Consider the following market timing strategy, which we’ll call “daily momentum”: (1) If the market’s total return for the day, measured from yesterday’s close to today’s close, is positive, then buy the market at today’s close and hold for one day. (2) If the market’s total return

Welcome to part two of an ongoing series, where I look at different breadth indicators and their viability in describing market health. You can read – and should read! – the introductory post here: Using Market Breadth to Gauge Market Health (part 1) So last post, we (ok, “I”, since I’m

We all want to know if it's the right time to trade. And we'd also like to know which direction. So for at least the last two months like forever, investors have tried to come up with ways to judge how the market is doing. One technique is to use market breadth as an indicator. There are a

Despite yesterday’s rally in the major indices, the underlying breadth statistics were historically weak. After a steep selloff to begin the day yesterday, the stock market rallied late to close with solid gains. At least, the major large-cap averages did. The broader, smaller-cap indices mostly

In this piece, I’ll explore the momentum factor in some detail, mainly because of the excellent article by @jesse_livermore on the dangers of back-testing and the recent deterioration in the momentum factor. As Jesse did, I’ll use Fama French data because its publicly available, even though I

Using a sample of 97 stock return anomalies documented in published studies, we find that anomaly returns are 7 times higher on earnings announcement days and 2 times higher on corporate news days. The effects are similar on both the long and short sides, and they survive adjustments for risk

The search for objective analysis in the cause of making informed investment decisions is the Holy Grail of finance. Unfortunately, narrative risk continually threatens to derail us on our crucial quest for perspective. Everyone loves a good story, and it’s no different when it comes to finance

Cut short your losses, let your profits run on. This principle above is the central tenet of trend following, a successful strategy for trading systems and CTAs alike. Digging through history, this maxim can be traced back all the way to David Ricardo, an eighteenth century British economist and

Summary We break portfolio construction into two unique phases: signal generation and the rules that determine allocations. We use the analogy that this process is like cooking, where our signals are the ingredients and our allocation rules are the recipe. While most firms focus their research on

Here's a python script I made to rank stocks according to their return on equity and trailing EV/EBITDA. I have named it the poor mans magic formula because all of the fundamental data is scraped from yahoo finance. Yahoo are friendly enough to provide this data for 'free' but have

This is the another post of the series: How to build your own algotrading platform. Building a backtest system is actually pretty easy. Easy to screw up I mean. Even though there are tons of excellent libraries out there (and we'll go through them at some point), I always like doing this on my

In a recent article, Advisor Perspectives editor Robert Huebscher noted: “During the last 40 years, an average of 60% of equity funds underperformed the S&P 500. But, according to the SPIVA data, 86.4% of large-cap managers underperformed their benchmark in 2014. The percentages were not much

Doing quantitative research implies a lot of data crunching and one needs clean and reliable data to achieve this. What is really needed is clean data that is easily accessible (even without an internet connection). The most efficient way to do this for me has been to maintain a set of csv files.

Crude oil has been in the news a lot recently. Just last week, after the OPEC meeting, its price declined by over 10%. With a lot of volatility, we wanted to test how a trend following strategy would have performed on the futures contract in recent history. Here is a quick post showing our benchmark

Creating robust trading strategies can be a difficult task, sometimes taking months or even years to generate something you find acceptable. Even then, once you start trading it live there is no guarantee it’ll work in the future. With strategy creation being such an involved process at times, how

The Halloween effect, aka “sell in May and go away” is the observation that equity market returns tend to be worse over summer time in the northern hemisphere. Anyone who has followed markets for a while has probably noticed a distinct lull over the summer period. But can we quantify this

Benchmarking Benchmarks: Much Ado About Nothing

Generalized Recovery

Tail-Risk Protection Trading Strategies

I. Trading Strategy Concept: Short-term momentum patterns with a trend filter. Source: Hill, J. R., Pruitt, G., Hill, L. (2000). The Ultimate Trading Guide. New York, N.Y.: John Wiley & Sons, Inc. Research Goal: To benchmark the Gap Pattern – Type B against the Gap Pattern – Type A.

A new paper from Christian Walkshäusl and Sebastian Lobe* called The Enterprise Multiple Investment Strategy: International Evidence examines the performance of the enterprise multiple (EV/EBITDA) in international markets, including Australia, Canada, France, Germany, hong Kong, Japan, Singapore,

Recent academic papers have shown that low-volatility stocks have provided better returns than higher volatility stocks. What’s more, this is a global phenomenon. These findings, however, run counter to economic theory, which predicts that higher expected risk should be compensated with greater

Buffett’s Asset Allocation Advice: Take it … With a Twist Javier Estrada October 26, 2015 One of the most important decisions retirees need to make is the asset allocation of their portfolios. They can have a static or a dynamic allocation, and simplicity usually favors the former. Warren

This paper describes how to create ex-ante expectation for generalized trend-following rules. This report first study the effect of trend-following rules applied to random data with varying degrees of drift and autocorrelation. There is a positive relationship between drift, autocorrelation and the

Jumps in the VIX during the month of December have (almost) always led to year-end stock market gains. It is the time of year when research houses trot out all matters of bullish seasonal stock market patterns pertaining to year-end. It seems as though each year brings more and more attention, and

Value investing was a lot easier in 2012 and 2013 when our value approach beat the market by a substantial margin and we had a reasonable edge on other active value players. But now that we have lived through 2014 and 2015, most value approaches (simple, complex, quant, human, small, large, etc.)

One of our readers, Corey Hoffstein, told me about an interesting paper, “Investor Attention, Visual Price Pattern, and Momentum Investing”, by Li-Wen Chen and Hsin-Yi Yu. Their basic idea is that investors are drawn to stocks that have attention grabbing behavior. And the thing that most grabs

Another day, another piece of evidence that the stock “market” is not what it may appear to be by looking at the major averages. I place the quotes around market as the word has a very different meaning to us than it seems to have for the superficial market observer – or at least mainstream

Awww…modern portfolio theory…that feel-good construct I teach to all of my graduate-level finance students each year. Simply input 1) a vector of expected returns and 2) a covariance matrix into your computer, and voilà, you have your optimal portfolio weights. Like all things viewed with the

I've previously outlined that high yield credit risk is typically less ideal than simply gaining credit exposure through stocks and rate exposure through bonds. Now Larry Swedroe outlines the case for avoiding investment grade credit risk altogether. There are many well-documented anomalies in

This is the third article in a series looking at the backtest results of selling at-the-money (ATM) options straddles on the Russell 2000 index (RUT). For background on the setup for the backtests, as well as the nomenclature used in the tables below, please see the introductory article for this

As we have discussed many times, much of the “conventional wisdom” on investing is simply wrong. For our purposes, we can define conventional wisdom as those ideas that become so commonly accepted that they go unquestioned. Today we’ll look at the idea that rising interest rates would doom

As I wrote about here, here, here and yes, here (and, um, also here), the holiday season tends to be a good time to invest in the stock market in general and in specific sectors in particular (with that pesky fly in the ointment, monkey in the wrench, pain in the rear caveat that “there are no

Choosing an appropriate performance measure is important for fund investors, nevertheless, many researchers find empirically that the choice of measures does not matter because those measures generate identical rank ordering, even though the distribution of fund returns is non-normal. In this paper

There are many well-documented anomalies in finance. Among them is the surprisingly small return that investors historically have earned for taking credit risk in fixed-income markets—the default premium, as measured by the difference in returns between long-term Treasurys and long-term corporate

First draft of 'JavaScript for Financial Analysts' Chapter 12. ~ Starting JavaScript development is like deciding to support the Yankees or Manchester United. It's got a lot of history; the most money; and the deepest bench of developers, but sometimes, sometimes you wish it was a

Basis-Momentum

Option Return Predictability

In multivariate volatility forecasting (4), we saw how to create a covariance matrix which is driven by few principal components, rather than a complete set of tickers. The advantages of using such factor volatility models are plentiful. First, you don't model each ticker separately, you can

Low Risk Anomalies?

In Search of Alpha - Trading on Limited Investor Attention

Average Skewness Matters!

Ninety Years of Media Coverage and the Cross-Section of Stock Returns

Dash for Cash: Month-End Liquidity Needs and the Predictability of Stock Returns

The best quant mashup links for the week ending Saturday, 12/05 as voted by our readers: Predicting volatility [EP Chan] Announcing the QuantStart Advanced Trading Infrastructure Article Series [Quant Start] Exploring mean reversion and cointegration with Zorro and R: part 1 [Robot Wealth] The

This part is awesome. Trust me! Previously, in Part 1, we examined two independent methods in order to estimate the probability of a very rare event (heavy or extreme loss) that an asset could experience on the next day. The first one was based on the computation of the tail probability, i.e.: given

1. Motivating Example A Popular Goal. Financial economists have been looking for variables that predict stock returns for as long as there have been financial economists. For some recent examples, think about Jegadeesh and Titman (1993), which shows that a stock’s current returns are predicted by

This is how your average buy-and-hold investor probably feels right now if they are looking to deploy new capital for the long run. Today, bond yields are puny while stock valuations are rich. In fact, we currently have one of the worst yield and value combinations in history as seen in the charts

Summary Traditionally, stocks have been used for growth and bonds for safety Therefore, investors looking for long-term capital appreciation tended to allocate heavily towards stocks while investors concerned about preservation allocate more heavily towards bonds With an anemic forecast for equity

This post will outline a first failed attempt at applying the ensemble filter methodology to try and come up with a weighting process on SPY that should theoretically be a gradual process to shift from conviction between a bull market, a bear market, and anywhere in between. This is a follow-up post