Quant Mashup 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(...) A Review of Modern Asset Allocation For Wealth Management, by David M. Berns, PhD [QuantStrat TradeR]This post will be a review of the book Modern Asset Allocation for Wealth Management, by Dr. David Berns, PhD. The long story short is that I think the book is a must-read for a new and different perspective on asset management, albeit one not without some fairly minor flaws that could be very(...) Factor Olympics Q3 2020 [Factor Research]Momentum & Quality are leading the performance scoreboard in Q1-3 2020 Value & Size generated negative returns, like in recent years, and Low Volatility ended a 10-year fantastic run 2020 is shaping up as a year of highly dispersed factor returns INTRODUCTION We present the performance of(...) Institutional Investment Strategies: Keep it Simple [Alpha Architect]Historically Institutional investors have been considered the “smart money” in investment circles. What academic research has tended to show is that the smart money status of institutional investing has some chinks in its armor, as can be seen in a previous paper we summarized here. In this(...) Exploring the PMFG Portfolios for Covid-19 Robustness [Hudson and Thames]Pozzi, Di Matteo, and Aste (2013) conclude that it is “better to invest in the peripheries” of the Planar Maximally Filtered Graph (PMFG), as investing in the peripheries lead to better returns, and reduced risk. This blog post explores the impacts of Covid-19 by simulating two investment(...) The Next 5 Weeks All Are Among The Weakest – And Strongest – Of The Year [Quantifiable Edges]October is a month that is known for volatility. And that is a well-earned reputation. Crashes in 1929, 1987, and 2008 all occurred in October. But volatility cuts both ways. If you break the year down into 1-week periods, October also contains some of the strongest seasonal edges of the year, both(...) Lottery Preferences and Their Relationship with Factor Investing [Alpha Architect]Among the assumptions in the first formal asset pricing model, the CAPM, is that investors are risk-averse, they maximize the expected utility of absolute wealth, and they care only about the mean and variance of return. However, research has found that these assumptions don’t hold. In the real(...) Using strength to exit a mean reversion trade [Alvarez Quant Trading]I had a long-time reader, Cristian Franchi, send me a mean-reversion strategy that he wanted me to test and write about. What caught my attention was the rules differing from what I typically see and use. Different ways of measuring strength of a sell-off and volatility expansion. Along with a(...) Safe Withdrawal Rates for Tactical Asset Allocation vs Buy & Hold [Allocate Smartly]In this post we model retirement Safe Withdrawal Rates (SWR) and Perpetual Withdrawal Rates (PWR) for a large collection of tactical and buy & hold strategies. We track 50+ tactical strategies, allowing us to draw some broad conclusions about TAA as a trading style. Learn more about what we do.(...) Does Financial Leverage Make Stocks Riskier? [Factor Research]The leverage of US stocks has been increasing over the last four decades The most leveraged stocks did not generate higher returns than the least leverages ones However, they were also not riskier INTRODUCTION The IMF issued a warning on corporate debt in their latest Global Stability Report and(...) September update, paper trading with IB [Regressionist]Quitting my job I’ve been working half-time for the past few months, trying to wrap up a major project and pass the baton to someone else. Now I feel like I’ve reached those goals, so I talked to my boss about fully quitting. I worried about quitting, because I thought I might lose whatever(...) Writing conundrums [OSM]We’re taking a break from our portfolio series and million sample simulations to return to a subject that we haven’t discussed of late despite its featured spot in this blog’s name—options. In this post, we’ll look at the buy-write (BXM) and put-write (PUT) indices on the S&P 500, as(...) API Algo Trading Landscape [Alpaca]In 2018, we wrote a blog post about the nine great tools for algo trading. At the time, the quant ecosystem had started to gain popularity among individual investors thanks to companies like Quantopian and Quantconnect making it easy to test and trade with algorithms. 9 Great Tools for Algorithmic(...) Petra on Programming: The Gann Hi-Lo Activator [Financial Hacker]Fortunately I could write this article without putting my witch hat on. Despite its name, the ‘Gann Hi-Lo Activator’ was not invented by the famous esotericist, but by a Robert Krausz in a 1998 article in the Stocks&Commodities magazine. In a recent article, Barbara Star combined it with(...) How To Design Machine Learning Models - A Market Timing Example [Alpha Architect]We at ENJINE are big believers in the potential of machine learning (or as some call, “artificial intelligence”) to transform asset management. However, it’s fair to say that machine learning hasn’t received mass adoption in the industry – yet. There are some great primers to get you going(...) An Introduction to Time Series Signatures [Quant Dare]The Signature of a time series is a universal description for a stream of data derived from the theory of controlled differential equations. Over the last years, this technique has been used successfully applied in a wide array of Machine Learning tasks dealing with sequential data, such as the(...) Optimal Stopping in Pairs Trading: Ornstein-Uhlenbeck Model [Hudson and Thames]Nothing makes a situation better like good timing. Whether it’s getting a promotion, catching the last train after a night out, meeting the love of your life, or joining a quant community – it is many of small consequential gambles of stopping decisions that get us to that triumphant “Yes!”(...) Market Valuations: Do they Still Matter? [NAVA Capital]“Price is what you pay; value is what you get.” B. Graham “In the short run, the market is a voting machine, but in the long run it is a weighing machine.” B. Graham “Value investing is at its core the marriage of a contrarian streak and a calculator.” S. Klarman "Never confuse(...) Video: Effective Market Regime Techniques w/ @AlvarezQuant [Better System Trader]Cesar Alvarez from AlvarezQuantTrading.com discusses effective Market Regime techniques to improve strategy performance and reduce risk by only trading in the best market conditions. Mean rolling correlation of XLF constituents [Foss Trading]I follow Quantocracy on Twitter, and I found Rolling mean correlation in the tidyverse by Robot Wealth. They say to let them know if you’d approach it differently. I would, so I thought it would be interesting to replicate the analysis using tools I’m familiar with: xts and TTR. The xts package(...) Intangible Capital and the Value Factor: Has Your Value Definition Just Expired? [Alpha Architect]Many in the academic and practitioner research world are arguing that the reported B/P ratio is approaching it’s “expiration date” because of the importance of intangibles, R&D, brand value, and so on. While the determination of true “intrinsic value” remains in the domain of active(...) Aging & Equities: Selling Stocks for the Long-Term [Factor Research]There is a negative relationship between aging populations and stock valuations Given that most developed markets are aging, this creates structural headwinds for equities The massive future population declines require investors to rethink traditional asset allocation INTRODUCTION “The curious(...) Algorithmic Trading Using Logistic Regression (h/t @PyQuantNews) [Hands Off Investing]With the increasing popularity of machine learning, many traders are looking for ways in which they can “teach” a computer to trade for them. This process is called algorithmic trading (sometimes called algo-trading). Algorithmic trading is a hands off strategy for buying and selling stocks that(...) Is the Weakest Week Still Weak When There is Weakness Prior to the Weakest Week? [Quantifiable Edges]As I have shown many times in the past, there isn’t a more reliable time of the year to have a selloff than this upcoming week. I have often referred to is as “The Weakest Week”. Since 1960 the week following the 3rd Friday in September has produced the most bearish results of any week. Below(...) R tidyverse for macro trading research [SR SV]The tidyverse is a collection of packages that facilitate data science with R. It is particularly powerful for macro trading research because [a] it supports efficient and standardized work with R’s vast universe of econometric models, [b] is well adapted for analyzing data vintages (i.e. data(...) Sequential satisficing [OSM]In our last post, we ran simulations on our 1,000 randomly generated return scenarios to compare the average and risk-adjusted return for satisfactory, naive, and mean-variance optimized (MVO) maximum return and maximum Sharpe ratio portfolios.1 We found that you can shoot for high returns or high(...) “Effective Market Regimes Techniques” with @AlvarezQuant – LIVE this weekend [Better System Trader]This weekend is the very first episode of the new BST Live show. On the show this week we’re going to discuss how to improve your trading performance and reduce risk by trading only when the market conditions are best for your strategies. I’ve got Cesar Alvarez from Alvarez Quant Trading joining(...) Aspect Partners' Risk Managed Momentum [Allocate Smartly]This is an independent test of Aspect Partners’ flagship tactical asset allocation strategy Risk Managed Momentum (RMM). By tactical standards, RMM is a very active, very aggressive strategy. It has done an excellent job navigating this difficult year so far. Backtested results from 1970 follow.(...) Accruals and Momentum and Their Implications for Factor Investors [Alpha Architect]The price momentum and accruals (the difference between accounting earnings and cash flows—adjustments made for revenue that has been earned but not received, and costs that have been incurred but not paid) anomalies are two well-documented financial phenomena. Recent research has focused on(...) Positional Option Trading by Euan Sinclair: A Review [Robot Wealth]Trading books set a low bar for the reviewer. 99% are full of facile feel-good advice (don’t fight the trend, always use a protective stop). The 1% that are useful tend to either be dry technical treatments (quants who don’t trade), or sporadically helpful insights from traders who make money(...) Announcement: What's next for BST [Better System Trader]There’s been alot of speculation about what’s next for BST. This video explains all the details you need to know, including what’s happening to BST this Sunday… QuantStart News - August 2020 [Quant Start]A couple of months ago we started a new set of posts designed to keep the QuantStart community aware of what the QuantStart team had been up to in previous month. In last month's post we discussed what we had been working on in July 2020. Articles and Tutorials In August we once again reviewed(...) Can the Best Stock Pickers Still Beat the Market? An Out of Sample Test [Alpha Architect]We all intuitively know we are better than average drivers, and if we’re investors, well we know we’re better than average there too. Frankly, we all put ourselves easily in the top 10%, at least. Those that are in the know will quote Buffet’s, “The Superivestors of Graham-and-Doddsville,”(...) Networks with MlFinLab: Minimum Spanning Tree (MST) [Hudson and Thames]Network analysis can provide interesting insights into the dynamics of the market, and the continually changing behaviour. A Minimum Spanning Tree (MST) is a useful method of analyzing complex networks, for aspects such as risk management, portfolio design, and trading strategies. For example,(...) Momentum Turning Points [Allocate Smartly]This is a test of two recent papers: Momentum Turning Points and Breaking Bad Trends. Learn more about what we do and follow 50+ asset allocation strategies like these in near real-time. Successful trend-following strategies must balance the “speed” of the trading signal. If the signal is too(...) Liquidity Cascades: The Coordinated Risk of Uncoordinated Market Participants [Flirting with Models]This paper is unlike any research we’ve shared in the past. Within we dive into the circumstantial evidence surrounding the “weird” behavior many investors believe markets are exhibiting. We tackle narratives such as the impact of central bank intervention, the growing scale of passive /(...) The Positive Similarity of Company Filings and the Cross-Section of Stock Returns [Quantpedia]The usage of alternative data is now a main-stream topic in investment management and algorithmic trading. So let’s together explore the textual analysis of 10-K & 10-Q filings and analyze how these datasets could be used as a profitable part of investment portfolios. We invite you to read(...) Can We Use the Shiller CAPE Ratio to Forecast Country Returns? [Alpha Architect]We all became relatively aware of the CAPE ratio when Shiller predicted the 2000 internet bubble in his book “Irrational Exuberance,” then after he added a touch of robustness when he called the 2007 housing crisis 1 we all became intimately aware of it. Since that time CAPE has been utilized to(...) Kelly criterion: Part 2 [Quant Dare]When investing, we spend plenty of time thinking about which securities should we buy but we rarely wonder how much money should we allocate in each asset. Although it does not seem like an important aspect, it is crucial when defining a strategy, up to the point that it can determine the hole(...) Predicting Bond Returns? Focus on GDP Growth and Inflation Indicators [Alpha Architect]Can the excess returns of government bonds be predicted? This is a classic research question in finance academic research circles. Sometimes practitioners, who are often buried in the more exciting parts of the financial markets, tend to forget that government bonds (do they even belong in your(...) CorrGAN: Realistic Financial Correlation Matrices [Hudson and Thames]There are 6 properties that empirical correlation matrices exhibit that no synthetic generation method has been able to replicate, until now. Enabling researchers to backtest strategies on an abundance of data would make our algorithms and strategies more robust, accurate, and efficient. Since(...) Volatility Hedge Funds: The Good, the Bad, and the Ugly [Factor Research]Volatility hedge funds provided attractive diversification benefits for equity portfolios However, long were preferable over short volatility strategies Some scepticism is required for the hedge fund index performance INTRODUCTION In finance 101, there is usually little doubt on what constitutes the(...) New Quant Blog: A Primer on State Space Models [Patrick Aschermayr]In my first series of posts, I will give a primer on state space models (SSM) that will lay a foundation in understanding upcoming posts about their variants, usefulness, methods to apply inference and forecasting possibilities. When talking about a state space model (SSM), people usually refer to a(...)