Thursday, June 19, 2014

Excite, Empower, Educate

“I love it when a plan comes together.”
-Hannibal Smith

Colonel John "Hannibal"
Smith of The A-Team
a/k/a George Peppard 
Nice quote, but my experience is more like, “The best laid plans of mice and men oft go awry,” or possibly Murphy’s Law, “Anything that can go wrong will, and at the worst possible moment.” In most cases, things do not go as planned. Every once in a while though, things fall into place and it’s great.

Take for instance some students in Tulane University’s Master of Management in Energy program. Bryce Robertson, Shanlong Zhou and Mingyu Liu were required to team up, analyze and research an energy industry issue for their Energy Projects class. This is when my phone rang. Bryce contacted me and said that they wanted to explore automated trading in the energy markets and that they want to use TT's ADL®, also known as Algo Design Lab, to do that.

To say the least, this was music to my ears. We partner with universities so that students can experience the markets in the same way our customers do, so I’m overjoyed to see them take advantage of everything we have to offer.

Their Strategy

The team wanted to trade December crude oil futures (CLZ3). They decided that instead of having a directional bias, they would watch the momentum of the market and trade based upon it. They chose the Relative Strength Index (RSI) to gauge momentum. The RSI is an oscillator that measures the strength of the market with readings between 0 and 100. Lower readings indicate that a down move is losing momentum (i.e., oversold), while higher readings indicate overbought conditions. They researched the crude oil futures market and determined that they would buy when the RSI dropped to 35 and sell when it hit 70. Since their strategy was short term, they wanted to keep it as simple as possible to avoid any latency issues.

They decided they would buy or sell 10 futures contracts at the market when conditions were met. An open position would be liquidated when a 10-tick profit was realized. The algorithm would monitor any positions and liquidate them when it realized a 10-tick profit. In the event this condition is never met, the position would be closed out at the end of the one-hour trading session.

Friday, May 23, 2014

Innovation Spurs More Innovation

Informatica recognized TT as an
Innovation Award Finalist in the
Embedded Applications category.
Last week Informatica hosted its annual customer conference, aptly named Informatica World 2014, where TT was recognized as an Innovation Award Finalist. I was lucky enough to attend the conference and accept the award on behalf of TT.

Although these types of vendor-sponsored awards are typically just marketing exercises for all involved, this was a different experience in my opinion. After speaking with various groups within Informatica, including their marketing team, as well as other conference attendees, it was obvious there was a genuine interest in and recognition of the innovation going into the development of TT’s recently unveiled next-generation trading platform, Nextrader.

I didn’t expect people to be very interested in us because we’re not a giant global enterprise like the typical Informatica customer. Informatica provides data integration software and services to a client roster that includes some of the most widely recognized companies in the world. Their products include the Ultra Messaging (UM) product suite, which we’re using in Nextrader. In retrospect though, I guess the response shouldn’t have been so surprising since the conference was heavily focused on cloud and big data. In particular, many discussions focused on the challenges of getting real-time data into cloud-based data warehouses; we faced similar challenges when designing the Nextrader platform.

UM is an innovative product in its own right. Designed to address the requirements of messaging middleware for financial trading platforms, the UM product suite offers very low latency, support for multiple transport protocols including multicast, shared-memory inter-process communication, guaranteed message delivery and efficient routing. By leveraging UM, TT can focus on delivering critical trading platform innovations to its customers.



Friday, May 16, 2014

20 Years of Trading Technologies

Look for the hashtag #TTturns20 on Twitter
for more about our milestone anniversary.
Today, as we celebrate 20 years of building trading software for our customers, I thought it was worth a look back at how the industry, and subsequently TT, has evolved over the past two decades and take a look at what’s ahead for our customers and TT.

On this date 20 years ago, we were founded in Frankfurt, Germany when nearly all trading on futures markets was conducted via open outcry. Access was extremely limited, and the ability for people to realize the benefits of listed futures, namely accurate price discovery and risk management, was limited to a select few.

When TT made Chicago its home a few years later, the floors of the Chicago Board of Trade and Chicago Mercantile Exchange roared. But as the trading community got comfortable with the concept of electronic trading, volume began to gradually migrate to the screen. A product we released in those early days, MD Trader®, had a huge impact because it was a radically different way to interface with the electronic market. It gave traders the ability to see and interact with the market with a level of confidence they hadn’t seen before and, in many ways, went hand-in-hand with the dramatic migration of volume to “the screens.”

Monday, May 5, 2014

Geographical Arbitrage

Have you ever wanted to buy something in one location to sell it in another location at a higher price? Imagine buying gold on CME only to turn around and sell it on TOCOM at a higher price. This type of trade is known as geographical arbitrage.

While there is risk in every trade, geographical arbitrage is relatively low risk. The faster you can execute and the more alike the underlying products, the better the arb. Gold as an underlying makes for an almost perfect hedge, as the gold quality is identical. This is not true for most other commodities.

One major factor here is the two products are priced in different currencies. A currency conversion is required, and this conversion value is not static like some other conversion factors used for spreading. For example, in this spread, I will use a static conversion of 1 kilogram equal to approximately 32.15 troy ounces. This value will not change during my arb, but the dollar-to-yen ratio will.

Let’s begin by calculating how to set up this trade. I will convert the yen-to-dollar using 6J on CME and grams to troy ounces. Below is a table that shows this conversion to get TOCOM gold priced in U.S. dollars and troy ounces.