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Quantocracy’s Daily Wrap for 04/28/2023

This is a summary of links featured on Quantocracy on Friday, 04/28/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Trading and investing performance: year nine, part one [Investment Idiocy]

    A bit late this year, due to a confluence of holidays, book launches, university exam writing and various other things. Here lies within my performance for the UK tax year 2022-23. Previous years can be found here. TLDR: Not great, absolute or relative. It was indeed a complete anus – horrible!. This will be a two parter this year. In this post I will look at my overall performance, with only a
  • Vintage Economic Data [Allocate Smartly]

    Some of the strategies we track use economic data, like the unemployment rate, when making investment decisions. Like 99.99% of strategy backtests youll encounter, weve always taken the shortcut of basing our historical results on that economic data as it looks today. The problem is that introduces a degree of lookahead bias. Economic data is often initially reported at one value and
  • The Drivers of Booms and Busts in the Value Premium [Alpha Architect]

    Over the almost 100 years that we have had data for U.S. stocks, the value premium (the annual average difference in returns, relative to accounting measures, from buying stocks whose market prices are low versus stocks whose market prices are high) has averaged 4.4% per year (when using book-to-market [HML: high minus low] as the valuation metric). In our book Your Complete Guide to

Quantocracy’s Daily Wrap for 04/27/2023

This is a summary of links featured on Quantocracy on Thursday, 04/27/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Machine Learning Trading Essentials (Part 2): Fractionally differentiated features, Filtering, and Labelling [Hudson and Thames]

    Welcome back, fellow traders and machine learning enthusiasts! We hope youve been enjoying our journey towards building a successful machine learning trading strategy. If you missed Part 1 of our series, dont fret you can always catch up on our exploration of various financial data structures, such as dollar bars. In this post, well continue to investigate key concepts related to
  • Democratize Quant 2023 is Live. Sign-up! [Alpha Architect]

    We will host our 6th annual Democratize Quant conference on May 18th via Zoom. The event is 100% free, but we do screen participants to enforce our no spammers policy. Request access Conference website Our speaker line-up is excellent, and we look forward to some exciting discussions. Date Time Topic Presenter Notes 5/18 09:30 09:45 Introduction Wes Gray CEO Alpha Architect 5/18
  • Novel explanations for risk-based option momentum [Alpha Architect]

    Stock momentum trading is popular in practice and extensively investigated in academic studies. The paper finds a new option momentum, extending a recent study by Heston et al. (2022), who show that options also display momentum. Our risk-based option momentum is substantially stronger, has a risk explanation, and is also an extension of the stock risk momentum patterns uncovered by Li, Yuan, and

Quantocracy’s Daily Wrap for 04/24/2023

This is a summary of links featured on Quantocracy on Monday, 04/24/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Russell Death Cross Implications for SPX [Quantifiable Edges]

    I have seen some chat about the Russell Death Cross that occurred on Friday and the potential bearish implications for the market. A Death Cross is a catchy (though not terribly accurate) term for when the 50-day moving average of a security cross below its 200-day moving average. It is sometimes promoted as a warning of a potential bear market. Of course all bear markets will see this
  • Book Review: Python for Finance Cookbook, 2nd Ed. [Quant at Risk]

    Thanks to the courtesy of Packt Publishing, I had the pleasure of receiving, reading, and studying the new release of Python for Finance Cookbook, the book by Eryk Lewinson. This is the second (and probably the last) edition, according to the author himself. Therefore, it must be solid and memorable. I do think Eryk made every effort to deliver a masterpiece in a neat and condensed form. Since
  • Downside Betas vs Downside Correlations [Finominal]

    Investors typically use correlation to identify diversifying strategies, but the metric can be misleading Upside and downside betas and correlations provide a better perspective Common hedge fund strategies failed to provide attractive diversification benefits INTRODUCTION Are investors as rational as portrayed in the finance literature? For example, when Lehman Brothers collapsed in October 2008,
  • Social Networks and Markets: What’s the connection? [Alpha Architect]

    What are the Research Questions? Communication in social networks is not new. In fact, it goes back to coffee houses in the 17th century. According to Standage (2006), the drama of the South Sea Bubble, a fraudulent investment scheme that collapsed in September 1720, ruining thousands of investors, was played out in coffeehouses. The author ask the following questions: How do social networks
  • The Quality Factor: can Intangible Intensity improve it? [Alpha Architect]

    In our book Your Complete Guide to Factor-Based Investing, Andrew Berkin and I provided evidence that among the hundreds of equity factors identified in the literature, there were only five that met our criteria for investment. The factor must have provided a premium that was: persistent across long periods and different economic regimes; pervasive across countries, regions, sectors, and

Quantocracy’s Daily Wrap for 04/19/2023

This is a summary of links featured on Quantocracy on Wednesday, 04/19/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Setting up an alpha-generating strategy from scratch: A practical example [DileQuante]

    As a quantitative researcher, your main goal is to find new financial edges. In this article, we will show an overview of the pipeline for designing alpha-generating investment strategies, with associated python code as usual. Here are the main steps that will be presented. Investment rationale Data collection Model training Backtesting Strategy falsification Strategy evaluation Before starting,
  • Financial Machine Learning pitfalls: it s levioosa, not leviosaa [Quant Dare]

    Financial data is one of kind: we think is non-stationary, and the samples are non-iid, which means one cannot simply apply common machine learning techniques. In this post, we briefly cover some pitfalls when using machine learning algorithms in a financial context. 1. Harry Potter and the model that predicts prices Internet is full of articles claiming it is possible to predict prices using

Quantocracy’s Daily Wrap for 04/18/2023

This is a summary of links featured on Quantocracy on Tuesday, 04/18/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Advanced Futures Trading Strategies [Investment Idiocy]

    Tommorrow marks the official release of my 4th book: Henceforth to be known as AFTS (I've had authors copies since the 24th February, but modern supply chains being what they are it takes considerably longer for the book to arrive in the hands of my readers; although plenty of people on twitter have been bragging about receiving their copies earlier). You can buy it here (why haven't you
  • Portfolio Allocations vs Risk Contributions [Finominal]

    Most investors analyze investment products based on their holdings However, holdings often misportray of what is determining the risk profile A factor exposure analysis can identify the performance & risk contributors INTRODUCTION It is difficult to watch an hour of European television and not see an advertisement from the Italian confectionary company Ferrero. The ads for Kinder Schokolade
  • Information Decay: which factors have the longest half-lives? [Alpha Architect]

    What are the research questions? The authors argue that factor exposures are random variables governed by a specific distribution that drives the behavior factor exposures over time. Five factors are examined including value, momentum, quality, investment and low volatility, over 12 developed and emerging markets for the period 2002-2019. The five factors analyzed are drawn from academic studies

Quantocracy’s Daily Wrap for 04/15/2023

This is a summary of links featured on Quantocracy on Saturday, 04/15/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Machine Learning Trading Essentials (Part 1): Financial Data Structures [Hudson and Thames]

    Trading in financial markets can be a challenging and complex endeavour, with ever-changing conditions and numerous factors to consider. With markets becoming increasingly competitive all the time, it is a never ending struggle to stay ahead of the curve. Machine learning (ML) has made several advances in recent years, particularly by becoming more accessible. One might think then why not use ML
  • Corrected Cornish-Fisher Expansion: Improving the Accuracy of Modified Value-at-Risk [Portfolio Optimizer]

    Modified Value-at-Risk (mVaR) is a parametric approach to computing Value-at-Risk introduced by Zangari1 that adjusts Gaussian Value-at-Risk for asymmetry and fat tails present in financial asset returns2 through a mathematical technique called CornishFisher expansion. Since its publication, mVaR has been widely adopted by academic researchers, financial regulators3 and practitioners, who

Quantocracy’s Daily Wrap for 04/12/2023

This is a summary of links featured on Quantocracy on Wednesday, 04/12/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Portfolio Tilts versus Overlays: It’s Long/Short Portfolios All the Way Down [Flirting with Models]

    Several years ago, I started using the phrase, Its long/short portfolios all the way down. I think its clever. Spoiler: it has not caught on. The point I was trying to make is that the distance between any two portfolios can be measured as a long/short strategy. This simple point, in my opinion, is a very powerful and flexible mental model for understanding portfolios. If that sounds
  • Trend-Following Filters Part 6 [Alpha Architect]

    This article analyzes six trend-following indicators from a digital signal processing (DSP) frequency domain perspective in which the indicators are considered as digital filters and their frequency response characteristics are determined. In addition, potential trading signals generated by each indicator in the time domain are displayed graphically by applying the indicator to the monthly S&P
  • BERT Model Bidirectional Encoder Representations from Transformers [Quantpedia]

    At the end of 2018, researchers at Google AI Language made a significant breakthrough in the Deep Learning community. The new technique for Natural Language Processing (NLP) called BERT (Bidirectional Encoder Representations from Transformers) was open-sourced. An incredible performance of the BERT algorithm is very impressive. BERT is probably going to be around for a long time. Therefore, it is

Quantocracy’s Daily Wrap for 04/10/2023

This is a summary of links featured on Quantocracy on Monday, 04/10/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Terms of trade as FX trading signal [SR SV]

    All other things equal, an improvement in a countrys terms of trade, the ratio of export to import prices, translates into increased demand for its currency and a boost for its growth outlook. However, terms of trade are a rather subtle and sporadic influence. Therefore, many market participants are rationally inattentive to smaller changes and unwilling to trade on large changes in times of
  • Informational Efficiency of Stock Prices and Index Investing [Alpha Architect]

    The authors ask the following questions: Does the rise of index investing change information production in the economy? Does it affect the informational efficiency of stock prices? What are the Academic Insights? The authors augment (and improve) the Grossman and Stiglitz (1980) model of endogenous information acquisition by including a choice by investors where investors choose to be passive,
  • The Alpha Games: Technology Funds [Finominal]

    US tech funds underperformed their benchmark indices by 4% between 2018 and 2022 The factor contributions were marginal This resulted in a median alpha of -4% over the 5-year period INTRODUCTION Every day, fortunes are won and lost on the stock market. However, investing in stocks is not a zero-sum game as wealth is created from the profits earned and distributed by public companies. In contrast,

Quantocracy’s Daily Wrap for 04/08/2023

This is a summary of links featured on Quantocracy on Saturday, 04/08/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Mean reversion in government bonds [OS Quant]

    Interest rates are not necessarily a pure random walk. This assumption falls out from noticing that yields of different bond maturities must be in some way related. Have a look at the yields of the 30 year and 3 year U.S. Treasuries in the plot below. Notice that the 3 year yield bounces up and down mostly below the 30 year yield. DGS3 DGS30 0%2%4%6%8%10%12%14%16%18% Interest
  • Undersampling [Financial Hacker]

    All the popular smoothing indicators, like SMA or lowpass filters, exchange more lag for more smoothing. In TASC 4/2023, John Ehlers suggested the undersampling of price curves for achieving a better compromise between smoothness and lag. We will check that by applying a Hann filter to the original price curve and to a 5-fold undersampled curve. The C code of the used Hann filter, straight

Quantocracy’s Daily Wrap for 04/07/2023

This is a summary of links featured on Quantocracy on Friday, 04/07/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Combining Reversals with Time-Series Momentum Strategies [Alpha Architect]

    The empirical evidence from studies such as the 2017 paper A Century of Evidence on Trend-Following Investing and the 2020 paper Time Series Momentum in the US Stock Market: Empirical Evidence and Theoretical Analysis has found that time-series momentum (TSMOM) has demonstrated above-average excess returns in stocks, bonds, commodities, and currencies. Also called trend momentum or
  • Wes Discusses Value Investing Foundations with Isaiah Douglass [Alpha Architect]

    Here is a link to our recent chat with Isaiah Douglass and Josh Bennett. An overview of the conversation is below: On this weeks episode, Isaiah is joined by expert Dr. Wesley Gray, CEO of Alpha Architect, to discuss the concepts of value