麻豆淫院

From the 2008 financial crash to today's volatile cryptocurrency markets, sharp fluctuations continue to disrupt global markets and economies. According to Masoumeh Fathi's doctoral dissertation at the University of Vaasa, traditional risk models often underestimate the possibility of extreme events, leaving investors and policymakers unprepared.

For decades, financial risk has been measured with Gaussian-based models built on the assumption that markets follow a bell-shaped curve. These models underpin decisions from investment strategies to regulation, yet they fail to capture the true scale of market disruptions. Masoumeh Fathi's dissertation in finance argues that power laws offer a more accurate lens through which to understand financial markets' risk dynamics.

"It was challenging as a young researcher to question such established theories, but the evidence was clear: the variance of financial markets is so wild that, in practice, we cannot鈥攐r better: should not鈥攔ely on it. This means that many standard econometric methods simply do not provide a reliable basis for decision-making," Fathi notes.

The study shows that financial markets' volatility exhibits power-law behavior with heavy tails, meaning that sharp rises and crashes are far more common than the bell curve predicts. The interesting result is that these patterns appear consistently across equities, commodities, foreign exchange (FX) markets and especially cryptocurrencies.

Better tools for investors, analysts and policymakers

Fathi argues that power-law models can help financial professionals and regulators better assess extreme risks, improve portfolio strategies, and provide more accurate statistical tools for understanding market instability. Moving beyond Gaussian assumptions allows for a more accurate understanding and prediction of market risk behavior.

The study also reveals that power laws are potentially influenced by behavioral factors such as herding鈥攁 phenomenon where investors follow the actions of a larger group. For Fathi, the value of the work lies in connecting abstract theory with everyday market behavior.

"What excites me most is that my research allows me to combine advanced mathematics with real-world finance in a way that can shed light on these dynamics," Fathi says.

Fathi's research consists of four essays and draws on extensive datasets covering stocks, currencies, commodities, and cryptocurrencies. It employs analyses based on variance measures, statistical tests, and tail exponent estimation. In addition, the study makes use of a model that enables the identification of market bubble formation and the prediction of the timing of crashes.