Quantocracy

Quant Blog Mashup

ST

Quantocracy’s Daily Wrap for 08/01/2017

This is a summary of links featured on Quantocracy on Tuesday, 08/01/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Tactical Asset Allocation in July [Allocate Smartly]

    This is a summary of the recent performance of a wide range of excellent tactical asset allocation strategies. 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 follow these strategies in
  • Leveraged ETF A Simulation [Alphaism]

    This post is a token of appreciation for Faisal Habib who taught us structured products this summer. As commonly known among people who are familiar with leveraged ETFs, the tracking error of those products tend to be larger than what we intuitively expected. This phenomenon has been explored and explained by Avellaneda and Zhang (2009). More information can also be found here. In a nutshell, the

Quantocracy’s Daily Wrap for 07/31/2017

This is a summary of links featured on Quantocracy on Monday, 07/31/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Academic Research Insight: Digging into ETF Trading Spreads [Alpha Architect]

    The article provides new empirical evidence on the state of market efficiencies in ETFs by studying the following questions: What is the magnitude of the ETF premiums across all US-listed ETFs and all underlying asset class and over time? In particular, what is the magnitude of true ETF premiums when stale NAVs are accounted for? What do these premiums depend on? What is the economic

Quantocracy’s Daily Wrap for 07/29/2017

This is a summary of links featured on Quantocracy on Saturday, 07/29/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Micro Caps, Factor Spreads, Structural Biases, and the Institutional Imperative [Factor Investor]

    So far in this series, weve covered faulty benchmark construction, the wide array of fundamental drivers, and the critical importance of quality in cutting through the noise among micro cap stocks. Now, we turn to the largest factor spreads Ive come across in any segment of the market, real world considerations for implementation, and why the dichotomy of scale versus alpha could result in a

Quantocracy’s Daily Wrap for 07/28/2017

This is a summary of links featured on Quantocracy on Friday, 07/28/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • We Love Free Data: Replacing Yahoo Finance Market Data [Robot Wealth]

    In keeping with our recent theme of providing useful tidbits of algo trading practicalities, heres an elegant solution that resolves Yahoos unceremonious exit from the free financial data space. Regular readers would know that I use various tools in my algo trading stack, but the one I keep coming back to, particularly when Im ready to start running serious simulations, is Zorro. Not only

Quantocracy’s Daily Wrap for 07/27/2017

This is a summary of links featured on Quantocracy on Thursday, 07/27/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Vigilant Asset Allocation from Dr. Wouter Keller and JW Keuning [Allocate Smartly]

    This is a test of the Vigilant Asset Allocation (VAA) strategy from the recently published paper: Breadth Momentum and Vigilant Asset Allocation, by Dr. Wouter Keller and JW Keuning. This is an aggressive momentum trading model, similar in spirit to Keller and Keunings popular Protective Asset Allocation strategy. Results versus the 60/40 benchmark from 1971 to the present, net of
  • Trend and Carry Everywhere [Cantab Capital]

    Simple rules on macro assets can create very attractive returns. We present a simple trend system and a simple carry system and show how the combination of the two return streams appears very attractive. Summary Trend following in one form or another has been an investment style for decades. Surprisingly to us, there is still a considerable amount of mystery about how trend works and the important
  • Financialization of Crude Oil Market [Quantpedia]

    The financialization of crude oil markets over the last decade has changed the behavior of oil prices in fundamental ways. In this paper, we uncover the gradual transformation of crude oil from a physical to a financial asset. Although economic demand and supply factors continue to play an important role, recent indicators associated with financialization have emerged since 2008. We show that
  • Derivatives Pricing II: Volatility Is Rough [Quant Start]

    In this new article series QuantStart returns to the discussion of pricing derivative securities, a topic which was covered a few years ago on the site through an introduction to stochastic calculus. Imanol Prez, a PhD researcher in Mathematics at Oxford University, and an expert guest contributor to QuantStart discusses how the assumption of constant volatility in the Black-Scholes model can be

Quantocracy’s Daily Wrap for 07/26/2017

This is a summary of links featured on Quantocracy on Wednesday, 07/26/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Why Today s Fed Day Setup May Not Be As Bullish As Most [Quantifiable Edges]

    Wednesday is a Fed Day. Fed Days have historically shown an upside tendency. I have documented this tendency in great detail over the years, with the most complete documentation coming in The Quantifiable Edges Guide to Fed Days. Based on what the market did Tuesday, this does not seem to be the most favorable Fed Day setup. A big reason for this is that SPX closed at a 20-day high on Tuesday. Fed
  • Stochastic portfolio theory, revisited! [Quant Dare]

    Im here today to talk about the Stochastic Portfolio Theory (SPT). SPT is a relatively new portfolio management theory. It was first introduced in 1999 by Robert Fernholz. In my opinion, SPT is very attractive for several reasons: its theoretical, its not very well known and, most importantly, its cool. Lets begin this post with a gentle introduction to the topic. This theory is all
  • Testing Equity Factor Allocation Strategies With Random Portfolios [Capital Spectator]

    Designing and managing asset allocation strategies based on factors is promoted in some corners as a better way to build portfolios. Not surprisingly, theres no shortage of studies that support this view. But the jurys still out on whether its prudent to throw out the standard asset-class buckets. Factor-based investing can play a productive role in enhancing a conventionally designed

Quantocracy’s Daily Wrap for 07/24/2017

This is a summary of links featured on Quantocracy on Monday, 07/24/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Information Content in the Limit Order Book for Crude Oil Futures (WTI) [Golden Compass]

    Order book imbalance strategies have been a big alpha source in automated market making. Tick by tick observations provide important information about general market sentiment and direction, and high frequency trading firms (HFTs) have been very efficient at trading on this information at very low latency intervals. In their recent paper on HFT strategies, Goldstein, Kwan and Philip analyzed six
  • Separating Positions from Allocations [Following the Trend]

    Most trading models I see are missing an important concept. Its not a terribly difficult concept, but it is an important one. Its not at all strange that most traders, in particular on the retail side, are missing this point. Most trading books skip over it. Most books gloss over it, or just dont mention it at all. My books included. The Traditional Way Heres how a regular type of
  • Trick Question: How is the Momentum Factor Performing YTD? [Alpha Architect]

    If you ask your typical long-only investor (or financial advisor) how momentum is doing this year theyll likely say, Amazing! This statement will almost surely be based on the fact they own (or know about) the iShares Momentum Factor Fund (Ticker: MTUM). MTUM is on fire year to date (through 5/31/2017):(1) 17.42% based on market prices versus 8.66% for the S&P 500 Total Return
  • The Case for the Harmonic Mean P/E Calculation [EconomPic]

    The most recent "analysis" seemingly spreading like wildfire across the perma-bear community was performed by Horizon Kinetics in their most recent quarterly commentary. Their claim is that the price-to-earnings of the Nasdaq (or any index really) is much higher than reported because we are being fed a manipulated harmonic mean rather than arithmetic mean calculation for the price to
  • Managing Capital Market Assumption Risk [Flirting with Models]

    Calculating an optimal portfolio from a set of capital market assumptions (CMAs) is a straightforward quantitative exercise, but the results are highly dependent on the assumptions holding in the future. Any portfolio that is initially assumed to be optimal will be sub-optimal if any single assumed parameter turns out to be different. By utilizing multiple sets of capital market assumptions, we
  • Academic Research Insight: When Does International Investing Make Sense? [Alpha Architect]

    What are the research questions? Market globalization is said to be the culprit of decreased benefits of international diversification. In 1995, a US investor investing in Vodafone had exposure to 99% of UK based sales. The same investor in 2012 is exposed to UK sales only for 8% while at the same time he is exposed to 30% of US sales, his home country. Vodafone is an example of a multinational

Quantocracy’s Daily Wrap for 07/21/2017

This is a summary of links featured on Quantocracy on Friday, 07/21/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Building an Insider Trading Database and Predicting Future Equity Returns [EP Chan]

    Ive long been interested in the behavior of corporate insiders and how their actions may impact their companys stock. I had done some research on this in the past, albeit in a very low-tech way using mostly Excel. Its a highly compelling subject, intuitively aligned with a companys equity performance – if those individuals most in-the-know are buying, it seems sensible that the stock
  • Trend-Following with Valeriy Zakamulin: Types of Moving Averages (Part 2) [Alpha Architect]

    In my previous blog post we considered the general weighted moving average. In this post we aim to give an overview of some specific types of moving averages. Specifically, we cover ordinary moving averages and mention some examples of exotic moving averages. Ordinary Moving Averages These are the most common types of moving averages used to time the market.(1) Simple Moving Average The

Quantocracy’s Daily Wrap for 07/19/2017

This is a summary of links featured on Quantocracy on Wednesday, 07/19/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How to Run Trading Algorithms on Google Cloud Platform in 6 Easy Steps [Robot Wealth]

    Earlier this year, I attended the Google Next conference in San Francisco and gained some first hand perspective into whats possible with Googles cloud infrastructure. Since then, Ive been leaning on Google Cloud Platform (GCP) to run my trading algorithms (and more) and it has become an important tool in my workflow. In this post, Im going to show you how to set up a GCP cloud compute
  • How to Improve Shiller’s CAPE Ratio [Quantpedia]

    The accuracy of U.S. stock return forecasts based on the cyclically-adjusted P/E (CAPE) ratio has deteriorated since 1985. The issue is not the CAPE ratio, but CAPE regressions that assume it reverts mechanically to its long-run average. Our approach conditions mean reversion in the CAPE ratio on real (not nominal) bond yields, reducing out-of-sample forecast errors by as much as 50%. At present,

Quantocracy’s Daily Wrap for 07/18/2017

This is a summary of links featured on Quantocracy on Tuesday, 07/18/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Backtesting Systematic Trading Strategies in Python: Considerations and Open Source Frameworks [Quant Start]

    In this article Frank Smietana, one of QuantStart's expert guest contributors describes the Python open-source backtesting software landscape, and provides advice on which backtesting framework is suitable for your own project needs. Backtesting is arguably the most critical part of the Systematic Trading Strategy (STS) production process, sitting between strategy development and deployment
  • EconomVIX…A Summary of Past VIX Posts [EconomPic]

    RCM Alternatives has a great piece (HT Tadas) out outlining what the VIX is, the market for VIX related products, and how to think about volatility as an asset class. It also happens to contain my new favorite quote for anyone thinking about trading volatility: Still, if you cannot see the VIX futures curve in your head, burning $100 bills is probably more profitable than trading them. I'll
  • Academic Research Insights: Does the Scope of the Sell-Side Analyst Industry Matter? [Alpha Architect]

    What are the research questions? Do variations in aggregate measure of size and activity of sell-side analysts affect the quality of research produced by that industry? Do those same variations in aggregate measures of size and activity of sell-side analysts affect optimism bias in the research produced? Do those variations extend to sectors where information is easily obtained and modelled? Do