009 and 2012, we attempt to implement a Cyclicals versus Defensives sector trade out-of-sample. Post-2012 returns prove unconvincing and we find little evidence supporting the notion that PMI changes can be used for constructing this trade. Using data from the Kenneth French website, we extend the study to 1948, and similarly find that
  • How Painful Can Factor Investing Get? [Factor Research]

    A classic long-short, multi-factor portfolio has lost close to 20% since 2018 The drawdown is within expectations, but the recovery period is abnormally long However, its difficult to argue for structural changes that make factor investing unattractive SEEKING DIVERSIFICATION THROUGH MULTI-FACTOR PRODUCTS Investors have flooded into multi-factor strategies over the last several years. The

Quantocracy’s Daily Wrap for 08/17/2019

This is a summary of links featured on Quantocracy on Saturday, 08/17/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Contract-Specific Trading Costs and Optimal Execution Strategy [Quant Fiction]

    There are as many strategies for extracting alpha from the markets as there are traders. Unfortunately, this article will be discussing none of them. If thats what youre looking for, I suggest you check out the very sophisticated techniques covered in this video. OK. If youre still reading, you probably take trading at least somewhat seriously. When setting up your trading business (and
  • The power of R for trading (part 2) [SR SV]

    The R environment makes statistical estimation and learning accessible to portfolio management beyond the traditional quant space. Overcoming technicalities and jargon, managers can operate powerful statistical tools by learning a few lines of code and gaining some basic intuition of statistical models. Thus, for example, R offers convenient functions for time series analysis (characterizing

Quantocracy’s Daily Wrap for 08/16/2019

This is a summary of links featured on Quantocracy on Friday, 08/16/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Variance Risk Premium is Pervasive [Alpha Architect]

    The variance risk premium (VRP) refers to the fact that, over time, the option-implied volatility has tended to exceed the realized volatility of the same underlying asset. This has created a profit opportunity for volatility sellersthose willing to write volatility insurance options, collect the premiums and bear the risk that realized volatility will increase by more than implied volatility.

Quantocracy’s Daily Wrap for 08/14/2019

This is a summary of links featured on Quantocracy on Wednesday, 08/14/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Synthetic ETF Data Generation (Part-2) – Gaussian Mixture Models [Black Arbs]

    This post is a summary of a more detailed Jupyter (IPython) notebook where I demonstrate a method of using Python, Scikit-Learn and Gaussian Mixture Models to generate realistic looking return series. In this post we will compare real ETF returns versus synthetic realizations. To evaluate the similarity of the real and synthetic returns we will compare the following: visual inspection histogram

Quantocracy’s Daily Wrap for 08/13/2019

This is a summary of links featured on Quantocracy on Tuesday, 08/13/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Movement Capital’s Composite Strategy: Balancing Strategy and Asset Risk [Allocate Smartly]

    This is a test of Movement Capitals Composite Strategy. It combines tactical asset allocation with passive buy & hold. This balance between strategy risk and asset risk may be psychologically easier to trade, encouraging investors to stick with a smart investment plan when either style finds itself out of favor. Results from 1970 net of transaction costs follow. Read about our backtests or
  • Do Most Individual Stocks Outperform Cash? No. [Alpha Architect]

    Id argue that a typical investor believes the followingIn the past and over the long run, stocks outperformed bonds.(1) However, as highlighted here, an academic paper last year shows that the majority of individual U.S. stocks actually lost compared to Treasury Bills (i.e. the return to cash)! For many investors, that is a stunning finding. (note: the stats for stocks with value and