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Quantocracy’s Daily Wrap for 02/27/2023

This is a summary of links featured on Quantocracy on Monday, 02/27/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Performance attribution of a crypto market-neutral book on a statistical risk model [Gautier Marti]

    In this short blog post, we investigate whether a simple systematic market-neutral stat arb crypto book loads on the main components of a statistical risk model. from datetime import timedelta import pandas as pd from tqdm import tqdm import statsmodels.formula.api as smf def compute_pnl_attribution( symbol, date, weights, returns, factor_returns, info, fexp_cols, ): if symbol not in
  • ETF Crusades [Finominal]

    This research note is a guest post from Rodolfo Martell, PhD, Head of Portfolio Strategy, of Pluribus Labs LLC, a San Francisco-based systematic active equity manager that is part of Exos Financial. SUMMARY Religious-themed ETFs have increased their AUM to roughly $1 billion 3 / 4 products outperformed their benchmarks since 2020 The outperformance can be attributed to their factor exposures

Quantocracy’s Daily Wrap for 02/25/2023

This is a summary of links featured on Quantocracy on Saturday, 02/25/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Inside the Minds of Expected Stock Returns [Alpha Architect]

    Financial literature has produced a long list of firm characteristics (referred to as factors) that provide information as to future stock returns, with the explanation for the casual relationship between the characteristics and returns being either risk- or behavioral-based. The traditional finance (risk-based) explanation is that stocks with certain characteristics tend to perform worse when the
  • How to Deal With Missing Financial Data [Quantpedia]

    The problem of missing financial data is widespread yet often overlooked. An interesting insight into the structure of missing financial data provides a novel research paper by authors Bryzgalova et al. (2022). Firstly, examining the dataset of the 45 most popular characteristics in asset pricing, the authors found that missing data is frequent among almost any characteristic and affects all kinds
  • Predicting base metal futures returns with economic data [SR SV]

    Unlike other derivatives markets, for commodity futures, there is a direct relation between economic activity and demand for the underlying assets. Data on industrial production and inventory build-ups indicate whether recent past demand for industrial commodities has been excessive or repressed. This helps to spot temporary price exaggerations. Moreover, changes in manufacturing sentiment should

Quantocracy’s Daily Wrap for 02/23/2023

This is a summary of links featured on Quantocracy on Thursday, 02/23/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

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

    Deutsche Bank Currency Volatility Index was developed to provide an implied volatility benchmark for major currency markets. The index is designed to represent investors expectation of future volatility, and is calculated as the weighted arithmetic average of the 3-month level of implied volatility for 9 major currency pairs – with weights: EURUSD 35.90% USDJPY 21.79% GBPUSD 17.95 USDCHF 5.13%
  • What Is Managed Futures? [Flirting with Models]

    Much like in 2008, managed futures as an investment strategy had an impressive year in 2022. With most traditional asset classes struggling to navigate the inflationary macroeconomic environment, managed futures has been drawing interest as a potential diversifier. Managed futures is a hedge fund category that uses futures contracts as their primary investment vehicle. Managed futures managers can
  • Exploring the finnhub.io API [Robot Wealth]

    Over the last few years, a number of new market data providers have come online. They tend to have modern websites, broad coverage, and well-documented RESTful APIs. Their services are often priced very competitively especially for personal use and usually have generous free tiers. One such newcomer is finnhub.io . Its offering includes stock, bond, crpto, and FX historical price data and
  • The Hard-Knock Life of Short Sellers [Finominal]

    Short-biased hedge funds provided negative S&P 500 beta until 2011 Thereafter returns became less negatively correlated, but worsened The strategy has generated limited diversification benefits for investors INTRODUCTION Running a hedge fund is tough, but some types are tougher to manage than others. For example, an equity long-short fund benefits from a structurally rising stock market, which
  • On the origins of Bayesian statistics [Quant Dare]

    Bayesian statistics is a powerful field of mathematics that has wide-ranging applications in many fields, including finance, medical research, and information technology. It allows us to combine prior beliefs with evidence to obtain new posterior beliefs, thereby enabling us to make more informed decisions. In this post we will have a brief look at some of the main mathematicians that gave birth

Quantocracy’s Daily Wrap for 02/17/2023

This is a summary of links featured on Quantocracy on Friday, 02/17/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Introducing Hybrid Asset Allocation (HAA) [TrendXplorer]

    HAA aims to offer retail investors a tactical asset allocation strategy that is both balanced and aggressive at the same time. HAAs hybrid approach combines traditional dual momentum with canary momentum which results in robust crash protection with low cash-fractions. HAA effectively selects assets only when they are most likely to appreciate. HAAs ability to obtain positive returns
  • Major brokerages and news media feature technical analysis [Mathematical Investor]

    Suppose, in a national TV newscast, instead of citing data, analysis and predictions from major government agencies, the weatherperson displayed a chart of recent temperatures, noting trends, waves and breakout patterns. Most of us would not have confidence in such a dubious and unorthodox forecast. Or suppose, at a medical clinic, that a cardiologist made some hand measurements
  • A Dark Winter for Value Stocks [Alpha Architect]

    As seen in the table below, the four-year period November 2016-October 2020 could be described as a dark winter for value stocks. U.S. value stocks underperformed U.S. growth stocks by 16.81 percentage points per annum (20.35% vs. 3.54%), the largest historical drawdown for value stocks in the U.S.even greater than the during the dot-com bubble of the late 1990s. While the value
  • Research Review | 17 February 2023 | Risk Analysis [Capital Spectator]

    Submergence = Drawdown Plus Recovery Dane Rook (Stanford University), et al. February 2023 Drawdowns and recoveries are often analyzed separately yet doing so can leave investors with a distorted view of risk. Indeed, this problem is so commonplace that theres no consistently-used term for the joint event of a drawdown plus its subsequent recovery. We propose the term submergence for

Quantocracy’s Daily Wrap for 02/15/2023

This is a summary of links featured on Quantocracy on Wednesday, 02/15/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Investigating Price Reaction Around Bitcoin & Ethereum Events [Quantpedia]

    Cryptocurrencies are a high-risk and very speculative asset class that, from being used only by tech geeks worldwide, spread from small retail craziness of early adopters to institutional adoption and mainstream. Some claim it to be a world-changing concept with the utilization of blockchain (databases) and smart contracts that open a wide range of opportunities, from decentralizing finance to
  • Yield curve modeling [Quant Dare]

    The financial industry is constantly searching for models that can help accurately predict the behavior of interest rates. In this article we will explore one of the most widely used models for this purpose, the Nelson-Siegel (NS) model. What is the Nelson-Siegel Model? The NS model is a yield curve factor model. Yield curve factor models are based on the idea that the yield curve can be

Quantocracy’s Daily Wrap for 02/14/2023

This is a summary of links featured on Quantocracy on Tuesday, 02/14/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • What’s My International Exposure? [Finominal]

    The S&P 500 has meaningful exposure to international markets Measuring geographical exposure can be done top-down or bottom-up However, both approaches have flaws INTRODUCTION Globalization has significantly improved our lives, although some countries like Germany have benefitted more than others given export-oriented industries. It is easy for politicians to highlight damage done by foreign
  • Dominate the Markets with ChatGPT and TradingView [Analyzing Alpha]

    Attention all traders! Are you looking for a cutting-edge way to dominate the markets and maximize your profits? Look no further than the power of ChatGPT and TradingView. By combining the advanced AI capabilities of ChatGPT with the unparalleled charting and analysis tools of TradingView, you can create custom trading strategies with ease and precision without knowing how to code Say goodbye
  • Open or Close? Why Not Both? [Financial Hacker]

    In his TASC February 2023 article, John Ehlers proposed to use the average of open and close, rather than the close price, for technical indicators. The advantage is a certain amount of noise reduction. On intraday bars the open-close average is similar to an SMA(2). It makes the data a bit smoother, but at cost of additional lag by half a bar. The script below, in C for the Zorro platform,
  • Testing macro trading factors [SR SV]

    The recorded history of modern financial markets and macroeconomic developments is limited. Hence, statistical analysis of macro trading factors often relies on panels, sets of time series across different currency areas. However, country experiences are not independent and subject to common factors. Simply stacking data can lead to pseudo-replication and overestimated significance of

Quantocracy’s Daily Wrap for 02/10/2023

This is a summary of links featured on Quantocracy on Friday, 02/10/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

Quantocracy’s Daily Wrap for 02/09/2023

This is a summary of links featured on Quantocracy on Thursday, 02/09/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Equities, Bonds and maximising CAGR [Investment Idiocy]

    Lots of things have changed in the last year. Many unthinkable things are now thinkable. A war in Europe. The UK coming 2nd in the Eurovision song contest rather than the usual dismal 'null points'. And of course, the correlation of stocks and bonds has recently gone more positive than it has been for over 20 years: Rolling 12 month correlation of weekly returns for S&P 500 equity

Quantocracy’s Daily Wrap for 02/06/2023

This is a summary of links featured on Quantocracy on Monday, 02/06/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Growth ETFs: Performance & Factor Exposures [Finominal]

    Growth ETFs are not very differentiated, despite growth having various interpretations 34 out of 40 growth ETFs underperformed the stock market over the last 3 years Nor was the long-term performance attractive INTRODUCTION Factors like value or momentum are also called stock market anomalies as there should not be any repeatable investing process that allows investors to harvest excess returns

Quantocracy’s Daily Wrap for 02/03/2023

This is a summary of links featured on Quantocracy on Friday, 02/03/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Percentage or price differences when estimating standard deviation – that is the question [Investment Idiocy]

    In a lot of my work, including my new book, I use two different ways of measuring standard deviation. The first method, which most people are familiar with, is to use some series of recent percentage returns. Given a series of prices p_t you might imagine the calculation would be something like this: Sigma_% = f([p_t – p_t-1]/p_t-1, [p_t-1 – p_t-2]/pt-2, ….) NOTE: I am not concerned with the
  • Does dividend impact matter to stock returns? [Alpha Architect]

    Many investors, especially those using a cash flow approach to spending, have long known that they prefer cash dividends. From the perspective of classical financial theory, this behavior is an anomaly. In their 1961 paper, Dividend Policy, Growth, and the Valuation of Shares, Merton Miller and Franco Modigliani famously established that dividend policy should be irrelevant to stock returns.
  • Playing around with leveraged ETFs; or how to get positive skew without trend following [Investment Idiocy]

    As readers of my books will know, I don't recommend leveraged ETFs as a way to get leverage. Their ways are very dark and mysterious. But like many dark and mysterious things, they are also kind of funky and cool. In this post I will explore their general funkiness, and I will also show you how you can use them to produce a positive skewed return without the general faff of alternative ways
  • SPX Golden Crosses Since 1928 [Quantifiable Edges]

    SPX will post a Golden Cross on Thursday afternoon. A Golden Cross occurs when the 50ma crosses over the 200ma. Having the 50ma above the 200ma is commonly considered a bullish market condition and generally it is. In the 7/9/20 blog post I looked at SPX Golden Crosses dating all the way back to 12/31/1928. I have updated that research tonight with Amibroker Software and Norgate Data. Below is