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Quantocracy’s Daily Wrap for 11/15/2020

This is a summary of links featured on Quantocracy on Sunday, 11/15/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Research Review | 13 November 2020 | Factor Investing [Capital Spectator]

    Resurrecting the Value Premium David Blitz (Robeco) and Matthias X. Hanauer (Technische Universitt Mnchen) October 15, 2020 The prolonged poor performance of the value factor has led to doubts about whether the value premium still exists. Some have noted that the observed returns still fall within statistical confidence intervals, but such arguments do not restore full confidence in the value
  • An Introduction to the NAVA Toolbox [Nava Capital]

    We decided to allow anyone to take advantage of some tools we constantly use at NAVA Capital. Investors and financial managers often need to perform similar tasks, like analyzing financial time series, comparing two investments, adjusting gross performance by management fees, performance fess and so on. Doing it in Excel is time consuming, error prone and unpractical. Doing it in Python is
  • Temporal Clustering, Part 3 [Dekalog Blog]

    Continuing on with the subject matter of my last post, in the code box below there is R code which is a straight forward refactoring of the Octave code contained in the second code box of my last post. This code is my implementation of the cross validation routine described in the paper Cluster Validation by Prediction Strength, but adapted for use in the one dimensional case. I have refactored

Quantocracy’s Daily Wrap for 11/12/2020

This is a summary of links featured on Quantocracy on Thursday, 11/12/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Round about the kernel [OSM]

    In our last post, we took our analysis of rolling average pairwise correlations on the constituents of the XLI ETF one step further by applying kernel regressions to the data and comparing those results with linear regressions. Using a cross-validation approach to analyze prediction error and overfitting potential, we found that kernel regressions saw average error increase between training and
  • The Case Against Using the CAPE Ratio for Relative Valuation Across Markets [EconomPic]

    Bloomberg has an article You May Regret Staying Parked in U.S. Stocks which made the case that theres "widespread agreement" and "the answer isnt in dispute" that foreign stocks will outperform going forward. Simplified version of my view of that statement…. c'mon now. Extended version of my view of that statement is in line with what Jamie Powell outlines here: So
  • Trend Following Research: Breaking Bad Trends [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. In Your
  • Free webinar series on algorithmic trading [Philipp Kahler]

    I am happy to announce that I will be hosting a free webinar series on quantitative analysis and algorithmic trading. Dates and times for the first shows can be found over here: Tradesignal Webinar Series Date and Time based patterns will be the topic of the first webinar. It will focus on the question if there are date based and time based patterns to be found in the markets. I will show some
  • Mean-Reversion Trading Strategies in Python Course [CSS Analytics]

    This post contains affiliate links. An affiliate link means CSSA may receive compensation if you make a purchase through the link, without any extra cost to you. CSSA strives to promote only products and services which provide value to my business and those which I believe could help you, the reader. In the last post I interviewed Dr. Ernest Chan who is the author of the Mean-Reversion Trading

Quantocracy’s Daily Wrap for 11/10/2020

This is a summary of links featured on Quantocracy on Tuesday, 11/10/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • An Interview with Dr. Ernest Chan (@ChanEP) [CSS Analytics]

    In the last post I reviewed the Momentum Trading Strategies Course by Quantra (a division of QuantInsti) which I reviewed as part of a recent educational journey to improve my quantitative skill set. The next course that I will be reviewing is Mean-Reversion Strategies in Python which is taught by Dr. Ernest Chan. I have personally read Ernies book Machine Trading which is very well
  • Podcast: The Magic of Momentum Trading Alan Clement of @HelixTrader [Better System Trader]

    Ive been sitting here for 5 mins trying to come up with a witty intro for this episode about momentum, but I just couldnt seem to get it going, so
  • Where does FX sit in a Systematic Trading Portfolio? [Robot Wealth]

    This post is a BONUS LESSON taken directly from Zero to Robot Master Bootcamp. In this Bootcamp, we teach traders how to research, build and trade a portfolio of 3 strategies including an Intraday FX Strategy, a Risk Premia Strategy and a Volatility Basis Strategy. If youre interested in adding strategies to your portfolio or are just keen to start on the path to becoming a successful and
  • One Look At Monday s Massive Rotation [Quantifiable Edges]

    Monday saw a massive market rotation. It could be noted by the performance in the IWM vs the QQQ, or in looking at performance among S&P 500 sectors, where Energy beat Technology by 15% on Monday. But to really see how strong the rotation was, youd need to take a look at individual stock performance within the SPX. Below is a list of the Top 10 S&P 500 stocks, ranked by YTD performance
  • Do Analysts Exploit Factor Anomalies when recommending stocks? [Alpha Architect]

    Do analysts actively exploit anomalies when they recommend stocks? Do analysts research efforts contribute to efficiency in the equity markets? Good questions. This research clarifies the relationship between established stock return anomalies and analyst recommendations. Given that anomalies are so well-documented and so well-known, and if analysts are sophisticated informed and
  • A Temporal Clustering Function, Part 2 [Dekalog Blog]

    Further to my previous post, below is an extended version of the "blurred_maxshift_1d_linear" function. This updated version has two extra outputs: a vector of the cluster centre index ix values and a vector the same length as the input data with the cluster centres to which each datum has been assigned. These changes have necessitated some extensive re-writing of the function to include

Quantocracy’s Daily Wrap for 11/09/2020

This is a summary of links featured on Quantocracy on Monday, 11/09/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • New @Robot_Wealth Bootcamp Open! Self-Paced Algo Trading Course Taught by Pro Traders

    Successful trading is HARD. And most approaches we've seen suck, quite frankly. In this Bootcamp, you'll learn a high-probability approach to trading which is simple and systematic. The path to sustainable trading profits is straight and narrow. Bootcamp keeps you on that path. In this Bootcamp, we'll take you step-by-step through the process of setting up your systematic trading
  • Market Neutral Funds: Powered by Beta? [Factor Research]

    The long-term track record of equity market neutral hedge funds is attractive, but should be viewed with scepticism due to Madoff and survivorship bias Only one index from HFRX seems sound, but his highlights negative alpha since the GFC and positive returns primarily from market beta A factor exposure analysis reveals unusual factor loadings INTRODUCTION The mutual fund selection process would be
  • SPX Performance After Big Weekly Reversals [Quantifiable Edges]

    After losing 5.6% this in the week ending 10/30/20, the S&P 500 completely reversed the losses this past week with a 7.3% gain. That is a fairly remarkable turnaround. Below is a look at all other times the S&P 500 lost 5% or more one week, and then made up for the losses and more the next week.
  • Forecasting energy markets with macro data [SR SV]

    Recent academic papers illustrate how macroeconomic data support predictions of energy market flows and prices. Valid macro indicators include shipping costs, industrial production measures, non-energy industrial commodity prices, transportation data, weather data, financial conditions indices, and geopolitical uncertainty measures. Good practices include a focus on small models and a

Quantocracy’s Daily Wrap for 11/05/2020

This is a summary of links featured on Quantocracy on Thursday, 11/05/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Deflated Sharpe Ratio (how to avoid been fooled by randomness) [Quant Dare]

    As we test more and more strategies the overall probability of choosing at least one poor strategy grows. So we must be very careful with how many backtests we run. We should always record all of them, to later deflate the Sharpe Ratio accordingly. In this post, we are going to analyze how the Deflated Sharpe Ratio, exposed by Marcos Lpez de Prado and David H. Bailey in this paper, can help us
  • Should Treasury Bills Be The Risk-Free Asset in Asset Pricing Models? [Alpha Architect]

    In virtually all studies on asset pricing and asset pricing models, the one-month Treasury bill is the choice as the risk-free rate. In his study The Risk-Free Asset Implied by the Market: Medium-Term Bonds instead of Short-Term Bills, published in the September 2020 issue of The Journal of Portfolio Management, David Blitz challenged that choice. He began by noting that the choice of the
  • 3 Takeaways from Quantopian Shutting Down [Quant Rocket]

    Quantopian announced that it is shutting down its community platform. This doesnt entirely come as a surprise. Quantopian returned money to investors earlier this year after its investment strategy underperformed. It shut down paper trading in 2019 (having already ended live trading in 2017), then terminated its daily contests in May of this year. Since that time, Quantopian's website has

Quantocracy’s Daily Wrap for 11/03/2020

This is a summary of links featured on Quantocracy on Tuesday, 11/03/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Improving the use of correlations in portfolio optimisation when handcrafting [Investment Idiocy]

    Remember the handcrafting method, which I described in this series of posts? Motivating portfolio construction Methodology Implementing Testing Adjusting portfolio weights for Sharpe Ratios All very nice, all very theoretically grounded, except for one thing: the 'candidate matrices'. Remember, what we do is group our portfolio into subportfolios of 2 or 3 assets, and find some initial

Quantocracy’s Daily Wrap for 11/02/2020

This is a summary of links featured on Quantocracy on Monday, 11/02/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Dead versus The Living Stocks [Factor Research]

    Zombie stocks are a diverse group, both from a country and sector perspective Zombie stocks were fundamentally riskier, yet outperformed non-zombie stocks over the last year Oddly, investors need to pay up as they are also more expensive INTRODUCTION Walking through financial centers like London or New York in the spring of this year felt in many ways like being a zombie movie. Shops were boarded
  • What Assumptions Are You Making About Time In Your Trading? [Robot Wealth]

    I recently listened to a podcast about one of the earliest human civilizations the ancient Sumerians. Apparently, our system of minutes, hours, and days has been with us since the time of these ancient people, who developed it based on a simple base-12 counting system: There are three joints in each of the four fingers You can count twelve by tapping each joint in turn with the thumb of the
  • How Do You Think the Global Market Portfolio Has Performed from 1960-2017? [Alpha Architect]

    This paper complements Doeswijk, Lam, and Swinkels 2014 paper, which documents the historical composition of the market portfolio. Doeswijk, Lam, and Swinkel stopped their research in building the market portfolio, but left the work of the market portfolios historical returns undone. In this post, the original authors pick up where they left off and work on finding the returns of the

Quantocracy’s Daily Wrap for 11/01/2020

This is a summary of links featured on Quantocracy on Sunday, 11/01/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • New Site! Stock Market Valuation and the 2020’s in R [Light Finance]

    Ive been thinking about valuations a lot lately. If youve been following the stock market in recent months, then you will doubtlessly be aware that the past 6-months have witnessed a historic 44% rally across global markets. This rally has drawn particular attention because it has been dominated by tech stocks which deftly shrugged of lockdowns and the ensuing recession. The combination of
  • Podcast with Wes Gray of @AlphaArchitect [System Trader Show]

    Wes Gray after serving as a Captain in the United States Marine Corps earned an MBA and a PhD in the finance from the University of Chicago where he studied under Nobel Prize Winner Eugene Fama. He worked as a finance professor at Drexel University. He then found Alpha Architect a research-intensive asset management firm with a focus on high-conviction value and momentum factor exposures. In
  • Scanning Crypto Exchange for Available Cryptocurrency Close Price-Series [Quant at Risk]

    One of the most common problem encountered by all novice researches of the crypto-markets and (algo-)traders is knowing a list of all cryptocurrency pairs being actively traded at specific crypto exchange. This knowledge is a gateway to a vast research over correlations of crypto-assets, looking for arbitrage trading opportunities, targeting exchanges with most liquid assets or lowest spreads,
  • Fundamental trend following [SR SV]

    Fundamental trend following uses moving averages of past fundamental data, such as valuation metrics or economic indicators, to predict future fundamentals, analogously to the conventions in price or return trend following. A recent paper shows that fundamental trend following can be applied to equity earnings and profitability indicators. One approach is to pool fundamental information across a

Quantocracy’s Daily Wrap for 10/31/2020

This is a summary of links featured on Quantocracy on Saturday, 10/31/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Using AWS Timestream for tick data [Cuemacro]

    Whats the most important thing we need to have in order to follow financial markets? Burgers ok, I made that up, the real answer is market data! Whilst there are many other datasets including those drawn from alternative data, which are becoming increasingly important, having a handle on the asset prices is still key. When it comes to daily data, storing it is pretty easy. We can use an SQL
  • Combining Value and Profitability Factors to Improve Performance [Alpha Architect]

    The 1997 publication of Mark Carharts paper On Persistence in Mutual Fund Performance led to the four-factor model, which added momentum to market beta, size, and value, becoming the workhorse model in financereplacing the Fama-French three-factor model. The next major contribution came from Robert Novy-Marx. His 2013 paper The Other Side of Value: The Gross Profitability Premium
  • Momentum Trading Strategies Course [CSS Analytics]

    This post contains affiliate links. An affiliate link means CSSA may receive compensation if you make a purchase through the link, without any extra cost to you. CSSA strives to promote only products and services which provide value to my business and those which I believe could help you, the reader. One of the biggest barriers to creating a quantitative strategy is knowing how to code. The other

Quantocracy’s Daily Wrap for 10/30/2020

This is a summary of links featured on Quantocracy on Friday, 10/30/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Migrating from @Quantopian to QuantConnect [Quant Connect]

    As some may know, on October 29th, Quantopian users received notification the company would be terminating its free community platform on November 14th, leaving users with two weeks to download their code and find another home. We understand this closure has come suddenly, leaving many quants adrift. While we know not all will migrate to Quantconnect, our goal with this post is to let the
  • My Thoughts on Quantopian’s Closing [Robot Wealth]

    I was very sad to learn that Quantopian is shutting down its community services. Quantopians efforts to bring quant finance outside of institutions was a genuine game-changer. The educational content was solid, the tech was excellent, and the QuantCon conferences were professional, well-run, and inclusive in a way that you never see at the finance insider equivalents. Any of us who are