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

Or why you aren't, and will never be, John Paulson The systematic versus discretionary trading argument is alive and well; or if you prefer, computers versus humans*. In this post I pose the question - who is better the average systematic trader, or the average discretionary human? * Though

This post serves three main purposes: Firstly, I'm going to explain the main features I've just added to my python back-testing package pysystemtrade; namely the ability to estimate parameters that were fixed before: forecast and instrument weights; plus forecast and instrument

One of the most overused– and misunderstood — terms I’ve seen used by finance practitioners is “behavioral finance.” Many professionals consider themselves to be “behavioral finance experts” because they identify irrational investors.1 Newsflash: Identifying irrational investors is not

The stock market’s wild ride to begin the year continues, with the latest twist reminiscent of a roller coaster. Over the past 4 days, the Dow Jones Industrial Average (DJIA) has moved at least 1%, with each day alternating up and down. Since 1900, this is the 68th such streak and just the 17th in

We study the effects of FX liquidity risk on carry trade returns using a low-frequency market-wide liquidity measure. We show that a liquidity-based ranking of currency pairs can be used to construct a mimicking liquidity risk factor, which helps in explaining the variation of carry trade returns

Recently, I participated in a Kaggle contest sponsored by Winton Capital. The contest provided various market related data and asked participants to predict intraday and next two day return forecasts over unseen future data. Prizes included $50,000 in monetary rewards and a chance to join Winton

Which investment would you prefer to invest in to diversify your existing stock allocation? Asset A with an expected: 3% annualized return 3.5% annualized standard deviation 0.00 correlation with your existing investment Asset B with an expected: -5% annualized return > 50% annualized standard

We examine the effect of security analyst recommendations on stock price momentum. Results show that momentum profits are directly linked to analyst optimism. Specifically, we find that a 1-unit change in recommendation quintile translates to about a 50 basis point change in subsequent 3-month

The internal bar strength or (IBS) is an oscillating indicator which measures the relative position of the close price with respect to the low to high range for the same period. The calculation for Internal Bar Strength is as follows… IBS = (Close – Low) / (High – Low) * 100; For example, on

In my last post I introduced how I identified possible technologies and learned the basics about different languages, operating systems and IDE’s. I also mentioned that my choice was to build on top of .Net’s C# and Visual Studio, as my base for developing. In this post I want to dig a little

We have a large number of vendor-developed backtesting platforms available in market which can be very efficient in backtesting automated strategies; but to decide which once will suit your requirements, needs some research. Ideally custom development of a backtesting environment within a

It is with a giddy sense of schadenfreude that every year around this time, we get to read bold prediction rubbish like this: A best-selling personal finance guru, a behavioral economics columnist at MarketWatch, a Harvard-educated economist and other notable financial experts all warn the stock

We investigate whether two clustering techniques, k-means clustering and hierarchical clustering, can improve the risk-adjusted return of a random equity portfolio. We find that both techniques yield significantly higher Sharpe ratios compared to random portfolio with hierarchical clustering coming

We often see statements like “linear regression makes the assumption that the data is normally distributed”, “Data has no or little multicollinearity”, or other such blunders (you know who you are..). Let’s set the whole thing straight. Linear regression assumes nothing about your data It

Recently I posted a number of articles on various breadth diffusion indicators and their relative effectiveness in predicting the health of the S&P 500. The big winner was the system that compared the number of stocks in the historical constituents of the Russell 3000 that were up 30% or more

I'll leave it to others to chime in whether forward P/E's are useful or not given the fact they typically overstate earnings and I'll ignore that earnings may be at a cyclical peak (more on the latter here). As an aside, technicals in the market are filthy, as most short-term signals

In the last two articles (here and here), we reviewed the backtest results of 28,840 short options straddles on the Russell 2000 Index (RUT). If you haven't read the last two articles, you may want to first read the introductory article for this series Option Straddle Series - P&L Exits. In

At the end of last year I announced that I would be working on a series of articles regarding the development of an Advanced Trading Infrastructure. Since the initial announcement I haven't mentioned the project to any great extent. However, in this article I want to discuss the progress

Summary We run a U.S. sector-based, long-or-flat trend following strategy. With largely sideways market action, 2015 was a tough year for trend following, especially for long-only trend following, since the large negative trend in the Energy sector could not be monetized. We believe portfolio

We show that opportunistic insider traders can be identified through the profitability of their trades prior to quarterly earnings announcements (QEAs), and that opportunistic trading is associated with various other kinds of managerial and firm misconduct. The subsequent buys and sells of

In the words of Asness et al (2014), “No other factor…has nearly as long a track record, as much out-of-sample evidence (including across time, geography and even security type), or as strong and reliable a return premium as momentum.” They were speaking only of relative strength momentum.

For those traders looking for an edge in every aspect of trading, today's topic is something that isn't discussed too much but has had a great impact on the 2 guests of this episode. The topic is collaboration in trading and the guests are Michael Cook and Kevin Davey. Both guests have

As index investing has grown in popularity, investors focus more and more on the market’s overall return and less on the return of its component parts (individual stocks). But underneath the hood of each market index we find many inequalities. The top 20% of stocks represent 85% of the overall

Stock markets as a fundamental component of financial markets play an important role in the countries’ economies. The factors that a ↵ ect the price of stocks include the political situations, company performance, economics activities, and some other unpredicted events. The traditional

In a previous post, I showed some elementary properties of discrete time Markov Chains could be calculated, mostly with functions from the markovchain package. In this post, I would like to show a little bit more of the functionality available in that package by fitting a Markov Chain to some data.

Joe Marwood has recently posted an article which includes a variety of tests of the RSI(2) when applied to the SPY etf or individual stocks. You can see the original article here. A while back I also tested the RSI(2) on a variety of Equity Index ETFs and I figured that readers might be interested

Hi Guys, please find the information about the upcoming event in Singapore where I also submitted my proposal to host and conduct a full-day workshop on Frontiers of Python for Finance. I hope to see You there! -Pawel SCF2016-logo_final_retina2 You are cordially invited to contribute as an author or

This code box contains updated code from my previous post. The main change is the inclusion of bias units for the directed auto-regressive weights and the visible to hidden weights. In addition there is code showing how data is pre-processed into batches/targets for the pre-training and code showing

West Texas Intermediate (WTI) Crude Oil price started plummeting from a high of US$107.95 in June 20, 2014 to a low of US$31.42 in Jan 11, 2016. Prices of US Banks and oil are becoming more coupled now due to US Banks’ exposure to energy companies; especially medium size companies and shale oil

Momentum in firm fundamentals, i.e., earnings momentum, explains the performance of strategies based on price momentum. Earnings surprise measures subsume past performance in cross sectional regressions of returns on firm characteristics, and the time-series performance of price momentum strategies