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Quantocracy’s Daily Wrap for 04/13/2024

This is a summary of links featured on Quantocracy on Saturday, 04/13/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Use Markov models to detect regime changes [PyQuant News]

    Its rumored that Renaissance Technologies uses hidden Markov models in their trading. In fact, the Baum-Welch algorithm used with Markov models was partially invented by Leonard Baum who would help found RenTec. In todays newsletter, well look an example of using a Markov model to detect regime changes in the equities market. Lets go! Use Markov models to detect regime changes A Hidden
  • Research Review | 12 April 2024 | Equity Risk Premium [Capital Spectator]

    Macroeconomic Announcement Premium Hengjie Ai (University of Wisconsin-Madison), et al. November 2023 The paper reviews the evidence on the macroeconomic announcement premium and its implications on equilibrium asset pricing models. Empirically, a large fraction of the equity market risk premium is realized on a small number of trading days with significant macroeconomic announcements. We review
  • Minimizing the Risk of Cross-Sectional Momentum Crashes [Alpha Architect]

    While empirical research on cross-sectional (long-short) momentum has shown high returns, investors have also experienced huge drawdownsmomentum exhibits both high kurtosis and negative skewness. Since 1926, there have been several momentum crashes that featured short but persistent periods of highly negative returns. For example, from June to August 1932, the momentum portfolio lost about 91%,

Quantocracy’s Daily Wrap for 04/11/2024

This is a summary of links featured on Quantocracy on Thursday, 04/11/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Trend Following with Return Stacking [Investing For A Living]

    After my last post on using trend following in Crypto markets I thought Id continue on that thread and look at applying trend following on a newish concept (similar concepts have existed at the institutional level for a long time) in creating diversified portfolios, called return stacking. First, what is return stacking? The term return stacking was coined by the team at Newfound research and
  • Factor Olympics Q1 2024 [Finominal]

    Some factor trends continued from 2023, but there were also two significant rotations Momentum performed the best, size the worst Most long-short multi-factor products have generated positive excess returns 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

Quantocracy’s Daily Wrap for 04/06/2024

This is a summary of links featured on Quantocracy on Saturday, 04/06/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Trend Following in Crypto Markets [Investing For A Living]

    It has been a while since Ive updated the blog. These days I spend most of my time writing for subscribers of my newsletter but Id like to get back to writing publicly again. So, to launch myself back into public blogging I thought I would write about Crypto and how classic trend following principles can be applied to these new assets. For long time readers or those familiar with trend
  • FX trading signals with regression-based learning [SR SV]

    Regression-based statistical learning helps build trading signals from multiple candidate constituents. The method optimizes models and hyperparameters sequentially and produces point-in-time signals for backtesting and live trading. This post applies regression-based learning to macro trading factors for developed market FX trading, using a novel cross-validation method for expanding panel data.
  • How to replicate your favorite investment portfolio [PyQuant News]

    Market indices are vital in finance, offering investors a quick look at the overall performance of a specific market or sector. They act as benchmarks for assessing the performance of different investment portfolios. Investors can copy the performance of an index for exposure to securities without the need to buy each one. This process is called index replication. In this newsletter, well make

Quantocracy’s Daily Wrap for 04/05/2024

This is a summary of links featured on Quantocracy on Friday, 04/05/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How to Test the Assumption of Persistence [Robot Wealth]

    An assumption we often make in trading research is that the future will be at least a little like the past. I see a lot of beginners making this assumption implicitly without recognising that theyre making it or thinking about whether its reasonable to do so. Thats a mistake. If you are making this assumption, you need to be aware of it and you need to have confidence that its a good
  • Macro trends and equity allocation: a brief introduction [SR SV]

    Macroeconomic trends affect stocks differently, depending on their lines of business and their home markets. Hence, point-in-time macro trend indicators can support two types of investment decisions: allocation across sectors within the same country and allocation across countries within the same sector. Panel analysis for 11 sectors and 12 countries over the last 25 years reveals examples for

Quantocracy’s Daily Wrap for 04/02/2024

This is a summary of links featured on Quantocracy on Tuesday, 04/02/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Economic Momentum [Alpha Architect]

    Out of the hundreds of exhibits in the factor zoo, momentum was 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. Because of the strong empirical evidence, momentumthe tendency of assets that have performed well recently (e.g., over the
  • Optimal Mean-Reversion Strategies [Jonathan Kinlay]

    Consider a financial asset whose price, Xt, follows a mean-reverting stochastic process. A common model for mean reversion is the Ornstein-Uhlenbeck (OU) process, defined by the stochastic differential equation (SDE): Objective The trader aims to maximize the expected cumulative profit from trading this asset over a finite horizon, subject to transaction costs. The traders control is the
  • Duration as an Equity Factor [Finominal]

    Stocks can have a high, low, or negative sensitivity to interest rates The duration profile of stocks changes frequently Having rates exposure in an equities portfolio is not necessarily a concern INTRODUCTION The goal of conducting research is to provide clarity by answering questions or confirming theories, but that is not always achieved. For example, we published two research articles on

Quantocracy’s Daily Wrap for 03/27/2024

This is a summary of links featured on Quantocracy on Wednesday, 03/27/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Cryptocurrency Market Dynamics Around Bitcoin Futures Expiration Events [Quantpedia]

    In the rapidly evolving landscape of cryptocurrency markets, understanding the underlying dynamics that drive price movements and investor sentiment can be a matter of survival. However, there are myriad facets of trading reality, and the only thing that we can do is to slowly understand them one after another, one step at a time. This article picks one corner of the cryptocurrency market and
  • UPRO/TQQQ Leveraged ETF Strategy [Alvarez Quant Trading]

    Recently a reader sent me a leveraged ETF strategy that he wanted tested for the blog. Over the last couple of months, I have been noticing renewed interest in leveraged ETF trading. More clients are coming to me to test out leverage trading ideas. I have been testing my own ideas. What I liked about this strategy is that it moved between leveraged ETFs, non-leveraged ETFs and TLT. The Strategy On
  • Inflation-Themed ETFs: Part II [Finominal]

    Inflation-themed ETFs have heterogeneous portfolios However, commodities and oil have been better inflation hedges And offer higher diversification benefits INTRODUCTION In November 2021 we analyzed inflation-themed ETFs (read Inflation-Themed ETFs: As Complicated as Inflation) and concluded that there were relatively few products on the market given the typical importance of inflation in

Quantocracy’s Daily Wrap for 03/24/2024

This is a summary of links featured on Quantocracy on Sunday, 03/24/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Trading 0DTE Options with the IBKR Native API [Robot Wealth]

    Heres a thing that I suspect will make money, but that I havent yet tested (for reasons that I will explain shortly): Every day, at the start of the trading day, get the SPX straddle price and convert it to an expected SPX price move. Then at the end of the trading day, take the SPX price and calculate if it moved more or less than the straddle implied. Aggregate this over a few days the
  • Macro trends and equity allocation: a brief introduction [SR SV]

    Macroeconomic trends affect stocks differently, depending on their lines of business and their home markets. Hence, point-in-time macro trend indicators can support two types of investment decisions: allocation across sectors within the same country and allocation across countries within the same sector. Panel analysis for 11 sectors and 12 countries over the last 25 years reveals examples for
  • Tracking Error is a Feature, Not a Bug [Alpha Architect]

    The benefits of diversification are well known. In fact, its been called the only free lunch in investing. Investors who seek to benefit from diversification of the sources of risk and return of their portfolios must accept that adding unique sources of risk means that their portfolio will inevitably experience what is called tracking errora financial term used as a measure of the

Quantocracy’s Daily Wrap for 03/19/2024

This is a summary of links featured on Quantocracy on Tuesday, 03/19/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Meb Faber’s 12-Month High Switch [Allocate Smartly]

    This is a test of the 12-Month High Switch Model, a Tactical Asset Allocation (TAA) strategy from Meb Faber. Meb has done more than anyone to popularize TAA as a trading style, including many of the fundamental concepts used today. This is another of his simple but effective ideas. Backtested results from 1970 follow. Results are net of transaction costs see backtest assumptions. Learn about
  • Building a Stock Portfolio for a Debt-Averse World [Finominal]

    Stocks for a low-growth & high-interest rate environment should have high-quality characteristics However, there are many ways to define quality stocks Historically quality portfolios have not generated excess returns INTRODUCTION Ignoring the past is one of the biggest investing mistakes. However, simply looking back and expecting that history will repeat itself is likely an equally large

Quantocracy’s Daily Wrap for 03/17/2024

This is a summary of links featured on Quantocracy on Sunday, 03/17/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Generate synthetic market data with TensorFlow [PyQuant News]

    The lifeblood of quant finance is data. The problem is that data is sometimes hard to come by. It may be expensive or just not available. What if we had a way to generate synthetic market data? Artificially recreating a dataset is a complex process. The new data needs to mimic the existing data distributions and not introduce biasing or noise in the dataset. Thats where Generative Adversarial
  • The Gap Momentum System [Financial Hacker]

    Jerry Kaufman, known for his technical indicators bible, presented in TASC 1/24 a trading strategy based on upwards and downwards gaps. For his system, he invented the Gap Momentum Indicator (GAPM). Here Im publishing the C version of his indicator, and a simple trading system based on it. The indicator is a straighforward conversion of Kaufmans EasyLanguage code to C: var GAPM(int Period,
  • Breaking Bad Momentum Trends [Alpha Architect]

    Perhaps the most well-documented and researched asset pricing anomaly is momentumthe tendency of past winner stocks to outperform past loser stocks over the next several months. While average time-series momentum (trend following) returns have been high, strategies employing trend following have also experienced huge drawdowns (crashes) at turning points (which mark reversals in trend from

Quantocracy’s Daily Wrap for 03/12/2024

This is a summary of links featured on Quantocracy on Tuesday, 03/12/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Systematic Hedging of the Cryptocurrency Portfolio [Quantpedia]

    Cryptocurrencies are already one of the major asset classes. They fill the top pages of magazines and are a topic of a day to day conversation. There are a lot of ways to buy them through a lot of different channels. But some of the hardcore HODLers like to keep their coin portfolio safe they buy a portfolio of cryptocurrencies and hold them in cold storage. It has a lot of advantages (you
  • Volatility Forecasting: GARCH(1,1) Model [Portfolio Optimizer]

    In the previous post of this series on volatility forecasting, I described the simple and the exponentially weighted moving average volatility forecasting models. In particular, I showed that these two models belong to the generic family of weighted moving average volatility forecasting models1, whose members represent the volatility of an asset as a weighted moving average of its past squared
  • A Two-Factor Model for Capturing Momentum and Mean Reversion in Stock Returns [Jonathan Kinlay]

    Financial modeling has long sought to develop frameworks that accurately capture the complex dynamics of asset prices. Traditional models often focus on either momentum or mean reversion effects, struggling to incorporate both simultaneously. In this blog post, we introduce a two-factor model that aims to address this issue by integrating both momentum and mean reversion effects within the