Handling multiple professions all at once, and succeeding at ALL of them - that’s extraordinary. As is the story of EPAT alumnus David U. Ordiz. Besides being a CEO and a Professor, David is also a Trader. He credits his tremendous experience in algo trading, and how it has moulded him into the trader that he is today.
He continues to learn and evolve himself, adapting to this rapidly growing domain. Now, armed with the Certificate of Excellence from EPAT by learning Algorithmic and Quantitative Trading, he is closer to achieving his goals.
David shares with us his complete journey.
Hi David, tell us about yourself!
I am David U. Ordiz, I am 42 years old, and I live in the north of Spain with my wife and two kids. I have been trading and investigating the markets for more than 18 years.
I work as an algorithmic trader and Chief Executive Officer (CEO) at ATP Capital Management LLC. This is a Commodity Trading Advisor focused on the development of quantitative trading models.
I also work as a guest professor of "Systems and Quantitative Models of Algorithmic Trading", a postgraduate course offered by the Polytechnic University of Madrid (Spain).
How has the pandemic affected you and your work?
Unfortunately, because of this difficult situation, in Spain, as in many other countries, we are experiencing long periods of lockdown. It means that now I have even more time to study, research the markets and develop new strategies. In terms of algorithmic trading, the extreme volatility seen in the markets recently has served us to review and further tighten our risk control mechanisms.
Most of our strategies are intraday, and to minimize slippage and increase control risk, we had volatility filters in place that prevented opening trades during periods of extreme volatility. During the pandemic, we have added other new intraday filters that help us have even stricter risk control.
From a self-taught trader to a CEO, you’ve had quite an interesting journey. Can you tell us a little bit about that?
I finished my studies in electronics in 2002. At that moment I was very interested in the stock market, and I started to study as much as I could about it on my own. The more I learned, the more I realized that I wanted to become a professional trader. However, I was aware that to dedicate myself to it, I needed to acquire the proper training first.
For the next two years, I worked in the electronics industry. During this time, I continued my education and research in the financial markets, mostly self-taught. These were times of great sacrifice as I combined a full-time job with my market education, to which I devoted most of my available time.
In 2004, I quit my job to trade full time, managing the funds I had saved over the past few years. At that time, I had several non-quantitative trading strategies designed to trade Bund futures (FGBL). I was trading these strategies for a few months. However, the results were not as expected.
Since strategies were not behaving as expected and had a certain degree of subjectivity, I started to doubt their actual edge. At that moment, I saw the need to evaluate their potential by eliminating subjectivity, and that is how I got into algorithmic trading. From that moment on, I started my training to learn how to code, design strategies and evaluate them using historical data.
During the following years, I continued to research the market, dedicating a great deal of effort, and designing and implementing trading strategies, albeit with limited capital and trading only futures contracts that had little nominal.
From 2006 to 2008, I worked on the design and implementation of a portfolio of intraday trading strategies that worked on a basket of futures; Indices, bonds and currencies.
From 2009 to 2012, I offered this portfolio on Collective2, a social trading platform. The portfolio had a great evolution and was ranked several times among the top strategies of the moment. This was an important point in my trading career.
Because of the high number of subscribers, I could capitalize on my account enough to work with large futures contracts (e.g. the FDAX) further diversifying my portfolio. This, coupled with the favourable performance of my portfolio, allowed me to get high risk-adjusted returns in my proprietary accounts consolidating my trading.
In 2011, I co-founded Optimal Quant Management SL with my partners Andres A. Garcia and Carlos Prieto. It was a company that offered high-quality training on algorithmic trading.
And in 2013, the three partners founded ATP Capital Management LLC. It is a Commodity Trading Advisor specialized in managing portfolios of short term trading strategies.
Being an algo trader, how was your experience with EPAT?
It has been a very enriching experience in which I have enjoyed a lot, although I must admit that it has also been quite intense. I found the curriculum very well structured, with an appropriate balance between theory and practice.
I consider it a must study programme both for those who want to get into algorithmic trading and for those who are already professionally engaged in it.
Does it feel different to be a Professor yourself and learn from other Professors at EPAT?
There are many methodologies that can be used to trade within algorithmic trading, and specializing in one of them can take years.
In my case, I have specialized in the design and implementation of algorithms that aim to capture micro-trend or micro-anti-trend movements on index futures, bonds and commodities, and during the last years, I have gained more experience in the cryptocurrency markets.
EPAT involves highly experienced professors who have spent years specializing in other types of methodologies. Learning new methodologies from widely experienced professors is something of great value. Without a doubt, I would say that one of the most valuable points of the EPAT is the quality of its professors.
Finally, in the postgraduate course in which I take part as a professor, I also have the honour of working with other professors who have achieved excellence in specific methodologies. The fact of having shared my experiences, my investigations and having had long discussions with them over the years has contributed a lot to my professional growth.
Therefore, I consider it very important to learn and continue learning from widely experienced professors. EPAT offers an excellent opportunity for this.
Which feature of EPAT is your favourite?
I would highlight the quality of the contents and the support. I think the contents are of high quality and adjusted to what the industry currently demands. I especially liked the content focused on the design of strategies based on artificial intelligence.
I also found the lectures on options trading or momentum strategies excellent, which also introduced very interesting ideas for strategy design. Likewise, the programme has also helped me to extend my Python programming skills, which has contributed to speeding up my strategy design and evaluation processes in this language.
The programme’s support has also been excellent, and even on specific occasions, I have received help with topics not covered in the course. During the programme, I have worked in parallel in creating an interactive complex application in Python for private use that allows analyzing portfolios of strategies.
I would like to thank the faculty for the help I received in creating this application.
What message would you give to the individuals who wish to pursue algo trading?
I would tell them not to be intimidated and encourage them to go ahead with it. Algorithmic trading allows you to approach the market using different methodologies; Statistical Arbitrage, HFT, Trend Following, etc. And this makes it easy for each person to find a trading style that fits their personality, needs and goals.
In my experience, it is the most efficient approach I have found to trade. And over the years, it has proven to me, time and time again, its potential when done correctly. It does not mean that all designed algorithms will be profitable. Some will be and some will not, for a variety of reasons.
The point is to maximize the returns of winning strategies by applying efficient money management techniques for the duration of the inefficiency. Therefore, diversification is also essential in algorithmic trading and is one of its significant benefits.
Finally, algorithmic trading allows approaching the market with models that have been statistically tested on historical data and implementing strict money management rules. Two essential points increase the chances of survival in the long term. Therefore, go ahead with it.
Even with the pandemic and your multiple roles, you taking out the time to connect with us, sharing your journey, experience and some phenomenal tips for all the aspiring Algo Traders out there - means a lot. Thank you, David and Godspeed!
If you too desire to equip yourself with lifelong skills which will always help you in upgrading your trading strategies. With topics such as Statistics & Econometrics, Financial Computing & Technology, Machine Learning, this algo trading course ensures that you are proficient in every skill required to excel in the field of trading. Enroll in EPAT now!
Disclaimer: In order to assist individuals who are considering pursuing a career in algorithmic and quantitative trading, this success story has been collated based on the personal experiences of a student or alumni from QuantInsti’s EPAT programme. Success stories are for illustrative purposes only and are not meant to be used for investment purposes. The results achieved post completion of the EPAT programme may not be uniform for all individuals.