“Meet our Financial Math Alumni Series”- Meet Sai Raman

"Go beyond the program!" -Sai Raman

Sai Raman graduated from the Financial Math Program in May 2015. He is currently working as Business Controller at Credit Suisse, in North Carolina. Sai did his Bachelors in Mathematics in India before completing his Masters in Financial Mathematics at NC State. Sai had the opportunity to do a summer internship at GE in Australia and was an active student participating in several musical events at NC State.

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Why did you decide to get a Master’s Degree in Financial Math program at NCSU?

Sai: I completed my Bachelors in Mathematics and was planning to further my studies. I felt a combination of Computer Science, Finance and Mathematics would be my area of interest. I did some research on graduate programs that combined those focuses and decided Financial Mathematics was the right direction to head in, and I liked NC State's program.

Did you do an internship while you were in the Financial Math program, and if so, please tell me about your internship experience?

Sai: Yes, I did an internship at GE (General Electric) in Australia. My internship work combined mathematics and statistics. I built metrics tool to calculate the online time delivery for GE equipment for an oil project. I used Data Manipulation techniques and Statistical analysis models to build a dashboard that could give desired output in 30 seconds.

It was a great learning experience to work for a big company like GE. The internship helped me to enhance my professional business skills such as improving my communicational skills. I am able to carry the knowledge and experience into my current role at Credit Suisse.

Can you explain more about your current job?

Sai: I work as a Business Controller at Credit Suisse. My job is focused on reviewing the P&L (Profit & Loss) after every trading day. Generally, for every single trading desk, there is a control team behind it and I belong to Emerging Market Group trading risk. We review the trades of the previous day, see the impact of P&L for every market move in the trade and calculate the risk based on the linear approximation for a portfolio and then compare to the actual P&L. Then we check how accurate our models are and see if any assumptions were
considered wrong. Then correct the wrong assumptions and re-do everything. Mostly MS-Excel is used for the calculations.

Sounds interesting, can you tell us a little more about your job at Credit Suisse?

Sai: The job is rewarding and challenging. The first two weeks we had a training program from all new employees of Credit Suisse from New York. However, the job forces us to continually learn daily with new challenges and situations to problem solve. Dealing with P&L of big amounts daily makes my work interesting. There will be days where we see millions of dollars missing in the accounts, few due to some technical reasons and few due to real market reasons. It is the Business Controller's role to come into the picture and resolve the issue. Sometimes the work becomes very hectic, especially the month end and first 10 days of the month. Work day can start in the morning 8.30 and end by 8.30 in the night. The rest of the month the work-load is normal.

Tell us about the interview experience with Credit Suisse?

Sai: The interview went quite smoothly. I attended an information session held by Credit Suisse in our one of the Friday Seminar classes, Later I went and spoke to the people and applied online for a few finance jobs. The following week, I got a call from Credit Suisse asking for my work interest and was invited for an on-site interview. There were two rounds of interviews, mostly testing my knowledge and experience from my resume.

In your opinion, what courses are more important and which concepts are more useful at your current place of work?

Sai: In my perspective, all the courses are equally important. Financial Mathematics and Computational Methods in Finance are the courses that I am currently applying at my job. I personally like these subjects very much and I have always paid special attention to those courses. I did a project on pricing barrier options using a single algorithm; that was a very good learning experience.
Solid understanding of Financial Mathematics (MA 547) helps a lot in the Computational Finance course (ECG 766).

What are the suggestions you want to give for the current and future students of Financial Math?

Sai: Go beyond the program. The program gives you the foundation and direction, but take it one step further. Take the FRM exams. Do projects. Apply for jobs with plenty of time and apply for many positions as the job market is very competitive. Network and get connected to Human Resources and recruiters through
LinkedIn.

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Thank you Sai!

“Meet our Financial Math Alumni Series”- Meet Yi Chao

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"Speak to people…Increase your network!"- Yi Chao, May 2015 Graduate

Yi Chao recently graduated from the Financial Math program in May 2015. She was an active student in our program as a Career Ambassador and Intern. While studying hard to be among the top of her class, she also took full advantage of all career development activities. Her hard work paid off as she received a full-time job opportunity to work at Maxpoint.

Yi Chao is currently working as a Product Analyst at Maxpoint in RTP (Research Triangle Park) in North Carolina. We are glad she took the time to share her experiences and advice to incoming, current and prospective students. Her interview below- by Preethi Kankanala

Why did you decide to get a Master’s Degree in Financial Math program at NCSU?

Yi Chao: I received a Bachelors in Applied Mathematics in China. While I was studying I always wanted to do something that can be applied to daily life situations. After taking courses Microeconomics, Econometrics and Game- Theory, I felt finance was the best direction for me to take as a career choice.

I was fascinated by real-time data, the movement of stock prices and how the daily market situations affect the price. With the Mathematics background I had, Financial Mathematics was the best field to choose.

How did the Financial Math program prepare you for your job?

Yi Chao: I took mostly statistic courses as I was interested in analyzing data. Also, I enhanced my programming skills after coming here. I did not have much programming experience before coming here, but after the Monte Carlo class, the assignments and projects in the course helped me improve my programming skills and I ended up with an A+ in that class.

Also it is very important to concentrate on all the courses equally, because you never know which one will help you more during the job search, so I put equal effort in all classes.

How was your experience with your summer internship at Altrius Capital?

Yi Chao: Working with Altrius Capital Investment company gave me a great hands-on experience on valuation and real world concepts behind trading. My project at Altrius included doing market research for a fixed income market trader. I used financial statements & balance sheets to analyze the different companies, and give suggestions to the trader.

The other project I worked on is more quantitative, using Morningstar software we transferred the data to excel and analyzed the data of public companies.

Can you explain more about your current job? And how is internship helping you for this job?

Yi Chao: I am now working in Maxpoint as a Product Analyst. My job mainly consists of market research, analyzing data, try to get insights from it and improve our product. My project is mostly done in Python. We use statistical models to analyze the data, find target users and serve advertisements.

From the surface, my present job and the internship projects seems to be different but at the core they are almost the same. The thinking method is similar by using quantitative methods to do research and solve problems.

Important to note, at work we give lot of presentations. My internship allowed me to enhance my soft skills and learn how to communicate better. I am now more confident in giving presentations in my current job.

What are the different position you have applied for the full time and how did you apply for those?

Yi Chao: I applied mostly for the Quantitative jobs, Risk Management and Data Analyst roles. Most of the jobs I have applied were through LinkedIn and Glassdoor. However, besides applying to jobs online, it is also very important to follow up with the application through the respective HR manager or with any alumni working in the same company (If there are any).

How did the career fairs help you?

Yi Chao: Career fairs gives you a lot information. You will get to know the companies and the different positions they offer. It is the best place to network and market yourself. Many job requirements ask for 3-5 years of experience in any of the programming languages, but if you show you have great analytical and problem solving skills and learn quickly, there is a chance they may hire you. It helps to be confident in the skills you have.

What are your suggestions for the current and future students?

Yi Chao: The main advice I would like to give to the students is, network with the people, do not let your fear or inhibitions to take a back step on this. There is never a harm if you speak to people, only good happens. Keeping aside about job, you will get to know lot of information from their experience. Also contact people through LinkedIn. I talked to lot of Financial Math Alumni and learned a lot from them. I also got a few interview calls because of my network.

Grasp every opportunity to talk to people, professors, alumni and people coming from industry. Keep looking for what you are interested in because that is what gives you the passion to learn or work. Push yourself to be the best you can and then you will know your potential.

Regarding jobs and internships, make sure you start applying as early as possible and make a very good resume, and be clear on each and everything that is written on your resume.

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Thank you Yi! We appreciate your time and advice.

Meet our Financial Math Alumni- Brandon Blevins

Meet Brandon Blevins, Product Controller at Credit Suisse in New York City. Brandon graduated from the Financial Math program in 2009. We were glad to catch up with him in Manhattan and learn about his job and life in the city.

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Part I: Education & Job Background

1) How did the program prepare you for your job?

Brandon: The Financial Mathematics program gave me the background about quantitative finance. It provided me with the basics on how financial assets work, how models applied to assets, and how interest rate curves work.

2) Describe your job.

Brandon: Currently, my job is Product Controller at Credit Suisse. The main point of Product Control is to ensure that the Profit and Loss (PL) generated by portfolios reviewed gets to the general ledger of the bank, which then is reported to shareholders and board members who make financial decisions based on Credit Suisse earnings.

My day involves reviewing risks on books, making sure risks are within tolerances, and P/L are in line with the risks. For example, suppose you have net Vega on a single position of $100K. The volatility moved on the position by 100 basis points and you did not make or lose any money on that position. Did that make sense? It is the Product Controller’s job to make sure it does makes sense. If something is wrong, we flag it. We make comments on any big moves, big losses, and provide reasons why money is lost.

Part II: Analytic techniques

3) Does your company use stochastic models? If it does, what kind of models are used? Is there any reason for choosing these models?

Brandon: We use Black-Scholes formula to build up implied volatility curve. Options with the same underlyings and maturity but different strike prices have different implied volatility. The same options with different maturities may also have different implied volatility. Thus, implied volatility is a function of strike price and maturity, and we can define a volatility surface. We also use jump-diffusion models to model certain protocols. For example, is there a big court case coming up in the next few years for a specific company, or does this specific company have any big products coming out in a few years? That is where jump-diffusion comes into play.

Part III: Risk management

4) How does the crisis and the regulation policies enacted afterwards affect the behavior of your company?

Brandon: Radically. Since then, many parts of businesses have been shut down. Interest rate products have been drastically cut by 90%, because the Feds have kept rates low. There is a huge push to move everything onto exchange and standardize all products. Any flow business has been hit hard such as the credit default swap (CDS) market. Junk bond market has been on fire lately. But it did excite the mortgage back portion.

5) The goal of risk management is to achieve a balance between returns and risks. Thus, with lots of capitals and human resource spent, risk management may, to some extent, reduce a company’s profits. Now suppose you are a leader of a financial institution. Driven by the motivation of maximizing the profits, will you pay enough attention for risk management?

Brandon: Lead traders will listen to risk management and work in conjunction to set risk limits and VAR measures. If the limits get breached, everyone will look at it.

6) You used to be an interest rate derivative analyst, but now you are focusing on equity derivatives. So in your opinion, what is the difference between the interest rate derivative market and the equity derivative market?

Brandon: Interest rate market and equity derivative market start to look alike with low volatility. The bond market did very well in the past, but now it hover sideways because of the flat yield curve environment. Equity market is experiencing the same problem. Rates are not moving and are low.

Part IV: Suggestion & Advice

7) What skills set are important to succeed in your field? And what kind of courses will you recommend for current students to take.

Brandon: Networking! Make sure people like you, so they will recommend you. I landed all of my jobs because I knew people who worked for companies that I wanted to join as well. I got the interviews because people recommended me. Therefore, students should get out there, meet people, talk to them, learn from them, make relationship with them, and then they will recommend you for jobs. Just get connected! People can put you in positions to succeed, and give you opportunities to help you succeed. If they like you, they want to you succeed.

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Thank you Brandon!

Meet our Financial Math Alumni- Coffee chat with Albert Hopping- Part 2

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Part II: Analytic techniques continued...

6) Do you believe the future movement of the market data is, to some extent, driven by the models used by major financial institutions, even though these models may not be correct?

Albert: Does the market move because the model is assumed to be correct? I would say yes. Consider the market crash in 1987. Prior to the crash, there was no “volatility smile,” but there was after the crash. The market had actually been acting correctly, according to the model, until they realized the model made terrible assumptions. The market moved much more than their model implied. One event is meaningless; however, this highlights an incorrect model driving the market.

For a more current example, look to the way mortgages were priced before the recent mortgage bubble. Banks priced mortgages with the assumption that housing prices wouldn’t fall. The entire market priced that way because that was what everybody else did; it was group think. They used this assumption because the price had never gone down in their historical data set. Models are only as good as their assumptions. Could somebody have built a better model and actually predicted the housing price collapse? Yes, it could have been done and a few people did it.

Unfortunately, in a time of high earnings, it is easy to ignore risk. Risk is especially underweighted when quarterly earnings are prioritized over long term security. I feel that compensation packages are lagging the culture shift at most companies. This disconnect leads people to act as individuals focused on their personal bonuses rather than acting as representatives of their company. Further, a system which provides bailouts for bad behavior begets that bad behavior. The “smart” companies wouldn’t receive a bailout, leading some to assume they are better off to employ the incorrect group think model. Of course, this would not work in a free market.

7) Does your company use stochastic models? If it does, what kind of models are used?

Albert: We primarily work with customers who have reasons for the models they use. Sometimes, they ask us to implement specific models in their system. Other times, they come to us for advice asking what model may be best. For instance, in regards to interest rates, I am a big fan of the Libor Market Model (also known as the BGM Model). It is a term structure model. However, the industry almost exclusively seems to use short rate models. The Hull-White Model is very common because it’s very easy to parameterize, simple, and everyone else is using it.

However, I enjoy commodities more than interest rates or equities. In commodities, we have different issues because it is such a physical market. These models can be much more complicated. If I picked a favorite model, it is one that I was lucky enough to have helped develop (I’m biased). That model takes the term structure for a commodity and relates it back to the spot price allowing them to be simulated together. I really enjoy working with that model. In general, my favorite model is the right model for the situation; a model that makes logical sense and fits the data.

Part III: Risk management

8) How do the recent financial crisis and the regulation policies enacted after that affect the behavior of your company?

Albert: As a vendor, our business is based on our customers’ business. A crisis like that causes additional regulation or at least the changing of regulation. To handling that regulation it is very logical that a third party, a vendor would make a solution and sell it to customers. Typically, that type of regulation would cause a company like SAS to make a new product and be able to provide that solution to more people. Unfortunately, the capital expended on satisfying regulations cannot be used elsewhere in the economy.

9) The goal of risk management is to achieve a balance between returns and risks. Thus, with lots of capital and human resource spent, risk management may, to some extent, reduce a company’s profits. Now suppose you are a leader of a financial institution. Driven by the motivation of maximizing the profits, will you pay enough attention for risk management?

Albert: As a risk professional my answer must be yes. There are two aspects to consider in regards to risk: monitoring and management. Consider risk monitoring first. One should spend resource and pay attention to know the rules of the game. For an example, let’s think back to mortgages. What if housing prices could go down? I may go bankrupt. Well, that would be very important to know. If you don’t know the rules of the game, you cannot play your best.

In the same way, you need risk monitoring to help you see what the possibilities are. In terms of risk management, it’s like getting an insurance policy. Let’s say I have a house and all my money is in my house. If my house burns down, I may go bankrupt. I should clearly buy fire insurance on my house. That’s how risk management can be considered as well. Yes, if I am concerned about anything other than the very short term, I would spend enough resource on risk management and pay attention to my risk team.

Part IV: Suggestions & Advice

10) What skill sets are important to succeed in your field?

Albert: I get asked that question often: by students, by some of my friends, and some of my peers. I change the details of my answer almost every time, but there are key components that remain consistent. First and foremost is communication. No matter how smart you are, no matter how brilliant your model may be, if you cannot convince others and if you cannot explain your ideas, it is not going to matter.

Another component in my list is passion. Passion is not a skill, but an ingredient to success. Is it necessary? No. But if you are not passionate about your field, why work in it? Your passion allows you to have better ideas and think outside of the box which is critical. If you just think like everyone else, you are very replaceable. This makes it more difficult to advance. Your passion may present itself in the form of problem solving. This is an important skill.

Another skill of importance is programming. In our field, people are often not formally trained in programming. We are more likely to be self-taught with at most one or two university courses in programming. This is very different than those people who come out of school with an entire degree in computer science. They have different level of understanding the way a machine thinks. In some parts of our field, this understanding is critical and you will need to learn it. Being skillful enough to have a computer automate you work is always important. Automation frees your time to think and add real value.

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Thank you Albert for inviting us to SAS for coffee and taking the time for this fun and informative interview!

 

Meet our Financial Math Alumni- Coffee Chat with Albert Hopping- Part 1

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Meet Albert Hopping, ERP- Manager of Risk Consulting at SAS Institute in Cary, North Carolina. Albert graduated from the Financial Math program in 2007. He is a Board Member and an active alumnus of our program. We were happy to meet with Albert for coffee at his office at SAS.

Part I: Education & Job Background:

1) Why did you decide to get a Master’s degree in Financial Mathematics from North Carolina State University?

Albert: That I might receive more wages. That is the short answer. I finished my undergraduate degree before this program existed. When I joined the program, I was working full time. I had been out of my undergraduate program for a few years and I ended up in a risk analytics team at a diversified energy company. At that point, I didn’t have a risk background and didn’t know much about the field. I was on the risk team looking around and I saw these quant guys programming in Matlab. It looked like fun to me and I thought that it was a cool job. I wanted to be a part of what they were doing, so I started helping them with their work as much as I could.

Eventually, it got to the point where I was doing this risk work a majority of my time. I told my manager that I should be moved to the quant job family. I was told that a master’s degree in Financial Mathematics was a prerequisite for the job. Not having the degree was a roadblock for me. I applied to the Financial Mathematics program that week and I am glad I did.

2) How did the program prepare you for your job?

Albert: I was already doing risk work; I was self-taught to a certain extent. This put me in a different position compared to most students, and I got different things out of the program than other people might have, as a result. Most students learn theory first and practice second. I started the program with the perspective of a practitioner. While in the program, I learned about models I used on the job. I used these tools at work, but I didn’t really know about stochastic partial differential equations. I used Black-Scholes, but I could not derive it.

What I received from the classes is a much deeper conceptual understanding and a firmer foundation from which to see my work. What I really took from this program is a fundamental, basic understanding of financial mathematics. I also learned new models and conceived great ideas to use in practice.

3) Please briefly describe your job, your job title, and your responsibility?

Albert: At SAS Institute, I am a Manager on the Risk Solution team of Professional Services & Delivery (PSD). Let me explain from the top down. PSD is the consulting, customization, and delivery arm of SAS. Many customers of SAS software want services, consulting, or even staff augmentation. PSD provides these services. We are the ones who go to the customer site and work with the customer to help them get the most benefit from our products. Our team within PSD specializes in the risk management domain. We work with all the risk solutions and provide consulting for all risk topics. Our team has about 20 members and is growing.

Within risk, I specialize in three industries Energy, Financial Services, and Healthcare. I am responsible for leading customer projects, providing industry and risk domain expertise to the sales teams, mentoring fellow team members, and most importantly providing value to the customer. Note that the views and opinions I express today are my own.

Part II: Analytic techniques

4) “Big Data” is a hot specialization in the field. Do you see this as a long term trend or something that might pass as a fad?

Albert: Big Data is definitely a long term trend. In fact, I would go beyond that; I would say it is going to be the new norm. It will progress to the point where big data is simply the paradigm. I will even extend that to unstructured data. Companies, who are not using big data and unstructured data to their advantage, are starting to fall behind. They are tomorrow’s luddites.

5) The trend of “Big Data” implies that people believe historical data can shed light on future prediction. However, this contradicts with “efficient market hypothesis” to some degree. What are your thoughts about this?

Albert: One of the things I would like to point out in terms of the “efficient market hypothesis,” is the irrationality in the market. A simple example comes to mind: technical traders discuss how a stock index will meet resistance or break through a barrier. But what are those points where the index meets resistance or breaks through? They are numbers with lots of zeroes on the end, round numbers. Why are those numbers important? They are only important because we tend to be emotional and we have ten fingers. I propose that if we had a different number of fingers we would use a different base for our number system. The round numbers where the stock index meets resistance would be different numbers.

Clearly, these barriers are irrational, as they are based on how many fingers we have. This means I cannot be a full believer in the “efficient market hypothesis.” The question remains, is all this historical data priced into the market already? To the extent that people are doing analytics on big data, perhaps yes. Was it priced in before? No. Was the data available? Mostly, but people could not convert the data into knowledge. It was impossible - until analytics on this big data was possible.

Now, we are in the place where something can be done because of the advancements in software and the physical hardware. Data can be restructured and put into use in the market. The fact that the data is available is clearly important, but prior to these advancements one could not glean actual insights. The data must be converted into information that helps those insights that yield a better price or a better model. Acting upon those insights is what makes the market more “efficient”.

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Stay tuned for Part 2 & follow Albert on twitter @SASQuant 

“Meet our Financial Math Alumni”- Emmanuel Sanchez

 

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Meet Emmanuel Sanchez. He is currently an Associate with Allianz Risk Transfer in New York City. He is one of the first students to graduate from NC State's Financial Mathematics program in 2004. We were able to chat with Emmanuel in New York City, and catch him when he visits Raleigh, North Carolina.

Part I: Education & Job Background

1) Why did you decide to get a Masters in Financial Math at NC State?

Emmanuel- I was studying at NC State to get a Masters in Computer Science at the time. It was in 1999 or 2000 before the Financial Math program had started. I was in Harrelson Hall for a Math class and a professor had pinned outside his office a description of a course he was going to teach the following semester: the course was Financial Mathematics and the professor was Jean-Pierre Fouque. I got very interested, took the class and when the program started a few years later, I enrolled full-time.

 (side note - Harrelson Hall is an iconic round building at NC State's brickyard, and after many, many years of controversy it will be torn down!)

2) Briefly describe your job, and if possible list some financial products you are dealing with.

Emmanuel- I work for a company called Allianz Risk Transfer where I price and structure weather insurance. Here are a couple of examples of weather products:

  • Utilities with hydro plants are dependent on rainfall. To protect them against low rainfall they could purchase a put option on cumulative rainfall.
  • In the North-East and Midwest in winter, snow removal can be very expensive for municipalities. They could purchase a call option on cumulative snowfall.

Part II: Analytic techniques

3)  The trend of “Big Data” implies that people do believe historical data can shed some lights on future prediction. And interestingly, such predictions may sometimes affect the future movement of the market. Is this also true in your area?

Emmanuel- In the weather business it is critical to have enough historical data. Unlike other markets like equities, it won’t be hotter or colder because people buy or sell more temperature contracts. Similarly weather forecast will have no impact on the actual weather: the fact that tomorrow’s maximum temperature in New York is forecast to be 80F won’t change the value of the actual temperature. There is no concept of implied volatility in weather.

4) In your area of specialization, what kinds of models or methods are used? Please briefly describe the basic process for applying them.

Emmanuel- For a lot of the deals I price, I do not use models. For example, if I am pricing a structure where the payout depends on cumulative rain in New York from July to September, I will first get historical daily rain data and compute the cumulative amount for the specified period. In a lot of locations (like New York) there will be at least 50 or 60 years of data available. This gives me 50 or 60 data points (1 per year). I will then try to find a probability distribution that best fits the data and use that distribution to simulate rainfall data.

Part III: Risk management

5)  How do the regulation policies enacted after crisis affect the behavior of your company? Do you see this as long term trend or fad?

Emmanuel- Regulation policies enacted after the crisis (e.g. Dodd-Frank) made my company pay more attention to compliance and regulatory requirements. I don’t see this going away any time soon.

6)  The goal of risk management is to achieve a balance between returns and risks. Thus, with lots of capitals and human resource spent, risk management may, to some extent, reduce a company’s profits. Driven by the motivation of maximizing the profits, will the leaders of your company pay enough attention for risk management?

Emmanuel- I work for an insurance company. Generally insurance companies have a tendency to be conservative (and definitely much more conservative than investment banks). I find my company to pay a lot of attention to risk management in general (not just financial risk management). The legal and compliance departments are very important.

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Part IV: Suggestions & Advice

7) Any suggestions for current FM students to get a job?
Emmanuel- My suggestion to students is to take full advantage of their internship to learn as much as they can about the company and the problems/challenges it faces.
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Big thanks to Emmanuel for participating in our alumni interview series from New York City.

New Series- “Meet our Financial Math Alumni”- Coffee Chat with Jonathan Leonardelli

"Meet our Financial Math Alumni" is an up-close interview series with select Financial Math alumni to learn more about their career, experience and knowledge after receiving their Masters in Financial Math degree from NC State University. Alumni are important part of our program for many reasons. They provide support, vision and strategy to ensure the success of our program. They are role models and mentors for current students. They strengthen the reputation of the Financial Math program. They provide job leads and recruitment activity for students. Our alumni are intelligent and awesome! Thank you to those who participant in this series"- Leslie Bowman, Director of Career Services

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Meet Jonathan Leonardelli, FRM, Risk Consultant (Graduated 2004)

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Interview conducted and summarized by Yi Chao and Xiaohong Chen, Financial Math Interns, May 2015 Graduates

Jonathan is currently a Risk Consultant at Financial Risk Group. He is also one of the first students to graduate from NCSU’s Financial Mathematics program. We were honored to have the opportunity to interview him.

Part I: Education & Job Background

1) Interviewer: Why did you decide to get a Masters in Financial Math at NC State?

Jonathan: I had just moved here and was interested in changing careers. I wanted to find a program that combined mathematics and finance. As it happened, NC State was in the process of creating the Financial Mathematics program. Although the start of the program was still a couple years off, that time allowed me to get the necessary mathematics background I needed. Entering the program produced the exact result that I wanted: it gave the mathematics I need to do interesting work in the banking industry.

2) Interviewer: How did the program prepare you for your job?

Jonathan: The program really gave me the depth of math that I needed to work in the field of risk. It also taught me how to apply rigorous logic to a problem to help find a solution. Beyond this, though, I learned that life was filled with randomness. This randomness, as a result, causes the quantification of some metrics to be difficult.

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Part II: Analytic techniques

3) Interviewer: "Big Data" is a hot specialization in the field. Do you see this as long term trend or something that might pass as a fad?

Jonathan: It is definitely not a fad. In this day and age many actions we take, especially when using a piece of technology, is probably captured and stored in some database. Now, think about all those action and all the data that comes along with it. What is a company going to do with this data? They are going to improve their sales, improve their risk practice…the list goes on. Having skills to work with big data, to be able to find the relevant information and then integrate it into a model, is very useful.

4) Interviewer: The trend of “Big Data” implies that historical data can shed some lights on future prediction. However, this contradicts with “efficient market theory” to some degree. What are your thoughts about this?

Jonathan: I think concerns should always be involved when using historical data because the tacit assumption is that the future is going to behave like the past. That being said, there are ways to mitigate these concerns. For example, when we calibrate models one of the first things we do is test it with a different period of data to see if the model is robust. Sometimes we might use the model on data representative of a stressed scenario (i.e., a scenario that is uncommon but still possible) and see how the model performs. If it performs badly, we try to assess why that is. Are the parameter estimates wrong? Are different variables needed?

5) Interviewer: Does your company use stochastic models to predict interest rate? What kind of models are used?

Jonathan: To be honest, in my current job the main stochastic (i.e., diffusion based) models I have used are CIR (Cox-Ingersoll-Ross) and GBM (Geometric Brownian Motion) with the occasional jump-diffusion model thrown into the mix. Most of the models I have worked with recently are linear regression, logistic regression, and Markov chains.

6) Interviewer: In your area of specialization, what is your favorite method or model and why? Do you believe it is perfect?

Jonathan: Markov chains and their resulting transition matrices. This comes from the years when I worked in the banking industry. At a glance, the transition matrix tells you the behavior of different segments of accounts. Depending on how the states of the Markov chain are defined, the transition matrix can tell you: 1) The probability of going to default, 2) the probability of paying off, 3) the probability of curing, 4) the probability of moving across multiple states over a given time, etc.

The transition matrix is a great summary tool. Of course, it is not perfect. Always keep that in mind when you build a model. Even though the model looks pretty and deals well with the data – now – it is not perfect. It is an easy move from complacency, when the model is performing well during good times, to anxiety when the model is performing poorly during a financial crisis.

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Part III: Risk Management

7) Interviewer: How do the regulation policies enacted after crisis affect the behavior of your company?

Jonathan: The regulations have not impacted the behavior of our company. However as a risk consulting company, we have seen more requests from financial institutions asking us to help them comply with the regulations.

8) Interviewer: The goal of risk management is to achieve a balance between returns and risks. Thus, with a lot of capital and human resource spent, risk management may, to some extent, reduce a company’s profits. Driven by the motivation of maximizing the profits, will the companies pay enough attention for risk management?

Jonathan: I may be biased, given my chosen career path, but I think with the recent financial crisis still fresh in our memories as well as all the regulations that were created as a result of it, businesses will continue to pay enough attention to risk management. And, I think, it will be that way for a while.

Part IV: Suggestions & Advice

9) Interviewer: Any tips for those interested in getting into the field?

Jonathan: First, be comfortable with the idea of randomness. Randomness is uncertainty and uncertainty is risk. Second, companies do not only seek candidates that are good at math and programming. They also seek those candidates who can clearly present their ideas in writing and presentations. Third, get perspective from areas outside of mathematics. I strongly suggest taking business classes because it gives you a different view of a business. A company is multifaceted and does not solely revolve around models.

10) Interviewer: What courses do you recommend?

Jonathan: The courses in the Financial Math program are very good. Among them, I definitely think the probability course is the most important one. That course takes you deep into the world of randomness and, hopefully, makes you comfortable with it. If you have an option of taking a course on risk or financial regulation that would be good. I took econometrics as an elective and, more often than not, draw upon the math tools I learned from that class more than others. Another very good course I took, and have used frequently, is time series analysis.

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"It is a great experience to interview Jonathan. He is humorous and smart. We learned a lot when we talked with him. Thanks Jonathan for participating in our interview! We are sure that your answers will shed some light for those interested in Financial Mathematics!"- Yi Chao and Xiaohong Chen