Quant Mashup One Look At Monday’s Massive Rotation [Quantifiable Edges]Monday saw a massive market rotation. It could be noted by the performance in the IWM vs the QQQ, or in looking at performance among S&P 500 sectors, where Energy beat Technology by 15% on Monday. But to really see how strong the rotation was, you’d need to take a look at individual stock(...) Do Analysts Exploit Factor Anomalies when recommending stocks? [Alpha Architect]Do analysts actively exploit anomalies when they recommend stocks? Do analysts’ research efforts contribute to efficiency in the equity markets? Good questions. This research clarifies the relationship between established stock return anomalies and analyst recommendations. Given that anomalies are(...) A Temporal Clustering Function, Part 2 [Dekalog Blog]Further to my previous post, below is an extended version of the "blurred_maxshift_1d_linear" function. This updated version has two extra outputs: a vector of the cluster centre index ix values and a vector the same length as the input data with the cluster centres to which each datum has(...) Market Neutral Funds: Powered by Beta? [Factor Research]The long-term track record of equity market neutral hedge funds is attractive, but should be viewed with scepticism due to Madoff and survivorship bias Only one index from HFRX seems sound, but his highlights negative alpha since the GFC and positive returns primarily from market beta A factor(...) SPX Performance After Big Weekly Reversals [Quantifiable Edges]After losing 5.6% this in the week ending 10/30/20, the S&P 500 completely reversed the losses this past week with a 7.3% gain. That is a fairly remarkable turnaround. Below is a look at all other times the S&P 500 lost 5% or more one week, and then made up for the losses and more the next(...) Forecasting energy markets with macro data [SR SV]Recent academic papers illustrate how macroeconomic data support predictions of energy market flows and prices. Valid macro indicators include shipping costs, industrial production measures, non-energy industrial commodity prices, transportation data, weather data, financial conditions indices, and(...) Deflated Sharpe Ratio (how to avoid been fooled by randomness) [Quant Dare]As we test more and more strategies the overall probability of choosing at least one poor strategy grows. So we must be very careful with how many backtests we run. We should always record all of them, to later deflate the Sharpe Ratio accordingly. In this post, we are going to analyze how the(...) Should Treasury Bills Be The Risk-Free Asset in Asset Pricing Models? [Alpha Architect]In virtually all studies on asset pricing and asset pricing models, the one-month Treasury bill is the choice as the risk-free rate. In his study “The Risk-Free Asset Implied by the Market: Medium-Term Bonds instead of Short-Term Bills,” published in the September 2020 issue of The Journal of(...) 3 Takeaways from Quantopian Shutting Down [Quant Rocket]Quantopian announced that it is shutting down its community platform. This doesn’t entirely come as a surprise. Quantopian returned money to investors earlier this year after its investment strategy underperformed. It shut down paper trading in 2019 (having already ended live trading in 2017),(...) Improving the use of correlations in portfolio optimisation when handcrafting [Investment Idiocy]Remember the handcrafting method, which I described in this series of posts? Motivating portfolio construction Methodology Implementing Testing Adjusting portfolio weights for Sharpe Ratios All very nice, all very theoretically grounded, except for one thing: the 'candidate matrices'.(...) The Dead versus The Living Stocks [Factor Research]Zombie stocks are a diverse group, both from a country and sector perspective Zombie stocks were fundamentally riskier, yet outperformed non-zombie stocks over the last year Oddly, investors need to pay up as they are also more expensive INTRODUCTION Walking through financial centers like London or(...) What Assumptions Are You Making About “Time” In Your Trading? [Robot Wealth]I recently listened to a podcast about one of the earliest human civilizations – the ancient Sumerians. Apparently, our system of minutes, hours, and days has been with us since the time of these ancient people, who developed it based on a simple base-12 counting system: There are three joints in(...) How Do You Think the Global Market Portfolio Has Performed from 1960-2017? [Alpha Architect]This paper complements Doeswijk, Lam, and Swinkels’ 2014 paper, which documents the historical composition of the market portfolio. Doeswijk, Lam, and Swinkel stopped their research in building the “market portfolio,” but left the work of the market portfolios historical returns undone. In(...) New Site! Stock Market Valuation and the 2020's in R [Light Finance]I’ve been thinking about valuations a lot lately. If you’ve been following the stock market in recent months, then you will doubtlessly be aware that the past 6-months have witnessed a historic 44% rally across global markets. This rally has drawn particular attention because it has been(...) Podcast with Wes Gray of @AlphaArchitect [System Trader Show]Wes Gray after serving as a Captain in the United States Marine Corps earned an MBA and a PhD in the finance from the University of Chicago where he studied under Nobel Prize Winner Eugene Fama. He worked as a finance professor at Drexel University. He then found Alpha Architect — a(...) Scanning Crypto Exchange for Available Cryptocurrency Close Price-Series [Quant at Risk]One of the most common problem encountered by all novice researches of the crypto-markets and (algo-)traders is knowing a list of all cryptocurrency pairs being actively traded at specific crypto exchange. This knowledge is a gateway to a vast research over correlations of crypto-assets, looking for(...) Fundamental trend following [SR SV]Fundamental trend following uses moving averages of past fundamental data, such as valuation metrics or economic indicators, to predict future fundamentals, analogously to the conventions in price or return trend following. A recent paper shows that fundamental trend following can be applied to(...) Combining Value and Profitability Factors to Improve Performance [Alpha Architect]The 1997 publication of Mark Carhart’s paper “On Persistence in Mutual Fund Performance” led to the four-factor model, which added momentum to market beta, size, and value, becoming the workhorse model in finance—replacing the Fama-French three-factor model. The next major contribution came(...) Momentum Trading Strategies Course [CSS Analytics]This post contains affiliate links. An affiliate link means CSSA may receive compensation if you make a purchase through the link, without any extra cost to you. CSSA strives to promote only products and services which provide value to my business and those which I believe could help you, the(...) Migrating from @Quantopian to QuantConnect [Quant Connect]As some may know, on October 29th, Quantopian users received notification the company would be terminating its free community platform on November 14th, leaving users with two weeks to download their code and find another home. We understand this closure has come suddenly, leaving many quants(...) My Thoughts on Quantopian's Closing [Robot Wealth]I was very sad to learn that Quantopian is shutting down its community services. Quantopian’s efforts to bring quant finance outside of institutions was a genuine game-changer. The educational content was solid, the tech was excellent, and the QuantCon conferences were professional, well-run, and(...) Trading the US Election – Profiting from “Known Unknowns” [Robot Wealth]You’ve probably noticed that there’s a US election on the horizon. This is an event of known uncertainty: a “known unknown” in the now immortal language of Donald Rumsfeld. In trading, we sometimes observe marginal pricing inefficiencies around these “known unknowns”. For example, ahead(...) Slippage and low liquidity stocks [Alvarez Quant Trading]Recently, I have been working on a strategy that trades stocks with low dollar turnover. The initial performance was attractive and I was liking the strategy. But there were two issues that I needed to deal with in the backtesting. How much slippage to add to these stocks. The strategy enters and(...) Dream team: Combining classifiers [Quant Dare]When you are in front of a complex classification problem, often the case with financial markets, different approaches may appear while searching for a solution. These systems can estimate the classification and sometimes none of them is better than the rest. In this case, a reasonable choice is to(...) Best Ways to Use Momentum [Dual Momentum]There are many ways to use momentum. Some are better than others. Let us look at some of the best approaches. Stock Momentum In 2018, Dimensional Fund Advisors (DFA) issued a report on the performance of all public momentum funds from June 2003 through 2017. Only one fund had outperformed the(...) Kernel of error [OSM]In our last post, we looked at a rolling average of pairwise correlations for the constituents of XLI, an ETF that tracks the industrials sector of the S&P 500. We found that spikes in the three-month average coincided with declines in the underlying index. There was some graphical evidence of a(...) Does Portfolio Timing Based on Volatility Signals Outperform Buy and Hold? [Alpha Architect]The popularity of using volatility to inform portfolio strategies has grown as the research tying volatility-managed techniques and improved risk/return portfolio performance has proliferated in the literature. The portfolios examined in the empirical literature generally utilize conservative(...) Build a Financial Data Database with Python [Python For Finance]Hi all, and welcome back to the site – I appreciate it has been an unexpectedly long time since I last posted…in fact my last post was around this time last year. Hopefully I can get back on the “treadmill” and churn out some articles at a somewhat faster rate than 1 a year over the next(...) Building Factor Portfolios Based with the Lowest Correlations [Alpha Architect]The two basic rules of asset allocation are: i) identify assets with positive expected payoffs, and ii) ensure that the assets are not too highly correlated, so that diversification benefits can be harvested. Although the rules are simple, implementation is often complex. Equities have a positive(...) A Comparison of Stock Market Performance Among Countries [Grzegorz Link]The performance of stock market indices varies between different countries. Market-to-market and stock-to-stock correlations tend to get high during downturns[5], but differ considerably during other, more peaceful market environments. MSCI, a financial market data company, offers great quality data(...) ArbitrageLab Release Update [Hudson and Thames]ArbitrageLab is a python library that helps traders who want to exploit mean-reverting portfolios by providing a complete set of algorithms from the best academic journals. How to Get Access Recently there has been a lot of interest in the development of our most recent library which focuses(...) Don't Get Carried Away by Carry [Factor Research]Carry across asset classes has not performed strongly over the most recent decade Currency carry and Value & Size equity factors exhibited the same trends in performance since 1999 All three factors are likely driven by risk sentiment, essentially offering the same risk exposure INTRODUCTION(...) A Temporal Clustering Function [Dekalog Blog]Recently a reader contacted me with a view to collaborating on some work regarding the Delta phenomenon but after a brief exchange of e-mails this seems to have petered out. However, for my part, the work I have done has opened a few new avenues of investigation and this post is about one of them.(...) Discrimination of Correlated Random Walk Time Series using GNPR [Hudson and Thames]Discriminating random variables on time-series on both their distribution and dependence information is motivated by the study of financial assets returns. For example, given two assets where their returns are perfectly correlated, are these returns always similar from a risk perspective? According(...) Prospect theory value as investment factor [SR SV]Prospect theory value is a valid investment factor, particularly in episodes of apparent market inefficiency. Prospect theory is a popular model of irrational decision making. It emphasizes a realistic mental representation of expected gains and losses and an individual’s evaluation of such(...) The Quant Conference Digital | November 4-6 | Global Audience - Online Event - Cutting Edge ResearchThe Quant Conference Digital engages the foremost thought leaders from the industry and academia to dive into the latest innovations in quant finance, foster collaboration and facilitate opportunities. Series of panel discussions and keynotes offer an in-depth exploration of the challenges and(...) The Knapsack problem implementation in R [Quantpedia]Our own research paper ESG Scores and Price Momentum Are More Than Compatible utilized the Knapsack problem to make the ESG strategies more profitable or Momentum strategies significantly less risky. The implementation of the Knapsack problem was created in R, using slightly modified Simulated(...) Equity Trend Following Performance Around the Globe [Alpha Architect]Time-series momentum (TSMOM) historically has demonstrated abnormal excess returns. Also called trend following, it is measured by a portfolio that is long assets that have had recent positive returns and short assets that have had recent negative returns. Trend following has attracted a lot of(...) Research Review | 16 October 2020 | Index Investing [Capital Spectator]Does Joining the S&P 500 Index Hurt Firms? Benjamin Bennett (Tulane University), et al. July 20, 2020 We investigate the impact on firms of joining the S&P 500 index from 1997 to 2017. We find that the positive announcement effect on the stock price of index inclusion has disappeared and the(...) Factor Exposure Analysis 101 [Factor Research]Linear regression is widely used for factor exposure analysis However, a high R2 and low p-value can be misleading Unsurprisingly the data quality matters INTRODUCTION Some fields of science like math or statistics seem to be too dry to be joking about, but a quick Google search for jokes on(...) Clustering S&P500 using Fully Convolutional Autoencoders [Quant Dare]Clustering data into groups that share common characteristics can be very useful, but using experts to perform this grouping is costly and in many cases decisions are influenced by emotions. That is why clustering is one of the main topics of Unsupervised Machine Learning algorithms, that doesn’t(...) News and its Impact on Risk and Returns Around the World [Alpha Architect]News is now data. But how is this data associated with changes in stock market returns and risks, and is there predictive power in the news via the words used? This innovative paper asks and answers nine important questions about the interrelationship of news and stock market outcomes. How should(...) Corr-correlation [OSM]We recently read two blog posts from Robot Wealth and FOSS Trading on calculating rolling pairwise correlations for the constituents of an S&P 500 sector index. Both posts were very interesting and offered informative ways to solve the problem using different packages in R: tidyverse or xts.(...) López de Prado on machine learning in finance [Mathematical Investor]Marcos López de Prado, whom we have featured in previous Math Scholar articles (see Article A, Article B and Article C), has been invited to present a keynote presentation at the ACM Conference on Artificial Intelligence in Finance, to be conducted virtually October 14-16, 2020. López de Prado is(...) Value Investing Factor Research: How to Improve the Piotroski F-Score Measure [Alpha Architect]This project builds on research conducted by J. Piotroski, who published his paper Value Investing: The Use of Historical Financial Statement Information to Separate Winners from Losers in 2000, offering a simple yet powerful framework to separate the winners from the losers in a value-investing(...) "Please Send Me a Trading System!" [Financial Hacker]“It should produce 150 pips per week. With the best indicators that you know. How much does it cost? Please also send live histories of your top systems.” Although we often get such requests, we still don’t know the best indicators and can’t send live histories. We do not invent systems, but(...) Profiling Diversification Attributes With Principal Components [Capital Spectator]The holy grail of portfolio design is combining assets so that returns are relatively stable if not higher, risk is generally lower and the overall mix delivers stronger risk-adjusted performance that’s not otherwise available through owning the components separately. Diversification, as the(...) New Site: Cleaning Tick and Quote Data [Machine Factor Tech]Every business that cares about machine learning needs its Sandor Straus. Cleaning and enriching data to make it more useful is the secret ingredient to every successful AI strategy. Sandor Straus was Renaissanse Technologies data guru responsible for cleaning, storing and enriching the data used in(...) FX Swap pricing and the mystery of Covered Interest Parity [Quant Dare]Sometimes described as a sort of physical law in international finance [1], Covered Interest Parity (CIP) has failed to hold after the Global Financial Crisis (GFC) of 2008. This has given rise to an interesting debate during the last decade that has resulted in relevant insights regarding(...) Should I run my trading system at a fixed expected volatility target? [Investment Idiocy]This is a blog post which has been coming for a while. It relates to a lot of themes I've discussed before, and a recurring conversation I've had with a few people. As most regular readers will know, I run my trading strategy to hit a particular risk target. That risk target is expressed(...)