Risk. The only ingredient of life that makes us growing and pushing outside our comfort zones. In finance, taking the risk is a risky business. Once your money have been invested, you need to keep your eyes on the ball that is rolling. Controlling the risk is the art and is the science: a

We have updated the details of the Reversion-to-Value (RTV) Model and the Real Earnings Yield (REY) Model of the U.S. stock market to incorporate data for 2014.

Again, before starting this post, I’d like to inform readers that the book Quantitative Trading With R, written by Harry Georgakopoulos, with contributions from myself, is now available for order on Amazon. Already, it has garnered a pair of five-star reviews, and it deals not only with

Gross margin peak for INTC spells trouble for Semis $SMH

Collectively, the Wizards added another good month to an already very good 2014 (the come-back year for trend following). A near-100% of positive results for the year, with an average just shy of +25% and a handful of strong performers.

In July 2012 I published a strategy about an end of month strategy in S&P 500. Here are the criterias: Entry: Day 29, 30 or 31 of the month must be negative. Then enter on close. Exit: Two successive positive closes in a row, OR SPY hits a 1% target. (no stops). Here are the results from 2005

Before I get into the meat of this article, I wanted to share some of my thoughts regarding this blog. Over the past few months the site has undergone many changes in the front and back end. The site has a more professional theme, mail subscriptions have been moved to a third party with more

Hi everyone! I am happy to announce that our book shipment has arrived and Quantitative Value is back on the market at $19.99! We ordered 760 copies, but our daily sales have really accelerated as of late, so don't wait to grab a copy. David wasn't smiling this much when we were hand

This is a test of a strategy from Ilya Kipnis of QuantStrat TradeR for trading VIX ETPs like XIV and VXX. Ilya provides a framework for testing the robustness of a given set of trading parameters. I encourage you to read Ilya’s piece, but that isn’t the subject of this post. Here I test the

I’ve been doing a lot of writing about Momentum Based ETF Rotation Systems lately and for good reason. The systems are low maintenance and have historically provided a good return in a variety of market conditions. In this post we’re going to look at backtest results for the Schwab Commission

One thing that stood out about Wednesday’s action was that the market closed down but still enjoyed a strong reversal of the lows. In the study below I combined the multi-day pullback concept with the fact that the market saw a relatively strong close.

One area of recent interest for me is trading rotational strategies on a monthly timeframe using S&P500 stocks and ETFs. Areas of exploration include Momentum and Dual Momentum. Recently I came across The Secret to Momentum is the 52-Week High??? on Alpha Architect, a blog I highly recommend on

Predictable variation in equity returns might reflect either (1) predictable changes in expected returns or (2) market inefficiency and stock price "overreaction." These explanations can be distinguished by examining returns over short time intervals since systematic changes in fundamental

Notes From Academia: Exercise Boundary Violations in American-Style Options Here is the link to the research paper - Exercise Boundary Violations in American-Style Options: The Rule, not the Exception Abstract: An exercise boundary violation (EBV) occurs when the current bid price for an American

In this post we will look at the equity curves for the three versions of the RUT "no touch" Iron Condor (IC) trades at 80 days to expiration (DTE). The three versions tested were: Standard: 10 put credit spreads, and 10 call credit spreads Delta Neutral: 10 put credit spreads, and from 5

I recently read an article which showed how to download Option Chain data from Google Finance using R. Interestingly, that article appears to be a close adaption of another article which does the same thing using Python. While playing around with the code from these articles I noticed a couple of

This is a follow up to the posts here and here from the always excellent Trading the Odds. We’ve covered TTO’s work previously when we looked at their variation of a “VRP” strategy, comparing implied vs historical volatility to trade VIX ETPs like XIV and VXX. In these new posts, TTO looked

Well.. better late than never: The solid winner this year is: R vs MATLAB (Round 3) Followed by a far second Mom, are we bear yet? (2) and third: Detecting bubbles in real time And my own personal favorite for the year:

Crude oil has a tendency to bottom in mid-February and then rally through July (highlighted in yellow in second chart below). It is that early February low that can give traders an edge by buying ahead of a seasonally strong period. Going long crude oil’s July contract on or about February 13 and

The first professional book on Python programming is coming up very soon! Designed around Quants, Risk Analysts, and Algorithmic Traders in mind, Volume I of Python for Quants will deliver all what is essential to start coding in Python straight away! For more details and sneak peek click here:

Stocks and bonds are negatively correlated. Translation: they must move against each other most of the time. Because intuitively, stocks bear higher risk than bonds so investors go to stocks when they want to take more risks and flee to bonds when they feel a storm is coming. Plus the numbers tell

Over the past thirty-two years, since 1983, the S&P 500’s performance during January’s option expiration week has been essentially a mixed bag. Monday has been up 18 of the last 32 years, Friday is similar; up 16 and down 16, and the entire week has been down roughly three times

Financial intermediaries trade frequently in many markets using sophisticated models. Their marginal value of wealth should therefore provide a more informative stochastic discount factor (SDF) than that of a representative consumer. Guided by theory, we use shocks to the leverage of securities

Our first guest for the “Interviewing the Quants” series is Vangelis Maderakis. Many of you probably know him as Sanz Prophet through the eponymous blog (sanzprophet.blogspot.com). Recently, he became a partner at Logical Invest, a successful business dedicated to logical, rules based

Scott’s Investments provides a free “Dual ETF Momentum” spreadsheet which was originally created in February 2013. The strategy was inspired by a paper written by Gary Antonacci and available on Optimal Momentum. Antonacci has a new book out, Dual Momentum Investing: An Innovative

In this post we will look at the backtest results (summary statistics) for the three versions of the SPX "no touch" Iron Condor (IC) trades. The three versions tested were: Standard: 10 put credit spreads, and 10 call credit spreads Delta Neutral: 10 put credit spreads, and from 5 to 10

This is the first article in what will become a set of tutorials on how to carry out natural language document classification, for the purposes of sentiment analysis and, ultimately, automated trade filter or signal generation. This particular article will make use of Support Vector Machines (SVM)

Different commodity including some volatility and bitcoin futures settle to an average value. For example VSTOXX settles to 1 minute sampled average value of the index in the last half hour of trading, Bitmex XBT/USD futures settle to 1 minute sampled average value of the last two hours of trading,

Simply looking at a graph of a VIX ETP like VXX or XIV doesn’t tell us much about the underlying forces at play in the VIX complex. ETP prices are merely the end result of the relationship between these underlying forces (which is why traders shouldn’t rely too heavily on price to

First off, before beginning this post, I’d like to make my readers aware of the release of a book that I contributed almost an entire chapter for. Quantitative Trading With R is a primer on quantitative trading in R written by Harry Georgakopoulos, one of Chicago’s better quants. I

Research in experimental psychology suggests that, in violation of Bayes' rule, most people tend to “overreact” to unexpected and dramatic news events. This study of market efficiency investigates whether such behavior affects stock prices. The empirical evidence, based on CRSP

In a post on LinkedIn I referred to the concept of CrashMetrics and how it can be used for portfolio protection. It’s a simple approach to the management of extreme risk that works rather well. It can be summarized as “CAPM for crashes”. Here’s how it works. Let’s

ear cycle for S&P500 and the top graph shows mean and median for year 1957 to 2014, the second graph is from 2000 to 2014. The graph is marked with year trading days from 1 to 249.

I have shown the study below a several times in the last year or so, but not since September, and the employment night hot streak remains strong. The overnight futures market has been loving the Employment Report since the summer of 2012. The Employment Report is released at 8:30 AM Eastern

This is a follow up to a piece from the always excellent VIX & More: 2014 Had Third Highest Number of 20% VIX Spikes. V&M finds, as the title suggests, that 2014 exhibited the third most 1-day VIX spikes of at least 20% since 1990. In this post I look at a different definition of VIX spikes

As some of you know, I recently began trading two monthly ETF Rotation Systems. One is a Basic ETF Rotation system that trades a diverse group of markets and the other covers similar markets using Schwab Commission Free ETF’s. The Basic System is intended to take the place of the ETF Portion

It’s that time of year again. Yup, that jolly, happy time of year when the soothsayers of Wall Street start trumpeting their views on what’s going to happen in 2015, and how to position portfolios to profit. Esteemed Wharton professor, Jeremy Siegel, author of the permabull bible, Stocks for the

By Yang GaoEstimize is an online-community utilizing 'wisdom of crowds' to offer intelligence about market. It contains a wide range of crowd-sourced estimates from over 4,500 buy-side, sell-side and individual analysts. Studies (from Deustche Bank and Rice University among others) show

We enjoy collaborating on new research projects simply because nobody has a monopoly on interesting ideas. Where our expertise in asset allocation, tactical strategies and portfolio optimization methods might prove useful, we are always open to discussing new and ongoing research.

There were a number of Quantifinder studies yesterday that looked at SPY and/or SPX making short-term lows, closing down 3+ days in a row, and/or leaving unfilled gaps down. The study below it combined all of these ideas.

As I discussed last week, the time between Christmas and New Year’s tends to be a very strong seasonal period. (And even through the 1st or 2nd trading day in January). Wednesday was only the 11th time since 1960 that SPX fell greater than 1% on a day during this week.

I’ve been posting and updating the “Twas 3 Nights Before Christmas” study on the blog here since 2008. The study will kick in at today’s close. This year I will again show the Nasdaq version of the study. While all the major indices have performed well during this period, the

One of the best months of the year for our Trend Following Wizards. Not so surprisingly after the strong performance of the State of Trend Following Index (nearing +10% return for November).

From my post on Heikin-Ashi Charts, another researcher wrote Luck: The Difference Between Hired or Fired about how luck of the draw could account for the difference in returns depending on the starting date. This is a completely valid question. Are three better returns for a strategy in a particular

I’ve written an awful lot about the Quantifiable Edges Capitulative Breadth Indicator (CBI) here on the blog. The CBI moved up from 8 to 12 on Tuesday. While 10 has been a strong indication for a short-term bounce, 11 or higher has been a reliable indication for the

When we left off in Part 1, we promised to examine how select Global Tactical Asset Allocation products stack up against the Global Market Portfolio from the perspective of several performance measures – particularly Sharpe ratio, alpha and information ratio. Without further adieu: