We examine whether the predictability of future returns from past returns is due to the market's underreaction to information, in particular to past earnings news. Past return and past earnings surprise each predict large drifts in future returns after controlling for the other. Market risk,

Note: I’m holding a cover design contest for my new book out next week, feel free to enter! This is normally something I would send to The Idea Farm, but since we started the conversation here I wanted to follow up. One of the best parts of writing is getting feedback. I posted an article the

January started the year as strong — if not stronger — than last year for trend following. Keeping the momentum going, and profiting from a continuation in a few big trends (US Dollar Index, Energies or Swiss Bonds for instance), the index opens the year with a double-digit positive monthly

James Picerno of Capital Spectator recently did a good review of Error-Adjusted Momentum in his post “A Momentum-Based Trading Signal with Strategic Value“. The Capital Spectator blog is rich with great content covering a diverse range of subjects from economics to asset allocation and

in rate for Tuesday, data from 2014-01-07 until February 2015-01-27, total of 55 days in 5 min interval. First graph from every 5 min start to end, impossible to follow a specific line. Second graph from start and Europe close, third graph starts from every hour.

Largest monthly SPX loss in over a year $SPY

January Barometer, fwiw $SPY

We use a large recent sample of Form 4 insider trading filings to provide evidence on the process through which SEC filings are disseminated via EDGAR. We find that while the delay from a filing’s acceptance by EDGAR to its initial public availability on the SEC website is relatively short, with a

Monthly statistics for the S&P500 based on the closing price between year 1950-1958 and 2014 or 1995 to 2014. In pictures, mean, median, win rate per trading day, sum %, profit factor, avg. trade %, quartiles and percentiles. Quartiles and Percentiles on monthly development, graph at top is the

A quick glance at Figure 1 is enough to scare the daylights out of most sane investors.fsenx 1 Figure 1 – SPDR Energy (ticker XLE) (Courtesy AIQ TradingExpert) Thanks primarily to Saudi Arabia’s desire to “boost market share” by putting a lot of oil producers around the globe “out of

I’ve been working at The University of Manchester for almost a decade and will be leaving in just less than 3 weeks time! A huge part of my job was to support a major subset of Manchester’s site licensed application software portfolio so naturally I’ve made use of a lot of it over the years.

I have been asked to join a live discussion panel ​being put on by TimingResearch​. Each week, TimingResearch surveys a large group of traders to get their thoughts about current market conditions. TimingResearch then produces a report based on the survey.

Part 3 of this series demonstrated how to train a HMM on a toy model, this post will focus on how to actually go about modelling real life data. A trend following strategy will be developed for trading the S&P 500. In most machine learning classification problems you need a set of training data

The January Barometer is a fairly famous study from the Stock Traders Almanac. It says that “as goes January, so goes the year”. In other words, a positive January will typically lead to a positive year, while a negative January can be a warning. Let’s look at how the SPX has done for the

Scott’s Investments provides a daily Ivy Portfolio spreadsheet to track the 10 month moving average signals for two portfolios listed in Mebane Faber’s book The Ivy Portfolio: How to Invest Like the Top Endowments and Avoid Bear Markets. Faber discusses 5, 10, and 20 security portfolios that

We have been thinking a lot about winning streaks lately. Looking at charts of the S&P 500 index it is hard not to be impressed by how many positive monthly returns we have had since the “resolution” of the last full-blown Euro crisis in mid-2012. We wanted to gain some historical

So recently, I tried to combine Flexible and Elastic Asset Allocation. The operative word being–tried. Essentially, I saw Flexible Asset Allocation as an incomplete algorithm — namely that although it was an excellent method for selecting securities, that there had to have been a better way to

Reading old investment books is somewhat of a hobby of mine (I know probably need a better hobby). Glancing up on my bookshelf there are titles most have never heard of such as Once in Golconda, The Zurich Axioms, and Supermoney. I was flipping through another book new to me that I found when

We examine the relation between a measure of male CEOs’ facial masculinity and financial misreporting. Facial masculinity is associated with a complex of masculine behaviors (including aggression, egocentrism, risk-seeking, and maintenance of social status) in males. One possible mechanism for

Off to Bad Start. Down Januaries after 3 or more up years $SPY

See this (In Dec, it did not actually get triggered because it was down a little less than 1 pct) End of Month down 1 pct (ish) triggered 12/31/2014

We have corrected the Momentum Strategy winners list for January 2015 (to be held during February 2015). The third place winner was incorrect due to omission of a dividend.

Friday is the last trading day of January. The first day of the month is well known for having a seasonal bullish tendency. Interestingly, I have noted this tendency has not been prevalent over the last few years. This can be seen in the equity curve below.

Recently, volatility has been on the up. Generally, we associate rising volatility with a bear regime, but we also know there is a percolating oil shock. Is the volatility we see in the stock market broad-based, or is it the effect brought about by sharp the drop in oil prices (so related to the

Readers, I need your input for a research project. http://smeal.qualtrics.com/SE/?SID=SV_0JKTpsCsXIXnJ9H As many of you are aware, my primary passion is serving as the team leader for Alpha Architect. That said, I still conduct "serious" academic research with various colleagues in my

In this post, we will continue the work from the last post, RUT Iron Condor - Dynamic Exit Overview - 80 DTE, but this time we will look at the performance of several dynamic exits for the 66 days-to-expiration (DTE) RUT Iron Condors (IC). We are going to backtest dynamic exits on three basic IC

In part 1 and 2 of our volatility series I discussed a technique that I've developed to monitor broad market volatility with a Synthetic Volatility Index. Today I'm going to quantify our index by applying it to a liquid universe of equities as a simple entry filter. If volatility indeed

Small-caps hanging in there $IWM

Dual Momentum is a robust portfolio allocation tool. Relative 12 month returns are used to rank assets. Shelter is sought in a safe asset when 12 month absolute returns fall below a threshold. Gary Antonacci describes Global Equities Momentum using US …

This study shows that the recent trajectory of a firm’s profits predicts future profitability and stock returns. The predictive information contained in the trend of profitability is incremental beyond that provided by the profit level, and it is not subsumed by other well-known determinants of

The Data Science Institute at Columbia University and Bloomberg are holding a workshop on Machine Learning in Finance. The presentations look interesting and the price is right - just $30 if you have a valid student ID, or $100 if you don't. Some research articles are already available for

Trading stock splits is something that I have read about for long time but never researched. This article, A simple way to beat the market with stock splits, caught my eye and gave me the push to investigate the topic. This falls into the category of a topic I have heard a lot about that …

Suddenly business as usual for small-cap investing is in need of a makeover, thanks to a new research paper (a landmark study for asset pricing) that revisits, reinterprets and ultimately revives the case for owning these shares — after controlling for quality, i.e., “junk”. Cliff Asness of

Selloffs as strong as we saw on Tuesday have been fairly rare just ahead of a Fed Day. In fact it was the 1st time since October 2012 that SPY closed down over 1% on the day before a Fed Day. Below are results of all instances since SPY’s inception in 1993.

Calculations of daily Value-at-Risk (VaR) for any N-asset portfolio, as we have studied it already in Part 1, heavily depend on the covariance matrix we need to estimate. This estimation requires historical return time-series. Often negligible but superbly important question one should ask here is:

Strategies employing Risk Parity have been favored by mutual funds and other market participants the past few years. The attraction of risk parity strategies is the great story associated with the approach and the historical performance over the past 30 years has been favorable. However, there is an

It seems like every other month there is a new bitcoin exchange. For the purposes of trading research & backtesting it is important to have historical data across, at least, the most liquid exchanges. My list would be at least: USD/BTC bitfinex (15%) bitstamp (5%) coinbase (new, but likely to

We reviewed market correlations for eight core groups: (a) Equities, (b) Interest Rates, (c) Currencies, (d) Energy, (e) Metals, (f) Grains & Oilseeds, (g) Livestock, (h) Softs & Woods. Setup: Market Returns = ln(Close[n] / Close[n − LookBack]), where LookBack = 10 bars. Correlation window

In pre-election years, February’s performance generally improves with average returns all turning positive. NASDAQ performs best, gaining an average 2.4% in pre-election-year Februarys since 1971. Russell 2000 is second best, averaging gains of 2.1% since 1979. DJIA, S&P 500 and Russell 1000,

A couple of weeks ago I started a series of postings, all dealing with trading volatility ETNs / ETFs like XIV® (VelocityShares Daily Inverse VIX Short-Term ETN) and VXX (iPath® S&P 500 VIX Short-Term Futures™ ETN) and respective trading strategies. One of those strategies was DDN’s VRP

Factors driving this year's SP500 performance $SPY

The mild action on Monday did not trigger a whole of studies Monday afternoon but the one below was fairly compelling. It suggests that when SPY closes strong (in the top 10% of its range) but still only manages a small gain on the day, that the next day has a downside tendency.

Interviewing the Quants: An Inside Look With “Sanz Prophet”

European Surge

Investor mood may affect financial markets. Sports may affect investor mood. The biggest mood-mover among sporting events in the U.S. is likely the National Football League’s Super Bowl. Is the week before the Super Bowl especially distracting and anxiety-producing? Is the week after the Super

I prefer presenting new tools and concepts, but I know that there are a lot of readers that would like to see how they can be applied to creating strategies. So here is a very simple strategy that applies Percentile Channels from the last post to a tactical asset allocation strategy. The strategy

Traders and investors tend to operate in parallel universes, using different analytical toolkits and looking at markets from radically different perspectives. But sometimes there’s common ground. David Varadi’s recent investigation of what he calls error-adjusted momentum (EAM) to normalize

It has taken a long time to get to this point, but we are finally finished reviewing the backtests for our three basic starting structures for the Iron Condor (IC). The three basic starting structures backtested were: Standard: 10 put credit spreads, and 10 call credit spreads (72 total backtests /

So, Harry Long came out with a new strategy on SeekingAlpha involving some usual mix of SPXL (3x leveraged SPY), TMF (3x leveraged TLT), and some volatility indices (in this case, ZIV and TVIX). Now, since we’ve tread this path before, expectations are rightfully set. It’s a strategy that’s

We wanted to provide an update to everyone who signed up for a free copy of MKTSTK’s first book, Intro to Social Data for Traders by our very own Thomas Pendergrass. This book is intended for traders and investors that want to gain an edge on the competition by including social media and search