Newsletter 2019

1. What advice would you give to students about to enter the field?

I would advise students to pick up as many skills as they can while they are still students.  They will certainly have to learn other new things later (and should be prepared for that), but it is easiest when you are still a student. As for specific topics, clearly the traditional OR skills in optimization and stochastic models are necessary, but increasingly these must also combined with skills in handling data (and writing code) for computation, and in statistics, data analysis, and machine learning.  For financial applications, it is also necessary to have a solid background in economic theory and of course financial economics.

Beyond getting these broad skills and then becoming extremely deep in a topic area for a dissertation or Master's concentration, I would advise students to stay flexible.  They may find that a different area offers more potential or opportunities to develop. They should be open to following that path, whether in a different industry position, research direction, or career choice.

2. How has your involvement with INFORMS impacted your career?

I have been fortunate to have gained from my involvement with INFORMS in multiple ways.  My first professional conference presentation was at a regional INFORMS (then ORSA) meeting that I became aware of shortly after I joined as a student member. For meetings since then, I've organized many tracks and sessions (including the plenary speakers at the next Annual Meeting in Seattle) that have helped me learn about the latest developments and to stay current with the latest interests. Among communities, I particularly valued my service as a regional chapter officer where I was able to connect with industry members that I might otherwise have not met. I've also gained insight into the range of the OR field through my service with sections (including the section on finance), societies, and fora (a group designation I launched as vice president of subdivisions).

Clearly, INFORMS publications have had an enormous impact on the visibility and recognition of my work and my research has also benefited from my service to publications as a reviewer, editorial board member, and now editor-in-chief of Operations Research.  Finally, having the opportunity to serve the profession as president of INFORMS gave me both professional recognition as well as much deeper appreciation of the accomplishments of the entire field.

3. What value do you think that the section on finance can provide to members?

The section provides members with a sense of community and a variety of ways in which members can expand their knowledge and appreciation of OR in finance as well as opportunities to present their work, receive constructive feedback, and gain professional recognition.  The talks in sessions at the annual meeting certainly provide these opportunities, but informal discussions that may follow a session can often be even more rewarding.  Participating in the best student paper competition also can provide valuable feedback even for papers not selected as finalists for presentation at the annual meeting.   Regular communication through the newsletter will also help build the sense of community and can help keep members current.

4. What research you have been involved with do you think has had the biggest impact or you are the proudest of?

My work on developing methods for solving dynamic stochastic optimization problems has no doubt had the greatest impact of the work I have done. I am particularly proud of the applications of the nested decomposition approach I developed at several financial institutions for asset-liability management.  In the energy sector, I am also particularly heartened by the impact these approaches have had in electric power and particularly hydro resource planning.  Beyond these methodology contributions, I am also especially pleased of the role that my research has played in raising appreciation of work at the interface of operations and finance.

5. What is the biggest change you have seen in the field of Finance over your career?

In the finance field overall, the importance and centrality of rigorous empirical analysis has probably been the greatest change that I have witnessed over the years.  While empirical work was always important, the availability of data and the capabilities of new methods and tools have certainly raised the bar in finance considerably.  Clearly, there will continue to be a role for new theory, pricing methods, or  portfolio and trading approaches, but the demands for empirical validation seem to continue to grow.   While this may not be a central skill for OR, I think OR researchers (and even more so practitioners) need to be aware that strong empirical demonstration may be necessary to ensure that their work gains the recognition it deserves.

6. How did you become involved in the field of Finance?

I became particularly interested in finance when I learned that people in the financial industry were implementing the methods that I had developed.  I felt compelled to learn about the models that they were building and discovered that I needed to deepen my knowledge of finance to appreciate the details that went into those models.  This then drove me to develop classes to teach others with mathematics and engineering backgrounds about the subject and eventually to launching a degree program in financial engineering when I was at Michigan.

7. What directions do you see the field moving into the future?

As I noted earlier, I see increasing uses of large (often unstructured) data sets and tools from artificial intelligence and machine learning across the field of finance and particularly at the interface of OR and finance.  I think this quantitative drive will come at the same time with greater appreciation of the role of human behavior (which may not always agree with standard economic models). I would envision considerable research opportunities into exploring relationships across markets driven by models of behavior and strategic interactions. 

8. What research questions most interest you right now?

A fundamental question that I have explored since pursuing my PhD (and which was the foundational question that inspired my thesis supervisor, George Dantzig) is whether we can devise an efficient computational method for solving dynamic optimization models under conditions of uncertainty.   From some theoretical computational viewpoints, we know this is impossible in all imaginable cases (unless perhaps P=NP), but can we devise something that seems to work quite well for the vast majority of cases (and better yet show this rigorously) is still an open question.  In terms of specific (but related) financial questions, I would like to define what fundamentals drive prices of assets and whether we can identify those most basic drivers. We may need to answer the first question to fully answer the second, but I hope to make some headway in both directions.

9. What do you think INFORMS Finance should feature that is currently missed?

I think it would be ideal if INFORMS Finance could have more connection with the traditional Finance community. I think this is a challenge since each community has its own conference and focus journals, but some initiatives to develop stronger ties would be of value. 

10. What should be the topics in Finance that the OR community should focus on in the next few years?

I think the general areas of data analysis and uses of machine learning as noted above should be important areas of focus.  I also think other Fintech topics such as blockchain applications could be of particular relevance for the OR community. The proliferation of ICO's, for example, represent a ripe area in which OR researchers can contribute.

11. How are the job prospects different between students with a master vs PhD?

The biggest difference clearly in terms of job prospects is that PhD students are also of value to academic institutions.  OR PhD students are fortunate (especially those with finance skills) that they can often fit in many departments in schools of mathematics, engineering, computer science, or business.  For industry positions, clearly the lines between Master's and PhD student opportunities start to blur.  Research departments in industry would still be dominated by PhD's but often also have opportunities for Master's students.  In other areas, Master's students would often have equal opportunities to PhD students.