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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

Quantocracy’s Daily Wrap for 03/11/2024

This is a summary of links featured on Quantocracy on Monday, 03/11/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The HAA strategy revisited [NLX Finance]

    In February 2023, peer Wouter Keller and JW Keuning published a study of an interesting strategy, Dual and Canary Momentum with Rising Yields/Inflation: Hybrid Asset Allocation (HAA), which uses the Treasury Inflation-Protected Securities (TIPS) markets to decide when a strategy should be invested offensively or defensively. More recently, the Allocate Smartly website also presented the results of
  • Value vs Quality: More Correlated than Ever? [Finominal]

    P/E and ROE factors were highly correlated in recent years However, this is counterintuitive as cheap stocks should not be highly profitable We can explain this perplexity with stocks with negative earnings INTRODUCTION In our recent article Value vs Quality: More Correlated than Ever? we highlighted that the correlations of the long-short P/E and return-on-equity (ROE) factors have changed
  • Betting on a Short Squeeze as Investment Strategy [Alpha Architect]

    Academic research, including the studies Do Investors Overpay for Stocks with Lottery-like Payoffs? An Examination of the Returns on OTC Stocks, Lottery Preference and Anomalies and Do the Rich Gamble in the Stock Market? Low Risk Anomalies and Wealthy Households, has found that there are investors who have a taste, or preference, for lottery-like investments those that
  • Research Review | 8 March 2024 | Combination Model Forecasting [Capital Spectator]

    Market Risk Premium Expectation: Combining Option Theory with Traditional Predictors Hong Liu (Washington University in St. Louis), et al. December 2022 In general, the slackness between the Martin lower bound (solely based on option prices) and the market risk premium depends on economic state variables. Empirically, we find that combining information from option prices and economic state

Quantocracy’s Daily Wrap for 03/07/2024

This is a summary of links featured on Quantocracy on Thursday, 03/07/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Log-normal stochastic volatility with quadratic drift [Artur Sepp]

    Our article Log-normal Stochastic Volatility Model with Quadratic Drift co-authored with Parviz Rakhmonov is published in International Journal of Theoretical and Applied Finance with open access https://www.worldscientific.com/doi/10.1142/S0219024924500031 The log-normality of realised and implied volatilities of asset returns is a well-documented empirical feature. For example, see
  • Why the last good State of the Union speaker was Bill Clinton [Quantifiable Edges]

    Joe Biden will be giving his State of the Union Address tonight, and people are wondering how his talk might impact the market over the next several days. I have looked at performance following State of the Union before and decided to update that research today. The data table below looks back to 1982. There were a few instances, such as 2001 and 2009 where the speech was not an official State

Quantocracy’s Daily Wrap for 03/06/2024

This is a summary of links featured on Quantocracy on Wednesday, 03/06/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Getting Started with the Interactive Brokers Native API [Robot Wealth]

    Here at Robot Wealth, we trade with Interactive Brokers (IB) primarily because they offer access to global markets at a reasonable price. In recent times, IB has put some time and effort into upping its tech game, including development of an API for interacting with its desktop trading applications. An application that interacts with IBs desktop trading applications via the API is essentially a
  • Fitting with: exponential weighting, alpha and the kitchen sink [Investment Idiocy]

    I've talked at some length before about the question of fitting forecast weights, the weights you use to allocate risk amongst different signals used to trade a particular instrument. Generally I've concluded that there isn't much point wasting time on this, for example consider my previous post on the subject here. However it's an itch I keep wanting to scratch, and in
  • Value vs Quality: More Correlated than Ever? [Finominal]

    P/E and ROE long-short factors have become highly correlated During certain periods investors favor expensive and unprofitable stocks However, it is difficult explaining the positive correlation outside of bubbles INTRODUCTION The older I get, the less I seem to know for certain about investing. The confidence in my knowledge has been steadily eroded over the years and much of the curriculum

Quantocracy’s Daily Wrap for 03/02/2024

This is a summary of links featured on Quantocracy on Saturday, 03/02/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Navigating Tradeoffs with Convex Optimisation [Robot Wealth]

    This is the final article in our recent stat arb series. The previous articles are linked below: A short take on stat arb trading in the real world A general approach for exploiting stat arb alphas Ideas for crypto stat arb features Quantifying and combining crypto alphas A simple and effective way to manage turnover and not get killed by costs How to model features as expected returns Building
  • Stochastic Volatility for Factor Heath-Jarrow-Morton Framework [Artur Sepp]

    Let me present our recent research paper with Parviz Rakhmonov on the stochastic volatility model for Factor Heath-Jarrow-Morton (HJM) interest rate framework (available on SSRN: Stochastic Volatility for Factor Heath-Jarrow-Morton Framework). Factor Heath-Jarrow-Morton (HJM) model Under the risk-neutral measure, the interest rate curve can be conveniently modeled using the forward curve f_t(tau)
  • Matlab vs. Python [Jonathan Kinlay]

    In a previous article I made a detailed comparison of Mathematica and Python and tried to identify areas where the former excels. Despite the many advantages of the Python technology stack, I was able to pinpoint a few areas in which I think Mathematica holds the upper hand. Whether those are sufficient to warrant the investment of time and money required to master the Wolfram Language is another
  • Backtest powerful intraday trading strategies [PyQuant News]

    Multi-timeframe (MTF) analysis lets traders build powerful intraday trading strategies. It does this by analyzing asset prices during different timeframes throughout the trading day. The problem is most people get MTF wrong. It requires a vector-based backtest to speed up the operations making it easy to introduce look-ahead bias. When a backtest introduces look-ahead bias, it will overstate
  • Cut your losses: is it a good strategy? [Alpha Architect]

    Conventional wisdom can be defined as ideas that are so accepted that they go unquestioned. Unfortunately, conventional wisdom is often wrong. Two examples are that millions of people once believed the conventional wisdom that the Earth is flat, and millions also believed that the Earth is the center of the universe. An example of conventional wisdom in investing is: Dont just stand

Quantocracy’s Daily Wrap for 02/27/2024

This is a summary of links featured on Quantocracy on Tuesday, 02/27/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Replacing the 40 with qrvx, in R [Babbage9010]

    Select portions of quant_rv can be combined to craft a new strategy (qrvx) that provides positive returns, negative correlation to SPY and crisis alpha, making it nice for combining with SPY (like a 60/40 combo) to create strong returns with low drawdowns. In my last Replacing the 40 post, we coded a trend strategy based on the blog post by Elliot Rozner of the same title, and replaced the

Quantocracy’s Daily Wrap for 02/26/2024

This is a summary of links featured on Quantocracy on Monday, 02/26/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How Much Bitcoin Should We Allocate To the Portfolio? [Quantpedia]

    After years of waiting, the recent launch of spot Bitcoin ETFs marked a significant milestone in the cryptocurrency market, making Bitcoin even more accessible for investors. Spot ETFs provide a convenient and regulated way to gain exposure to Bitcoin without the need to hold the digital asset directly, potentially attracting a broader range of market participants. Many investors are waiting to
  • Hedging Bear Markets & Crashes with Tail Risk ETFs [Finominal]

    Tail risk ETFs have achieved similar return profiles despite different portfolios TAIL represents a traditional tail risk strategy, but offers limited diversification benefits BTAL is more diversifying, but not more than CTAs INTRODUCTION Although more than 3000 ETFs are trading on U.S. exchanges, the majority simply provide exposure to the stock market in various shades. Naturally, there are

Quantocracy’s Daily Wrap for 02/24/2024

This is a summary of links featured on Quantocracy on Saturday, 02/24/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Building Intuition for Trading with Convex Optimisation with CVXR [Robot Wealth]

    This article continues our recent stat arb series. The previous articles are linked below: A short take on stat arb trading in the real world A general approach for exploiting stat arb alphas Ideas for crypto stat arb features Quantifying and combining crypto alphas A simple and effective way to manage turnover and not get killed by costs How to model features as expected returns Next, well
  • Build state-of-the-art portfolios with machine learning [PyQuant News]

    Portfolio optimization usually requires an estimate of the future returns of the assets in the portfolio. This is hard because we cant see into the future. Traditional risk parity uses a quadratic optimizer A cutting edge technique called Hierarchical Risk Parity (HRP) uses graph theory and machine learning to build a hierarchical structure of the investments. By the end of todays
  • Regression-based macro trading signals [SR SV]

    Regression is one method for combining macro indicators into a single trading signal. Specifically, statistical learning based on regression can optimize model parameters and hyperparameters sequentially and produce signals based on whatever model has predicted returns best up to a point in time. This method learns from growing datasets and produces valid point-in-time signals for backtesting.
  • Biotech stocks – is making a bet on them a lottery ticket? [Alpha Architect]

    The academic research, including the 2023 studies Lottery Preference and Anomalies and Do the Rich Gamble in the Stock Market? Low Risk Anomalies and Wealthy Households, the 2022 study Lottery Demand and the Asset Growth Anomaly, and the 2014 study Do Investors Overpay for Stocks with Lottery-like Payoffs? An Examination of the Returns on OTC Stocks, has found that there

Quantocracy’s Daily Wrap for 02/20/2024

This is a summary of links featured on Quantocracy on Tuesday, 02/20/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Robustness Testing of Country and Asset ETF Momentum Strategies [Quantpedia]

    The investment world witnessed a paradigm shift with the introduction of momentum strategies, a concept pioneered by Jagadeesh and Titman in their landmark 1993 study Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Their groundbreaking approach, hinged on the concept of buying stocks with a strong past performance (over 3- to 12-month periods) and
  • Python vs. Wolfram Language [Jonathan Kinlay]

    As an avid user of both Python and Wolfram Language for technical computing, Im often asked how they compare. Pythons strengths as an open-source language are clear: Ubiquity With millions of users, Python has become ubiquitous across fields like data science, ML engineering, web development, and scientific research. This massive adoption fuels continuous enhancement of its tools.
  • Absolute versus Relative Momentum Across Asset Classes [Finominal]

    Absolute and relative momentum can be used as simple asset allocation frameworks Both would have generated a higher return than an equal-weighted portfolio across asset classes However, risk-adjusted returns were lower and drawdowns higher INTRODUCTION Investing is often overwhelming given the enormous number of strategies and asset classes that are available to investors. Deciding on how to
  • Benchmark selection: addressing strategic distortions [Alpha Architect]

    The paper aims to provide insights into the dynamics of benchmark selection, the effectiveness of Relative Performance Evaluation ( RPE ) incentivization, and the broader implications for fund performance and market competition. Self-Declared Benchmarks and Fund Manager Intent: Cheating or Competing? Chen, Evans and Sun FMA working, 2024 A version of this paper can be found here Want to read

Quantocracy’s Daily Wrap for 02/18/2024

This is a summary of links featured on Quantocracy on Sunday, 02/18/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How to Model Features as Expected Returns [Robot Wealth]

    Modeling features as expected returns can be a useful way to develop trading strategies, but it requires some care. The main advantage is that it directly aligns with the objective of predicting and capitalising on future returns. This can make optimisation and implementation more intuitive. It also facilitates direct comparison between features and provides a common framework for incorporating