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Quantocracy’s Daily Wrap for 05/11/2022

This is a summary of links featured on Quantocracy on Wednesday, 05/11/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Selecting a Stock Market Data (Web) API: Not So Simple [Portfolio Optimizer]

    I am sometimes asked if I recommend any stock market data (web) API for a personal use, especially because I mention Alpha Vantage in a couple of previous posts1. I will describe in this post part of the thought process and of the due diligence which led me to select this financial market data provider together with another one (suspense). Notes: Some code snippets for pulling data out of
  • Historic and recent performance by trading rule [Investment Idiocy]

    Another brief post this month; the deadline for the first draft of my latest book is only a couple of months away and I haven't got much free time! But I was asked an excellent question on twitter recently, which was how the various types of trading rule have contributed to my p&l this year. TLDR: divergent eg momentum good, skew brilliant, other convergent rules poor. In fact with my new

Quantocracy’s Daily Wrap for 05/07/2022

This is a summary of links featured on Quantocracy on Saturday, 05/07/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Top Quantitative Finance Blogs and Vlogs: Review 2022 [Quant at Risk]

    The Internet is full of articles covering all kinds of aspects related to finance. Stocks, crypto, indexes have always been a hot topic and many are seeking new ideas in these areas. It is true that in a vast amount of the content one may get lost. There are tons of blogs with irrelevant, outdated, or even false subject matter. Quite often these blogs cover market commentary with off the subject

Quantocracy’s Daily Wrap for 05/05/2022

This is a summary of links featured on Quantocracy on Thursday, 05/05/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Using Momentum to Find Value [Alpha Architect]

    Value and momentum are two of the most powerful explanatory factors in finance. Research on both has been published for over 30 years(1). However, it was not until recently that the two had been studied in combination and across markets. Bijon Pani and Frank Fabozzi contribute to the literature with their study Finding Value Using Momentum, published in The Journal of Portfolio Management
  • Achieving a well-diversified portfolio based on Graph Theory [Quant Dare]

    Graph Theory is widely used in almost every area of interest for visualization or analysis purposes but, for some reason, it is not usually applied in finance. Why not trying to take advantage of its potential in portfolio management? Introduction Current uncertainty is causing very pronounced movements in financial markets, so having a well-diversified portfolio is now more important than ever.
  • The Future of Factor Investing [Alpha Architect]

    In this article, the authors expound on the importance of the factor revolution in finance. Factor investing has moved from a bedrock position to a future of innovation and disruption. With respect to factors the authors discuss where we have been and what can we look forward to. What are the Academic Insights? At the most basic level, factors have been at the center of modern portfolio

Quantocracy’s Daily Wrap for 05/01/2022

This is a summary of links featured on Quantocracy on Sunday, 05/01/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Economic growth and FX forward returns [SR SV]

    Economic growth differentials are plausible predictors of foreign exchange return trends because they are related to differences in monetary policy and return on investment. Suitable metrics for testing growth differentials as trading signals must replicate historic information states. Two types of such metrics based on higher-frequency activity data are [i] technical GDP growth trends, based on
  • Video: Economic Data Analysis with Python Pandas (h/t @PyQuantNews) [Medallion Data Science]

    In this video kaggle grandmaster Rob Mulla takes you through an economic data analysis project with python pandas. We walk through the process of pulling down the data for different economic indicators, cleaning and joining the data. Using the Fred api you can pull up to date data and compare, analyze and explore.

Quantocracy’s Daily Wrap for 04/29/2022

This is a summary of links featured on Quantocracy on Friday, 04/29/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Absorption Ratio: Measuring Financial Risk, Part 2 [Portfolio Optimizer]

    In the previous post, I reviewed the turbulence index, an indicator of financial market stress periods based on the Mahalanobis distance, introduced by Chow and al.1 and Kritzman and Li2. In this post, I will review the absorption ratio, a measure of financial market fragility based on principal components analysis, introduced by Kritzman and al.3. I will also show how to compute this absorption
  • How Does Weighting Scheme Impacts Systematic Equity Portfolios? [Quantpedia]

    How often do you think about the weights of the assets in your portfolio? Do you weigh your assets equally, or do you prefer value-weighting? The researchers behind a recent research paper analyzed various weighting schemes and examined their effect on factor strategy return. They studied five weighting schemes that ignore prices: equal weighting, rank weighting, z-score weighting, inverse
  • Betting Against Beta: New Insights [Alpha Architect]

    The 2014 study by Andrea Frazzini and Lasse Pedersen, Betting Against Beta, established strong support for low-beta (as well as low-volatility) strategies. The authors found that for U.S. stocks, the betting against beta (BAB) factor (a portfolio that holds low-beta assets leveraged to a beta of 1 and shorts high-beta assets deleveraged to a beta of 1) realized a Sharpe ratio of 0.78 between
  • Random Forest on Financial Ratios as an Investment Strategy [Quant Dare]

    Random Forests are widely used Machine Learning algorithms. In finance, certain financial ratios are used to try and predict whether or not a company will outperform the market. Can we use the random forest on financial ratios to articulate an investment strategy which outperforms a buy and hold strategy? Thesis on financial ratios In previous posts, we have seen how certain financial ratios

Quantocracy’s Daily Wrap for 04/26/2022

This is a summary of links featured on Quantocracy on Tuesday, 04/26/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Crypto Tokens and Crypto Coins: What Drives Performance? [Factor Research]

    Investors assume that token prices increase with product utilization in the token ecosystem However, the correlation between the token prices and token volumes has been zero Likely explained by token prices substantially being driven by speculation INTRODUCTION Much of the crypto world is, by definition, cryptic and difficult to understand. But two crypto trends are crystal clear: Both talent and
  • Inflation Deep Dive: An Examination of the Underlying BEA PCE Data [Light Finance]

    Inflation is perhaps the least well understood phenomenon in economics. Once said to be exclusively a monetary phenomenon, our current predicament is significantly more complicated and there is little consensus as to the root cause. Until recently the concern was that inflation would run permanently too low. The topic garnered little interest from the public but has seen a sharp reversal in recent

Quantocracy’s Daily Wrap for 04/24/2022

This is a summary of links featured on Quantocracy on Sunday, 04/24/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Hacking 1-Minute Crypto Candlesticks: (2) Custom Charts using Plotly [Quant At Risk]

    A clear and informative time-series visualisation is often a challenge. Especially this is true when it comes to candlestick charts in Python. Searching the Web for a perfect solution may bring you to the Plotly package which stores in its arsenal the corresponding function allowing for easy charting (see some examples here). The candlestick chart is a popular way to present the traded assets
  • The Price of Transaction Costs [Quantpedia]

    Capturing the systematic premia is the main aim of many quantitative traders. However, investors tend to overlook an important factor when backtesting. Trading costs are an essential part of every trade, and yet even when we consider them, we often only use an approximation. The recent article from Angana Jacob (SigTech) looks into how heavily trading costs affect the overall return of various

Quantocracy’s Daily Wrap for 04/21/2022

This is a summary of links featured on Quantocracy on Thursday, 04/21/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Measuring uncertainty in time series data [Quant Dare]

    In financial time series it is very common to make predictions of single points such as expected future prices or returns. But is there any other way of adding more information in our forecasts? In todays post we will be making probabilistic forecasts for time series data using recurrent neural networks with pytorch. Introduction Even though point forecasting gives us information about
  • The Implementation Costs of Indexed ETFs [Alpha Architect]

    A common mistake made by many passive investors is that they view all index funds in the same asset class as commodities(1), often considering only the expense ratio when making their investment choices. However, not all index funds are alike, and not all passively managed funds (what I refer to as systematically structured portfolios) are index funds. Index funds and systematically
  • Can Market Maker Capital Constraints Result in Mispricing of ETFs? [Alpha Architect]

    In this research, the authors explore the role of financial intermediaries in contagion or comovements in pricing efficiency. Specifically, lead market makers (LMMs) like Goldman Sachs, Cantor Fitzgerald, RBC Capital Markets, and others, have funding constraints that may influence their ability to accurately price ETFs and cause contagion in the pricing of financial assets. The market for ETFs
  • Thematic Indices: Looking at the Past or the Future? [Factor Research]

    Thematic indices from MSCI have outperformed their benchmark since 2018 However, they have a rather unattractive factor mix Going against decades of research is not a sound investment strategy INTRODUCTION Although much of the future is uncertain, some technological innovations are rather certain. At some point, we will all have self-driving cars, robots that help us with daily chores, can travel

Quantocracy’s Daily Wrap for 04/18/2022

This is a summary of links featured on Quantocracy on Monday, 04/18/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Government Bonds Have Failed to Deliver When Needed [Allocate Smartly]

    Most government bond funds have suffered major losses this year. What is worse is that those major losses have come when theyre needed most, when stocks and other risk assets are also falling. During times of market stress, gov bonds tend to act as a counterbalance to risk assets, but so far this year theyve failed to deliver when needed. Data dump: It has been 71 trading days since the
  • The Turbulence Index: Measuring Financial Risk [Portfolio Optimizer]

    One of the challenges in portfolio management is the timely detection of financial market stress periods, typically characterized by an increase in volatility and a breakdown in asset correlations1. Chow and al.2 propose to detect such periods through the usage of the caste distance, a measure initially introduced by Mahalanobis34 to classify human skulls in India and now commonly called the
  • How to use FX carry in trading strategies [SR SV]

    FX forward-implied carry is a valid basis for trading strategies because it is related to divergences in monetary and financial conditions. However, nominal carry is a cheap and rough indicator: related PnLs are highly seasonal, sensitive to global equity markets, and prone to large drawdowns. Simple alternative concepts such as real carry, interest rate differentials, and volatility-adjusted
  • Research Review | 15 April 2022 | Risk Factor Premia [Capital Spectator]

    A Look Under the Hood of Momentum Funds Ayelen Banegas and Carlo Rosa (Federal Reserve) February 2022 Momentum investing has surged over the past few years, with assets growing at three times the rate of conventional funds. Using a comprehensive dataset of US equity funds, this paper examines the economic value of momentum funds. Overall, we find that risk-adjusted returns of momentum funds are,

Quantocracy’s Daily Wrap for 04/14/2022

This is a summary of links featured on Quantocracy on Thursday, 04/14/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Trading and investing performance: year eight [Investment Idiocy]

    Eight years! Wow. In late 2013 I walked out of an office for the last time where I had been working for AHL, a large systematic futures trading fund. A few months later, in April 2014, I had my own very small systematic futures trading account, and I started doing these performance reviews. And this is my eighth review. Double wow! As usual these cover the UK tax year, in this case from April 6th
  • Bond Investing in Inflationary Times [Alpha Architect]

    As the chief research officer of Buckingham Strategic Partners, the issue I am being asked to address most often is about fixed income strategies when yields are at historically low levels and inflation risk is heightened due to the unprecedented increase in money creation (through quantitative easing), the extraordinary expansionary fiscal spending around the globe, and the war in Ukraine driving
  • Never Sell in May! [Financial Hacker]

    Sell in May and go away is an old stock traders wisdom. But in his TASC May 2022 article, Markos Katsanos examined that rule in detail and found that it should rather be Sell in August and buy back in October. Can trading be really this easy? Lets have a look at the simple seasonal trading rule and a far more complex application of it. The trading algorithm Sell in August and