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Quantocracy’s Daily Wrap for 01/29/2023

This is a summary of links featured on Quantocracy on Sunday, 01/29/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • A Couple of New Interesting Developments Concerning the Global Growth Cycle Strategy [Grzegorz Link]

    A couple of new and interesting developments concerning the Global Growth Cycle strategy are available: – first of all, what I've called an important test of the strategy from 2021/22 apparently went well. The ensuing bear market of 2022 has been largely avoided by positioning per the GGC. The risk-off signal from December 2021 appeared to be perfect timing, though keep in mind that
  • Trading Anomalies [Jonathan Kinlay]

    An extract from my new book, Equity Analytics.
  • Annualizing volatility [Quant Dare]

    Volatility is one of the best known and most widely used concepts in finance. Given a price series of a financial instrument, its volatility is defined as the dispersion of the returns. This measure is used to compare securities in terms of risk. But in order to compare, sometimes it is necessary to scale. In this post we explain the mathematical foundation of the annualized volatility. Anybody
  • Fiscal policy criteria for fixed-income allocation [SR SV]

    The fiscal stance of governments can be a powerful force in local fixed-income markets. On its own, an expansionary stance is seen as a headwind for long-duration or government bond positions due to increased debt issuance, greater default or inflation risk, and less need for monetary policy stimulus. Quantamental indicators of general government balances and estimated fiscal stimulus allow

Quantocracy’s Daily Wrap for 01/24/2023

This is a summary of links featured on Quantocracy on Tuesday, 01/24/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Hidden Cost in Costless Put-Spread Collars: Rebalance Timing Luck [Flirting with Models]

    We have published a new paper on the topic of rebalance timing luck in option strategies: The Hidden Cost in Costless Put-Spread Collars: Rebalance Timing Luck. Prior research and empirical investment results demonstrate that strategy performance can be highly sensitive to rebalance schedules, an effect called rebalance timing luck (RTL). In this paper we extend the empirical analysis to

Quantocracy’s Daily Wrap for 01/23/2023

This is a summary of links featured on Quantocracy on Monday, 01/23/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Pairs Trading in the Equities Entity Store [Jonathan Kinlay]

    An extract from the chapter on pairs trading from my forthcoming book Equity Analytics
  • What Are Growth Stocks? [Finominal]

    Growth stocks can be defined via valuations, fundamentals, or performance These stocks have generated essentially zero excess returns since 2005 Neither has the inverse basket (low valuations, low growth, low momentum) INTRODUCTION When Yale history professor Sherman Kent interviewed 23 NATO officers on their interpretation of probabilistic words in 1964, the results were surprising and
  • Research Review | 20 Jan 2023 | ETFs and Related Strategies [Capital Spectator]

    Do Sector ETFs Outperform Treasury Bills? Gow-Cheng Huang (Tuskegee U.) and Kartono Liano (Mississippi State U.) June 2022 Unlike individual stocks, more than 67% of sector ETFs have lifetime buy-and-hold returns that are higher than the T-bill rates. Thus, the majority of sector ETFs outperform T-bills. However, less than 26% of sector ETFs have lifetime buy-and-hold returns that are higher than
  • Mitigating Risks with Factor Strategies [Alpha Architect]

    The year 2022 was a difficult one for investors in traditional 60/40 portfolios, as equities all around the globe and bonds produced double-digit losses, a very rare event. Can factor strategies mitigate risk? That performance has heightened interest in the diversification benefits of factor-based strategies. Redouane Elkamhi, Jacky Lee and Marco Salerno contribute to the literature with their

Quantocracy’s Daily Wrap for 01/20/2023

This is a summary of links featured on Quantocracy on Friday, 01/20/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Varying Coefficient GARCH [Sarem Seitz]

    As you can probably tell by my other articles (for example here, here and here), I am a big fan of GARCH models. Forecasting conditional variance is arguably the best we can get in predicting stock returns out of themselves. Still, the GARCH family is no silver bullet that suddenly makes you a stock wizard. Countless variations imply that there is no single best approach to handle conditional

Quantocracy’s Daily Wrap for 01/19/2023

This is a summary of links featured on Quantocracy on Thursday, 01/19/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Return Stacking in an Inverted Yield Curve Environment [Flirting with Models]

    When we first started publicly writing and talking about capital efficiency in 2017 the predecessor conversation to return stackingTM the 13-week U.S. Treasury Bill rate sat around 1.30%. The prototypical example at the time was a 1.5x levered 60% stock / 40% bond portfolio (also referred to as a 90/60). Such a portfolio would allow investors to achieve the exposure of a 60/40 using
  • How earnings reports affect stocks? [Quant Dare]

    Surely everyone has suffered/enjoyed a sudden movement of a stock in a portfolio when the underlying company has reported earnings. Now that the earnings report season is starting you may wonder if there exists a way to avoid those shocks in the stocks without missing performance in your investments. How often are earnings shocks? In order to analyse the impact of the earnings publication in the

Quantocracy’s Daily Wrap for 01/17/2023

This is a summary of links featured on Quantocracy on Tuesday, 01/17/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Diversification Ratio: Measuring Portfolio Diversification [Portfolio Optimizer]

    Continuing the series of blog posts on diversification indicators, I describe in this post a correlation-based measure of portfolio diversification called the diversification ratio, initially introduced by Yves Choueffaty and Yves Coignard in their paper Toward maximum diversification1 and later extensively studied in other papers from people at Think Out of the Box Asset Management (TOBAM)23. I
  • Expected Returns for Private Equity Will Probably Suck [Alpha Architect]

    This article attempts to demystify the approach and methodology used to characterize the risk and return relationship in private equity today. The illiquid nature of the asset class makes the demystification of private equity returns difficult to achieve under any circumstances. Still, the framework presented in this article should move the reader closer to the goal. Demystifying Illiquid Assets:
  • An Unprecedented Breadth Trifecta has Triggered [Quantifiable Edges]

    On Thursday afternoon I witnessed 3 different breadth thrust signals I watch all trigger on the same day. The signals, with link to learn more about them are: Walter Deemers Breakaway Momentum (BAM) signal Wayne Whaleys Advance Decline Thrust (5) from his paper Planes, Trains, and Automobiles: A Study of Various Market Thrust Measures Quantifiable Edges Triple 70 thrust signal.
  • Beta in Beta-Neutral Factors? [Finominal]

    Beta-neutral value, momentum, and low volatility factors are currently highly correlated to the S&P 500 The correlation is temporary rather than structural Likely explained by the downturn in tech stocks that benefits these factors INTRODUCTION We recently published our quarterly Factor Olympics report (read Factor Olympics 2022) which highlighted the best year for factor investing in the last

Quantocracy’s Daily Wrap for 01/14/2023

This is a summary of links featured on Quantocracy on Saturday, 01/14/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Can ChatGPT Self-Improve Self-Written Python Code for Cholesky Decomposition? [Quant at Risk]

    It is needless to say about next big thing in the field of artificial intelligence (AI) known as ChatGPT. ChatGPT is a large language model developed by OpenAI. It is based on the GPT (Generative Pre-training Transformer) architecture and is trained on a massive dataset of text data. This allows it to generate human-like text and perform a wide range of natural language processing tasks, such as
  • Building a sector rotation strategy based on Fed s interest rate policy [Quant Dare]

    The Feds interest rate actions, which have been a topic of much discussion recently, can be very valuable information when making investment decisions. In particular, this post shows how to improve our sector allocation following the Feds announcements. Introduction The Federal Reserve System (FRS), better known as the Fed, is the central bank of the United States and, among all its tasks,
  • Detecting trends and mean reversion with the Hurst exponent [SR SV]

    The Hurst exponent is a statistical measure of long-term memory of time series. The existence and form of such memory are of great interest in financial markets, as financial returns are not generally governed by random walks. The Hurst exponent is a single scalar value that indicates if a time series is purely random, trending, or rather mean reverting. Thus, it can validate either momentum or
  • The Value Factor and Deleveraging [Alpha Architect]

    In his 2011 presidential address to the American Finance Association, John Cochrane coined the term zoo of factors, reflecting concerns about the quality of financial research. How do you separate the signal from the noise? In our book Your Complete Guide to Factor-Based Investing, Andrew Berkin and I provided five criteria investors could use to minimize the risk of data mining

Quantocracy’s Daily Wrap for 01/09/2023

This is a summary of links featured on Quantocracy on Monday, 01/09/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Robust Log-normal Stochastic Volatility for Interest Rate Dynamics [Artur Sepp]

    The volatility of interest rates in 2022 has been indeed extreme. In Figure 1, I show the dependence the between the MOVE index (which measures the implied volatility of one-month options on UST bond futures and which is constructed similarly to the VIX index for implied volatilities of the S&P index futures), realized 10y UST rate volatility over the 6 months rolling window, and the level of
  • Alternative Credit Funds: Credible Alternatives? [Finominal]

    Alternative credit funds aim to provide returns uncorrelated to traditional fixed income markets However, most of the performance can be explained by equities and plain-vanilla bonds All funds have lost money in the last 12 months, indicating that they are not alternative enough INTRODUCTION As savvy marketers say, the best way to sell a $2,000 watch is to place it next to a $10,000 one. In the

Quantocracy’s Daily Wrap for 01/07/2023

This is a summary of links featured on Quantocracy on Saturday, 01/07/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Slava Ukraini! Latest from Quantocracy contributor in Ukraine [Only VIX]

    Russias economy was already in decline before the WW1 began, and its involvement in the conflict only exacerbated the situation. By 1917, russia was on the verge of collapse, with widespread poverty and a deep political divides. In March Tsar Nicholas II was forced to abdicate, and a provisional government was formed in his place. In 1918 bolsheviks signed a peace treating withdrawing from WW1
  • Defining Market Cycles Out of Sample [Quantpedia]

    We have already published a few articles about how the different market cycles affect the performance of your portfolio and performance of market factors. So far, these states of the market were identified in-sample, with the benefit of hindsight. The full methodology of how we defined bull/ bear market, low/ high inflation, and rising/ falling interest rates is described in this article. Today,

Quantocracy’s Daily Wrap for 01/05/2023

This is a summary of links featured on Quantocracy on Thursday, 01/05/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Scream if you want to go faster [Investment Idiocy]

    Happy new year. I didn't post very much in 2022, because I was in the process of writing a new book (out in April!). Save a few loose ends, my work on that project is pretty much done. Now I have some research topics I will be looking at this year, with the intention of returning to something like a monthly posting cycle. To be clear this is *not* a new years resolution, and therefore is
  • Which System Has The Lowest Risk of Ruin? [Relative Value Arbitrage]

    Would you rather choose a trading system that wins small amounts most of the time but when it loses, the loss is big? Or would you rather choose a trading system that loses small amounts most of the time but when it wins, the gain is big? In this blog post, we will examine such systems from the risk of ruin perspective. The risk of ruin is the probability of an investors eventual bankruptcy due
  • Optimal Trend Following with Transaction Costs [Alpha Architect]

    Despite the widespread popularity of trend-following investing, little is known about optimal trend-following with transaction costs. A few existing studies consider this question using a continuous-time model within the stochastic optimal control theory framework. However, despite being theoretically the most appropriate, this approach makes the problem intractable analytically, and the numerical