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Quantocracy’s Daily Wrap for 02/02/2022

This is a summary of links featured on Quantocracy on Wednesday, 02/02/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Exogenous risk overlay: take two [Investment Idiocy]

    This is a short follow up post to one I did a couple of years ago, on "Exogenous risk management". This was quite an interesting post which dug into why expected risk changes for a typical diversified futures trading system. And then I introduced my risk overlay: "Now we have a better understanding of what is driving our expected risk, it's time to introduce the risk overlay.
  • Backtest overfitting and the post-hoc probability fallacy [Mathematical Investor]

    In several articles on this site (see, for instance, A and B), we have commented on the dangers of backtest overfitting in finance. By backtest overfitting, we mean the usage of historical market data to develop an investment model, strategy or fund, where many variations are tried on the same fixed dataset. Backtest overfitting, a form of selection bias under multiple testing, has long plagued
  • What Explains the Momentum Factor? Frog-in-the Pan is Still the King [Alpha Architect]

    A lot of ink has been spilled on a seemingly simple question: Why does the momentum factor exist? We have done our fair share contributing to the question and our collective conclusions are in our book Quantitative Momentum. We walked away from the question and determined the following: We will never really know why the momentum factor actually exists. But we know that is does exist and it is

Quantocracy’s Daily Wrap for 01/31/2022

This is a summary of links featured on Quantocracy on Monday, 01/31/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Naive modelling of credit defaults using a Markov Random Field [Gautier Marti]

    Mid-2020, I read a book on probabilistic graphical models (PGMs) applied in finance by Alexander Denev. Mid-2021, I hosted a machine learning meetup with an application of PGMs to predict the future states of economic and financial variables, and geopolitical events based on forward-looking views expressed by experts in news articles. In this blog post, I finally provide some basic code to
  • Introduction to Dollar-Cost Averaging Strategies [Quantpedia]

    Most of you have probably heard the saying that somebody averaged into or out of his investment position. But what does it exactly mean, and what different dollar-cost averaging strategies exist? We plan to unveil our new Dollar-Cost Averaging report for Quantpedia Pro clients next week, and this article serves as a short introduction to this term. What is dollar-cost averaging?
  • Cryptocurrency Hedge Funds [Factor Research]

    Cryptocurrency hedge funds generated abnormally high and uncorrelated returns since 2014 However, the returns can be simply attributed to the performance of Bitcoin Many crypto-beta ETFs & ETPs have been launched, so crypto hedge funds need to move from beta to alpha INTRODUCTION Cryptocurrencies have reached politics far quicker than other financial instruments given their use in criminal

Quantocracy’s Daily Wrap for 01/27/2022

This is a summary of links featured on Quantocracy on Thursday, 01/27/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Portfolio Strategies for Volatility Investing [Alpha Architect]

    The most basic tenet of financial theory is that risk and expected return are related. One widely used measure of risk is volatility. As far back as 1976, with the publication of Fischer Blacks Studies of Stock Price Volatility Changes, financial economists have known that volatility and returns are negatively correlated. This relationship results in the tendency to produce negative
  • Factor Performance in Bull and Bear Markets [Quantpedia]

    Do common equity factors suffer during bear markets? Undoubtedly, the market factor is a rather unpleasant investment during bear markets, but what about the long-short factors? Are they able to deliver performance? The research paper by Geertsema and Lu (2021) provides several answers and interesting insights. Returns of value, profitability, investment, and momentum are highly positive and
  • The Best Strategies for Dealing with Inflation? Factors and Trend-Following [Alpha Architect]

    Inflation whats that? It has been quite a while since inflation has been considered a problem. Today, however, the angst surrounding the possibility of a resurgence in inflation is real and top of mind for investors. If the current fear becomes a reality, how should investors react? What strategies and asset classes perform well in a rising inflationary environment? If inflation

Quantocracy’s Daily Wrap for 01/24/2022

This is a summary of links featured on Quantocracy on Monday, 01/24/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Tactical Asset Allocation During Bear Markets and Major Pullbacks [Allocate Smartly]

    One of the primary benefits of Tactical Asset Allocation (TAA) is the ability to manage losses during major market declines. TAA does that by reducing allocation to risk asset classes like stocks and real estate, and increasing allocation to defensive assets like bonds and gold. In this post, we test how the 60+ TAA strategies we track would have fared through the 10 most significant market
  • How to Build the Best Quant Team in the World [Hudson and Thames]

    Building on our last article regarding best practices for quantitative finance research groups, this article asks the question: What is the best setup and culture for a quant team? This question may have different answers depending on who you ask. Fortunately, there are some glimpses and statements from the top quantitative research groups that afford us a window into their work environment behind
  • Myth-Busting: ETFs Are Eating the World [Factor Research]

    ETFs are a negligible owner of US stocks Primary and secondary ETF trading has not grown quicker than total stock trading The impact of ETFs on stocks is less strong than frequently suggested INTRODUCTION Software is eating the world. The venture capitalist Marc Andreessen wrote these words back in 2011. From todays perspective, with companies like Alphabet, Microsoft, and Meta dominating

Quantocracy’s Daily Wrap for 01/23/2022

This is a summary of links featured on Quantocracy on Sunday, 01/23/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Option Implied Stock Price vs. Actual Traded Stock Price [Newmark Risk]

    Stock and options markets can disagree about a stocks value because of informed trading in options and/or price pressure in the stock. This difference between the options implied stock price and the actual traded stock price (DOTS) can give insight into the markets view on the expected future price and thus can be utilized to predict the underlying stock return. First Glance As with many
  • VIX-Yield Curve Cycles May Predict Recessions [Quantpedia]

    Equities provide significant long-term returns, but the growth certainly is not constant or even stable. Anyway, this holds for almost every financial asset. Bear markets alternate bull markets, and expansion periods rotate with recession periods. Since recessions and bear markets come hand in hand for several asset classes, recession predictions have always been the foremost concern. The yield
  • How to estimate factor exposure, risk premia, and discount factors [SR SV]

    The basic idea behind factor models is that a large range of assets returns can be explained by exposure to a small range of factors. Returns reflect factor risk premia and price responses to unexpected changes in the factors. The theoretical basis is arbitrage pricing theory, which suggests that securities are susceptible to multiple systemic risks. The statistical toolkit to estimate factor

Quantocracy’s Daily Wrap for 01/19/2022

This is a summary of links featured on Quantocracy on Wednesday, 01/19/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Best Research Practices for Your Quant Group [Hudson and Thames]

    Its early in the morning and the markets are about to open. As an individual trader/investor, or perhaps the manager of a group of traders/investors, you are intensely studying the latest news feed that you think may have an impact on your portfolio. Amongst the other plethora of tools at your disposal, you have often read about some of the amazing stories from algorithmic trading groups that
  • Clustering and correlations [Investment Idiocy]

    Happy new year! A very quick post from me this month – I'm trying to get ready for teaching next week and also cracking on with my latest book. On the Systematic Trader podcast I recently discussed using a clustering algorithim to group instruments. Using my software, pysystemtrade, I can get a correlation matrix of asset returns and cluster it quite easily (all the code for this post is here

Quantocracy’s Daily Wrap for 01/18/2022

This is a summary of links featured on Quantocracy on Tuesday, 01/18/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Financial Mentor’s Optimum3 Strategy [Allocate Smartly]

    This is an independent test of Optimum3, a tactical asset allocation strategy from Todd Tresidder of FinancialMentor.com. Optimum3 starts as a momentum strategy similar to many of the TAA strategies we track. It combines that with a unique approach to portfolio optimization to enforce a degree of high momentum diversification. Backtested results from 1987 follow. Results are net of
  • Analyzing stock data near events with pandas [Wrighters.io]

    Stock returns can be heavily impacted by certain events. Sometimes these events are unexpected or a surprise (natural disasters, global pandemics, terrorism) and other times they are scheduled (presidential elections, earnings announcements, financial data releases). We can use pandas to obtain financial data and see the impacts of events the returns of stocks. In my earlier article on financial
  • Lottery Effect in ETFs Across Several Asset Classes [Quantpedia]

    Indisputably, we are witnesses of an ETF mega boom. From passive to active ETFs, their numbers seem to be ever-increasing. Since these exchange-traded funds can be excellent (accessible, transparent, liquid) instruments, it is a great necessity to examine their possible usage in active and systematic trading or investing. Therefore, the short research critically assesses the possibility of using
  • Analyzing Floating Rate ETFs [Factor Research]

    Floating rate ETFs pursue differentiated strategies Some of them are highly correlated to equities, limiting any diversification benefits The correlation with interest rates and inflation has been low INTRODUCTION Despite the consensus on high inflation being transitory in 2021, the five-year, five-year forward inflation expectation rate in the US remains stubbornly above 2%. Investors that hoped

Quantocracy’s Daily Wrap for 01/14/2022

This is a summary of links featured on Quantocracy on Friday, 01/14/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Quality Factor in Sector Investing [Quantpedia]

    In general, a factor is described as a characteristic that can be associated with a group of assets, and it helps to explain their returns and risks. As noted in the literature focusing on CAPM, the market itself can be viewed as the primer and most significant equity factor. Besides the market factor, academics generally look for persistent factors over time with solid explanatory power over a
  • SP-500 Seasonality [Alvarez Quant Trading]

    Ive been seeing lots of seasonality type charts on the S&P500 where they take the average return for each day of the year and then create a return curve for the year. The chart often shows the sell in May and buy in November flatness of the returns. And then the holiday end of the year run up. Steven, my trading buddy, sent me yet another chart and I noticed something I had not seen
  • Research Review | 14 January 2022 | Inflation [Capital Spectator]

    The Time-Varying Relation between Stock Returns and Monetary Variables David G. McMillan (University of Stirling) November 2, 2021 The nature of the relation between stock returns and the three monetary variables of interest rates (bond yields), inflation and money supply growth, while oft studied, is one that remains unclear. We argue that the nature of the relation changes over time and this
  • Factor Investing in Sovereign Bond Markets [Alpha Architect]

    In our 2016 book Your Complete Guide to Factor-Based Investor Andrew Berkin and I recommended that due to the risks of data mining (or p-hacking)researchers torture the data until it confessesfor you to consider investing in a factor it should have demonstrated a premium that was: persistent across long periods of time and economic regimes; pervasive across asset classes and around the

Quantocracy’s Daily Wrap for 01/12/2022

This is a summary of links featured on Quantocracy on Wednesday, 01/12/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How to get serious about making money trading [Robot Wealth]

    In Australia, if youre serious about getting the job done effectively and efficiently, you might say: Im not here to f*** spiders. Many traders act like they are, indeed, here to f*** spiders. If youre making soup, you first need a good stock. Stock isnt exciting. Everyone has stock. Garnish is exciting, but you cant make soup from just garnish. Similarly, you need some stock
  • Finding Alpha on the Internet – Part 2 [Derek Wong]

    I was continuing from the last post. I will explain why I picked the paper I did, answer the questions from the previous post, and show my note-taking and thought process. After reading hundreds if not thousands of whitepapers, blogs, or articles, this is my distilled version of how I approach it. I will document this for the first time. It may be different from how others approach it. Over time
  • Trend-Following Filters Part 4 [Alpha Architect]

    Previous articles in this series examine, from a digital signal processing (DSP) frequency domain perspective, various types of digital filters used by quantitative analysts and market technicians to analyze and transform financial time series for trend-following purposes. An Introduction to Digital Signal Processing for Trend Following Trend-Following Filters Part 1 Trend-Following Filters
  • Analyzing S&P 500 Constituents Returns by Sector [Quant Dare]

    In a previous post we analyzed the performance of US Sectors using SPDR Sector ETFs. Now, lets dive into the analysis of sectors using S&P 500 components and some measures of its performance. Before going any further, it is important to note that there are some differences between the Sector SPDR and the figures that we are going to see. In this analysis, we weight each company equally but

Quantocracy’s Daily Wrap for 01/11/2022

This is a summary of links featured on Quantocracy on Tuesday, 01/11/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How backtest overfitting in finance leads to false discoveries [Mathematical Investor]

    The present author, together with Marcos Lpez de Prado, has just published the article How backtest overfitting in finance leads to false discoveries in Significance, a journal of the British Statistical Society. The published article is now available at the Significance (Wiley) website. This article is condensed from the following manuscript, which is freely available from SSRN: Finance is Not
  • Asset Allocation and Private Market (i.e. illiquid) Investing [Alpha Architect]

    Allocations to illiquid assets(1) have become increasingly popular, thus requiring asset managers to consider portfolio-wide liquidity characteristics. Although determining the price of illiquidity is a challenge for investors, the construction of a portfolio that includes liquidity constraints can be even more daunting. Improvised, or other less formal approaches to manage illiquidity, are less