Quantocracy

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Quantocracy’s Daily Wrap for 05/13/2023

This is a summary of links featured on Quantocracy on Saturday, 05/13/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Clustering trading rule p&l [Investment Idiocy]

    I recently upgraded my live production system to include all the extra instruments I've added on recently. I also did a little consolidation of trading rules, simplifying things slightly by removing some rules that didn't really have much allocation, and adding a couple from my new book. As usual I set the instrument weights and forecast weights using my handcrafting methodology, which
  • Pursuing Factor Premiums at the Industry and Country Level [Alpha Architect]

    Given the strong empirical evidence demonstrating the persistence, pervasiveness, robustness, and implementability of premiums for the factors of size, value, momentum, and profitability in the cross-section of returns, investors may be tempted to gain exposure to those factors across industries and countries. Intuitively, some industries and countries may appear smaller, of deeper value, or more

Quantocracy’s Daily Wrap for 05/10/2023

This is a summary of links featured on Quantocracy on Wednesday, 05/10/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Winning with Simple, not even Linear Time-Series Models [Sarem Seitz]

    As the name implies, today we want to consider almost trivially simple models. Although the current trend points towards complex models, even for time-series models, I am still a big believer in simplicity. In particular, when your dataset is small, the subsequent ideas might be useful. To be fair, this article will probably be most valuable for people who are just starting out with time-series

Quantocracy’s Daily Wrap for 05/09/2023

This is a summary of links featured on Quantocracy on Tuesday, 05/09/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • A Beginner’s Guide to Using DuckDB with Stock Price Data in R [Robot Wealth]

    In this blog post, I will demonstrate how to work with stock price data using the DuckDB database management system in R. DuckDB is a fast and lightweight analytical database engine that is designed to work with various programming languages, including R. You can use Duck DB from the command line or from a client library for your favourite language. In this areticle, Ill use the R client

Quantocracy’s Daily Wrap for 05/08/2023

This is a summary of links featured on Quantocracy on Monday, 05/08/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Gerber Statistic: A Robust Co-Movement Measure for Correlation Matrix Estimation [Portfolio Optimizer]

    The Gerber statistic is a measure of co-movement similar in spirit to the Kendalls Tau coefficient that has been introduced in Gerber et al.1 to estimate correlation matrices within the Markowitzs mean-variance framework. In this post, after providing the necessary definitions, I will reproduce the empirical study of Gerber et al.1 which highlights the superiority of the Gerber correlation
  • Finding Funds with Diversification Potential [Finominal]

    Downside betas do not help to identify diversifying strategies These need to be combined with upside betas Betas to the S&P 500 were more useful than betas to the VIX INTRODUCTION In our article Downside Betas vs Downside Correlations (read Downside Betas vs Downside Correlations) we contrasted the downside and upside betas of eight hedge fund types that are marketed as diversifying

Quantocracy’s Daily Wrap for 05/07/2023

This is a summary of links featured on Quantocracy on Sunday, 05/07/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

Quantocracy’s Daily Wrap for 05/06/2023

This is a summary of links featured on Quantocracy on Saturday, 05/06/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Trading and investing performance year nine – part 2: Futures trading [Investment Idiocy]

    Here is part two of my annual review. Part one looked at my overall portfolio, including long only, but there was only a cursory look at my futures. Here in this second part I will be looking a my futures trading account in a lot more detail. It's important to say why I'm doing this. I'm certainly not doing it so I can upweight good strategies, and delete badly performing ones. A
  • Macroeconomic cycles and asset class returns [SR SV]

    Indicators of growth and inflation cycles are plausible and successful predictors of asset class returns. For proof of concept, we propose a single balanced cyclical strength score based on point-in-time quantamental indicators of excess GDP growth, labor market tightening, and excess inflation. It has clear theoretical implications for all major asset markets, as rising operating rates and
  • Retail Investors – naive and biased? [Alpha Architect]

    A series of events has led to significantly increased interest in stock and options trading by retail investors: The arrival of investing platforms (such as Robinhood) with zero trading commissions and no account minimums. The COVID-19 pandemic, causing many workers to largely remain at home for most of 2020, leading to lower consumer spending and more time to pursue alternative ventures. The

Quantocracy’s Daily Wrap for 05/04/2023

This is a summary of links featured on Quantocracy on Thursday, 05/04/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

Quantocracy’s Daily Wrap for 05/02/2023

This is a summary of links featured on Quantocracy on Tuesday, 05/02/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • ETF Trading: What’s the best time? [Alpha Architect]

    The expense ratio aside, the cost of transacting in an ETF depends on the size of the bid/ask spread at any point in time during the trading day. The ETF investor should make evidence-based trading decisions since the bid/ask spread can range from 1 basis point (bp) to several hundred bps. What are some intelligent guidelines for ETF investorsavoid the open, avoid the close, and what about
  • Book Review: Volatility Trading [Gautier Marti]

    A good book for an introduction to volatility from a trading perspective. Some excerpts from Volatility Trading by Sinclair: I am a trader. I am not a mathematician, financial engineer, or philosopher. My success is measured in profits. The tools I use and develop need only be useful. They need not be consistent, provable, profound, or even true. My approach to trading is mathematical, but I am no
  • Upside versus Downside Stocks [Finominal]

    Stocks can be ranked by their upside and downside betas to the S&P 500 Results in strong sector biases and factor exposures Excess returns from upside stocks were negative, zero for downside stocks INTRODUCTION Most capital allocators use correlation to identify strategies that may add diversification benefits to their portfolios. However, average correlations are often misleading. For

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