In one of our recent articles we’ve talked about most popular backtesting platforms for quantitative trading. Here we are sharing most widely used Python libraries for quantitative trading. Python is a free open-source and cross-platform language which has a rich library for almost every task

First things first. What do we mean by sparse estimation? Sparse – thinly scattered or distributed; not thick or dense. In our context, the term ‘sparse’ is installed in the intersection between machine-learning and statistics. Broadly speaking, it refers to a situation where a solution to a

Momentum is the tendency for winning stocks to keep winning and losing stocks to continue underperforming. It was identified as a risk factor in the early 1990s and targeted by investment practitioners since then. Unlike the value and size factors, the momentum factor has remained robust and

I’m happy to publish my first paper on SSRN entitled, “Speculation in a Path Dependent World” I found many otherwise talented managers entering a multi-manager platform (assigned capital with strict risk limitations) having a difficult time transitioning. The paper is my simple attempt to

In my previous post I talked about a architectural concept I had defined for my trading platform. Looking backward from now, it was a good decision to go for a service oriented architecture. But how do all the communication is done in a distributed system? Lets talk about this, and try to find some

Given recent performance, the question of whether small-cap stocks really do outperform over time has made its way into the financial media. So far, we’ve sought to answer it by considering a multifactor approach and examining international evidence. Today we’ll tackle a behavioral explanation.

As established in a previous post, Tadawul All Shares Index (TASI) of the Saudi stock market has high excess kurtosis (9.903). The high kurtosis indicates that TASI has heavy tails. This means that the probability of extremely large negative returns is higher compared to a normal distribution. In

The current study examines the turn of the month effect on stock returns in 20 countries. This will allow us to explore whether the seasonal patterns usually found in global data; America, Australia, Europe and Asia. Ordinary Least Squares (OLS) is problematic as it leads to unreliable estimations;

Hot off the press and haven’t had time to reverse engineer and verify, but this is pretty interesting stuff at first glance. The Enduring Effect of Time-Series Momentum on Stock Returns Over Nearly 100-Years This study documents the significant profitability of “time-series momentum”

Recently, Quandl interviewed a senior quantitative portfolio manager at a large hedge fund. We spoke about how she builds trading strategies–how she transitions from an abstract representation of the market to something concrete with genuine predictive powers. Can you tell us how you design new

Ben Carlson of A Wealth of Common Sense has a recent post, When Global Stocks Go On Sale, outlining that it is typically a pretty good time to be buying when the MSCI World stock index is in a 20% or greater drawdown. His insightful takeaway and chart outlining the historical drawdowns and forward

“A stop order is an order placed with a broker to sell a security when it reaches a certain price. A stop-loss order is designed to limit an investor’s loss on a position in a security” —investopedia. In this article we investigate how the addition of stop-loss orders affect a generic

I’m running a high risk of running out of movies with “short” in the title. So this had better be the last blog post on the subject! In my previous post (here), I looked at a short-sale signal where a stock was shorted after it averaged 3% gains each day over five days (in any distribution).

First draft of 'JavaScript for Financial Analysts' Chapter 15. ~ Like all superheroes JavaScript's biggest strength is also its main weakness. JavaScript can be distributed and run anywhere, easily. The problem is that each browser or platform supports a slightly different subset of

In the book, Short Term Trading Strategies that Work, which Larry Connors and I published in early 2008, we wrote about a simple strategy called “Double 7’s Strategy.” Through the years people often ask about this strategy. Does something that simple really work? How does it do in a portfolio?

In this article I will test a well-known relative strength trading model using ETFs. The test period will include the data between 01/01/2001 – today. The starting hypothetical balance will be $100,000. The ETFs I will be testing are as follows: IYZ (Telecoms) XLB (Materials) XLE (Energy) XLF

Summary We’ve heard from several market participants that they feel that markets have “gotten faster” lately. We define two quantitative measures of speed and examine how speed has evolved since the 1920s We demonstrate that market speed is actually well within normal ranges – but perhaps

Because volatility seems to cluster in real life as well as the markets, it has been a while since my last article. Sorry about that. Today we will be taking our first giant leap along A Non-Random Walk down Wall Street. The Non-Random Walk Series A Non-Random Walk Down Wall Street is the cheeky

Our friends at Alpha Architect just wrote a great piece titled "Even God Would Get Fired as an Active Investor." In the study, they show that while an omnipotent investor with perfect foresight would have delivered great returns over the long run, he would be fired many times along the way

We study the out‐of‐sample and post‐publication return predictability of 97 variables shown to predict cross‐sectional stock returns. Portfolio returns are 26% lower out‐of‐sample and 58% lower post‐publication. The out‐of‐sample decline is an upper bound estimate of data mining

My previous post was about my thoughts concerning general architecture of a trading platform. During my way rethinking it from end to end it becomes clear that a “client only” approach would not fit with my needs. So I went back to my list of entities and started the puzzling again. To see all

So in this last post, I data-mined the hell out of the S&P500 index (well ok SPY) and found an “anomaly”: every time SPY drops more than 1% from the previous close to the current close, you wait (that’s Day 0). You then buy at the close 13 days later, and sell at the close of Day 14. This

Is Jeremy Grantham, co-founder and CIO of GMO bullish or bearish these days? According to Myles Udland at Business Insider, he’s both. He quotes Grantham: “I think the global economy and the U.S. in particular will do better than the bears believe it will because they appear to underestimate the

Murray Ruggiero is the chief systems designer and market analyst at Tuttle Tactical Management with around 200 million dollars under management. He is one of the world’s foremost experts on the use of intermarket and trend analysis in locating and confirming developing price moves in the markets.

The Challenge of Being a Passive Investor Investors face the prospect of poor expected long-term returns making buying and holding less desirable for both equity and bond holders Given that bond yields are so low, investors are being forced to hold risky assets such as equities to earn sufficient

I was really surprised by a huge popularity of the past section of QuantAtRisk entitled Motivation for Quants. My readers made me thinking. Again. If there is a need for posts that expose and discuss the naked truth about quant job space, let’s make it, again! This time bigger, better, and with

Today in SmileOfThales we will provide you some brief but useful C# code (the whole code is available at the end of the article) to retrieve historical cash dividend data in Excel. The topic covers Excel-Dna, data caching, Html parsing with HtmlAgilityPack … that’s it and it’s already pretty

There have been 1,700 individual U.S. stocks (with starting market caps of at least $200MM, inflation adjusted) which have tripled in a 12-month period since 1962. Many of these individual stocks tripled in more than one 12-month period, so we have 7,500 or so separate observations of a stock

I’ve been reading books by Michael Halls-Moore and my head hurts. Not having any formal training in statistics, I only understand about half of the material. None the less, I found his discussion of ‘correlograms’ interesting. I even installed R on my computer (even though I haven’t fully

We examine the causal effect of limits to arbitrage on ten well-known asset pricing anomalies using Regulation SHO, which reduced the cost of short selling for a random set of pilot stocks, as a natural experiment. We find that the anomalies become substantially weaker on portfolios constructed with

Private equity funds tend to select relatively small firms with low EBITDA multiples. Publicly traded equities with these characteristics have high risk-adjusted returns after controlling for common factors typically associated with value stocks. Hold-to-maturity accounting of portfolio net asset

Recently, I wrote about fitting mean-reversion time series models to financial data and using the models’ predictions as the basis of a trading strategy. Continuing my exploration of time series modelling, I decided to research the autoregressive and conditionally heteroskedastic family of time

Exactly one month ago clients of ReSolve Asset Management received our 2015 annual letter, entitled “Navigating Active Asset Allocation When Diversification Fails”. People who signed up for our email distribution list received it aa few days later. If you would like to receive premium content in

Investors and managers are concerned with “fat tails”. In the second part of this post, we look at kurtosis in more detail. An apology and a warning This piece is more technical and longer than I had expected. The problem we're looking at here is subtle and not easy to distill down to a

As the news cycle spins faster and faster, we are seeing more and more market observations based on gut feelings. One such observation that I have heard recently is that oil and energy are driving stocks more than ever before. I thought we would look to the hard data in our own version of

Strong start of the year for the State of Trend Following index, nearly closing the month with double-digit gains. Please check below for more details. Detailed Results The figures for the month are: January return: 8.28% YTD return: 8.28% Below is the chart displaying individual system results

I have discussed the employment report a number of times here on the blog. Over the years the release of the report has generated a high amount of volatility for overnight trades. While the direction of those volatile moves has undergone some big hot and cold streaks, it has not provided a

Factor modelling is everywhere these days. I wrote about smart beta here. It is good to quantify performance drivers but the usual caveats apply to quantitative studies utilizing backward looking data, “past performance does not guarantee future results”. I wanted to share a little exercise I

Can a set of weak systems turn into a single strong system? When you are in front of a complex classification problem, often the case with financial markets, different approaches may appear while searching for a solution. These systems can estimate the classification and sometimes none of them is

Similarly to last year, trend following starts the year on strong footing. January returned over 5% for our trend following index after flirting with the double-digit territory to establish new all-time highs. Below is the full State of Trend Following report as of last month. Performance is

The last article on RUT straddles (here) was very popular, so I thought I'd write a similar post on SPX straddles. Recall that from September, 2015 through November, 2015 I reviewed the backtest results form 28,840 short options straddles on the S&P 500 Index (SPX). You can read the summary

I seem to be in a ‘shorting’ mood lately. Can’t think why that might be… (oh yeah, the general state of the market perhaps?). Above and below you can see some recent examples of stocks that went up a lot, and then either kept going up or dropped down again. Yes, that amazing analysis is

Empirical asset pricing research can sometimes get monotonous because you end up circling back relentlessly to the same conclusions: value works, momentum works, and yet, markets are remarkably efficient. But, sometimes, research uncovers absolutely stunning and counter-intuitive results–and this

In my last post, I talked about my starting point and how to develop guesses to segregated entities. This was a very important step but by doing this at same time I got another point on my agenda – and unfortunately it was a question not a answer… The question was about in which way I should put

As a developer in the world of vast technologies available to us at the click of a button, many of us more often than not, care about the fun part of building a program from scratch and seeing it work, eventually. Hoping that requirements don’t change from a higher power that basically fills our

Summary Most investment strategies can be broken down into the risk premia they wish to harvest, whether it is vanilla like the equity risk premium or more exotic, like the value premium. Different risk premia mature at different rates. Value can take years to mature while momentum can take only a

The best quant mashup links for the two weeks ending Saturday, 01/30 as voted by our readers: Advanced Trading Infrastructure – Position Class [Quant Start] Why Is Momentum Neglected? [Dual Momentum] Automated Trading: Order Management System [Quant Insti] Correlations, Weights, Multipliers….

I’ve been teaching myself Python, and I’ve had a couple of successes recently where I took a concept or “need” and coded it to completion. Yay, me! One thing I find myself doing a lot is sorting a batch of data by one column in Excel/Google Sheets, then dividing up another column into

First draft of 'JavaScript for Financial Analysts' Chapter 14. Download all the code here and give it a test run! ~ There has been a subterranean theme flowing under each chapter of this book. Furthermore, you see it again and again in far flung fields and yet people rarely discuss it.

In hindsight, it’s fun to look at stocks that have had a huge surge, only to collapse violently after they peak. And by “fun” I mean sitting on the sidelines watching, as opposed to pulling one’s hair out when you’re long that particular trade. Above you can see Apple (AAPL) in 2008, where