Joe Signorelli, founder of RCM-X, has a 20+ year history of providing algorithmic trading software and needed data to universities, as well as conducting student practicums through the RCM University Program. He is joined by industry participants and university professors in inviting other industry leaders to join in addressing the educational needs of the next generation. Let’s help students with better education on markets, in turn producing more prepared future employees and more knowledgeable future customers.
The Financial Trading Industry is facing a significant and far-reaching challenge, in that it has lost its long-standing training ground for future industry leaders. The move away from the trading floors to trading via computers and automated trading technologies has eliminated the most common chain of knowledge transfer that occurred between industry veterans and newcomers. The result has been to place even more demand on academia to produce work-ready future employees for the Financial Trading Industry.
Even with multiple successful collaborations between business and universities, there is much left to do – starting with the multiple hurdles for universities to overcome in accessing reliable data. Collaborations in other fields have had great success like the Caltech/Boeing Strategic agreement or the Nonwovens Institute (NWI) at NC State University (an Industry/University/Government cooperation).
The automation and computerization of the field brings with it a need for quick, easy, and free access to real market data to learn new and innovative ways to model financial transactions utilizing that data. Billion-dollar hedge funds can afford to pay full price for access to the data which fuels their trading models, but, too often, non-profit university programs can not.
Life in the Trenches
Prof. Olivier Ledoit of UCLA’s Masters of Financial Engineering program describes the environment as:
“more geared to academics who need to write a paper, not teaching traders how to make trades to test their theories”.
Prof. Ehud Peleg, also of UCLA’s Anderson School says that:
“learning to practice data analysis without data is meaningless”. While acknowledging that industry profit concerns related to data need to be respected, Prof. Peleg says “few if any education institutions can pay the fees to get good data access”.
Prof. Alex Lau of Carthage College says his biggest challenge is:
“Missing access and data. Personal experience with live data is the biggest disconnect between what universities can offer and what the industry needs.” He continues, “It’s hard to make the case that academia is not prepping people for finance in general. It’s the trading/investment, and specifically algorithmic trading skillset that is difficult to prepare people for without good access to data.
Brian Curcio of Rapunzl believes it is an even broader problem than one that just impacts finance majors. He states:
“The financial education opportunities for high school students in public education is virtually non-existent, and 45% of US citizens have never owned a stock”.
Curcio’s Rapunzl currently reaches over 4000 high school students with its investment education and stock-picking app, meeting a need recently outlined by the CME Group’s CEO Terry Duffy, who stated in a recent op-ed,
“The industry needs to take educational steps to put the world of finance on the radar of middle and high school students”.
Creating tools and apps which allow student access to real-time data can create not just the next layer of practitioners which plug into the industry as employees, but also create a base layer of people familiar with the derivatives markets to become future customers. But how do we make it easier for said students to access the world of financial markets?
To address the gap, schools need data, platforms, and greater insight into how the industry works:
- Open source data is improving in quality, but students and academic researchers still do not have access to high-quality, granular data with which to test new theories or familiarize themselves with commonly applied theories as an industry professional would in practice. Also lacking is the ability to test theories in real-time against live data, primarily due to the prohibitive costs associated with the data.
- Streamline access to high quality, historical data across all asset classes and time horizons with exchanges offering – easily applied for and quickly granted – data fee waivers for educational programs focused on teaching the next generation of market users.
- Open source technology provides valuable platforms for researching trading topics and testing trading models. But in practice, most professional trading firms utilize established, front-end trading platforms from highly-regarded industry vendors instead of the software used in the academic setting. Understanding the building blocks of trading systems can provide valuable insight, but not all researchers should have to rebuild the wheel in order to test how those ideas transfer to actual market conditions via the most commonly used front end trading platforms.
- Industry vendors should offer universities and/or students “Educational” versions of their platforms at little or no cost. This can provide the vendors with a large pool of users for feedback and testing, as well as provide some stickiness to their potential future client bases. Limited time offerings such as those provided during sponsored “trading challenges” is a good start, but those should be expanded outside of specified annual windows.
Insights into Industry Workings:
- Many careers and job functions in the financial and trading industry are not well known to students. Broad descriptions of “financial analyst”, “trader”, and “banker” accompanied by an adjective do not come close to providing an overview of the jobs available in the industry. Beyond career fairs and internships, the latter of which limits the reach based on employment constraints, the industry should find more and new ways to engage with the next generation. Firms should look to plan events with schools where employees taking a day to meet with students and discuss their careers. Young people are exposed to many industries much more directly than the financial industry, and that needs to change.
- School curriculums outside of specialized programs often focus on theory, equations, and topics that don’t always permeate in day-to-day work. These topics are important, but that doesn’t mean there shouldn’t be an opportunity for specific learning related to more practical topics that can help prepare students for their future careers. The MOOC model and expansion of learning modules in general across industries provides a template for new ways to engage young people on these topics.
- Firms should establish projects to create either learning modules or micro-courses based on their line of business. Certifications could be added to serve as resume material for students.
Why invest in the Future?
This problem causes enormous opportunity for both industry leaders and academia, as outlined by several professors currently running academic programs focused on financial markets and financial modeling of those markets.
Prof. Peleg of UCLA’s Anderson School, says:
“When you train someone to work with their system you get stickiness (e.g. Bloomberg). Make the data more useful and attractive by explaining how to use the data and it will drive more people to work with it.”
Prof. Morton Lane, Founder and Director of the MSFE program at the University of Illinois, considers himself fortunate,
“I’ve been able to leverage my industry connections to connect my students to significant financial data. This is not a widespread experience for my peers”. He continues, “What strikes me is that while traditional analysis certainly needs fresh financial data, the new Data Analytic techniques of Machine Learning and Artificial Intelligence desperately need full financial data. Students in that area are learning techniques on generic data sets. We will only unleash the power of AI and ML in finance if we get students to study on real data. Financial data is different.”
Christian Oesch, PhD remembers:
“Getting my hands on Strategy Studio was an important step on my journey from a researcher to a practitioner. I originally used it to verify the results of my own simulation of a high-frequency trading strategy. Doing so, I learned a lot about the US exchange system, the market structure, the different feeds (TotalView, UQTF, UTDF, SIP, and what not), latency, as well as order execution and hidden liquidity. These are things that are usually ignored in academia, but are of great concern in the real world. While I was lucky to have some Nasdaq equities data at my hand from (University of Basel), getting access to tick data poses a big problem for researchers. Usually getting the data is very expensive and doesn’t fit into a tight research budget. Having a point of entry for research on real-world financial data and tools would make it a lot easier for academics to do their work. Once you have academics researching with real data more frequently, they will bring in Masters and PhD students that become valuable job market prospects.”
Solutions aren’t just for future job seekers at the university level. There’s a broader reach that can be assisted by more collaboration between industry and academia. This is evidenced by Rapunzl Investments, a technology company formed by 20 year olds that is currently reaching 4000+ high school students. They have conducted over 11,000 trades using their Rapunzl app, in addition to monthly trading contests to educate students on the concepts of trading.
Arne Duncan, Former US Secretary of Education says of Rapunzl’s approach:
“Our country needs more innovative approaches like Rapunzl that aim to tackle financial illiteracy and close the achievement gap.”
Joseph Signorelli of RCM-X concludes:
“The industry has a responsibility to help train the next generation of Trading Industry leaders. RCM is committed to supporting this effort through the RCM University program, partnering with like-minded industry groups and serving as a focal point for discussion with other industry leaders.”
The signatories below invite serious participation and concrete ideas that will provide universities and their students, with the solutions to address the gap in data, platforms, and greater industry insights noted in the specific needs above, and ask for your support in petitioning industry leading exchanges, vendors, and firms to further bridge the gap between industry and academia.
Please add your signature to this change.org petition to highlight how important this is to both sides of the equation. Together, we can make real change and help arm the next generation with the skills they need to succeed.