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

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

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 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 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

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.

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

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

“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

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

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

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

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

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

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

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

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

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

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

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

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.

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

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

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

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

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

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

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

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!”

“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

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.

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

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

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

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

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

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

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

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

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.

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

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

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…

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

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,”

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,

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

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 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

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