Quantocracy’s Daily Wrap for 05/12/2015

In a previous article I outlined the best degree courses to take in order to help you get a job as a quant. I also mentioned that to discuss the best UK universities was an article in itself. This is that article! Coincidentally, the QS World University Rankings for 2014/15 have just been released and some of the best UK universities have made it into the Top 10. While rank

We dont talk too often (because we dont use them) about traditional technical analysis indicators. We have nothing against them; its just that we have our own methodologies and processes that work for us. One indicator we do like to keep an eye on is the ADX, or Average Directional Index. It is essentially an indicator of the strength (or lack of strength) of the prevailing trend ove

Material improvement $XLB

A while back I got over my addiction to Elliott Wave analysis. I finally realized I needed help and joined a five wave, er, step program. But some obsessions still linger. As an admitted "systemaholic" ("Hi, my name is Jay") I am always on the lookout for new ways to make money without thinking. That's actually not quite a fair statement. With a trading system you do your

Many recent articles discuss rising rates with a focus on how to weather them along with some predictions of when they will occur and how much they will rise. Duration is a common theme among the articles since it quantifies how much a particular bond is likely to lose when rates rise. We've written many blog posts in the past about duration (for instance: this and this), and earlier th

Following up on my post The Relationship Between Stocks and Bonds, which outlined why it is probable that stocks will outperform Treasury Bonds over the next 10 years, let's take a look at what appears to be another expensive area of the bond universe… high yield U.S. corporate bonds. High yield bonds: Where's the high yield? As the right-hand chart be

Building machine learning strategies that can obtain decent results under live market conditions has always been an important challenge in algorithmic trading. Despite the great amount of interest and the incredible potential rewards, there are still no academic publications that are able to show good machine learning models that can successfully tackle the trading problem in the real m

A recent paper by Cam Harvey and his co-authors on the statistical validity of many so-called finance anomalies has attracted a great deal of attention in quantitative finance crowd. It seemed worthwhile to discuss the implications of the paper with one of our favorite quants, Wes Gray of Alpha Architect and manager of the ValueShares US Quantitative Value ETF ($QVAL) and the ValueShare

Quantler is an online trading system development and analysis platform, that uses templates to (co-)create new algorithms. You can develop your own templates or reuse existing ones. With Quantler, you can test your ideas quick and easy. Entry Entry templates tell us when, where and how we enter the markets. Timing is everything, efficiency is of vital i

I have been look at equities a bit of late, I am particularly interested in ranking a universe of equities for low frequency manual trading on a weekly or monthly basis. Every period I would rank each name on a bunch of different factors, then invest in the highest ranked ones for that month. I was initially working in R but the code grew unwieldy, and I want

I have disavowed myself from technical analysis. Life's too short. Similar to Saruman however, the lure of more power is drawing me perilously close to an ancient and dark evil. To paraphrase Nietzsche, When you take a long gaze into the financial blogosphere, the blogosphere also gazes back into you Prices are used in

Scotts 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 Strategy for Higher Returns with Lower Risk. If you want to see how he applies Dual Momentum t

Improving Neural Networks by Preventing Co-adaptation of Feature Detectors

DART: Dropouts meet Multiple Additive Regression Trees