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Quantocracy’s Daily Wrap for 06/18/2019

This is a summary of links featured on Quantocracy on Tuesday, 06/18/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Shannon Entropy: A Genius Gambler’s Guide to Market Randomness [Robot Wealth]

    Before you commit your precious time to read this blog post, I need to warn you that this is one of those posts that market nerds like myself will get a kick out of, but which probably wont add much of practical value to your trading. The purpose of this post is to scratch the surface of the markets from an information theoretic perspective, using tools developed by none other than the father
  • Factor Investing Research On Steriods [Alpha Architect]

    What are the research questions? Do the most prominent long/short factors value, momentum, carry, and defensive survive out of sample? Can long/short factors be timed? What are the Academic Insights? YES. All of the factors exist out of sample, albeit their magnitudes are generally muted.(1) NOT REALLY. After a mind-numbing battery of tests, the evidence is mixed and inconsistent across

Quantocracy’s Daily Wrap for 06/17/2019

This is a summary of links featured on Quantocracy on Monday, 06/17/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Time-Series Signals and Multi-Sector Bonds [Flirting with Models]

    We expand last weeks commentary to explore momentum, carry, value, and long-term reversal signals in a time-series context. Using these signals, we generate long/short portfolios for each asset class. We use a sub-sampling methodology to bootstrap and annualized return distribution. We find that the signals are only selectively significant, and rarely consistent. We believe this initial study
  • A Horse Race of Liquid Alternatives [Factor Research]

    Investors can access alternative strategies via mutual funds and ETFs Most of these show moderate to high correlations to equities, which is concerning Bonds would have been a better diversifier in recent years INTRODUCTION Investing is challenging as it is complex and complicated, which requires continuous learning and updating of mental frameworks. Conflicts and contradictions are found

Quantocracy’s Daily Wrap for 06/15/2019

This is a summary of links featured on Quantocracy on Saturday, 06/15/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • DeepTrading with TensorFlow II [Todo Trader]

    OK, you know what tensors are or perhaps you dont, but you are sure you want to use TensorFlow to trade with it. This post introduces you to how to create elemental NN tensors in TensorFlow. This is the second post of the serie, so you need to be familiarized with the concepts exposed in the first post DeepTrading with Tensorflow. Tensors Tensors (of order higher than two) are data structures
  • DeepTrading with TensorFlow [Todo Trader]

    Do you want to maximize your trading knowledge using TensorFlow? Here are several tips that will surely help you. Introduction Within TodoTraders commitment related to the generation and dissemination of knowledge, I want to offer a series of tutorials on the use of TensorFlow for algorithmic trading. The objective of these tutorials, which will be published periodically, is to offer in a
  • Natural language processing for financial markets [SR SV]

    News and comments are major drivers for asset prices, maybe more so than conventional price and economic data. Yet it is impossible for any financial professional to read and analyse the vast and growing flow of written information. This is becoming the domain of natural language processing; a technology that supports the quantitative evaluation of humans natural language. It delivers textual

Quantocracy’s Daily Wrap for 06/12/2019

This is a summary of links featured on Quantocracy on Wednesday, 06/12/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Market Timing with a Canary, Gold, Copper, LQD, IEF and much more [Alvarez Quant Trading]

    One commonality in my strategies is the inclusion of a market timing component. This could be a signal to go into cash or reduce position size or enter a safe ETF. This applies to my swing trading strategies, my monthly rotation strategies and my Tactical Assert Allocation strategies. As a researcher, I am always on a looking to improve this part of my strategies. There have been a handful
  • The Threat of Rising Rates and the Impact on TAA vs B&H Investing [Allocate Smartly]

    Weve written a lot here and on our sister site BetterBuyAndHold.com about the threat of rising interest rates. You can read some of our past work projecting returns for Treasury ETFs and other interest rate sensitive assets here and here. In a nutshell, assuming that were near the tail end of this 37+ year march lower in interest rates, and in the coming decade(s) rates either rise or remain

Quantocracy’s Daily Wrap for 06/11/2019

This is a summary of links featured on Quantocracy on Tuesday, 06/11/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Value Factor Valuations Over Time: US and Developed [Alpha Architect]

    We built a simple tool recently to review so-called value spreads over time. (1) This tool maps out the median valuations for the top decile and bottom decile cheap stock portfolios (as measured by EBIT/TEV). Why might this be useful? This tool allows one to identify the valuation spread between the cheapest stocks and the most expensive stocks in the universe. Some research suggests
  • The Cross-Section of Emerging Market Stock Returns [Alpha Architect]

    As a non-academic finance person, I was never really exposed to academic research until I started working on articles for Alpha Architect. Fortunately (or unfortunately, depending on your perspective), I am now very familiar with the so-called cross-section of expected returns debates. (explained here). This research seeks to identify the core factors that explain why stock move the way they

Quantocracy’s Daily Wrap for 06/10/2019

This is a summary of links featured on Quantocracy on Monday, 06/10/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Portfolio construction tilting towards higher moments [Eran Raviv]

    When you build your portfolio you must decide what is your risk profile. A pension funds risk profile is different than that of a hedge fund, which is different than that of a family office. Everyones goal is to maximize returns given the risk. Sinfully but commonly risk is defined as the variability in the portfolio, and so we feed our expected returns and expected risk to some optimization
  • Quantitative Styles and Multi-Sector Bonds [Flirting with Models]

    In this commentary we explore the application of several quantitative signals to a broad set of fixed income exposures. Specifically, we explore value, momentum, carry, long-term reversals, and volatility signals. We find that value, 3-month momentum, carry, and 3-year reversals all create attractive quantile profiles, potentially providing clues for how investors might consider pursuing higher
  • Strategy Risk vs Asset Risk [Two Centuries Investments]

    Alternative Title: How to Avoid Bad Manager Timing Lets look at the two types of risks in most investments: Strategy Risk: If you own a black-box go-anywhere hedge fund that invests long and short and uses futures and derivatives at any frequencies, you are mostly exposed to the strategy risk. It doesnt really matter what is happening to the underlying assets – the strategy either
  • The Case Against Small Caps [Factor Research]

    The performance of the Size factor in the US was positive since 1926, but not particularly attractive Returns in Europe were more favorable, but not in Japan Alternative metrics to market capitalization would not have resulted in better performance SMALL VERSUS LARGE STOCKS In the David vs. Goliath scenario, a smaller, weaker character faces down and defeats a larger and stronger opponent. Such
  • State of Trend Following in May [Au Tra Sy]

    Strong result in May for the Trend Following index, taking the Year-to-Date performance in positive territory. Please check below for more details. Detailed Results The figures for the month are: May return: 5.01% YTD return: 2.94% Below is the chart displaying individual system results throughout May: StateTF May And in tabular format: System May Return YTD Return BBO-20 16% 6.37% Donchian-20

Quantocracy’s Daily Wrap for 06/09/2019

This is a summary of links featured on Quantocracy on Sunday, 06/09/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Future-Proofing Quant Conference from QuantMinds, September 9 – 11 in Boston

    Join experts from banks, buy-side, Silicon Valley and academia to meet, network and share ideas at America's leading quant finance event. 3 key themes shaping the agenda: 1. Innovations in machine learning, HFT, AI and data 2. Quant techniques in investment and trading 3. Advances in option pricing, trading and modelling Learn from the brightest quant minds 50+ quant strategists, analysts,
  • Selection of Sparse Mean-reverting Portfolios – Part 1 [Alex Botsula]

    Mean-reverting portfolio construction is an exciting area that involves a wide range of forecasting and optimisation techniques. In Part 1 of the setries, I demonstrate the approach to the construction of optimal mean reverting portfolios satisfying sparsity and volatility constraints.
  • A theory of hedge fund runs [SR SV]

    Hedge funds capital structure is vulnerable to market shocks because most of them offer high liquidity to loss-sensitive investors. Moreover, hedge fund managers form expectations about each other based on market prices and investor flows. When industry-wide position liquidations become a distinct risk they will want to exit early, in order to mitigate losses. Under these conditions, market

Quantocracy’s Daily Wrap for 06/06/2019

This is a summary of links featured on Quantocracy on Thursday, 06/06/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Frank Fabozzi blasts the state of academic economics and finance [Mathematical Investor]

    In an interview published at the Enterprising Investor blog, Frank Fabozzi, a well-known researcher and author in the mathematical finance field, has sharply criticized the current state of academic economics and finance. Here are some highlights: The rational models constructed in economics and finance are increasingly disconnected from real-world behavior, as has been shown by research in
  • Determining the Noise Covariance Matrix R for a Kalman Filter [Dekalog Blog]

    An important part of getting a Kalman filter to work well is tuning the process noise covariance matrix Q and the measurement noise covariance matrix R. This post is about obtaining the R matrix, with a post about the Q matrix to come in due course. In my last post about the alternative version extended kalman filter to model a sine wave I explained that the 4 measurements are the sine wave value
  • The Re-Death of Value, or D j Vu All Over? [Alpha Architect]

    The underperformance of value stocks over the past 10 years has received much attention from the financial media and led at least some investors to conclude that value investing is dead. From 2009 through March 2019, while the S&P 500 Index returned 14.2 percent per annum (total cumulative return of 290 percent), the Fama-French large value and small value research indexes returned 11.3

Quantocracy’s Daily Wrap for 06/03/2019

This is a summary of links featured on Quantocracy on Monday, 06/03/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Tactical Asset Allocation in May [Allocate Smartly]

    This is a summary of the recent performance of a wide range of excellent Tactical Asset Allocation (TAA) 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
  • Tactical Credit [Flirting with Models]

    In this commentary we explore tactical credit strategies that switch between high yield bonds and core fixed income exposures. We find that short-term momentum signals generate statistically significant annualized excess returns. We use a cross-section of statistically significant strategy parameterizations to generate an ensemble strategy.Consistent with past research, we find that this ensemble
  • Quantamental Investing – A Century of Inventions [Two Centuries Investments]

    Last weeks talk by Edward Altman at the 50-year anniversary of Altmans Z-score event at the CFA New York inspired me to compile an expanded list of memorable inventions in equity analysis. Each one is a successful blend of quantitative and fundamental thinking – which is increasingly being called quantamental investing, for example see here and here. I am inspired by this list,
  • How to Allocate Smartly to Smart Beta [Factor Research]

    This research note was originally published in the Beyond Beta magazine from ETF Stream. Here is the link. SUMMARY Single factor excess returns are attractive over the long-term, less in the short-term Comparing popular asset allocation models does not highlight one superior methodology Multi-factor portfolios generated excess returns in two out of three regions since 2008 INTRODUCTION Obesity
  • Is factor momentum really everywhere? [Alpha Architect]

    The research presented here covers the largest number of factors (65) tested in the academic literature. The most robust and well-cited factors appear in the list of data items, available since the 1960s. A notable exclusion is the IBES dataset, which is available only in the 1980s. Is there persistence in factor returns? If so, can timing models based on autoregressive patterns work successfully

Quantocracy’s Daily Wrap for 05/31/2019

This is a summary of links featured on Quantocracy on Friday, 05/31/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Optimising MetaTrader for Algorithmic Trading [Robot Wealth]

    If youve ever delved into the world of retail foreign exchange trading, youll have come across the MetaTrader platform. Lets be clear. The platform has its drawbacks. If youve traded grown-up markets, some of the features will leave you scratching your head. But one things for sure MetaTrader provides fast, convenient access to pretty much every retail forex broker on the
  • Downloading option chain and fundamental from Yahoo! Finance with Python [Ran Aroussi]

    The recently updated yfinance added a lot more capabilities to this already popular library. You can now download fundamental data, including company financials, balance sheet and cashflow, as well as option chain data. Here's how… First, import yfinance and create a ticker object: 1 2 import yfinance as yf aapl = yf.Ticker("AAPL") Next, let's get information about the stock
  • Extended Kalman Filter, Alternative Version [Dekalog Blog]

    Below is alternative code for an Extended Kalman filter for a sine wave, which has 4 states: the sine wave value, the phase, the angular frequency and amplitude and measurements thereof. I have found it necessary to implement this version because I couldn't adjust my earlier version code to accept and measure the additional states without the Cholesky decomposition function chol() exiting and