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Quantocracy’s Daily Wrap for 09/20/2018

This is a summary of links featured on Quantocracy on Thursday, 09/20/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Market Timing The Credit Cycle [EconomPic]

    Over the last few years, youve likely heard the following competing narratives: Credit spreads are tight, a sign of exuberance among investors that are willing to overlook risk. This will end in tears. Credit spreads are tight, reflecting an environment of high economic growth and low default rates. This supports risk assets. This post will outline why both of the above comments
  • Practical TDD and numerical precision [Quant Dare]

    The Test Driven Development (TDD) philosophy improves your productivity and helps you write better code. But if you are new at it, you might find some trouble with its procedures. Lets dive into a simple example that (hopefully) will help you solve it. When applying TDD methodology, the objective is to have the most robust and reliable code. To do so, we would need to get all the tests passed,
  • SPX Near Monthly Highs With RUT Near Monthly Lows [Quantifiable Edges]

    I have spoken a fair amount lately about the split market, and how that has historically been followed by declines. But not all kinds of splits are bad. Wednesday we saw the SPX rise while the RUT closed lower. That is not unusual on a 1-day basis. But it has now been several weeks in which they have been heading in opposite directions. RUT closed in the bottom 25% of its 20-day range on

Quantocracy’s Daily Wrap for 09/19/2018

This is a summary of links featured on Quantocracy on Wednesday, 09/19/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Accelerating Dual Momentum [Allocate Smartly]

    This is a test of the tactical asset allocation strategy Accelerating Dual Momentum (ADM) from EngineeredPortfolio.com. ADM is especially aggressive strategy that ties together multiple concepts from other TAA models that we track. Results from 1990 to the present, net of transaction costs, follow. Read more about our backtests or let AllocateSmartly help you follow this strategy in near
  • StockCharts Technical Rank (SCTR) Rotation Strategy [Alvarez Quant Trading]

    My post last week on the analysis of SCTR produced lots of emails and comments with great ideas. One idea that I liked was a simple rotation strategy using SCTR. I mentioned in the post that maybe using SCTR as ranking method would produce different results. Normally I dont post this quickly but I wanted to share these new results because they give a different view of SCTR. The Test Date range:

Quantocracy’s Daily Wrap for 09/18/2018

This is a summary of links featured on Quantocracy on Tuesday, 09/18/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Momentum Investing, Like Value Investing, is Simple, but NOT Easy [Alpha Architect]

    Weve covered momentum investing extensively over the years, to include 94 posts, a book on the subject, and numerous discussions on various podcast outlets. There are a few things one notices after thinking about a topic for so long: You forgot half of the things you read and/or wrote (yes, we have redone research on specific ideas and realized after that fact that we had already done the same
  • Maximum Pain Theory [Only VIX]

    I think if you're reading this blog, you're probably already a knowledgeable options trader, and have heard of maximum pain theory – an idea that market moves in a path that hurts ( causes losses ) most amount of market participants. In options it is typically stated that simulating options expiration losses by open interest at different strikes will help you to divine its expiration

Quantocracy’s Daily Wrap for 09/17/2018

This is a summary of links featured on Quantocracy on Monday, 09/17/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Principal Component Momentum? [QuantStrat TradeR]

    This post will investigate using Principal Components as part of a momentum strategy. Recently, I ran across a post from David Varadi that I thought Id further investigate and translate into code I can explicitly display (as David Varadi doesnt). Of course, as David Varadi is a quantitative research director with whom Ive done good work with in the past, I find that trying to investigate
  • Beating the S&P500 Index with a Low Convexity Portfolio [Jonathan Kinlay]

    A primer on beta convexity and its applications is given in the following post: The essential idea is to evaluate the beta of stock during down-markets, separately from periods when the market is performing well. Beta convexity is a measure of how stable a stock beta is across market regimes, and by choosing a portfolio of stocks with low beta-convexity we seek to stabilize the overall risk
  • Leveraged ETFs and Volatility Jumps [Alpha Architect]

    The paper investigates the following research question: What has the absolute risk behavior of leveraged products been historically? Did they behave as intended by design? Is the leverage multiple a reliable indicator of the volatility multiple? Is the leverage multiple a reliable indicator over shorter horizons? What are the Academic Insights? By studying the empirical evidence of the top 10
  • Portfolio Optimization: Simple versus Optimal Methods [Invest ReSolve]

    Our whitepaper The Optimization Machine: A General Framework for Portfolio Choice presented a logical framework for thinking about portfolio optimization given specific assumptions regarding expected relationships between risk and return. We explored the fundamental roots of common portfolio weighting mechanisms, such as market cap and equal weighting, and discussed the rationale for several
  • A Trend Equity Primer [Flirting with Models]

    Trend-following strategies exploit the fact that investors exhibit behavioral biases that cause trends to persist. While many investment strategies have a concave payoff profile that reaps small rewards at the risk of large losses, trend-following strategies exhibit a convex payoff profile, one that pays small premiums with the potential of a large reward. By implementing a trend-following
  • Short-Term Momentum in Equity Factors [Factor Research]

    Short-term momentum persists in common equity factors The persistence is strong in Value and Dividend Yield However, these results conflict with short-term mean-reversion on equity index level INTRODUCTION When Trump won the US presidential election in November 2016, small and cheap stocks started rallying, which surprised most investors as the consensus was a risk-off positioning. As new trends
  • Visualizing Time Series Data [Eran Raviv]

    This post has two goals. I hope to make you think about your graphics, and think about the future of data-visualization. An example is given using some simulated time series data. A very quick read. In visualization, like in programming, presenting or any other skill, there is much to learn. Also like in other skills, there is no one best way of doing things. Rather, creating a good chart is
  • Our Extremely Split Market & What That Has Meant Historically [Quantifiable Edges]

    One indicator that has gotten some play in the news lately is the Hindenburg Omen. In last weekends subscriber letter I discussed the Hindenburg Omen signal in detail. (Click here for a free trial.) A core premise behind the Hindenburg Omen is that there are a large number of stocks hitting both new highs and new lows. This indicates a split market. When this has happened for multiple days
  • State of Trend Following in August [Au Tra Sy]

    A late edition of the State of Trend Following report, showing a strong return for August and a YTD figure back in the black. Please check below for more details. Detailed Results The figures for the month are: August return: 6.74% YTD return: 3.36% Below is the chart displaying individual system results throughout August: StateTF August And in tabular format: System August Return YTD Return

Quantocracy’s Daily Wrap for 09/16/2018

This is a summary of links featured on Quantocracy on Sunday, 09/16/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Law of Large Numbers – Part 2 [Robot Wealth]

    Even if youve never heard of it, the Law of Large Numbers is something that you understand intuitively, and probably employ in one form or another on an almost daily basis. But human nature is such that we sometimes apply it poorly, often to great detriment. Interestingly, psychologists found strong evidence that, despite the intuitiveness and simplicity of the law, humans make systematic

Quantocracy’s Daily Wrap for 09/15/2018

This is a summary of links featured on Quantocracy on Saturday, 09/15/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Predicting equity volatility with return dispersion [SR SV]

    quity return dispersion is measured as the standard deviation of returns across different stocks or portfolios. Unlike volatility it can be measured even for a single relevant period and, thus, can record changing market conditions fast. Academic literature has shown a clear positive relation between return dispersion, volatility and economic conditions. New empirical research suggests that return
  • How Leverage Constraints Effect Mutual Fund Risk Taking [Alpha Architect]

    The 2014 study by Andrea Frazzini and Lasse Heje Pedersen, Betting Against Beta, found strong support for low-beta strategies. Ive previously written on low-beta strategies here. This paper finds that, for U.S. stocks, the betting against beta (BAB) factor (a portfolio that holds low-beta assets, leveraged to a beta of 1, and that shorts high-beta assets, de-leveraged to a beta of 1)
  • Video: Alpha Architect Weekly Research Recap [Alpha Architect]

    You can watch the video via the link below: Video Summary Ryan and I discuss three articles published on our blog this week. First, we examine a summary by Larry Swedroe that highlights the Betting Against Beta (BAB) factor and dives into two new papers examining when the BAB factor performs well. Second, we discuss a paper titled The Conservative Formula: Quantitative Investing Made Easy

Quantocracy’s Daily Wrap for 09/12/2018

This is a summary of links featured on Quantocracy on Wednesday, 09/12/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • StockCharts Technical Rank (SCTR) Indicator Analysis [Alvarez Quant Trading]

    Overall the last few months, Ive had several consulting clients strategy use SCTR for either a ranking or a filter. I finally got curious about the predictive ability of SCTR. How good is? I could find no information on how each of the ranking buckets did X days later on StockCharts.com. Maybe these results are hidden behind the paywall which I do not have access to. I developed PowerRatings
  • The Conservative Formula: Quantitative Investing made Easy [Alpha Architect]

    Is it possible to build a simple systematic approach that beats investing in complex factor models? The research team here has proposed that a simple formula based on low return volatility, high net payout yield (dividends +/- stock buybacks), and strong price momentum gives investors exposure to the most important factor premiums in one easy-to-implement investment strategy. Does the conservative
  • Evening class imbalance before the war [Quant Dare]

    Class imbalance can seriously damage the precision of your binary classifier. In this post you will learn some simple ways of evening the size of your classes before training to prevent your classifier from cheating. The class imbalance problem Binary classification is a very common problem in machine learning. The algorithm learns the underlying relationship between the features and the label.

Quantocracy’s Daily Wrap for 09/11/2018

This is a summary of links featured on Quantocracy on Tuesday, 09/11/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • FX Risk, International ETFs and Asset Allocation [Allocate Smartly]

    In our previous post, we touched on FX rates and their impact on international ETFs like EFA or EEM. In short, because international ETFs trading in the US are denominated in USD, most are affected not just by changes in underlying assets, but also by changes in the exchange rate between USD and local currencies (1). This FX risk can have a huge impact on performance. That came as a surprise to

Quantocracy’s Daily Wrap for 09/10/2018

This is a summary of links featured on Quantocracy on Monday, 09/10/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Volatility White Papers and Presentations [Six Figure Investing]

    Below Ive collected links to some of my favorite white papers and presentations on volatility. Ive organized them in the following categories: Volatility Concepts & Volatility Trading Probability DistributionsNormal and Otherwise The VIX and VIX Futures Volatility ContagionWill Short Volatility Destroy the World? Variance Swapsthe Technology That Underlies VIX & VIX Futures
  • The Misleading Lessons of History [Flirting with Models]

    Constructing an asset allocation that never lost money over given rolling periods leads to unsettling allocations: large positions in small-caps, long-term U.S. Treasuries, and precious metals. In many investment analyses, past results may be a downright misleading guide to the future because one realization of historical data leads to a result that is overfit. To combat this, a common approach it
  • What’s in Your Benchmark? [Alpha Architect]

    This article examines the magnitude of exposures to a set of systematic factors present in widely accepted Benchmarks (S&P500, the Russells, and MSCI global indices) and how they change over time. The authors use conventional style factors of value, size, quality, momentum, and minimum volatility, and third-party indexes tradeable via ETFs. MSCI single factor indices that are tracked by ETFs
  • Deep Learning – Artificial Neural Network Using Tensorflow In Python [Quant Insti]

    In this article, we are going to develop a machine learning technique called Deep learning (Artificial Neural network) by using tensor flow and predicting stock price in python. At the end of this article you will learn how to build artificial neural network by using tensor flow and how to code a strategy using the predictions from the neural network. System Requirements: Python 3.6 If you are new
  • Volatility, Dispersion & Correlation – Friends or Foes? [Factor Research]

    Higher volatility & dispersion imply higher stock market risks The relationship between correlation and risk is not linear However, these market technicals do not behave consistently across time INTRODUCTION Financial reporters frequently comment on stock market technicals like volatility and correlation, although most investors struggle to process this information adequately. The VIX jumping

Quantocracy’s Daily Wrap for 09/09/2018

This is a summary of links featured on Quantocracy on Sunday, 09/09/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Algo Trading Workshops with Dr. Ernie Chan (@ChanEP) in Australia

    A unique opportunity to attend one or all of Ernie Chan's signature workshops live in Sydney for the first time: Algorithmic Options Strategies A two day workshop on Wednesday 5 December and Thursday 6 December 2018 for $1,650 if bought separately. This workshop will focus on backtesting algorithmic trading strategies on options. Examples will be drawn from intraday events-driven trading,
  • Jonathan Kinlay on Volatility Modelling [Only VIX]

    Few weeks ago Dr Jonathan Kinlay from Quantitative Research and Trading blog published a series of excellent articles on volatility. I wanted to review and comment on the notes. Forecasting Volatility in the S&P500 Index Modeling Asset Volatility Long Memory and Regime Shifts in Asset Volatility Range-Based EGARCH Option Pricing Models There are four main articles that discuss practical