Valtteri Peltonen profile picture
Valtteri
Peltonen
Doctoral Researcher, Department of Accounting and Finance
Master of Science in Economics and Business Administration, University of Turku

Contact

Areas of expertise

Finance
risk management
quantitative finance

Biography

I am a second year PhD student interested in topics related to risk management, quantitative finance and finance in general. My master's degree in economics and business administration is also from the University of Turku. I graduated in 2017 and applied into a doctoral program almost straightaway. My master's thesis concerned issues related the risk management of delta-neutral derivative allocations, and I intend to continue to study the field in my dissertation. My master's thesis was awarded for its merits by Suomen Arvopaperimarkkinoiden Edistämissäätiö (a Finnish foundation promoting security market related activities, no official translation available).

Teaching

LRS31 Asset pricing and portfolio theory, exercise session instructor;

LR05 An elementary follow-up course in finance (no english name), exercise session instructor;

Bachelor's thesis seminar, thesis supervisor; 

Master's thesis seminar, assistant thesis supervisor.

Research

My research concerns financial risk management, especially market risk management, and new advancements in the field. After the financial crisis in 2008 it has become apparent that the current regulatory framework requires some fundamental changes in order to enhance the reliability and robustness of the models in use. The pre-2008 models severely underestimated many risks related to financial instruments, especially derivatives and other complex instruments. 

From an academic point of view, this offers a fruitful situation due to the numerous open questions in the field. For example, it is not clear what risk measure or measures should be used and how risk factors should be statistically modeled. The upcoming regulatory changes will likely shift the emphasis from VaR (Value-at-Risk) based models to ES (Expected shortfall) based models. This would fix the problem that VaR is not a subadditive, but would bring other issues, because ES is not elicitable (i.e. it cannot be backtested). There are also other new advancements in the field: lately some authors have studied the so called expectiles. Expectiles have some desirable properties from the point of view of risk management. They are both elicitable and subadditive, which makes them an attractive alternative to ES and VaR.