New statistical models for companies that want to simulate and manage financial risk

Volatility is a measure of how much a financial asset fluctuates. Volatility thus provides insights into how risky investments are.  
In his thesis, Alexander and co-authors propose two new volatility models to estimate the risk of an investment.  

“The first model can be used in situations where the volatility of an asset is changing slowly over time. This might for example capture structural changes in the risk profile of a young company as it matures and the business model becomes more established, or in a commodity as its role as a good used in the production of some industry evolves”, says Back.

The authors discuss how the model can be fitted to real-world data sets, which in formal statistical terminology is broadly referred to as estimation. Using statistical theory, the thesis delves into both how and why the method of estimation works. The thesis also covers the theory and practice of some statistical tests that can be used to determine whether the proposed model captures the idiosyncrasies of time series of financial returns.  

A commonly accepted and well-motivated prediction of financial theory is that financial leverage makes equity riskier. Back’s second model is a stochastic volatility model. The results of this model can also have a bearing on the financial industry.  

“The model can be used to generate scenario analyzes where people tasked with monitoring and mitigating financial risk simulate possible future outcomes, taking both correlation with a broad equity market and the unique financial profile of the firm at hand into account” proposes Back.

While some similar models exist, the author contributes to the literature by developing a model in the empirically and theoretically interesting stochastic volatility class.

You can read more about the thesis here: Essays on Volatility Modeling

Alexander Back will defend his thesis on 18 September, at 14.00 in Hanken School of Economics, Arkadiankatu 22, Helsinki.
Opponent: Yongmiao Hong, Professor Emeritus, Cornell University, USA
Custos: Professor Niklas Ahlgren, Svenska handelshögskolan

The doctoral defence will be held as hybrid. Participants can attend on site or via videoconference.
Access the video conference via the link: https://go.hanken.fi/defence-back

More information:
Alexander Back
e-mail: alexander.back@hanken.fi