This weeks research was consumed by the concept of Meta-Labeling, how it works, and does it work out-of-sample? We have published a research report as well as an accompanying slide show. There was quite a bit of discussion this on the topic, the following is a link to a Github issue where a few

As the chief research officer for Buckingham Strategic Wealth and The BAM Alliance, I’m often asked, after any asset class or factor experiences a period of poor performance, if the historical outperformance of stocks with that characteristic has disappeared because the premium has become well

Some time ago ( here, here and here ) I posted about the Kalman filter and recently I have been looking at Kalman filters again because of this Trend Without Hiccups paper hosted at SSRN. I also came across this Estimation Lecture paper which provides MATLAB code for the testing of Kalman filters

Five recent asset allocation articles (tactical or otherwise) that you might have missed: 1. ETF Bond Rotation (Alvarez Quant Trading) Cesar looks at different flavors of a simple momentum-based bond rotation strategy. Using momentum to time bond asset classes has not worked nearly as well as it has

The scarcity of historical financial data has been a huge hindrance for the development of algorithmic trading models ever since the first models were devised. In the ever-changing economic reality we live in, countless models are tried and evaluated. Most of these models seek to extract information

Do intraday strategies have a place in the portfolios of long-term investors and fund managers? This post explores an intraday strategy that works best in high volatility regimes and thus makes an attractive candidate for hedging long-term portfolio risk. Trading hypothesis: first half hour predicts

Well...That took a lot longer than I expected it too. 6 weeks later and I finally have the last installation in these series of posts. It's also the longest one so you could say it was worth the wait. I recently found out that Python 2.7 (the python I've used for EVERY project) will soon

Part 1 – Theoretical Background The Dynamic Mode Decomposition (DMD) was originally developed for its application in fluid dynamics where it could decompose complex flows into simpler low-rank spatio-temporal features. The power of this method lies in the fact that it does not depend on any

Monte Carlo Simulation uses the historic returns of your trading strategy to generate scenarios for future strategy returns. It provides a visual approach to volatility and can overcome limitations of other statistical methods. Monte Carlo Simulation Monte Carlo is the synonymous for a random

Cash balance plans are retirement plans that allow participants to save higher amounts than in traditional 401(k)s and IRAs and are quickly becoming more prevalent as an attractive alternative to defined benefit retirement plans. The unique goals of these plans (specified contributions and growth

Most smart beta strategies outperformed the market since 1990, but few have in recent years Diversifying across strategies mitigates the risk of underperformance Various asset allocation models for creating multi-factor portfolios highlight similar results INTRODUCTION The appearance of smart beta

Can quantitative and fundamental approaches be successfully combined? In my estimate, this has been a top 5 industry question for a long time, including this conference at which I’ll be speaking at tomorrow The short answer is: Yes More-so, I believe quantitative approaches cannot work without

Estimating portfolio risk in extreme situations means answering two questions: First, has the market entered an extreme state? Second, how are returns likely to be distributed in such an extreme state? There are three different types of models to address these questions statistically. Conventional

I just finished reading an interesting paper by Justin Birru titled: “Day of the week and the cross-section of returns” (reference below). The story is much too simple to be true, but it looks to be so. In fact, I would probably altogether skip it without the highly ranked Journal of Financial

A Twitter follower ( @SonnyRico ) asked me about weeks following Quad-witching, which occurs in March, June, September, and December. As I have shown in the past, the 2nd half of December has shown bullish tendencies historically (ignore 2018), but those other 3 have NOT been good weeks for the

Factor Timing Revisited: Alternative Risk Premia Allocation Based on Nowcasting and Valuation Signals Olivier Blin (Unigestion), et al. 10 September 2018 Alternative risk premia are encountering growing interest from investors. The vast majority of the academic literature has been focusing on

There is a substantial debate on the topic of factor investing and whether or not the “backtested” excess returns are actually achievable in practice. Much of the research on the topic suggests that practitioners in the field are unable to capture any of the so-called “factor premiums”. For

First of all we want to thank everyone who has reached out to us with ideas and contributions to our package. Without all of your help, none of this would be possible. We have done a lot of work this week and hope that this update provides you with more insight into both the package for Advances in

A common question I get from readers is “does mean reversion still work?” The last time I wrote about this topic was in 2015, a long time ago, in the post “The Health of Stock Mean Reversion: Dead, Dying or Doing Just Fine” I did not realize it had been so long. Time to look at it again. The

In Nassim Taleb’ book Antifragile he emphasizes that ‘if you see a fraud and do not say fraud, you are a fraud,’ I am thus compelled to note that Antifragile is a fraud because its theme is based on intentional misdirection. The most conspicuous and popular examples he presents are also

R is a programming language that owes it’s lineage to S, a language designed in it’s own developers words, “to turn ideas into software, quickly and faithfully.”(1) Shiny is an “interactive web technology” that makes it easy to take R models and publish them to the web. Jonathan L.

The application of Machine Learning for ranking is widely spread. This application of Machine Learning is a little different from the classical ones of classification and regression. In the case of ranking, the interest is not in the accuracy of an estimated value (regression) or the guess about the

A fairly late and flat report for our State of Trend Following Index. Not the greatest start of the year. Please check below for more details. Detailed Results The figures for the month are: February return: 0.71% YTD return: -6.26% Below is the chart displaying individual system results throughout

In this blog, we’ll discuss what are Random Forests, how do they work, how they help in overcoming the limitations of decision trees. With the boom of Machine Learning and its techniques in the current environment, more and more of its algorithms find applications in various domains. The functions

GARP aims to combine Growth and Value investing GARP stocks have outperformed the market since 1989 It is somewhat perplexing how well the strategy worked VALUE VERSUS GROWTH With their thousands of employees, suites of products, international reach, and legendary histories, General Electric (GE)

What are the research questions? What is the relationship between turnover and returns from a low volatility portfolio that integrates value and momentum exposures with low volatility? Does the relationship change if a only one factor is integrated with a low volatility strategy? Note: This is a

Successful investing requires that investors navigate around a large number of risks throughout their lifecycle. We believe that the two most daunting risks investors face are the risk of failing fast and the risk of failing slow. Slow failure occurs when an investor does not grow their investment

Alternative Title: The Gap Everywhere There exist many flavors of market timing. Some are obvious: In 1929, an influential businessman states that US Equities will return 24% per year for the next 20 years; or in 1999, a stock market forecaster predicts Dow Jones to double On dollar-weighted basis,

Data is at the core of quantitative research. The problem is history only has one path. Thus we are limited in our studies by the single historical path that a particular asset has taken. In order to gather more data, more asset data is collected and at higher and higher resolutions, however the

Next week is monthly options expiration week. I’ve noted several times over the years that Op-ex week in general is pretty bullish. March, April, October, and December it has been especially so. S&P 500 options began trading in mid-1983. The table below is one I have showed in March each of

There are different investment approaches to identify sector winners and losers, such as price momentum strategies, top down approach based on specific macroeconomic indicators or bottom-up approaches to identify sectors with improving fundamentals. One widely used approach is business cycle

Does forced buying and selling of underlying shares by leveraged ETF sponsors cause predictable intraday price moves? This post explores an intraday momentum strategy based on the premise that it does. Daily rebalancing of leveraged ETFs Source: Ernie Chan, Algorithmic Trading: Winning Strategies

In the spring of 2017, Yahoo pulled a fast one on the crowd by suddenly changing the technical coding rules for accessing its financial data, leaving countless R users high and dry, including yours truly. Numerous R files that had been meticulously written, revised and maintained over months and

According to psychology literature, mood increases from Thursday to Friday and decreases on Monday. In general, people tend to evaluate future prospects more optimistically when they are in a good mood than when they are in a bad mood. In equity markets, the presence of optimism or pessimism that is

Commodity Futures contracts were established in 1865, but commercially available data starts in 1959, leaving an 80+ year period of unstudied history. In our latest academic paper “Two Centuries of Commodity Futures Premia” Chris Geczy and I use hand-collected futures data to extend the

It can be difficult to disentangle the difference between luck and skill by examining performance on its own. We simulate the returns of investors with different prediction accuracy levels and find that an investor with the skill of a fair coin (i.e. 50%) would likely under-perform a simple

This is a summary of the recent performance of a wide range of excellent Tactical Asset Allocation (TAA) strategies, net of transaction costs. These strategies are sourced from books, academic papers, and other publications. While we don’t (yet) include every published TAA model, these strategies

Long-only factor portfolios can be used for benchmarking smart beta ETFs Results highlight minor tracking errors Likely explained by relatively homogenous factor definitions by ETF issuers INTRODUCTION Investment professionals are not known for their creativity, but that is perhaps only because

Dear Hedge Fund Enthusiasts, It’s been long since we sent out a newsletter but we would like to report that the Open Source Hedge Fund Project is alive and kicking again! My Msc in Financial Engineering has provided me with the unique opportunity to build an open source python package, like

Salience theory suggests that decision makers exaggerate the probability of extreme events if they are aware of their possibility. This gives rise to subjective probability distributions and undermines conventional rationality. In particular, salience theory explains skewness preference, i.e. the

In this post I discuss a well known stylised fact of the investment industry: "Trend following is a positively skewed strategy". Spoiler alert: yes it is (sort of), but it's much more complicated (and interesting!) than you might think. A quick primer on positive skew So what actually

This post will display some robustness results for KDA asset allocation. Ultimately, the two canary instruments fare much better using the original filter weights in Defensive Asset Allocation than in other variants of the weights for the filter. While this isn’t as worrying (the filter most

My last article used Warren Buffett’s pre-crisis sale of put options to highlight the risk of getting over our financial skis. In both temperament and negotiation, Warren can outlast most bear markets. Many of us cannot. Proponents of rebalancing should acknowledge the real risk that downturns can

This is a test of Ilya Kipnis’ “Defensive Adaptive Asset Allocation” (KDA). KDA is a “Meta” model of sorts, combining successful elements of multiple other tactical asset allocation strategies that we track. Results from 1989 to the present, net of transaction costs, follow. Read more

The last time the SPX closed below its 10-day moving average was January 3rd. That means it has now been 35 straight trading days that SPX has closed above the 10ma. That is a very long streak. Below is a list of all streaks since 1928 of 35 days or longer. (Note: prior to 1957 S&P 90 Index data

Traders and market analysts use volume data, which is the amount of buying and selling of an instrument over a given time period, to gauge the strength of an existing trend or identify a reversal. The back-and-forth movement between buyers and sellers for the best available price allows us to

Low volatility strategies have garnered a fair amount of popularity and a growing body of supporting research. Studies have shown risk reduction levels of 25%, while turnover has varied from 20% to 120%. However, higher turnover produces higher costs of trading, such that the excess return obtained

Trend equity strategies seek to meaningfully participate with equity market growth while side-stepping significant and prolonged drawdowns. These strategies aim to achieve this goal by dynamically adjusting market exposure based upon trend-following signals. A naïve example of such a strategy would

The largest smart beta Low Volatility ETF is technically a Minimum Variance strategy Low Volatility and Minimum Variance have comparable and attractive characteristics However, both currently feature a high sensitivity to interest rates INTRODUCTION The Low Volatility factor was the best performing

One of the first things you quickly come to understand in equity pairs trading is how important it is to spread your risk. The reason is obvious: stocks are subject to a multitude of risk factors – amongst them earning shocks and corporate actions -that can blow up an otherwise profitable pairs