“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.

Test drive the Quantitative Finance BETA site from Stack Exchange

Quantitative Finance Stack Exchange is a question and answer site for finance professionals and academics. This website http://quant.stackexchange.com/ covers questions on real-life problems you face such as:

  • securities valuation
  • risk modeling
  • market microstructure
  • portfolio management
  • financial engineering
  • econometrics

And this is not a discussion forum...Quantitative Finance Stack Exchange is all about answers. Pretty straight forward- Ask a question, get an answer! Great resource to check out while it is in BETA.

Other resources for Quantitative Finance:

1. Wilmott.com

Wilmott.com is a quantitative financial portal created by Paul Wilmott. One can find job postings, technical articles, up-to-date news, and other useful resources.

http://www.wilmott.com/

2. QuantStart

QuantStart is a personal website discussing Algorithmic Trading strategy research, development, backtesting and implementation. The author behind this website once worked in a hedge fund as a quantitative trading developer in London. Therefore, his articles are very practical. There are several articles on career development, which are very useful for those unfamiliar with the industry.

http://www.quantstart.com/

3. QuantLib

The QuantLib project is aimed at providing a comprehensive software framework for quantitative finance. QuantLib is a free/open-source library for modeling, trading, and risk management in real-life. It is written in C++ with a clean object model, and is then exported to different languages such as C#, Objective Caml, Java, Perl, Python, GNU R, Ruby, and Scheme.

http://quantlib.org/

4. Yahoo Finance

You can get free stock quotes, option prices, up to date news, portfolio management resources, international market data, message boards, and mortgage rates from here.

http://finance.yahoo.com/

5. Data and Charts of U.S. Department of the Treasury

Great resource to find all kinds of interest rates related with the U.S. treasury.

http://www.treasury.gov/resource-center/data-chart-center/Pages/index.aspx

6. QuantNet

It is a leading resource on Financial Engineering education and news, but the main focus is education. Quantnet provides detail information about Financial Engineering programs in North America.

https://www.quantnet.com/

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By- Xiaohong Chen, Financial Math Intern, May 2015 Graduate

Database trends in financial services that quants should know

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Recent trip to New York City included a small alumni meet-up and Data Summit 2014. At Data Summit 2014 we learned about several database trends in financial services well beyond the popular RDBMS (relational databases) including Hadoop Big Data Platforms, NoSQL, NewSQL, and in-memory databases.

Quants know SQL, and it's important for them to be aware of the above database trends and what's driving them in financial services - such as risk analytics and reporting, market data feeds, high frequency trading, regulation, among other use cases driving demand for high volume and scalable, specialized databases.  While many quants are proficient in programming, it's not reasonable to expect them to learn each programming language driving these technologies to access data (Erlang, Javascript, C#, Java, etc).  This is not unique to quants as we're seeing SQL enable wider adoption of the Hadoop Big Data Ecosystems.

Sumit Sarkar of Progress Software (Gold sponsor of our program) talks about how professionals such as those in quantitative finance can easily work with data in the growing landscape of highly specialized database technologies, MongoDB for example, using standard based SQL interfaces such as ODBC and JDBC.

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(Alumni Left to Right- Emmanuel Sanchez with Allianz; Director of Career Services, Leslie Bowman; Yoshi Funabashi with Credit Suisse; Brandon Blevins with Credit Suisse)

Keep a lookout for their  "Meet our Financial Math Alumni" interviews.

We will be back again in October, 2014- so all NYC alumni, plan for another fun gathering!

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