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Quantocracy’s Daily Wrap for 06/16/2021

This is a summary of links featured on Quantocracy on Wednesday, 06/16/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • More ideas for ranking methods on a monthly S&P500 Stock Rotation Strategy [Alvarez Quant Trading]

    My last post on Different ranking methods for a monthly S&P500 Stock Rotation Strategy generated lots of emails on other ideas to try. Below are the results of these ideas Base Rules Backtest from 1/1/2007-12/31/2020. Buy It is the last trading day of the month Stock is a member of the S&P500 index Stock is above the 200-day moving average (spreadsheet has results without this rule) The
  • Automating cryptocurrencies investment [Quant Dare]

    Who has never heard about cryptocurrencies: Bitcoin, Ethereum, Cardano, or even the latest ones, such as Shiba or Safemoon? The investors are rapidly increasing their positions in those assets, although investing in them is usually a pain in the neck. These assets have a high volatility and their movements dont follow any traditional market rule and cryptocurrencies markets are not efficient.
  • Podcast with Ernie Chan (@ChanEP): Predicting profitability using machine learning [Better System Trader]

    Quant trader Ernie Chan from PredictNow.ai joins us to discuss how to predict the profitability of trades using machine learning, including: Unconditional probability and the problem with win% in backtest reports, Why conditional probability is much more useful for a trader and how to apply conditional probabilities to capital allocation, Why you should use Machine Learning for risk

Quantocracy’s Daily Wrap for 06/14/2021

This is a summary of links featured on Quantocracy on Monday, 06/14/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Financial Mentor’s All-Weather Quad Momentum [Allocate Smartly]

    This is an independent test of the tactical strategy All-Weather Quad Momentum (AWQM) from Todd Tresidder of FinancialMentor.com. Many of our members came to us from Financial Mentor, so its fitting that we add a strategy to our platform that demonstrates his approach to asset allocation. Backtested results from 1970 follow. Results are net of transaction costs (see backtest assumptions).
  • Markowitz Model [Quantpedia]

    We again present a short article as an insight into the methodology of the Quantpedia Pro report this time for the Markowitz Portfolio Optimization. As usually, Quantpedia Pro allows the optimization of model portfolios built from the passive market factors (commodities, equities, fixed income, etc.), systematic trading strategies and uploaded users equity curves. The current report helps
  • Can Hedge Funds Successfully Time Factors? [Alpha Architect]

    This study pulls together several threads in the academic literature: (1) the persistence of hedge fund outperformance; (2) the apparent use of time-varying beta exposures by hedge funds, where betas are predicated on conditions such as leverage, carry trade, major events and conditions in the equity market; and (3) the timing of equity and market factors, as a strategy. The research summarized in
  • Create a Personal Portfolio/Wealth Simulation in Python [Python For Finance]

    This post will introduce the first part (of multiple) where we build up a personal finance model to help simulate future time periods based on certain chosen input variables. We will input variables such as our current investable asset base, our annual salary, expected monthly inflows and outflows and a range of other relevant values. Firstly, after our necessary imports, we look to start on
  • Mid-Caps The Hidden Champions? [Factor Research]

    Mid-cap stocks are less popular than small or large caps In the US, they only outperformed in one out of 10 decades Globally, they have done better, creating a conundrum for investors INTRODUCTION A few weeks ago, David Stevenson, a well-known journalist and entrepreneur, asked me about my view on mid-cap stocks. To my own surprise, I had no view. Although Ive published more than 150 research
  • Markets neglect of macro news [SR SV]

    Empirical evidence suggests that investors pay less attention to macroeconomic news when market sentiment is positive. Market responses to economic data surprises have historically been muted in high sentiment periods. Behavioral research supports the idea that investors prefer heuristic decision-making and neglect fundamental information in bullish markets, but pay more attention in turbulent

Quantocracy’s Daily Wrap for 06/12/2021

This is a summary of links featured on Quantocracy on Saturday, 06/12/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Honest Guide to Getting a Quant Job in Finance: (1) So, you want to be a Quant?! [Quant at Risk]

    They say that a journey of thousand miles commences with a single step. So, here you are, firm in your own resolutions or hesitating where to go. Graduated from a university or standing and trembling about next move in your life. Fired from one job or looking for another opportunity to seize. Battling against the wind, the haze, the misfortune that fell unexpectedly upon you, suddenly from
  • Combining Value and Profitability Factors: the International Evidence [Alpha Architect]

    My October 29, 2020, article for Alpha Architect examined the research on the profitability factor. I then reviewed the findings of the June 2020 study On the Conjoint Nature of Value and Profitability, which analyzed how combining the profitability factor with the value factor tilting the portfolios exposure to the two factorsimpacted the risk and return of a long-only U.S.

Quantocracy’s Daily Wrap for 06/10/2021

This is a summary of links featured on Quantocracy on Thursday, 06/10/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Concepts of Entropy in Finance: Transfer entropy [Quant Dare]

    The concept of entropy has many useful applications in finance such as measuring risk, uncertainty, or noise in a signal. In this post we will focus on transfer entropy, a useful tool for causal inference between financial time series. What is entropy? Entropy in general represents the uncertainty, ambiguity, and disorder of a stochastic process. The concept of entropy has been introduced in many

Quantocracy’s Daily Wrap for 06/07/2021

This is a summary of links featured on Quantocracy on Monday, 06/07/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Optimising my way out of a small fund problem – part one [Investment Idiocy]

    This is part one of a series of posts about using optimisation to get the best possible portfolio given a relatively small amount of capital. In this short post I present the idea, and discuss some issues that I need to resolve. It's a bit of a stream of conciousness! It's less of a blog post, and more my random jottings on the subject converted from scribbles to electronic prose.
  • Still Using Book to Market for a Value Metric? Read This. [Alpha Architect]

    Book to Market (B/M) has been a prominent indicator used to construct "value" tilted portfolios. The love affair with B/M started with Graham and Dodd (1934), but became the gold standard after Fama and French (1992). Historically, B/M was a reasonable ratio to express the value factor and it worked incredibly well when investors were hunting for value in steel mills, railroads, and
  • Liquid Alt Juggernauts: Worth their Salt? [Factor Research]

    Liquid alternative mutual funds only captured 10% of the market share from hedge funds The alpha generated since 2013 was essentially zero Long-short equity funds can be replicated simply via market beta + cash INTRODUCTION One of the most perplexing questions in the investment industry is why liquid alternatives have not been able to disrupt the hedge fund industry in the same way as ETFs have

Quantocracy’s Daily Wrap for 06/04/2021

This is a summary of links featured on Quantocracy on Friday, 06/04/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • This Time is Different? Consider Quantifying Subjective Priors [Alpha Architect]

    This time is different. –John Templeton "This time is different," is a sentiment that leads many investors to stray from using data analysis in their investment decision process and more towards discretionary judgment. The logic as to why data analysis techniques may not apply to different situations is often framed in the following way: These particular set of conditions have

Quantocracy’s Daily Wrap for 06/02/2021

This is a summary of links featured on Quantocracy on Wednesday, 06/02/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Linking Attribution Factors [Quant Dare]

    In the business of performance measurement, a recurrent task is the breakdown of a stream of returns into meaningful contributions from different factors, in order to identify the driving financial forces or sources of risk. Eventually, these daily contributions have to be aggregated to explain the complete period performance or the divergence between two different streams of returns. This step is
  • The Case against EM Equities [Factor Research]

    EM equities are highly correlated to US stocks & high yield bonds, limiting diversification benefits They outperform primarily when the USD is depreciating, making it a currency play The largest MSCI EM index members will experience 50% population declines INTRODUCTION Seeing latex slowly dripping out of rubber trees into wooden bowls on a plantation in Malaysia was a fascinating experience as
  • Get Green or Die Trying? [Alpha Architect]

    In 2015, 197 nations signed onto the Paris Agreement and committed to limiting global warming to less than 2 degrees C above preindustrial levels. Although the arguments are compelling, the drive to manage carbon risk presents quite a challenge for individual investors and portfolio managers. Although ESG investing spans the gamut of environmental issues, the specific case of carbon risk is

Quantocracy’s Daily Wrap for 05/31/2021

This is a summary of links featured on Quantocracy on Monday, 05/31/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Explanatory Power of Factor Momentum [Alpha Architect]

    Momentum is the tendency for assets that have performed well (poorly) in the recent past to continue to perform well (poorly) in the future, at least for a short period of time. 1 In 1997, Mark Carhart, in his study On Persistence in Mutual Fund Performance, was the first to use a momentum factor, together with the three FamaFrench factors (market beta, size, and value), to explain mutual
  • Factor momentum: a brief introduction [SR SV]

    Standard equity factors are autocorrelated. Hence, it is not surprising that factor strategies have also displayed momentum: past returns have historically predicted future returns. Indeed, factor momentum seems to explain all return momentum in individual stocks and across industries. Momentum has been concentrated on a subset of factors, most notably those related to betting against beta,

Quantocracy’s Daily Wrap for 05/27/2021

This is a summary of links featured on Quantocracy on Thursday, 05/27/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Fit forecast weights by instrument, by group or fit across all markets? Or all three? [Investment Idiocy]

    I've long been a critic of the sort of people who think that one should run a different trading system for each instrument that you trade. It is the sort of thing that makes intuitive sense; surely the S&P 500 is a completely different animal to the Corn future? And that's probably true for high frequency traders, but not at the sort of timescales that I tend to trade over (holding
  • Different methods for mitigating overfitting on Neural Networks [Quant Dare]

    Using Machine Learning and Deep Learning models to solve scientific problems of greater or lesser complexity is a challenge. Referring to neural networks, on the one hand, simple networks with too little capacity will not learn the problem well producing a model that underfits the data. On the other hand, complex networks with too much capacity will learn it too well leading to a model that
  • Update on Recent Matrix Profile Work [Dekalog Blog]

    Since my previous post, on Matrix Profile (MP), I have been doing a lot of online reading about MP and going back to various source papers and code that are available at the UCR Matrix Profile page. I have been doing this because, despite my initial enthusiasm, the R tsmp package didn't turn out to be suitable for what I wanted to do, or perhaps more correctly I couldn't hack it to get

Quantocracy’s Daily Wrap for 05/25/2021

This is a summary of links featured on Quantocracy on Tuesday, 05/25/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Value and Momentum Investing: Combine or Separate? [Alpha Architect]

    When it comes to Value and Momentum investing we often get asked the following set of questions: Should I use value and momentum, in one screen, to form a single portfolio of stocks? ("Blended", "combined", or "integrated") Or should I focus on the value and momentum factor separately, and then combine the factor portfolios? ("Pure", "Separated",
  • Estimating Fair Value For The 10-Year Treasury Yield, Part II [Capital Spectator]

    Earlier this month, I reviewed a model that estimates a theoretical level for the worlds most-important interest rate: the 10-year Treasury yield. In todays follow-up, lets consider a second model for additional context. The goal in this series is to select several models with an eye on combining the estimates. A long line of literature demonstrates, rather convincingly, that one of the
  • Portfolio Construction in Venture Capital [Factor Research]

    A few winners generate most of the venture capital returns Given this asymmetrical return distribution, portfolios should be constructed equally Missing the winners is simply too risky INTRODUCTION 2020 turned out to be a record year for the venture capital industry, despite the global pandemic. More than 12,000 investments were made into early to late-stage start-ups at a combined value of $166