Factor investing (value, momentum, low volatility, carry, trend, etc.) is well-known in equities but less discussed in other asset classes. However, many of these factors are just as prevalent in other asset classes, such as bonds, commodities, and currencies. In this case study, we explore the

In our previous post we demonstrated an approach to modeling US Treasury ETF performance in an era of rising interest rates. We showed results like the ones below, simulating the performance of various constant maturity ETFs from the interest rate peak in 1981 to the present (left half of the

Wednesday is a Fed Day. Fed Days have historically shown an upside tendency. I have documented this tendency in great detail over the years, with the most complete documentation coming in The Quantifiable Edges Guide to Fed Days. Based on what the market did Tuesday, this does not seem to be the

In trading and in trading-related research one could be quickly overwhelmed with the sea of ink devoted to trading strategies and the like. It is essential that you “pick your battles” so to speak. I recently finished reading Machine Trading, by Ernest Chan. Here is what I think about the book.

Momentum is the tendency for assets that have performed well (poorly) in the recent past to continue to perform well (poorly) in the future, at least for a short period of time. The momentum effect is one of the most pervasive asset pricing anomalies documented in the financial literature: Stocks

As you'll know if you've been following any of my numerous social media accounts I spent the weekend in New York at QuantCon, a conference organised by Quantopian who provide a cloud platform for python systematic trading strategy backtesting. Quantopian had kindly invited me to come and

This is the first in an exciting series of posts written by Frank Smietana, a new expert guest contributor to QuantStart. In this insightful new article Frank looks at the different career roles that are available in the systematic trading space. - Mike. The changing role of humans in capital

Position sizing and portfolio allocation have not received much attention in the options trading community. In this post we are going to apply a simple position sizing rule and see how it performs within the context of volatility trading. An option position can be sized by using, for example, a

As you are reading this blog you are definitely familiar with the concept of backtesting trading strategies, and probably have done so a significant amount of times. But do you also backtest your risk metrics? They are as important of a building block of your portfolios overall performance as the

I had some time yesterday while waiting for an appointment, and re-read "A Comparison of Tail Risk Protection Strategies in the U.S. Market". One particular sentence in the paper caught my attention: "Remarkably, of the 24 months with greater than 5% loss in the S&P 500 between

In the previous post, we reviewed momentum’s robustness. We looked at how momentum has stood the test of time. We also stress-tested the Global Equities Momentum (GEM) strategy to see whether it’s performance is not overly sensitive to changes in the strategy’s settings (i.e. the 12-month

This is a summary of the recent performance of a wide range of excellent tactical asset allocation strategies. These strategies are sourced from books, academic papers, and other publications. While we don't (yet) include every published TAA model, these strategies are broadly representative of

At the settlement time of the VIX Volatility Index, volume spikes on S&P 500 Index (SPX) options, but only in the out-of-the-money options that are used to calculate the VIX, and more so for options with a higher and discontinuous influence on VIX. We investigate alternative explanations of

ETFs and factor investing are on the tip of everyone’s tongue these days. Factor investing is being couched as a “new” thing, despite the fact that institutional investors have been deploying these strategies for years. (See this working paper discussing the effective use of smart beta

I recently read Gary Antonacci’s book Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk, and it was clear to me that this was an important book to share with the Robot Wealth community. It is important not only because it describes a simple approach to exploiting

I recently received an email asking me where all the trading ideas are. I think every episode provides at least 1 idea of value, but one that stands out in my mind was the chat with Rob Hanna in episode 7. In that episode he share loads of trading ideas. But he also goes one step further and

Our firm Allocate Smartly provides independent analysis of Tactical Asset Allocation (TAA) strategies. TAA strategies dynamically allocate to broad asset classes like stock indices, bond indices or gold. Unlike a traditional buy & hold portfolio, TAA is able to increase allocation to assets

This post will be detailing a process to create a VIX term structure from freely available CBOE VIX settlement data and a calendar of freely obtainable VIX expiry dates. This has applications for volatility trading strategies. So this post, as has been the usual for quite some time, will not be

This monday, we were witnesses to a rather large decline in Vix. Taking a quick look at how often drops like this happen and how has Vix behaved after large single day drops 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 import pandas as pd import numpy as np import matplotlib.pyplot as plt import

A few weeks ago, I was sipping coffee, thumbing through Barron’s as I do every weekend. It’s a way in which I keep a pulse on what’s going on in our space. Though I never consciously pay attention to ads, on that particular morning, one caught my eye – a big full pager from Schwab, below.

What investment strategy would have given you the highest returns in Europe over the 13 year period from July 2000 to July 2014? In this article I summarised the master’s thesis of Andreas Hennes (completed at Goethe University Frankfurt am Main on 14 September 2015) where he set out to test

Tomorrow I’ll be sitting with Pat O’Shaughnessy and Ben Johnson to discuss “Straight Talk About Smart Beta.” Here is a link to the big Morningstar event. In preparation for our discussion we were spitballing ideas and Ben brought up the concept of helping investors understand the

There are several big academic finance conferences that attract the best research and the best researchers in one bullpen — the AFA and the WFA meetings. We chatted about the AFA event last January (be sure to check that out). But now it is the WFA’s turn. I attended the WFA a few years back in

Quant is a broad word with many job descriptions in finance. In asset management, a quant is someone who applies mathematical (usually statistical) techniques to analyzing the securities market, usually with an eye towards identifying investment opportunities. Quants rely on factors: systematic

Imagine this, you have backtested a strategy adhering to all the “general rules”: you did proper in/out of sample testing, you have stable parameters (if the strategy has any), you didn’t overfit, you account for transaction costs and slippage, everything seems good and you are ready to deploy

A new paper, “Facts about Formulaic Value Investing,” is making the rounds and professes to plunge a dagger directly into the heart of systematic value investors. Half of my inbox is filled with questions regarding this paper, since we are considered by some — rightly or wrongly — to be

I am excited to announce that Abnormal Returns now supports memberships. The most common compliment I get about Abnormal Returns is that it saves you time. We all well know that time is money. A great way to help keep Abnormal Returns an ongoing, independent entity is to contribute to its upkeep at

We’ve spoken previously about different clustering methods many times: K-Means, Hierarchical Clustering, and so on. However, this field does not end here. In this post, I will try to find how K-Means clustering works in an investment solution. K-Means Clustering The K-Means algorithm partitions

Long-only commodity futures returns have been very disappointing over the last decade, leading some to wonder if it was a mistake to invest in commodities. The poor performance is the result of poor “income returns” and not of falling commodity prices. This observation may be surprising for many

Following on from my last post, I have recently been using the BayesOpt library to optimise my planned neural net, and this post is a brief outline, with code, of what I have been doing. My intent was to design a Nonlinear autoregressive exogenous model using my currency strength indicator as the

US Treasuries and other interest rate sensitive instruments form the backbone of many asset allocation strategies. Investors are justifiably concerned about a future of rising interest rates and the potential impact on those instruments. In this post we model that impact on constant maturity

Value and Momentum investing have been studied across many different markets and asset classes (Asness et al 2013) and have shown to be effective factors. A working paper, “Frontier Stock Markets: Local vs Global Factors” by Douglas W. Blackburn and Nusret Cakici examines Value and Momentum

Research Affiliates published a new piece of research exploring mutual fund returns over the last 25 years and the implied ability for managers to capture popular factor premiums published by the academic community. They argue that several factors accepted in academia may not be implementable after

Momentum is the tendency for assets that have performed well (poorly) in the recent past to continue to perform well (poorly) in the future, at least for a short period of time. In 1997, Mark Carhart, in his study “On Persistence in Mutual Fund Performance,” was the first academic to use

Generate an efficient frontier of random portfolios with custom constraints in R. Accelerate your project with the power of cloud computing using Techila Technologies’ solution in combination with R’s plyr functions. Source code included. The embedded source code below is available due to the

How do we know if a price is right and when do we enter the trade ? Is the S&P 500 Index trading at 2355 for that day to high or to low. Should I buy or sell ? Proponents of the Bollinger Band say that this indicator can greatly improve your odds in being on the right side of the market. The

The webinar will explain Mixture Models and explore its application to predict an asset’s return distribution and identify outlier returns that are likely to mean revert. The webinar will cover Why bother? Motivating experimentation with Mixture Models How do Mixture Models work? (An intuitive

This post will be about pre-processing custom indicators in quantstrat–that is, how to add values to your market data that do not arise from the market data itself. The first four parts of my nuts and bolts of quantstrat were well received. They are even available as a datacamp course. For those

An 18th century British nobleman, Baron Rothschild, was rumored to have made his fortune buying during the panic that followed the Battle of Waterloo against Napoleon. He is behind the often quoted saying "Buy when there's blood in the streets”, which he continued “even if the blood is

This is kind of a weird one. I was mulling over the question of what happens when the market opens up, i.e. above its previous close. Is the day likely to be an up day? A down day? I got out my data and started poking around. I looked at all “open-up” days with an open at least 0.25% above the

We were recently asked by Aaron Brask, one of our guest bloggers, why we don’t provide a “job board” on our site. Aaron works for several large family offices and he says it is incredibly difficult to find intellectually honest talent. Aaron also pointed out that we have a unique community of

Below is a quick look at how the SPX has performed in the past on Holy Thursday. Like the last day before many long weekends, it has shown a bullish propensity over the years. 2017-04-13 The numbers are compelling, and it is especially impressive to see how much the winners have outsized the losers

The Dark Side of ETFs? Sounds interesting, and in my humble opinion, an image of Darth Vader on page 1 would be a great addition to the paper. The paper, “Is there a dark side to exchange traded funds? An information perspective,” written by Doron Israeli, Charles M. C. Lee, and Suhas A.

In the previous post, Simple ConnorsRSI Strategy on S&P500 Stocks, I showed a simple strategy which I optimized which gave 1,300 variations. Today, I will cover various methods to choose a strategy to potentially trade. Goals The goals were to find a variation with over 20% CAR and Max Drawdown

Mebane Faber is the founder and CIO at Cambria Investment Management, where he manages Cambria’s ETFs, separate accounts and private investment funds. He’s also authored numerous white papers and five books now, on various investing subjects. Meb’s a budding podcaster too, his podcast; The Meb

Nearly all research related to algorithmic trading is empirical in nature. That is, it is based on observations and experience. Contrast this with theoretical research which is based on assumptions, logic and a mathematical framework. Often, we start with a theoretical approach (for example, a

In this paper, we propose a gold price index that enables market participants to separate the change in the ‘intrinsic’ value of gold from changes in global exchange rates. The index is a geometrically weighted average of the price of gold denominated in different currencies, with weights that

A central challenge in economics is understanding how price affects the quantity of supply and demand, a relationship often assumed to be approximately linear. But there are markets where this notion of linearity, sometimes called “elasticity,” may not hold. In a paper that deserves more

In the last post (here), I examined what happened after a stock moved down a significant multiple of its previous day’s Average True Range (ATR20 in this case). Stocks tended to have up days on day 1 and days 3-5, with a down day on day 2 as an average. What about bursts upward? Are they the

Another negative month for this (delayed) State of Trend Following report. To say that the last 12 months have been far from the best performing period for the index seems an understatement. I also include in this month’s report (further below) the 12-month chart from the post I write for the