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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

Filed Under: Daily Wraps

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

Filed Under: Daily Wraps

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

Filed Under: Daily Wraps

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

Filed Under: Daily Wraps

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

Filed Under: Daily Wraps

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

Filed Under: Daily Wraps

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,

Filed Under: Daily Wraps

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

Filed Under: Daily Wraps

Quantocracy’s Daily Wrap for 01/04/2023

This is a summary of links featured on Quantocracy on Wednesday, 01/04/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Interview with ChatGPT about its book ‘From Data to Trade: A Machine Learning Approach to Quantitative Trading’ [Gautier Marti]

    Introducing the first book ever generated by an artificial intelligence on the subject of using machine learning for quantitative trading: From Data to Trade: A Quantitative Approach to Machine Learning! This groundbreaking work offers a unique perspective on the use of machine learning in the financial markets, as it was created by an advanced AI using its own machine learning algorithms to
  • Most popular posts 2022 [Eran Raviv]

    As per usual this point in time, I check my blogs traffic-analytics to see which were the most popular pieces last year. Without further ado.. First: Correlation and Correlation Structure (6) Distance Correlation (08:33 minutes average time on page) Second: Similarity and Dissimilarity Metrics Kernel Distance (11:28 minutes average time on page) Third: What is the Kernel Trick? (11:51
  • Factor Olympics 2022 [Finominal]

    2022 is the best year for factor investing over the last decade Value generated the best and size the worst return in 2022 Despite the strong returns, investors remain cautious on factor investing 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
  • Asset pricing theory & the role labor displacement plays [Alpha Architect]

    In this article about asset pricing theory, we examine the research on the impact of technological advances that displace human labor in favor of machine capital to asset pricing. Automation and the displacement of labor by capita: Asset pricing theory and empirical evidence Jir Knesl Journal of Financial Economics, 2023 A version of this paper can be found here Want to read our summaries of

Filed Under: Daily Wraps

Quantocracy’s Daily Wrap for 01/02/2023

This is a summary of links featured on Quantocracy on Monday, 01/02/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • When Point Forecasts Are Completely Useless [Sarem Seitz]

    In the last article, we discussed one advantage of probabilistic forecasts over point forecasts – namely, handling time-to-exceedance problems. In this post, we will examine another limitation of point forecasts: Higher order statistical properties. The ideas will be very familiar to those with a background in mathematics or statistics. Readers without formal training in either will therefore
  • Survivorship Bias [Jonathan Kinlay]

    The relprice Index in the Performance Data table shows the price of the stock relative to the S&P 500 index over a specified period. Lets look at the median relPrice for all stocks that are currently members of the S&P500 index, eliminating any for which the relevant Performance Data is missing: currentSP500 = Select [ allStocks , # [ Symbol Information ] [ SP500 ] && Length [ #
  • Why Technical Analysis Doesn’t Work [Jonathan Kinlay]

    Generally speaking, one of the major attractions of working in the equities space is that the large number of available securities opens up a much wider range of opportunities for the quantitative researcher than for, say, futures markets. The focus in equities tends to be on portfolio strategies since the scope of the universe permits an unparalleled degree of diversification. Single stock
  • Modified and balanced FX carry [SR SV]

    There are two simple ways to enhance FX carry strategies with economic information. The first increases or reduces the carry signal depending on whether relevant economic indicators reinforce or contradict its direction. The output can be called modified carry. It is a gentle adjustment that leaves the basic characteristics of the original carry strategy intact. The second method equalizes
  • Expected Returns to Green Stocks [Alpha Architect]

    The past decade has seen a dramatic growth in sustainable investingapplying environmental, social and governance (ESG) criteria to investment strategies. Investments considered environmentally friendly are often referred to as green, while brown denotes the opposite. Important questions for investors are: What are the expected returns to green stocks? What does their past

Filed Under: Daily Wraps

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