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Quantocracy’s Daily Wrap for 10/14/2021

This is a summary of links featured on Quantocracy on Thursday, 10/14/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Meb’s Greatest Hits [Meb Faber]

    Weve been publishing papers, books and blog posts for over 15 years covering everything from asset allocation strategies and global value investing, to farmland investing, to startups, and even the question of whether or not institutions and endowments should just be managed by a robot. With thousands of pieces of content, we thought it was time to sift through them all and try to rank the
  • What is the Optimal Gold Allocation in a Portfolio? [Quantpedia]

    Ray Dalio, the founder of Bridgewater Associates L.P. and the creator of the All-Weather investment strategy, recommends having some gold in a contemporary environment. He states, In a world of ongoing pressure for policymakers across the globe to print and spend, zero interest rates, tectonic shifts in where global power lies, and conflict, gold has a unique role in protecting portfolios.
  • The Impact of ESG Scores on Asset Prices [Alpha Architect]

    Sustainable investing has grown substantially in recent years, demonstrating that investor demand can be driven by nonfinancial issues such as environmental (E), social (S), and governance (G) characteristics. A full list of our posts on ESG can be found here. The demand from investors who have a preference for investing based on their values could impact valuations and thus expected returns.

Quantocracy’s Daily Wrap for 10/13/2021

This is a summary of links featured on Quantocracy on Wednesday, 10/13/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The MAD indicator [Financial Hacker]

    As an application to the windowing technique described the the previous article, John Ehlers proposed a new trend indicator that he claimed is robust and yet simple. The latter is certainly true, as the MAD (Moving Average Difference) oscillator is, as the name says, just the difference of two moving averages normalized to +/-100. The MAD code in C for Zorro: var MAD(vars Data, int ShortPeriod,

Quantocracy’s Daily Wrap for 10/11/2021

This is a summary of links featured on Quantocracy on Monday, 10/11/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Optimal Trading Thresholds for the O-U Process [Hudson and Thames]

    Pairs trading or statistical arbitrage is a famous strategy among institutional and individual investors since the 1990s. The concept behind this kind of strategy is straightforward. If the prices of assets move together historically, this tendency is likely to continue in the future. When the spread of the prices diverges from its long-term mean, one can short sell the over-priced stock, buy the
  • Do Big Value Spreads Mean Big Returns to Value Strategies? [Alpha Architect]

    Okay, we cant keep it a secret, we are fans of value investing 1 So when Cliff Asness and his team at AQR write about value, we get excited. The analysis reported in this research confirms the relationship between static value strategies and future returns while incorporating the notion that the size of the value spread influences the size of the future value return. (you can use our free tool
  • Insider Trading: What Happens Behind Closed Doors [Quantpedia]

    Corporate insiders often have insight into a companys private information, which might help them predict how the shares price will move in the coming days. However, laws and regulations are designed to keep them from trading based on this knowledge, as it would be unfair and hurt the companys other shareholders. This includes the prohibition of insider trading or designing a 10b5-1 plan,
  • Less Efficient Markets = Higher Alpha? [Factor Research]

    Emerging market mutual fund managers struggle to outperform EM hedge fund managers failed to generate meaningful alpha EM opportunities seem to come with proportional risks INTRODUCTION Students often ask me for career advice. It is not a particularly satisfying experience. On the one hand, these are often exceptionally bright and hard-working people, with Oxford or Cambridge PhDs in chemical

Quantocracy’s Daily Wrap for 10/08/2021

This is a summary of links featured on Quantocracy on Friday, 10/08/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Three Simple Tactical FX Hedging Strategies [Quantpedia]

    There are many ways one can lose money when investing, and exchange rates are one of the potential risk factors. Luckily, there are several ways to minimize this type of loss in your portfolio. Systematic tactical FX hedging that uses currency factor strategies (for example currency carry, currency momentum and currency value) is a way of protecting an existing or anticipated position from an
  • Research Review | 8 October 2021 | Dynamic Portfolio Strategies [Capital Spectator]

    Time-Varying Factor Allocation Stefan Vincenz and Tom Oskar Karl Zeissler (Vienna U. of Economics and Business) September 15, 2021 In this empirical study, we provide evidence on how predictive information can be utilized to profitably allocate a cross-asset factor portfolio, covering various well-known factors over the asset classes equity, commodity, fixed income, and foreign exchange. We
  • ETF Liquidity Risks? A Discussion [Alpha Architect]

    Because of the complexity inherent to ETF trading in the secondary market, there are frequent misunderstandings about the relationship between the liquidity of the underlying securities and the liquidity of ETFs. Sometimes we hear that ETFs have excess liquidity to the underlying and at others, ETFs will have liquidity concerns. To get a better grasp on this relationship, well hit on the basics

Quantocracy’s Daily Wrap for 10/06/2021

This is a summary of links featured on Quantocracy on Wednesday, 10/06/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How to Use Deep Order Flow Imbalance [Quantpedia]

    Order book information is crucial for traders, but it can be complex. With the numbers of stocks listed in stock exchanges, it is impossible to track all the available information for the human mind. Therefore, the order flows could be an interesting dataset for machine learning models. The novel research of Kolm, Turiel and Westray (2021) utilizes deep-learning for high-frequency return forecasts
  • Studying Financial Idea “Infection Rates” [Alpha Architect]

    Previously, we have written about the Momentum of News, which highlights that lots of positive news can lead to future positive returns (without a look-ahead bias!). Todays post builds on the concept that news (and sentiment?) are predictive for returns which sounds intuitive. The writers of this paper apply the concept of disease transmission rates, and the average number of new infections

Quantocracy’s Daily Wrap for 10/04/2021

This is a summary of links featured on Quantocracy on Monday, 10/04/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How to Trade like a Turtle without $1,000,000 [Raposa Trade]

    A simple job ad was placed in a handful of major newspapers calling for participants to be trained as traders. Of the applicants, a total of 23 individuals were chosen to become Turtle Traders: systematic trend followers who simply followed rules and made millions in the process. These were average, ordinary people who were taught a system in order to determine whether trading could be taught, or
  • Factor Olympics Q3 2021 [Factor Research]

    2021 is shaping up as a year of undifferentiated factor performance Value is the only factor with positive performance in year-to-date 2021 The Size factor has generated the most negative returns INTRODUCTION We present the performance of five well-known factors on an annual basis for the last 10 years. Specifically, we only present factors where academic research supports the existence of
  • Why a Bounce on a Friday is Encouraging [Quantifiable Edges]

    Friday saw the market bounce after several indices closing at multi-month lows on Thursday. Fridays are interesting in that they are the least likely day of the week for a selloff to end or a rally to begin. But when rallies do start on a Friday, they have shown the best odds of success of any day of the week. Ive seen this a number of ways over the years. The study below is one simple way to

Quantocracy’s Daily Wrap for 10/01/2021

This is a summary of links featured on Quantocracy on Friday, 10/01/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Mr Greedy and the Tale of the Minimum Tracking Error Variance [Investment Idiocy]

    This is the sixth (!) post in a (loosely defined) series about finding the best way to trade futures with a relatively small account size. This first (old) post, which wasn't conciously part of a series, uses an 'ugly hack': a non linear rescaling of forecasts such that we only take positions for relatively large forecast size. This is the method I was using for many years. These
  • Value Investing and Intangibles [Alpha Architect]

    Recent research, including the 2020 studies Explaining the Recent Failure of Value Investing and Intangible Capital and the Value Factor: Has Your Value Definition Just Expired?, have investigated the impact on U.S. value strategies of the increase in the relative importance of intangible assets compared to physical assets. An interesting take on the rise of intangibles is Kai Wus

Quantocracy’s Daily Wrap for 09/29/2021

This is a summary of links featured on Quantocracy on Wednesday, 09/29/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Multi-day Limits for Mean Reversion [Alvarez Quant Trading]

    A reader recently suggested leaving the limit orders for a mean reversion trade on for a couple of days. Typically, these orders are good only for one day unless the stock sets up again. I did not think that this would help but as I always tell my consulting clients when they ask me if an idea will work or not, I am always surprised but what works and what doesnt, so I test everything and
  • Introduction to Clustering Methods In Portfolio Management Part 3 [Quantpedia]

    This is the third and final article from the clustering series. If youve missed the previous parts, here you can find the first and second parts of the series. This section examines trading strategies based on previously introduced clustering methods. The complete Portfolio Clustering report will be available for our Quantpedia Pro clients next week. Cluster Risk Parity Strategies In one of the

Quantocracy’s Daily Wrap for 09/27/2021

This is a summary of links featured on Quantocracy on Monday, 09/27/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Efficient Long Duration Treasury Investing [Simplify]

    The shape of the US Treasury curve over the past five decades has provided investors with the opportunity to create more efficient long duration exposure than simply buying long-dated Treasuries. In this article we will show how the most efficient long duration exposure is often generated by levering a point in the middle of the Treasury curve. This technique maximizes the attractive coupons, roll
  • Asset Pricing Models in China [Quantpedia]

    The CAPM model was a breakthrough for asset pricing, but the times where the market factor was most widely used are long gone. Nowadays, if we exaggerate a bit, we have as many factors as we want. Therefore, it might not be straightforward which factor model should be used. Hanauer et al. (2021) provide several insights into factor models. The authors postulate that the factor models should be
  • Macro risks and the term structure of interest rates [Alpha Architect]

    The authors of this paper identify aggregate supply and aggregate demand shocks for the US economy utilizing macroeconomic data on inflation, real GDP growth, core inflation, and the unemployment gap. They then go on to extract how these shocks to supply and demand impact the term structure of interest rates. This paper investigates two main research questions: Is it possible to use non-Gaussian
  • This Time It s Different!? [Factor Research]

    Options trading has increased to record highs Some data points indicate changes in the market structure However, these changes are likely temporary rather than structural INTRODUCTION During the 1954 recession in the U.S., Sir John Templeton wrote to his clients that this time its different are the four most dangerous words in investing. A pedantic reader might comment that its
  • How Random is the Market? Testing the Random Walk Hypothesis [Raposa Trade]

    A mainstay of academic research into the market is the Random Walk Hypothesis (RWH). This is the idea that market moves are random and follow a normal distribution that can be easily described using a concept borrowed from physics called Brownian Motion. This makes the market mathematics manageable, but is it true? Is the market really random? If it is, then theres little point to trying to

Quantocracy’s Daily Wrap for 09/25/2021

This is a summary of links featured on Quantocracy on Saturday, 09/25/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Podcast Interview with Grzegorz Link [System Trader Show]

    Todays guest is Grzegorz Link, who professionally works as a quant for an investment fund. Grzegorz is a physicist by education, which may surprise some. However, the thing is that in building market models, skills such as programming and mathematics are the primary tools, which is the same for contemporary physicists. We raise many interesting issues during the conversation, trying to answer
  • Crowding and Factor Premiums [Alpha Architect]

    My March 23, 2021, article for Alpha Architect addressed the issue that in recent years the field of empirical finance has faced challenges from papers arguing that there is a replication crisis because the majority of studies cannot be replicated and/or their findings are the result of multiple testing of too many factors. However, the finding that factor premium returns cannot be replicated