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Quantocracy’s Daily Wrap for 05/04/2020

This is a summary of links featured on Quantocracy on Monday, 05/04/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Using Apache Airflow to Extract CoT Data [Robot Wealth]

    In todays post we are going to be extracting CoT (Commitment of Traders) reports from the CFTC website using a pipeline built on Apache Airflow. What is CoT data? The CoT report is a weekly publication which reports the open positions of market participants in the U.S futures market. Its published every Friday at 3:30 E.T but the actual report from the participants is compiled on the same
  • Online Portfolio Selection: Momentum [Hudson and Thames]

    Today we will be exploring the second chapter of our newest online portfolio selection module, momentum. Momentum strategies have been a popular quantitative strategy in recent decades as the simple but powerful trend-following allows investors to exponentially increase their returns. This module will implement two types of momentum strategies with one following the best-performing assets in the
  • Value Crashes: Deep History [Two Centuries Investments]

    Value investing is struggling big time! As of March 2020, Value factor is down -51% from the peak reached 14 years ago. It is the longest and largest drawdown in values recent history. Many value investors have already rotated into growth. The remaining diehards also want to quit. Even Warren Buffett is selling. Source: Professor French Source: Professor French Is value investing dead? In the
  • Market Profile Chart in Octave [Dekalog Blog]

    In a comment on my previous post, visualising Oanda's orderbook, a reader called Darren suggested that I was over complicating things and should perhaps use a more established methodology, namely Market Profile. I had heard of Market Profile before Darren mentioned it, but had always assumed that it required access to data that I didn't readily have to hand, i.e. tick level data. With my
  • Merger Arbitrage: Arbitraged Away? [Factor Research]

    As AUM in merger arbitrage has increased, alpha decreased Investors can access merger arbitrage via hedge funds, bank indices, and ETFs The strategy is not as uncorrelated from equities as likely perceived by allocators INTRODUCTION Working in the restructuring team of a corporate finance boutique is like being a trader focused on short-selling. Most money is made when companies falter, and stocks
  • Equilibrium theory of Treasury yields [SR SV]

    An equilibrium model for U.S. Treasury yields explains how macroeconomic trends and related expectations for future short-term interest rates shape the yield curve. Long-term yield trends arise from learning about stable components in GDP growth and inflation. They explain the steady rise of Treasury yields in the 1960s-1980s and their decline in the 1990s-2010s. Cyclical movements in yields

Quantocracy’s Daily Wrap for 05/01/2020

This is a summary of links featured on Quantocracy on Friday, 05/01/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Tactical Asset Allocation in April: Stubbornly Defensive [Allocate Smartly]

    Tactical Asset Allocation (TAA) dodged the worst of the bear in February and March, but trailed the big bounce in April. Entering May, TAA remains stubbornly defensive. We track 50+ TAA strategies sourced from books, papers, etc., allowing us to draw broad conclusions about TAA as a style. In the table below we show the MTD and YTD returns of these 50+ strategies: TAA is designed to earn its keep
  • Performance After 10% Up Months [Quantifiable Edges]

    April finished with a 12.7% gain for the SPX. That is the strongest 1-month gain since January of 1987. In last nights subscriber letter I decided to look back at all other instances following 1-month SPX (or its predecessor the S&P 90) gains of 10% or more. The table below shows all instances since 1928. 2020-05-01 The averages, medians, and % wins all look very mild, suggesting there may
  • What’s the Story Behind EBIT/TEV? [Alpha Architect]

    A common question we receive at Alpha Architect is the following: Why do you focus on EBIT/TEV as a value screen for stocks instead of the more traditional measures such as book to price? In short, we believe stocks are ownerships in businesses (I know that sounds crazy coming from a quant shop!). As systematic business buyers, we want a valuation metric (or set of metrics) that, 1) make economic

Quantocracy’s Daily Wrap for 04/30/2020

This is a summary of links featured on Quantocracy on Thursday, 04/30/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Using random forest to model limit order book dynamic [R Trader]

    In this article I use the random forest algorithm to forecast mid price dynamic over short time horizon i.e. a few seconds ahead. This is of particular interest to market makers to skew their bid/ask spread in the direction of the most favorable outcome. Most if not all the literature on the topic (see references below) focuses on applying straight out of the box algorithm to create forecast at
  • The VIX Futures Basis [Robot Wealth]

    In the eye of the recent storm, with VIX up over 50, many traders were looking to short the VIX using products like TVIX. Surely its going to coming back down? Well yeah, it will, eventually, but that doesnt mean that you can profitably short VIX products. First, some basics What is VIX? VIX is a benchmark index for SPX volatility. It shows the SPX options markets expected
  • Understanding Neural Networks (with Graphs) [Quant Dare]

    Artificial Neural Networks (ANN) have been applied with success to many daily tasks that needed human supervision, but due to its complexity, it is hard to understand how they work and how they are trained. Along this blog, we have deeply talked about what Neural Networks are, how they work, and how to apply them to problems such as finding outliers or forecasting financial time series. In this

Quantocracy’s Daily Wrap for 04/28/2020

This is a summary of links featured on Quantocracy on Tuesday, 04/28/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How to Design Intraday Algo-Trading Model for Cryptocurrencies using Bitcoin-based Signals? [Quant at Risk]

    With a growing popularity of cryptocurrencies and their increasing year-over-year traded volumes, crypto algo-trading is a next big thing! If you study this market closely you will notice that it offers quick gains in much shorter unit of time comparing to stocks or FX. No wonder why a participation in trading, even using mobile apps like Coinbase or Binance attracts more people now than ever. A
  • Overnight Risk Premium in Equity and Commodity Markets [Philipp Kahler]

    Over the last 20 years equity markets and ETFs did a significant part of their total performance over night. This article will examine the relationship of in-session moves vs. the out-of-session moves of ETFs and commodities. The overnight risk premium As an investor you can expect to get paid for taking risk. If someone sell its stock to you he gets the risk free return for holding cash, but you
  • Ways to Measure Extreme Downside Risk [Alpha Architect]

    Larry Swedroe recently wrote a post titled Is there a Tail Risk Premium in Stocks. This post is a good complement to Larrys as this paper proposes two new measures of systematic tail risk and explores whether they are associated with a significant risk premium. The first measure, Extreme Downside Correlation (EDC), is based on the tendency of stock returns to crash at the same time as the

Quantocracy’s Daily Wrap for 04/27/2020

This is a summary of links featured on Quantocracy on Monday, 04/27/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Introducing Online Portfolio Selection [Hudson and Thames]

    Online Portfolio Selection is an algorithmic trading strategy that sequentially allocates capital among a group of assets to maximize the final returns of the investment. Traditional theories for portfolio selection, such as Markowitzs Modern Portfolio Theory, optimize the balance between the portfolios risks and returns. However, OLPS is founded on the capital growth theory, which solely
  • VIX – Simple and Intuitive Explanation of Volatility Index [Only VIX]

    Few years ago I published two post trying to give simple explanations and intuition behind complicated formulas used for calculating vol indexes. However few of you emailed that some charts are missing from these older posts, and for technical reasons since I could not restore them, I decided to re-created new charts from scratch, and re-write the posts. In this post I will make many
  • Tranching, Trend, and Mean Reversion [Flirting with Models]

    In past research we have explored the potential benefits of how-based diversification through the lens of pay-off functions. Specifically, we explored how strategic rebalancing created a concave payoff while momentum / trend-following created a convex payoff. By combining these two approaches, total portfolio payoff became more neutral to the dispersion in return of underlying assets. We have also
  • Tail Risk Hedge Funds [Factor Research]

    Tail risk funds tend to be most in demand when they are least attractive Short-term bonds provided similar benefits to tail risk funds The TAIL ETF closely replicates the performance of tail risk funds INTRODUCTION In a year where the S&P 500 lost more than 30% in a few weeks, there are few headlines that draw as much attention as these: This Black Swan Trade Saw 1,000% Profits This Week

Quantocracy’s Daily Wrap for 04/26/2020

This is a summary of links featured on Quantocracy on Sunday, 04/26/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Efficiently Simulating Geometric Brownian Motion in R [Robot Wealth]

    For simulating stock prices, Geometric Brownian Motion (GBM) is the de-facto go-to model. It has some nice properties which are generally consistent with stock prices, such as being log-normally distributed (and hence bounded to the downside by zero), and that expected returns dont depend on the magnitude of price. Of course, GBM is just a model and no model is a perfect representation of

Quantocracy’s Daily Wrap for 04/25/2020

This is a summary of links featured on Quantocracy on Saturday, 04/25/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Podcast with @MebFaber: Why an investment plan is a must and how to behave in a market crash [System Trader Show]

    Meb Faber is a co-founder and the Chief Investment Officer of Cambria Investment Management. His speciality is quant investing. Meb is the host of The Meb Faber Show podcast and has authored numerous white papers and books. He is a frequent speaker and writer on investment strategies and has been featured in Barrons, The Wall Street Journal, The New York Times, and The New Yorker. In this
  • Risk premia [OSM]

    Our last post discussed using the discounted cash flow model (DCF) as a method to set return expectations that one would ultimately employ in building a satisfactory portfolio. We noted that if one were able to have a reasonably good estimate of the cash flow growth rate of an asset, then it would be relatively straightforward to calculate the required return. The problem, of course, is figuring
  • Research Review | 24 April 2020 | Covid-19 Blowback [Capital Spectator]

    Howell E. Jackson (Harvard Law School) and Steven L. Schwarcz (Duke U.) April 19, 2020 The coronavirus has produced a public health debacle of the first-order. But the virus is also propagating the kind of exogenous shock that can precipitate and to a considerable degree is already precipitating a systemic event for our financial system. This currently unfolding systemic shock comes a
  • Visualising Oanda’s Orderbook [Dekalog Blog]

    My earlier post of 26th March shows code to visualise the most recent instantaneous snapshot of Oanda's order book, realised as a horizontal bar chart superimposed over a price chart. Below is a screen shot of a different type of chart designed to show the historical order book, which is similar to the proprietary Bookmap software. The background of the chart is a heatmap of the 20 order book

Quantocracy’s Daily Wrap for 04/23/2020

This is a summary of links featured on Quantocracy on Thursday, 04/23/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Paul Novell’s Flagship Strategy SPY-COMP [Allocate Smartly]

    This is a test of the flagship proprietary strategy from Paul Novells Investing for a Living. Paul has been kind enough to share his strategy rules to allow for independent verification of his results. SPY-COMP is like Growth-Trend Timing and a handful of other tactical strategies we track, in that it considers trends in both prices and key economic indicators to switch between risk and
  • Trend Following is Everywhere [Alpha Architect]

    Similar to some better-known factors, such as size and value, time-series momentum (TSMOM) historically has demonstrated abnormal excess returns. For the less familiar with trend following its worth your time to review Alpha Architects white paper on trend following here. TSMOM is measured by a portfolio that is long assets that have had recent positive returns and short assets that have had
  • Trend Analysis using Open Interest, Rollover and FII/DII Activity in Python [Quant Insti]

    The first quarter of 2020 has been one of the most challenging times in the post World War II era. The crash in oil prices due to geopolitical reasons and the COVID-19 global pandemic were the dominant themes. Financial markets act as bellwethers and give us a reflection of the overall sentiment for the world economy. These sentiments are reflected not only in the price but also in other metrics
  • Brent Oil Price Time-Series in Python with 1-Minute Data Sampling [Quant at Risk]

    Recent actions in WTI Futures pricing on Apr 20, 2020 caused my curiosity to have a deep look at intraday crude oil price time-series. With no surprise, I couldnt find any free and effortlessly available dataset on the Internet. This is a common problem for lots of quants and data analysts: conducting your own research over financial markets you are doomed to download and use daily data. The
  • The Pandemic Portfolio – Risk Parity, Convexity, and Multi-Asset Factors in Extreme Markets [Invest Resolve]

    How long will the recession last? How deep will it be? What are the long-term implications for the economy, markets, and society? The global pandemic has ushered in a period of extreme uncertainty and investors are left with too many unanswered questions and afraid for their portfolios. Where do we go from here? In this episode, the ReSolve team begins with an examination of some of the

Quantocracy’s Daily Wrap for 04/22/2020

This is a summary of links featured on Quantocracy on Wednesday, 04/22/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Market Cap vs. Crash Severity [Alvarez Quant Trading]

    Has the market sell-off and subsequent bounce treated all stocks the same? A good portion of the bull market move from 2009 to 2019 has been led by the big-cap stocks. Did they hold up better during the March sell-off? What about with the bounce? Did the smaller-cap stocks have a bigger bounce? The Setup February 19 At the S&P 500 high on February 19, I took all 503 stocks in the index and
  • Hedging an Option through the Black-Scholes model in discrete time [Quant Dare]

    The Black-Scholes formula can be used to create a hedge for an option. However, this model is derived in continuous time. What happens when we use it to hedge an option in discrete-time? European options are financial securities which give their holder the right (but not the obligation) to buy or sell an asset (called the underlying asset) at a predetermined price (called the strike price) at a
  • Geek Note: How to Properly Lag Monthly Economic Data [Allocate Smartly]

    Well be talking about Paul Novells flagship SPY-COMP strategy on the blog tomorrow. The strategy uses monthly economic data, like the kind available from the FRED database. Weve covered a handful of strategies like this in the past (think Philosophical Economics Growth Trend-Timing). Whenever we do, we invariably get a ton of questions, because it can be confusing to determine how to
  • How to Compute Active Share [Alpha Architect]

    In the short video below, I show how to compute Active Share. The accompanying excel file with the formulas can be found here. I start by computing the active share for two hypothetical funds, and then examine the active share of a few live ETFs.

Quantocracy’s Daily Wrap for 04/21/2020

This is a summary of links featured on Quantocracy on Tuesday, 04/21/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Factor Momentum vs Factor Valuation [Falkenblog]

    I am not a fan of most equity factors, but if any equity factor exists, it is the value factor. Graham and Dodd, Warren Buffet, Fama and French have all highlighted value as an investment strategy. Its essence is the ratio of a backward-looking accounting value vs. a forward-looking discounting of future dividends. As we are not venture capitalists, but rather, stock investors, all future