In addition to market valuation ratios like CAPE, the slope of the yield curve is one of the most talked about signals used to estimate future recessions and market returns. During the second half of last month (March 2019), the yield curve has inverted by about 5 basis points with the 10-year rate

Due to their highly active nature, trend following strategies are generally assumed to be tax inefficient. Through the lens of a simple trend equity strategy, we explore this assertion to see what the actual profile of capital gains has looked like historically. While a strategic allocation may only

Following on from my previous post, this post is a more detailed description of the testing methodology to test kinematic motion models on financial time series. The rationale behind the test(s) which are described below is different from the usual backtesting in that the test(s) are to determine

2019 has started favorable for factor investors, compared to 2018 Low Volatility generated the best and Value the worst performance Factor performance is comparable in the US & Europe, but different in Japan INTRODUCTION We present the performance of five well-known factors on an annual basis

Algorithmic trading adds noise to the markets we have known. So why not add some noise to your historic market data? This way you can check if your algorithmic trading strategies are fit for the future. Learn how to generate noisy data and how to test your strategies for stability in a noisy market.

The algorithmic strategy business likes quoting academic research to support specific trading factors, particularly in the equity space. Unfortunately, the rules of conventional academic success provide strong incentives for data mining and presenting ‘significant’ results. This greases the

When trading options, we often use the VIX index as a measure of volatility to help enter and manage positions. This works most of the time. However, there exist some differences between the VIX index and at-the-money implied volatility (ATM IV). In this post, we are going to show such a difference

It is worth noting that Friday is the last trading day of the quarter. And the last day of the quarter has some interesting characteristics. I often hear the term “window dressing” mentioned by the media when referring to end of quarter activity. The suggestion is that fund managers will make

Consider a market-timing strategy which supposedly predicts the direction of the stock market trend. Such a strategy generates Buy and Sell signals. A Buy signal is the signal to buy stocks, whereas a Sell signal is the signal to sell. Simple enough, but how does one evaluate the forecast accuracy

Quite a few of my recent blog pieces have been picked up by the lovely folk at allocate smartly. So I thought I'd write an asset allocation piece, as the readers of my second book "Smart Portfolios" probably feel neglected with the lack of articles on investment rather than trading.

One of the hardest and most frequent tasks for anyone in the quantitative finance world is to summarize or visualize in a simple way a vast amount of data to represent a company. In this blog, we have covered different Machine Learning techniques that allow us to summarize information through

Having just attended a great AI conference in New York, here are some observations: First about AI Most quants prefer the term Machine Learning (ML) instead of AI. Questions still remain of where AI (ML) adds value in a quant investment process. For example, Man’s CIO Sandy Rattray said that it

Information does not flow into the market at a constant frequency or with constant magnitude. By sampling data using a constant time horizon (e.g. “200-day simple moving average”), we may over-sample during calm market environments and under-sample in chaotic ones. As an example, we introduce a

With regards to seasonality, we are in an interesting period right now. The last couple of weeks the market played out well according to seasonal patterns. We saw March opex week put in nice gains as it often does. And then we saw the week after Quad-witching suffer losses this past week.

It is questionable if investors should prepare for catastrophic events Factor returns are almost random after black swan and major events Simple diversification is likely the best option for the expected and unexpected INTRODUCTION Investors fear black swan events, although it can be argued that

Systemic financial crises arise when vulnerable financial systems meet adverse shocks. A systemic risk indicator tracks the vulnerability rather than the shocks (which are the subject of ‘stress indicators’). A systemic risk indicator is by nature slow-moving and should signal elevated

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