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Quantocracy’s Daily Wrap for 01/19/2024

This is a summary of links featured on Quantocracy on Friday, 01/19/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Dr. Keller & Keuning s Simple Variation of Hybrid Asset Allocation [Allocate Smartly]

    This is a test of the simple variation of Dr. Keller and Keunings strategy from their paper Dual and Canary Momentum with Rising Yields/Inflation: Hybrid Asset Allocation (HAA). Weve covered the balanced version of HAA previously. It has become one of the more popular strategies on our platform, and members have asked us to add this simpler-to-execute variation as well.

Quantocracy’s Daily Wrap for 01/18/2024

This is a summary of links featured on Quantocracy on Thursday, 01/18/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Exploration of CTA Momentum Strategies Using ETFs [Quantpedia]

    Commodity Trading Advisor (CTA) funds are commonly associated with managed futures investing in futures and options, and are a subset of the broader hedge fund universe[1]. Beyond commodities, they have the flexibility to venture into other assets, including interest rates, currencies, fixed income and equity indices. Most of the CTA strategies are trend-following in nature. Trend-following

Quantocracy’s Daily Wrap for 01/17/2024

This is a summary of links featured on Quantocracy on Wednesday, 01/17/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Can You Trade Only The “Best” Trend Signals? [Return Sources]

    Trend following is a relatively simple strategy, at least at the concept level: buy when prices go up, and sell when they go down. The main way that trend followers differentiate themselves is the timeframe over which they measure whether the price has gone up or down. For example, one manager might follow short term trends, like one month price moves. Another might use long-term trends, like
  • Adaptive Asset Allocation Extended [Foss Trading]

    This post extends the replication from the Adaptive Asset Allocation Replication post by running the analysis on OOS (out-of-sample) data from 2015 through 2023. Thanks to Dale Rosenthal for helpful comments. The paper uses the 5 portfolios below. Each section of this post will give a short description of the portfolio construction and then focus on comparing the OOS results with the replicated

Quantocracy’s Daily Wrap for 01/16/2024

This is a summary of links featured on Quantocracy on Tuesday, 01/16/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Quant_rv_MV5_big, and a milestone [Babbage9010]

    The same multi-vol quant strategy we all love, but now with 2000+ vol signals to choose from. quant_rv is a daily SPY strategy that uses realized volatility measures of SPY to predict days of lower volatility ahead, that in turn predict positive returns. In the net, quant_rv wins by very modest improvements to the SPY win ratio and by modest improvements to the average win size relative to the
  • Advanced FX carry strategies with valuation adjustment [SR SV]

    FX forward-implied carry is a popular ingredient in currency trading strategies because it is related to risk premia and implicit policy subsidies. Its signal value can often be increased by considering inflation differentials, hedging costs, data outliers, and market restrictions. However, even then, FX carry is an imprecise and noisy signal, and previous research has shown the benefits of
  • 46 awesome books for quant finance, algo trading, and market data analysis [PyQuant News]

    One of the most common questions I get: What books should I read for quant finance, algorithmic trading, and market data analysis? And one of my favorite hobbies is collecting books on the subject. 46 awesome books for quant finance, algo trading, and market data analysis 46 books for quant finance, algo trading, and market data analysis. Books for quant finance, algorithmic trading, and market
  • Getting Value Exposure from Non-Value Funds [Finominal]

    The factor betas of value-focused ETFs range dramatically Non-value-focused funds can have high betas to the value factor However, these often come with large unintended bets INTRODUCTION While some investors are die-hard believers in value investing, others regard this more opportunistically and only occasionally seek exposure to this investing style. Perhaps cheap stocks have been outperforming,

Quantocracy’s Daily Wrap for 01/12/2024

This is a summary of links featured on Quantocracy on Friday, 01/12/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Pragmatic Asset Allocation Model for Semi-Active Investors [Quantpedia]

    The primary motivation behind our study stems from an observation of the Global Tactical Asset Allocation (GTAA) strategies throughout the existing papers the majority of them require relatively frequent rebalancing from the point of view of the ordinary investor. Portfolio rebalancing is usually done on a weekly or monthly basis, and while this period may seem overly boring and slow for the
  • A Short Take on Real-World Pairs Trading [Robot Wealth]

    In textbooks, one often sees pairs trading algorithms start by regressing prices of Asset A on Asset B to calculate a hedge ratio. Ive rarely seen anyone actually do this in the real world. Thats because it is a very unstable thing especially for a pair of volatile assets, and especially over a large amount of data. The basic pairs trading algorithm which you see out in the real world
  • Peer-Reviewed Theory and Expected Stock Returns [Alpha Architect]

    As professor John Cochrane observed, the literature on investment factors now fills a veritable factor zoo, with hundreds of options. How do investors select from among this huge array of possibilities? In order to minimize the risk that outcomes result from data mining, in our book Your Complete Guide to Factor-based Investing, Andrew Berkin and I established six criteria for a factor
  • Research Review | 11 January 2024 | Fat Tail Distributions [Capital Spectator]

    Optimal Portfolio Choice with Fat Tails and Parameter Uncertainty Raymond Kan (U. of Toronto) and Nathan Lassance (LFIN/LIDAM) December 2023 Existing portfolio combination rules that optimize the out-of-sample performance under estimation risk are calibrated assuming multivariate normally distributed returns. In this paper, we show that this assumption is not innocuous because fat tails in returns

Quantocracy’s Daily Wrap for 01/10/2024

This is a summary of links featured on Quantocracy on Wednesday, 01/10/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Skew preferences for crypto degens [Investment Idiocy]

    An old friend asking for help… how can I resist? Here is the perplexing paper: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4042239 And here is the (not that senstional) abstract: Bitcoin (BTC) returns exhibit pronounced positive skewness with a third central moment of approximately 150% per year. They are well characterized by a mixture of Normals distribution with one normal
  • How Do You Take Your Commodities? [Return Sources]

    Most portfolios are centered around stocks. Stocks are thought of as the primary return driver, while other additions to the portfolio are thought of less as return drivers, and more as diversifiers. The popular 60 / 40 portfolio is a prime example of this. The vast majority of the returns to this portfolio come from stocks, which are much more volatile than bonds. Bonds do contribute returns, of

Quantocracy’s Daily Wrap for 01/09/2024

This is a summary of links featured on Quantocracy on Tuesday, 01/09/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Choi’s Dividend & Growth Allocation [Allocate Smartly]

    This is a test of Paul Chois paper Balance Between Growth and Dividend: Dividend & Growth Allocation (DGA). This strategy would have delivered exceptional performance over the last 50 years, but we would temper future expectations for several reasons we discuss below. Backtested results from 1974 follow. Results are net of transaction costs see backtest assumptions. Learn about what we
  • Sparse Index Tracking: Limiting the Number of Assets in an Index Tracking Portfolio [Portfolio Optimizer]

    In the previous post, I introduced the index tracking problem1, which consists in finding a portfolio that tracks as closely as possible2 a given financial market index. Because such a portfolio might contain any number of assets, with for example an S&P 500 tracking portfolio possibly containing ~500 stocks, it is [sometimes desirable] that the tracking portfolio consists of a small number of
  • Defensive factor strategy – how do you build one? [Alpha Architect]

    Is there a defensive equity factor? Can one be built? Although it seems like an easy question, the answer is not straightforward. The authors of this piece argue for a careful assessment of factor strategies to deliver a defensive profile convincing enough to attract investors. A defensive return-to-risk posture may or may not be achieved by obvious candidates like quality, low volatility, or
  • Duration of U.S. Equities [Finominal]

    Sectors and factors were not very sensitive to changes in interest rates on average However, the averages are misleading as the sensitivity varies significantly over time The duration of factors was more dispersed than that of sectors INTRODUCTION If equity investors are from Mars, then fixed-income investors are from Venus. Despite nearly all investors holding various combinations of stocks and

Quantocracy’s Daily Wrap for 01/05/2024

This is a summary of links featured on Quantocracy on Friday, 01/05/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Why Do US Stocks Outperform EM and EAFE Regions? [Quantpedia]

    Investing in emerging markets (EM) or developed markets (DM) outside of the United States tends to follow cyclical trends. At times, it becomes popular and crowded to focus solely on U.S. stocks, while in other periods, the trend shifts to favor everything except U.S. equities. This inclination often relies on historical and past performance data, although it doesnt guarantee identical outcomes
  • Crowded Trades Increase Crash Risks [Alpha Architect]

    Arbitrageurs keep markets efficient by moving prices to reflect their fundamental values. However, anomalies can persist because of limits to arbitragethe costs and risks of shorting. The costs and risks of shorting, however, are not the only risks that arbitrageurs face. The publication of research on anomalies in asset pricing models has led to a dramatic increase in factor-based investment

Quantocracy’s Daily Wrap for 01/04/2024

This is a summary of links featured on Quantocracy on Thursday, 01/04/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Sketching the Option Backtester v2 (with Code downloadable for ALL readers) [Hanguk Quant]

    In the last post, we wrote code to test for the pnl of a system that continuously rebalances and shorts the atm straddle on index options. Sketching the Option Backtester (with Code downloadable for ALL readers) HangukQuant December 21, 2023 Sketching the Option Backtester (with Code downloadable for ALL readers) Read full story We just made a few notes – the code is rather inflexible in that

Quantocracy’s Daily Wrap for 01/02/2024

This is a summary of links featured on Quantocracy on Tuesday, 01/02/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • A Deep Dive into Volatility Targeting [Return Sources]

    In the world of trend following, the biggest, most longstanding debate is about whether or not to target a certain level of volatility on an ongoing basis. Listeners of the podcast Top Traders Unplugged will be very familiar with this debate. Unfortunately, some of the language surrounding this argument has become confusing and vague. When we say, volatility targeting, we need to be clear
  • Most popular posts 2023 [Eran Raviv]

    This blog is just a personal hobby. When Im extra busy as I was this year the blog is a front-line casualty. This is why 2023 saw a weaker posting stream. Nonetheless I am pleased with just over 30K visits this year, with an average of roughly one minute per visit (engagement time, whatever google-analytics means by that). This year I only provide the top two posts (rather than the usual 3).
  • Factor Olympics 2023 [Finominal]

    The performance of factors was unexciting and poor in 2023 Quality performed the best, low volatility the worst Low-risk and cheap stocks are currently highly correlated 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 of positive excess returns across