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Quantocracy’s Daily Wrap for 06/23/2022

This is a summary of links featured on Quantocracy on Thursday, 06/23/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Using Historical Volatility for Parameter Adjustment [Alvarez Quant Trading]

    The AllocateSmartly website often has interesting posts. Recently I was reading the article Trending Fast and Slow and thought about other ideas to test. The article is based on research on trading the SPX and depending on the current historical volatility one would either use a 12-month or a 1-month lookback to decide whether to enter or exit the trade. I had tried similar ideas before but not
  • Can Machine Learning Identify Future Outperforming Active Equity Funds? [Alpha Architect]

    Ron Kaniel, Zihan Lin, Markus Pelger, and Stijn Van Nieuwerburgh contribute to the asset pricing literature with their January 2022 study Machine-Learning the Skill of Mutual Fund Managers in which they used machine learning in the form of an artificial neural network to examine the universe of actively traded U.S. equity mutual funds between 1980 and 2019 and the stocks they hold in order
  • Using Institutional Investor’s Trading Data in Factors [Alpha Architect]

    Can the returns from running factor strategies be enhanced if institutional investors selectively and actively participate? Most of the evidence presented in this paper would suggest the answer is an unqualified YES. The authors argue this would require institutional investors to possess and then capitalize on private information. Consequently, the movement into and out of specific stock positions

Quantocracy’s Daily Wrap for 06/22/2022

This is a summary of links featured on Quantocracy on Wednesday, 06/22/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • From theory to practice: Challenging the market using MPT-based investment strategy [Quant Dare]

    In order to develop complex strategies for a successful asset allocation, portfolio managers need profound knowledge on the field. Apparently, this is the key to be able to consistently beat the market. In this post we will learn how to design investment strategy based in Modern Portfolio Theory in Python. Will we be able to outperform the market? Lets find out! Note that before diving into the

Quantocracy’s Daily Wrap for 06/21/2022

This is a summary of links featured on Quantocracy on Tuesday, 06/21/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Skewness/Lottery Trading Strategy in Cryptocurrencies [Quantpedia]

    A recent spring 2022 crisis in the cryptocurrency market emphasized the importance of market-neutral crypto trading strategies. Its not enough just to HODL crypto market and hope for the everlasting bull market. Therefore, we continue our series of research articles about the cryptocurrency market and offer an analysis of the skewness anomaly. So after our description of the skewness effect in
  • Macro Variables in Factor Exposure Analysis [Factor Research]

    Most investors treat factor and macro variables differently Including macro variables improves a factor exposure analysis Both should be considered simultaneously when analyzing investment portfolios INTRODUCTION The investment world is full of conundrums. For example, discussions on investment portfolios usually focus on the impact of change in inflation, interest rates, economic growth, and

Quantocracy’s Daily Wrap for 06/19/2022

This is a summary of links featured on Quantocracy on Sunday, 06/19/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Does Emerging Markets Investing Make Sense? [Alpha Architect]

    This post focuses on the costs and benefits of including generic broad-based emerging market exposures in ones portfolio (Note, we do not discuss factors/freedom/etc.). The analysis is not meant to be exhaustive and/or highly complex. Nor is it meant to sway the reader in one direction or the other. Like all things in life, there are costs/benefits to everything and everyone needs to identify a

Quantocracy’s Daily Wrap for 06/16/2022

This is a summary of links featured on Quantocracy on Thursday, 06/16/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Predicting US Treasury Returns [Allocate Smartly]

    This is a test of the paper Predicting Bond Returns: 70 Years of International Evidence. The authors use an ensemble model to trade US and international treasury bonds. Over the last 60+ years the strategy would have produced long-term returns in line with buy & hold, while significantly reducing short-term volatility and drawdowns, especially during the era of rising rates. Obviously, these

Quantocracy’s Daily Wrap for 06/15/2022

This is a summary of links featured on Quantocracy on Wednesday, 06/15/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Fed Days: Pre vs Post-Announcement Action During Downtrends [Quantifiable Edges]

    In a blog post a few years ago I showed that the Fed Day edge has basically played out before the announcement even takes place. Returns after the announcement have been somewhat random. In last nights subscriber letter I decided to take a similar look, but only examining instances during long-term downtrends. Below is a look at how the SPY has performed from 2pm to 4pm on Fed Days where SPY
  • Optimization problems with non-continuous restrictions [Quant Dare]

    In the financial field, managers usually take advantage of the great development in machine learning techniques to improve their models and get the best performance of their portfolios. These techniques may be clustering, neural networks, or even a more traditional one as optimization algorithms. In general, the existing algorithms are suitable in most of the problems that managers have to face
  • Relative Sentiment and Machine Learning for Tactical Asset Allocation [Alpha Architect]

    By the middle of 2019, we had been running an ensemble of relative sentiment(1) indicators in live asset management for several years. One of the components of that ensemble was a strategy that looked at Sentix sentiment indices. For those unfamiliar with Sentix (a German company), every week it polls institutions and individuals separately about their current and future outlooks on various
  • Factors Investing in Cryptocurrency [Alpha Architect]

    Cryptocurrency investing is a widely debated topic and one can find plenty of debates on Twitter discussing the fed, fiat currencies, and inflation. Regardless of where you fall on the crypto spectrum, we try and focus on research-centric takes on various investment themes whenever possible. The authors of this study research the cross-section of cryptocurrency returns and ask the following: Are

Quantocracy’s Daily Wrap for 06/13/2022

This is a summary of links featured on Quantocracy on Monday, 06/13/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Slava Ukraini! Latest from Only VIX, Quantocracy contributor in Ukraine: Modeling Implied Vol Surfaces of Crypto Options [Only Vix]

    This is a quick follow-up to my previous post with comments on Artur Sepps's video. From the start Mr Sepp sets up the practical problem familiar to anyone in the crypto options space. The leader is Deribit – an exchange that I wrote about extensively in this blog with ~ 89% market share. The next biggest is CME with ~ 6% market share, and expected to grow. One would naturally want to trade
  • A Rare Inverse Zweig Breadth Collapse Triggers [Quantifiable Edges]

    A few years back I wrote about Zweig Breadth Thrusts in some detail. The Zweig Thrust takes a 10-day exponential moving average of the NYSE Up Issues %. It looks for a move from Over the last 3 days we have essentially what could be considered the inverse setup trigger. The NYSE Up Issues % 10ema has fallen from above 61.5% to under 40% in 10 trading days. Rather than a breadth thrust, we have
  • Ehlers Loops [Financial Hacker]

    Price charts normally display price over time. Or in some special cases price over ranges or momentum. In his TASC articles in June and July 2022, John Ehlers proposed a different way of charting. The ratio of two parameters, like price over momentum, or price A over price B, is displayed as a 2D curve in a scatter plot. The resulting closed or open loop is supposed to predict the future price
  • Sector versus Factor Exposure Analysis [Factor Research]

    Investors tend to talk more about sector than factor performance However, few investors conduct a regression-based sector exposure analysis The high correlations of sectors, even if structured market-neutral, makes this less meaningful INTRODUCTION Switch on CNBC or Bloomberg TV during US stock trading hours and there is a good probability of listening to a lively discussion on current sector
  • Six ways to estimate realized volatility [SR SV]

    Asset return volatility is typically calculated as (annualized) standard deviation of returns over a sequence of periods, usually daily from close to close. However, this is neither the only nor necessarily the best method. For exchange-traded contracts, such as equity indices, one can use open, close, high, and low prices and even trading volumes. These provide different types of information on

Quantocracy’s Daily Wrap for 06/10/2022

This is a summary of links featured on Quantocracy on Friday, 06/10/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Trend-Following in the Times of Crisis [Quantpedia]

    When someone mentions a financial crisis, most people immediately think of the global financial crisis of 2007-2008. Even though this is the most significant economic crisis in recent years, there have been many more significant crisis periods in the past 100 years. This article examines the biggest crises in three asset classes: stocks, bonds, and commodities, during the past century.
  • The Unintended Consequences of Single Factor Strategies [Alpha Architect]

    Since the 1992 publication of The Cross-Section of Expected Stock Returns by Eugene Fama and Kenneth French factor-based strategies and products have become an integral part of the global asset management landscape. While top-down allocation to factor premiums (such as size, value, momentum, quality, and low volatility) has become mainstream, questions remain about how to efficiently
  • Research Review | 10 June 2022 | Risk Premia Sources [Capital Spectator]

    Inflation as the Source of the Bond, Equity, and Value Premia Martin Tarlie (GMO) May 2022 A no-arbitrage pricing model with inflation as the only priced risk factor explains the bond, equity, and value premia observed in the United States over the past sixty years. Even though inflation is the only priced factor, in an economy with three state variables inflation, the real rate, and corporate

Quantocracy’s Daily Wrap for 06/08/2022

This is a summary of links featured on Quantocracy on Wednesday, 06/08/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Best Performing Value Strategies – Part 2 [Quantpedia]

    Value trading strategies have come back into spotlight in recent years. After lackluster performance in years 2018, 2019, 2020, Value has staged a strong comeback in 2021 and also in 2022. With a long history of systematic equity Value strategies, many different variants of the strategy have emerged. In the first part of this article, we picked 16 US equity value trading strategies out of
  • Visualizing the Robustness of the US Equity ETF Market [Alpha Architect]

    Market commentators sometimes suggest that the equity ETF market is just a bunch of index funds that all do essentially the same thing: deliver undifferentiated stock market exposure. How true is that statement? Fortunately, we can test the hypothesis that the ETF market is roughly a few thousand different ways to capture the same basic risk/returns. To do so, we leverage our Portfolio

Quantocracy’s Daily Wrap for 06/07/2022

This is a summary of links featured on Quantocracy on Tuesday, 06/07/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Mean-Variance Optimization in Practice: Subset Resampling-based Efficient Portfolios [Portfolio Optimizer]

    In a previous post, I introduced near efficient portfolios, which are portfolios equivalent to mean-variance efficient portfolios in terms of risk-return but more diversified in terms of asset weights. Such near efficient portfolios might be used to moderate the tendency of efficient portfolios to be concentrated in a very few assets, a well-known stylized fact of the Markowitzs mean-variance
  • One-Month Trading Strategies [Falkenblog]

    About half of Robecos Quantitative Investing team recently published a short paper on monthly trading strategies (see Blitz et everybody Beyond Fama-French Factors: Alpha from Short-Term Signals Frequencies). I can imagine these guys talking about this stuff all the time, and someone finally says, this would make a good paper! Short-Term refer to one-month trading horizons. Anything
  • Do Connections Pay Off in the Bitcoin Market? [Alpha Architect]

    Traditional asset pricing theory holds that the workings of information networks among investors are good descriptors of equity markets. Investors that are better informed about fundamentals and who trade earlier than less well informed investors will receive higher returns. As the better information is passed on through trading, less informed investors will eventually join in
  • Factor Exposure Analysis of Fixed Income ETFs [Factor Research]

    Factor exposure analysis can be used in fixed income as easily as in equities More variables improve the explanatory power of the model However, it also can make the interpretation challenging INTRODUCTION Running a factor exposure analysis is a core element of the due diligence process for equity-focused mutual funds, and increasingly ETFs, especially actively managed ones. The holy grail is to