Hiromichi Kato, (he/him) a PhD student in the Department of Mathematics uses the power of math to inform financial market decisions. Hiro uses mathematical models to calculate accurate derivative values. By providing more accurate derivative values, stock market traders have a better way of assessing credit risks. This ensures that mathematical models that are used to calculate credit risks, as part of risk assessments, better reflect today's real markets and are as useful and accurate as possible tools for financial decision-making.
This episode features:
WLU Research Chat S03 Hiro
Unknown 00:00
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Shawna Reibling 00:04
Welcome to the third season of Research Chat. In this season graduate students share the challenges of their research work. In this episode Patricia Ferreira will interview Hiro Kato. First I would like to introduce this episode's participants.
Shawna Reibling 00:22
Patricia Ferreira, who uses pronouns she/her, is a comparative physiologist who is pursuing a PhD in biological and chemical sciences at Wilfrid Laurier University. She is working in Jonathan Mark Wilson's lab. To address her research questions, she creates knockout models and fish and, previously, in mice that target specific genes and proteins to better unveil their function and mechanism of action. She has been awarded two Ontario Graduate Scholarships and a Hypatia Award for women in science from the Laurier Center for Women in Science. She holds a bachelor's degree in biology and a Masters of Science in Marine Sciences from the University of Porto in Portugal. Hiro Kato, who uses pronouns he/him, is a third year PhD student in the Mathematical and Statistical Modeling Program offered by the Department of Mathematics at Wilfrid Laurier University. He is working under the supervision of Dr. Joe Campolieti et and Dr. Roman Makarov. He completed a Bachelor of Arts in economics and financial mathematics at Wilfrid Laurier University and a Master of Science in Mathematics at Wilfrid Laurier University. His research has been supported by multiple awards, including the Ontario Graduate Scholarship, and the Queen Elizabeth II scholarship. Welcome to Research chat. Thank you to you both for speaking to me today about the intricacies of your specialist topics and understanding how they apply in the world. You're both using models to understand the world and how things work. Patricia's research is focused on knockout models for studying the role of the stomach, and Hiro's research is refining models to determine derivative prices. I will turn the microphone over to you Patricia to learn more about heroes research.
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Patricia Ferreira 02:14
Hi, Hiro, and thank you so much for chatting with me about your research today. So I'd like to start by asking you what is the question that you plan to explore in your research?
Hiro Kato 02:27
The my research, I want to explore how mathematical models can help rectify the mismatch between the market and model derivative prices.
Patricia Ferreira 02:39
And what are derivatives and why are they important?
Hiro Kato 02:42
A derivative is a financial contract whose value depends on the value of another macro economic variable such as an asset price. Derivatives are used as protections to reduce the downside risk of a potential future market. There are numerous kinds of derivatives, but the focus will be put on credit derivatives. A credit derivative is a derivative whose value depends on credit worthiness of one or more firms. One example is a credit default swap, which is often abbreviated as a CDS. A CDS is a credit derivative that allows an investor to swap or offset their credit risk with that of another investor. When the reference entity defaults on the underlying bond, the protection buyer receives recovery payments from the seller.
Patricia Ferreira 03:40
Oh, that's fascinating, and what is the motivation of your research?
Hiro Kato 03:43
So I'm going to give you a practical example. In the early 2000s people in the United States were optimistic about investing in housing mortgages, because they believed that the housing prices will continue to rise in the future. Investment banks, including Lehman Brothers, sought an opportunity to learn houses to their customers by offering lower interest payments to the customers then that offered by the bank. At the same time, the Lehman Brothers acquired a large amount of CDS to insure against credit risk exposure. Then the US Federal Bank started to raise interest rates to cool down the economy. This eventually led to a massive default by the home owners and brought Lehman Brothers to bankruptcy. The bottom line is that the loss could have been minimized by charging the CDS at a higher price to incentivize investment banks to operate with a low level of leverage.
Patricia Ferreira 04:52
It's quite important indeed. So can we know what challenges have you faced throughout your research? Can you tell us a bit about that.
Hiro Kato 05:01
The most difficult part of my research is translations from real world problems to math problems, and vice versa. I have a solid background in mathematics, but my knowledge in finance is weak. So I often got stuck with abstracting the problems and explaining how new mathematical findings could bring about problem resolutions.
Patricia Ferreira 05:25
So, Hiro, if you don't mind, I'd like to ask a follow up question. And I'm quite interested in knowing how have you addressed this challenge that you that you just identified?
Hiro Kato 05:36
To set up mathematical models, we start by finding the real world problem which can be abstracted in a mathematical form, we then solve the math problems and translate the solution back to the real world. To overcome the problem, I spent quite some time to get a better knowledge in finance by asking my supervisors or by reading finance papers.
Patricia Ferreira 06:01
Quite nice. So how did you explore your research question?
Hiro Kato 06:06
Since credit derivative prices are driven by the credit worthiness of the firm credit ratings, such as the risk rating may be used as a metric. However, such ratings are revised infrequently. Alternatively, the total value of the firm's assets can be a key feature that describes the credit worthiness of the firm. In my study, the firm's value follows some diffusion process - a famous example is the Black Scholes Merton model. Diffusion processes capture natural phenomenon of the firm's value and have become the main tool among modern mathematicians in credit risk modeling. classical models attempt to find that likelihood of credit events completely determined by the firm's value. However, the classical models tend to underprice CDS values because of little information is incorporated in its price. The most influential factor of the CDS values is a hazard rate, also known as default intensity rate, which is the likelihood of default by the reference entity given that default has not already occurred. The hazard rate must be stochastic and correlated with the firm's value, meaning that the lower the firm's value, the higher the hazard rate is, I employed the stochastic hazard rates to my new model because it is mathematically tractable, and provides more appropriate credit derivative prices. The new model shows a significant improvement over the classical models and gives a near perfect fit to typical market CDS price data.
Patricia Ferreira 07:47
And what should people remember about derivative pricing?
Hiro Kato 07:52
In my view, including more relevant information helps determine a meaningful derivative prices and prevents the economy from huge losses impacted from a credit crisis. In my case, I incorporated stochastic hazard rates to my new model, which showed a significant improvement over the classical models.
Patricia Ferreira 08:16
So, Hiro, what should people remember about this topic?
Hiro Kato 08:20
My research revises classical credit risk modeling to be more effective in today's real markets. When I compare prices produced by the revised model with current data, the revised model produces a perfect fit to the actual market prices.
Patricia Ferreira 08:38
Thank you so much, Hiro, for sharing your research with me today.
Hiro Kato 08:42
Nice to speaking with you as well.
Shawna Reibling 08:45
Thank you to you both for participating in this episode. It's important to see the impact that modeling has on our everyday lives and how we can translate research from disciplines into its applications in the real world
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Shawna Reibling 09:06
I hope you enjoyed listening to today's discussion. If you want to learn more about Patricia and Hiro's research, there are resources, additional readings and details about the work of each researcher on our website located at wlu.ca/research-chat. Listeners like you are encouraged to share these episodes and use these podcasts to discuss these topics with your friends, or as an assignment in the classroom. Subscribe on your favorite podcast platform to be notified of new research chat episodes. Research Chat is a partnership between the Office of Research Services, the Faculty of Graduate and Postdoctoral Studies and the Laurier Library. Thank you to everyone who's contributed to the creation of Research Chat. a gratitude list can be found on our web page
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