Quant Mashup Understanding Pointwise Mutual Information [Eran Raviv]The term mutual information is drawn from the field of information theory. Information theory is busy with the quantification of information. For example, a central concept in this field is entropy, which we have discussed before. If you google the term “mutual information” you will land at some(...) Fighting U.S. FOMO [Flirting with Models]U.S. equities have out-performed international equities for 8 of the past 10 years, but this trend has tended to flip-flop historically and persist for multi-year stretches. Home country bias is a real phenomenon that investors have to deal with, especially during these streaks where U.S. equities(...) Liquidity and Factor Performance [Factor Research]Most institutional investors can only trade the largest, most liquid stocks Introducing minimum liquidity requirements impacts factors differently Factor portfolio construction with liquidity constraints is especially challenging in small stock markets INTRODUCTION Index funds have breached $11(...) Portfolio starter kit [OSM]Say you’ve built a little nest egg thanks to some discipline and frugality. And now you realize that you should probably invest that money so that you’ve got something to live off of in retirement. Or perhaps you simply want to earn a better return than stashing your cash underneath your bed, I(...) How to Turn Cross-Sectional into Time-Series Momentum [Alpha Architect]A point of confusion for many new quant momentum investors is the difference between Time- Series Momentum and Cross-Sectional Momentum: Time-series (TS) looks at each individual stock’s momentum and owns assets with positive momentum while shorting those with negative momentum; Cross-sectional(...) The q-factor model for equity returns [SR SV]Investment-based capital asset pricing looks at equity returns from the angle of issuers, rather than investors. It is based on the cost of capital and the net present value rule of corporate finance. The q-factor model is an implementation of investment capital asset pricing that explains many(...) The Hidden Risk FIRE Investors Miss [Movement Capital]The financial independence, retire early (FIRE) movement has gained a lot of traction. “We retired at 30” headlines get clicks and have made people question the typical retirement timetable: A main goal for those pursuing FIRE is to reach a portfolio balance that can reasonably fund their(...) Visualization Sector Trends with R Code [Alpha Architect]Welcome to a year-end installment of Reproducible Finance with R, a series posts that will be a little bit different from the norm on Alpha Architect (see here for my last post). We will search for and hopefully unearth some interesting market conditions, but we’ll primarily focus on the code that(...) Pre-Election Drift in the Stock Market [Quantpedia]There are many calendar / seasonal anomalies by which we can enhance our overall investment strategy. One of the least frequent but still very interesting anomalies is for sure the Pre-Election Drift in the stock market in the United States. This year is the election year, and public discussion is(...) Correlations Profile | Major Asset Classes | 23 January 2020 [Capital Spectator]Return correlations for the major asset classes have edged down in recent years, which implies that diversification opportunities have increased, if only marginally. The correlation readings are only modestly softer overall and for several asset class pairings it’s fair to say that nothing much(...) Persistency Beyond Almost All Other Rallies [Quantifiable Edges]Last week I noted the current rally was reaching historical extremes for persistency. Here I will look at another study from the subscriber letter, and then update last week’s study. In last night’s letter I looked at all times back to the inception of the NASDAQ in 1971 in which both SPX and(...) Calculating a VIX3M Style Index Back to 1990 Reveals Surprising Trends [Six Figure Investing]The Cboe’s VIX® (30-day) and VIX3M (93-day) indexes enable us to quantify volatility term structures but until now, historical analyses between VIX style indexes have been limited to dates after December 2001. This post introduces the results of VIX3M style calculations back to 1990, and reviews(...) Skew who? [OSM]In our last post on the SKEW index we looked at how good the index was in pricing two standard deviation (2SD) down moves. The answer: not very. But, we conjectured that this poor performance may be due to the fact that it is more accurate at pricing larger moves, which occur with greater frequency(...) Quant Summit Europe, March 11-12, 2020 in LondonMachine learning, quantum computing and beyond: cutting-edge quant solutions to finance problems Quant Summit Europe gives you the opportunity to meet with, learn and exchange ideas with over 130 renowned industry quants and data scientists from the world’s leading banks, buy-side institutions and(...) Enterprise Multiples and Expected Stock Returns [Alpha Architect]One of the foundation concepts of the Alpha Architect investment philosophy is the utilization of Enterprise Multiples in the value discovery process. Enterprise multiples are often referred to as the “business buyer metric” and are a key valuation tool used by investment bankers and business(...) Should I Stay or Should I Growth Now? [Flirting with Models]Naïve value factor portfolios have been in a drawdown since 2007. More thoughtful implementations performed well after 2008, with many continuing to generate excess returns versus the market through 2016. Since 2017, however, most value portfolios have experienced a steep drawdown in their relative(...) The Scholz Brake: Fixing Germany’s New 1000% Trader Tax [Financial Hacker]Would you like to read a 18-page pounderous law draft titled “Law for introducing a duty to report cross-border tax structuring”? The members of the German Bundestag apparently didn’t. Nothing can be said against reporting cum-ex or similar constructs, so the new law, proposed by finance(...) Diversification [Falkenblog]I was interested in calculating what the portfolio volatility would be for a portfolio given various correlation assumptions, and also the number of assets. So I took two portfolio of the S&P500 in two very different years: 2008 and 2017. The VIX had one of its highest average levels in 2008, at(...) Private Equity: Fooling Some People All the Time? [Factor Research]Private equity return data should be viewed with caution Returns are likely overstated while volatility is understated Private equity returns are highly correlated to public equities TWO MAGIC WORDS “This time is different” might be the four most dangerous words in investing. “Uncorrelated(...) Breaking Down 50 Years of Industry Data [Fortune Financial]It has long been a belief of mine that the industry in which a company operates has a huge impact on its performance, and that most industries simply are not worthwhile for long-term investment consideration. To further this discussion, I took the detailed industry data found in Professor Ken(...) Research Review | 17 January 2020 | Volatility [Capital Spectator]Macro News and Long-Run Volatility Expectations Anders Vilhelmsson (Lund University) December 10, 2019 I propose a new model-free method for estimating long-run changes in expected volatility using VIX futures contracts. The method is applied to measure the effect on stock market volatility of(...) Timing Low Volatility with Factor Valuations [Alpha Architect]Funds flows are frequently analyzed by investors to gauge the demand for investment strategies, but it represents a challenging exercise. Key issues are data availability as few market participants disclose their holdings as well as reporting frequency as limited data is published in real-time. The(...) Predicting Bank Nifty Open Price Using Deep Learning [Quant Insti]With the advent of several machine / deep learning models, there have been several theories emerging in applying these techniques for stock market prediction because of the difficulty and complexity it involves. In this project, we’re trying to solve the problem using a classifier to predict(...) Petra on Programming: A New Zero-Lag Indicator [Financial Hacker]I have been recently hired to code a series of indicators based on monthly articles in the Stocks & Commodities magazine, and to write here about the details of indicator programming. Looking through the magazine, I found many articles useful, some a bit weird, some a bit on the esoteric side.(...) Autoencoder based outlier detection in Forex [Quant Dare]In FOREX, both the EURCHF and USDCHF series have outliers that can be a problem when applying Machine Learning techniques to them. So, in this post, the performance of an autoencoder detecting these anomalies is going to be studied. Analyzing the EURCHF and USDCHF returns, it can be seen that there(...) Top 5 Most Interesting Papers from the Annual Finance Geek Fest [Alpha Architect]The American Finance Association Annual Meetings have now come and gone (here is information on the broader conference). The conference was in sunny San Diego this year and I’m told it did not disappoint! 1 This 3-day conference collects the brightest minds in academia to discuss hundreds of new(...) Skew and Kurtosis as trading rules [Investment Idiocy]This is part X of my series of blog posts on skew and kurtosis, where 2 A post on skew: measuring, and it's impact on future returns A post on kurtosis: measuring, it's impact on future returns, and it's interaction with skew. A post on trend following and skew (which I actually wrote(...) The Hierarchical Risk Parity Algorithm: An Introduction [Hudson and Thames]Portfolio Optimisation has always been a hot topic of research in financial modelling and rightly so – a lot of people and companies want to create and manage an optimal portfolio which gives them good returns. There is an abundance of mathematical literature dealing with this topic such as the(...) Bitcoin plus Harry Brown’s Permanent Portfolio – A mix in heaven? [Sanz Prophet]What would happen if you took $5,000 out of your $100,000 permanent portfolio and allocated it to Bitcoin? From 3.6% annual to 15% annual returns? Got to love the Permanent Portfolio I have been somewhat obsessed with the simplicity and fundamental thinking behind the permanent portfolio. I have(...) How ESG Affects Valuation, Risk, and Performance [Alpha Architect]We have done a fair amount on the investment merits of ESG investing, but the question of how ESG affects the fundamental performance of a firm (in a causal fashion) is addressed in this study. For example, this paper askes questions such as, “Are high ESG scoring firms more adept at managing(...) Beware Strategies That Fall Down on Good Data [Allocate Smartly]Sources of long-term historical data are few and far between. Because it’s been generously provided for free, one of the most often used is data from Professor French (of Fama-French fame). Others include Shiller and Ibbotson. These data sets are fine for a first pass at testing out ideas, but(...) How Expensive Are ESG Stocks? [Factor Research]Highly ranked ESG stocks trade at higher valuation multiples than the stock market However, the difference in multiples is minor and far less than extreme than for Growth stocks ESG ETFs generated lower returns than the stock market, but were also less volatile INTRODUCTION Europeans seem far more(...) Market Structure Part 1: Order Volume Density [Reproducible Finance]Welcome to another installment of Reproducible Finance! Inspired by a great visualization in Hands on Time Series with R by Rami Krispin, today we’ll investigate some market structure data and get to know the Midas data source provided by the SEC. Let’s start by importing data from the SEC(...) Principal Component Analysis in Trading [Quant Insti]As trading becomes automated, we have seen that traders seek to use as much data as they can for their analyses. But we all know that adding more variables leads to more complications and that in turn might make it harder to come to solid conclusions. Think about it, we have more than 3000 companies(...) The Idiosyncratic Volatility Puzzle: Then and Now [Alpha Architect]One of the interesting puzzles in finance is that stocks with greater idiosyncratic volatility (IVOL) have produced lower returns (see an earlier post here). This is an anomaly because idiosyncratic volatility is viewed as a risk factor—greater volatility should be rewarded with higher, not lower,(...) The predictive superiority of ensemble methods for CDS spreads [SR SV]Through R or Python we can nowadays apply a wide range of methods for predicting financial market variables. Key concepts include penalized regression, such as Ridge and LASSO, support vector regression, neural networks, standard regression trees, bagging, random forest, and gradient boosting. The(...) Inverse Volatility Position Sizing [Alvarez Quant Trading]Recently I’ve had several of my consulting clients come with a strategy that uses Inverse Volatility Position Sizing. The basic idea is that the more volatile positions have smaller size while the less volatile ones get a larger size. I have always been a fan of equal position sizing for several(...) Testing a Yield-Based Asset Class Rotation Strategy [Allocate Smartly]By reader request, this is a test of a tactical strategy from Harrison Schwartz that considers various economic yields in order to rotate among asset classes. Strategy results versus the 60/40 benchmark follow. We’ve extended Schwartz’s original test by an additional 6+ years, and accounted for(...) Forecasting US Equity Market Returns with Machine Learning [Alpha Architect]Shiller’s CAPE ratio is a popular and useful metric for measuring whether stock prices are overvalued or undervalued relative to earnings. Recently, Vanguard analysts Haifeng Wang, Harshdeep Singh Ahluwalia, Roger A. Aliaga-Díaz, and Joseph H. Davis have written a very interesting paper on(...) Stop Loss: Explained & The Best Strategy [Analyzing Alpha]A stop-loss order protects profit or limits risk on an investor’s open position by exiting at a predetermined price. Placing an order to sell a long stock position if the price drops 5% below the purchase price is an example of a stop-loss order. In this post, we’re going to dig into what a stop(...) A Python Investigation of a New Proposed Short Vol ETF - SVIX [QuantStrat TradeR]This post will be about analyzing SVIX–a proposed new short vol ETF that aims to offer the same short vol exposure as XIV used to–without the downside of, well, blowing up in 20 minutes due to positive feedback loops. As I’m currently enrolled in a Python bootcamp, this was one of my capstone(...) Quant Tools for Private Equity and Real Assets [Alpha Architect]Variance and covariance are widely accepted risk measures for liquid assets that trade in public markets. Illiquid assets are not part of this framework because of their lack of regular price quotes and thus time variance. Due to the difficulty in using standard risk measures to assess non-traded(...) Factor Scoring Smart Beta ETFs [Factor Research]The difference between the cheapest and most expensive smart beta ETF in the US is 59 bps on average Some smart beta ETFs offer negative factor exposure, which requires explanation Factor scores can be used to identify which smart beta ETFs offer the best ratio of factor exposure per dollar in fees(...) Pursuing Factor Purity [Flirting with Models]Factors play an important role for quantitative portfolio construction. How a factor is defined and how a factor portfolio is constructed play important roles in the results achieved. Naively constructed portfolios – such as most “academic” factors – can lead to latent style exposures and(...) Most popular posts – 2019 [Eran Raviv]As every year, I checked my analytics so that I can let you know what was popular. This year I have also experimented with a survey where I asked one question at the end of each relevant post. About 120 replies recieved, but the free Survey Monkey account (the survey provider I went with) only lets(...) Is Active Investing Doomed as a Negative Sum Game? A Critical Review [Alpha Architect]In an influential piece, Sharpe (1991) 1 put forward the proposition that active investing must be a losing pursuit in aggregate, as it amounts to a zero-sum game in gross terms and hence must be a negative-sum game after costs. I take a critical look at the underlying concepts and assumptions(...) Factor Olympics 2019 [Factor Research]As in 2018, Low Volatility produced the best and Value the worst performance Value did not recover significantly further after a short rally in Q3 2019 However, Momentum broke its upward trajectory since then INTRODUCTION We present the performance of five well-known factors on an annual basis for(...) 2019 Research Compendium [Flirting with Models]In 2019, we published 45 research notes (not including video + audio commentary), totaling over 100,000 words. Our research spanned a number of topics, including: ensemble techniques, deep dives on trend following, factor and sector rotation, fixed income analysis, and – of course – rebalance(...) Our Most Popular Posts of 2019 [Two Centuries Investments]We are closing 2019 with much gratitude to our clients, collaborators and online visitors. We have launched this blog less than a year ago and have had the pleasure of seeing many visitors from all over the world ranging from buy-side investors, financial advisors, asset owners, thought leaders,(...) Top Ten Blog Posts on Quantpedia in 2019 [Quantpedia]The end of the year is a good time for a short recapitulation. Apart from other things we do (which we will summarize in our next blog in a few days), we have published around 50 short blog posts / recherches of academic papers on this blog during the last year. We want to use this opportunity to(...)