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Quantocracy’s Daily Wrap for 12/30/2023

This is a summary of links featured on Quantocracy on Saturday, 12/30/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Quickly store 2,370,886 rows of historic options data with ArcticDB [PyQuant News]

    Over 1,200,000 options contracts trade daily. Storing options data for analysis has become something only professionals can do using sophisticated tools. One of the professionals recently open sourced their tools for lightening fast data storage and retrieval. ArcticDB is a DataFrame database that is used in production by the systematic trading company, Man Group. Its used for storage,
  • Tracking systematic default risk [SR SV]

    Systematic default risk is the probability of a critical share of the corporate sector defaulting simultaneously. It can be analyzed through a corporate default model that accounts for both firm-level and communal macro shocks. Point-in-time estimation of such a risk metric requires accounting data and market returns. Systematic default risk arises from the capital structures vulnerability and
  • The Financial Distress Puzzle [Alpha Architect]

    That riskier assets should command higher expected returns is the most basic of asset pricing theories. Clearly, financial distress is a risk characteristic, but it presents a puzzle, as there has not been a linear relationship between it and stock returns. For example, John Birge and Yi Zhang, authors of the April 2017 study Risk Factors That Explain Stock Returns: A Non-Linear Factor Pricing

Quantocracy’s Daily Wrap for 12/26/2023

This is a summary of links featured on Quantocracy on Tuesday, 12/26/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Differentiated Trend Following [Return Sources]

    Trend following boils down to one basic idea: buy when the price goes up, and sell when it goes down. Its implementation, though, could be much more complicated. There are a myriad methods and timeframes to choose from, and these methods and timeframes are by and large the dials that CTAs can turn in constructing their trend programs. One manager can focus on long term trend, another one medium
  • Easily cross-validate parameters to boost your trading strategy [PyQuant News]

    Trading strategies often rely on parameters. To enhance and effectively cross-validate these parameters can provide a competitive advantage in the market. However, reliable cross-validation strategies can lead to look-ahead bias and other pitfalls that can lead to overestimating a strategys performance. In todays newsletter, well use VectorBT PRO to easily implement a variety of
  • Are stock returns predictable at different points in time? [Alpha Architect]

    The question of whether stock returns are predictable is of long-standing interest to both academics and investment practitioners. Commonly accepted investment strategies, for example, will behave quite differently in the presence of stock return predictability. The research literature is unclear on the answer and suggests that return predictability, if it exists, will be difficult to exploit on
  • Momentum Everywhere, Including Equity Options [Alpha Architect]

    Because of the strong evidence, momentum continues to receive much attention from researchers. Out of the hundreds of exhibits in the factor zoo, one of just five equity factors that met all the criteria (persistent, pervasive, robust, implementable, and intuitive) Andrew Berkin and I established in our book Your Complete Guide to Factor-Based Investing was momentum (both cross-sectional

Quantocracy’s Daily Wrap for 12/21/2023

This is a summary of links featured on Quantocracy on Thursday, 12/21/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • 2023 Rally – How Strong Is It? [Alvarez Quant Trading]

    This end of year rally which started on October 2023 has been strong. My trading buddy and I started wondering how this compares to the past. Is this a normal strong rally or an abnormally strong one? Determining this is always tough because it depends on the indicators you use. Because of that, I tried lots of them. This will be a post short on words but with lots of tables. Where are
  • Judging the Quality of Indicators [Dekalog Blog]

    In my previous post I said I was trying to develop new indicators from the results of my new PositionBook optimisation routine. In doing so, I need to have a methodology for judging the quality of the indicator(s). In the past I created a Data-Snooping-Tests-GitHub which contains some tests for statistical significance testing and which, of course, can be used on these new indicators.
  • Research Review | 21 DEC 2023 | Portfolio Design & Risk Factors [Capital Spectator]

    Factor Zoo (.zip) Alexander Swade (Lancaster University) et al. October 2023 The number of factors allegedly driving the cross-section of stock returns has grown steadily over time. We explore how much this factor zoo can be compressed, focusing on explaining the available alpha rather than the covariance matrix of factor returns. Our findings indicate that about 15 factors are enough to

Quantocracy’s Daily Wrap for 12/20/2023

This is a summary of links featured on Quantocracy on Wednesday, 12/20/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Trend Following VS. Volatility Capping: Two Kinds of Insurance [Return Sources]

    An equity investor can purchase two kinds of financial insurance. The first, more straightforward kind, is a put option. This contract simply pays off when the S&P 500 (which well use as our stand-in for equity) goes down. In other words, its like any other insurance contract. It protects you against losses from a specific event by rising in value when the event occurs.

Quantocracy’s Daily Wrap for 12/19/2023

This is a summary of links featured on Quantocracy on Tuesday, 12/19/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Beyond Modified Value-at-Risk: Application of Gaussian Mixtures to Value-at-Risk [Portfolio Optimizer]

    In a previous post, I described a parametric approach to computing Value-at-Risk (VaR) – called modified VaR12 – that adjusts Gaussian VaR for asymmetry and fat tails present in financial asset returns3 thanks to the usage of a CornishFisher expansion. Modified VaR, when properly used4, provides accurate estimates of the VaR for a wide range of non-normal portfolio return distributions.
  • Can Machine Learning help to select mutual funds with positive alpha? [Alpha Architect]

    The study emphasizes the importance of integrating machine learning with other tools for investment managers, pension-plan administrators, financial advisors, and independent analysts to help investors select active mutual funds with positive alpha. It also highlights the significance of fund characteristics in predicting alpha, even when portfolio holdings are not disclosed.

Quantocracy’s Daily Wrap for 12/18/2023

This is a summary of links featured on Quantocracy on Monday, 12/18/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Spearman’s rank correlation of technical indicators [Grzegorz Link]

    RSI, MACD, Stochastic, ROC, CCI, %b – technical indicators come in many shapes and sizes.[1] Their names suggest something very technical at play. Maybe even scientific. Yet, they are a polarizing tool. They generate strong, opposing opinions. Some traders value them with near religious zeal, while others despise them as a useless mix of witchcraft and salesmanship, and quite simply, scams. Or at
  • Directional Change in Trading: Indicators, Python Coding, and HMM Strategies [Quant Insti]

    Usually, regime detection is made with an HMM estimation over price returns or price return volatility. However, Chen and Tsang (2021) propose to use the Directional Change indicators as input for a HMM to detect regime shifts. They show that the HMM applied to the Directional Change indicators detects regime shifts better than with an HMM applied to price return volatility. Here we apply
  • How to ingest premium market data with Zipline Reloaded [PyQuant News]

    This article explains how to build the two Python scripts you need to use premium data to create a custom data bundle using Zipline Reloaded. Step 1: Subscribe to premium data By now you should already have an account with Nasdaq Data Link. If not, head over to https://data.nasdaq.com and set one up. Youre looking for QuoteMedia End of Day US Stock Prices. This product offers end-of-day prices,

Quantocracy’s Daily Wrap for 12/16/2023

This is a summary of links featured on Quantocracy on Saturday, 12/16/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Are Alternative Social Data Predictors Useful for Effective Allocation to Country ETFs? [Quantpedia]

    The part of the attention of our own research from the last few months was a little skewed on the side of countries indices and their corresponding ETFs representing them, and we finally conclude our trilogy of investigation on the efficiency of these markets. Firstly, we analyzed price-based valuation measures, and then, in November, we investigated the impact of military expenditures on
  • The Temptation of Factor Timing [Alpha Architect]

    The timing of equity factor premiums has a strong allure for investors because academic research has found that factor premiums are both time-varying and dependent on the economic cycle. For example, Arnav Sheth and Tee Lim, authors of the December 2017 study Fama-French Factors and Business Cycles, examined the behavior of six Fama-French factorsmarket beta (MKT), size (SMB), value
  • Pick the best strike and expiration for trading options [PyQuant News]

    One of the hardest parts of trading options is picking the best strike price and expiration date for your strategy. Whether a simple covered call or more complex strangles, the key to success is constructing the position. But backtesting options is tough: There are millions of contracts that trade daily, they expire weekly, and are assigned if deep in the money. Recently, I stumbled on Optopsy

Quantocracy’s Daily Wrap for 12/13/2023

This is a summary of links featured on Quantocracy on Wednesday, 12/13/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How Much Damage Can I Do Turbo-Punting Shitcoins? [Robot Wealth]

    Here in Australia, were right in the depths of the silly season. We indulge in long lunches, take days off work, and generally let our hair down. In that spirit, I thought I might have some fun punting shitcoins. (Maybe my definition of fun differs from yours, but lets run with it). For the uninitiated, the technical definition of a shitcoin is a recently launched cryptocurrency of dubious

Quantocracy’s Daily Wrap for 12/12/2023

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

  • Portfolio optimisation, uncertainty, bootstrapping, and some pretty plots. Ho, ho, ho [Investment Idiocy]

    Twas the night before Christmas, and all through the house…. OK I can't be bothered. It was quiet, ok? Not a creature was stirring… literally nothing was moving basically. And then a fat guy in a red suit squeezed through the chimney, which is basically breaking and entering, and found a small child waiting for him (I know it sounds dodgy, but let's assume that Santa has been DBS
  • Why A New High Before A Fed Day Is Discouraging [Quantifiable Edges]

    Wednesday is a Fed Day. Fed Days have historically shown an upside tendency. I have documented this tendency in great detail over the years. A higher close today would not be the most favorable Fed Day setup. A big reason for this is that it would mark a 20-day high close. Fed Day bullishness has often occurred when a Fed announcement has helped to alleviate market stress. When the market closes

Quantocracy’s Daily Wrap for 12/11/2023

This is a summary of links featured on Quantocracy on Monday, 12/11/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Managed Futures Rotation [Return Sources]

    Managed futures / trend following is a valuable strategy to have in a portfolio, but it's also somewhat difficult to hold. The reason is that its positive performance tends to come in bursts, as opposed to steadily over time. This can (and does) lead to frustration as the investment in managed futures stagnates or falls over a period of years. I suspect that this property of trend following
  • The Illusion of the Small-Cap Premium [Finominal]

    Small-cap investing is intuitively appealing However, small-caps have underperformed in most markets Screening out low-quality small-caps has not helped significantly INTRODUCTION Investing means parting ways with your money, which is not something we tend to do lightly. The easiest way to get comfortable with an investment opportunity is if great performance is accompanied by a great story. The