Quantocracy

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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

Quantocracy’s Daily Wrap for 09/08/2018

This is a summary of links featured on Quantocracy on Saturday, 09/08/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Earnings yields, equity carry and risk premia [SR SV]

    Forward earnings yields and equity carry are plausible indicators of risk premia embedded in equity index futures prices. Data for a panel of 25 developed and emerging markets from 2000 to 2018 show that index forward earnings yields have been correlated with market uncertainty across countries and time. Earnings yields have been highest in emerging countries. However, equity carries have not,

Quantocracy’s Daily Wrap for 09/06/2018

This is a summary of links featured on Quantocracy on Thursday, 09/06/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Asset Allocation Roundup [Allocate Smartly]

    Recent asset allocation articles (tactical or otherwise) that you might have missed: We Are All FX Traders Now (Alpha Scientist) Because international ETFs trading in the US (ex. EFA or EEM) are denominated in USD, most are affected not just by changes in the underlying assets, but also by changes in the exchange rate between USD and local currencies (the exception is the occasional
  • Equity Factors in Emerging Markets [Quantpedia]

    This study investigates the relation between a comprehensive set of firm-specific attributes and future equity returns for a sample of stocks from 27 emerging markets. Univariate analyses based on equal-weighted portfolio returns reveal that the low beta, firm size, book-to-market ratio, momentum and illiquidity anomalies are also observed in emerging markets whereas short-term reversal, left-tail

Quantocracy’s Daily Wrap for 09/04/2018

This is a summary of links featured on Quantocracy on Tuesday, 09/04/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Timing Equity Returns Using Monetary Policy [Flirting with Models]

    Can the monetary policy environment be used to predict global equity market returns? Should we overweight/buy countries with expansionary monetary policy regimes and underweight/sell countries with contractionary monetary policy regimes? In twelve of the fourteen countries studied, both nominal and real equity returns are higher (lower) when the central banks most recent action was to cut (hike)
  • Chasing Mutual Fund Performance [Factor Research]

    Mutual funds exhibit momentum when measured by their one-year performance Momentum disappears when more reasonable fund selection criteria are applied Performance does not seem effective for fund selection for a full market cycle CHASING PERFORMANCE Chasing mutual fund performance suffers from a bad reputation these days. Of course, perspectives change all the time in finance. What was once
  • PPI and the Stock Market [CXO Advisory]

    Inflation at the producer level (derived from the Producer Price Index PPI) is arguably an advance indicator for inflation downstream at the consumer level (derived from the Consumer Price Index CPI). Do investors therefore reliably react to changes in PPI as an indicator of the future wealth discount rate? In other words, is a high (low) producer-level inflation rate bad (good) for the

Quantocracy’s Daily Wrap for 09/02/2018

This is a summary of links featured on Quantocracy on Sunday, 09/02/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Tactical Asset Allocation in August [Allocate Smartly]

    This is a summary of the recent performance of a wide range of excellent tactical asset allocation strategies, net of transaction costs. These strategies are sourced from books, academic papers, and other publications. While we dont (yet) include every published TAA model, these strategies are broadly representative of the TAA space. Learn more about what we do or let AllocateSmartly help you

Quantocracy’s Daily Wrap for 09/01/2018

This is a summary of links featured on Quantocracy on Saturday, 09/01/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Beta herding [SR SV]

    Beta herding means convergence of market betas of individual stocks that arises from investors biased perceptions. Adverse beta herding denotes the dispersion of such betas that arises from a reversal of the bias. A new paper suggests that overconfidence in predictions of overall market direction and positive sentiment are key drivers of beta convergence, while uncertainty and negative
  • R Code Best practices [R Trader]

    Nothing is more frustrating than a long piece of code with no standard way of naming elements, presenting code or organizing files. Its not only unreadable but more importantly not reusable. Unfortunately, unlike other programming languages, R has no widely accepted coding best practices. Instead there has been various attempts to put together a few sets of rules. This post is trying to fill

Quantocracy’s Daily Wrap for 08/31/2018

This is a summary of links featured on Quantocracy on Friday, 08/31/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How Members Are Using Our Site and What That Says About TAA Investors [Allocate Smartly]

    Were in unique position to analyze the behavior of Tactical Asset Allocation investors. Our platform helps members analyze 40+ published TAA strategies from many angles, including: historical performance, tax efficiency, exposure to rising interest rates, etc. Members can combine those strategies together into what we call custom model portfolios, which they can then follow in near
  • Enhanced Factor Portfolios [Quantpedia]

    We dissect the performance of factor-based equity portfolios using a characteristics-based multi-factor expected return model. We show that generic single-factor portfolios, which invest in stocks with high scores on one particular factor, are sub-optimal, because they ignore the possibility that these stocks may be unattractive from the perspective of other factors. We also show that differences
  • Video Digest: Trade Optimization [Flirting with Models]

Quantocracy’s Daily Wrap for 08/29/2018

This is a summary of links featured on Quantocracy on Wednesday, 08/29/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Timing the Market with Google Trends Search Volume Data [iMarketSignals]

    Past research suggests that the relative change in the volume of Google searches for financial terms such as debt or stocks can be used to anticipate stock market trends. In this analysis the search term debt was used to obtain monthly search volume data from Google Trends. The analysis shows, that a decrease in search volume typically preceded price increases of the S&P 500
  • A Short Introduction On Using R For Tail-Risk Analytics [Capital Spectator]

    Interactive Brokers (IB) just published the second installment in a series Im writing for the brokerage firm about using R for portfolio analysis: Modeling Tail Risk In R With Value at Risk. Todays update (part deux) is more or less adapted from my recent book: Quantitative Investment Portfolio Analytics In R: An Introduction To R For Modeling Portfolio Risk and Return. Theres so much
  • Two New Strategies Added: Defensive Asset Allocation and Accelerating Dual Momentum [Allocate Smartly]

    Weve begun tracking two new tactical asset allocation strategies: Defensive Asset Allocation (DAA) and Accelerating Dual Momentum (ADM). Well be introducing both in more detail on our blog in the coming weeks. Members can review their historical performance and begin tracking them in near real-time in our members area now: DAA | ADM. Defensive Asset Allocation DAA is the latest strategy from

Quantocracy’s Daily Wrap for 08/27/2018

This is a summary of links featured on Quantocracy on Monday, 08/27/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Trade Optimization [Flirting with Models]

    Trade optimization is more technical topic than we usually cover in our published research. Therefore, this note will relies heavily on mathematical notation and assumes readers have a basic understanding of optimization. Accompanying the commentary is code written in Python, meant to provide concrete examples of how these ideas can be implemented. The Python code leverages the PuLP optimization
  • Factor Momentum [Factor Research]

    The Momentum strategy can be applied to stocks, sectors, countries and factors Factor momentum shows positive excess returns across regions However, single-stock Momentum performance is comparable and less complex to implement INTRODUCTION We recently investigated applying the long-short Momentum strategy to sectors and countries in Europe, which revealed positive excess returns (Sector versus
  • Crypto-asset Risks and Returns [CXO Advisory]

    How do the major crypto-assets (Bitcoin, Ripple, and Ethereum) stack up against conventional asset classes? In their August 2018 paper entitled Risks and Returns of Cryptocurrency, Yukun Liu and Aleh Tsyvinski apply standard tools of asset pricing to measure crypto-asset exposures to: 160 equity factors. Macroeconomic factors (non-durable consumption growth, durable consumption growth,
  • Fintwit Might Matter for Momentum and Mean Reversion in Stock Prices [Alpha Architect]

    Do users of social media provide valuable information about liquidity that can be used to predict future liquidity? Does social media provide useful information, over and above that provided by traditional, fundamental news sources? Do positive and negative sentiment have the same effects on markets? Does information gleaned from social-media improve trading strategies? What are the Academic
  • New Highs On Low Volume During August [Quantifiable Edges]

    SPX closed at a new all-time high on Friday. But NYSE volume came in at the lowest level since mid-July. Low volume at new highs can sometimes be a negative. Of course August frequently has low volume as many market participants are on vacation and not trading as actively. So I decided to look back at other times the SPX made a long-term high on light volume during the month of August. Results