Saturday, September 20, 2025

Financial markets are more prone to sharp swings than traditional theory suggests

A new study from the University of Vaasa, Finland, shows that traditional risk models often underestimate the possibility of extreme events

University of Vaasa

image:
Masoumeh Fathi from the University of Vaasa.
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Credit: University of Vaasa

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 – or better: should not – rely 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 provides 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 – a 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 behaviour.

– 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.

Doctoral dissertation

Fathi, Masoumeh (2025) Essays on Power Laws and Financial Markets. Acta Wasaensia 560. Doctoral dissertation. University of Vaasa.

Publication pdf

Public defence

The public examination of M.Sc. Masoumeh Fathi’s doctoral dissertation “Essays on Power Laws and Financial Markets” will be held on Thursday 25 September 2025 at 12 at the University of Vaasa, auditorium Nissi.

It is possible to participate in the defence also online:
https://uwasa.zoom.us/j/66826502494?pwd=nn5oipLumUmvJxjlywRmX2sDyzxtoM.1
Password: 095330

Professor Mika Vaihekoski (University of Turku) will act as opponent and Associate Professor Klaus Grobys as custos.

Further information

Masoumeh Fathi was born in Iran in 1983. She completed a Bachelor’s degree in Applied Mathematics in Iran and a Master’s degree in Economics and Finance at the University of Milan, Italy. Fathi is currently a doctoral researcher at the University of Vaasa.

Smart robots revolutionize structural health monitoring

Intelligent inspection robots open a new era of infrastructure safety and maintenance

Journal Center of Harbin Institute of Technology

Ensuring the structural safety of bridges, tunnels, construction machinery, and other critical infrastructure is essential for public safety, economic stability, and environmental protection. Traditional inspection methods—mainly relying on manual visual checks—are time-consuming, expensive, and often dangerous, especially in high-altitude, underwater, or hazardous environments. They are also prone to human error and often fail to detect early-stage defects, leading to unexpected structural failures and costly accidents.

Intelligent inspection robots have emerged as a powerful alternative, offering high efficiency, precision, and safety. These robots integrate advanced sensor technologies (e.g., high-resolution cameras, LiDAR, ultrasonic sensors, and infrared thermal imagers) with artificial intelligence algorithms, enabling them to autonomously navigate complex environments and identify structural defects in real time.
The review systematically categorizes four main types of inspection robots:

Ground Mobile Robots – Designed for stable movement across complex terrains, these robots can perform long-duration, high-accuracy inspections of bridge decks, wind turbine blades, and roadways.
Wall-Crawling Robots – Equipped with magnetic or suction systems, these robots scale vertical surfaces to detect cracks, corrosion, and structural deformation in bridge piers, high-rise buildings, and ship hulls.
Aerial Robots – Offering rapid deployment and wide coverage, drones can inspect high and hard-to-reach areas such as bridge superstructures and crane components, capturing high-resolution images and 3D models even in challenging conditions.
Underwater Robots – Adapted to harsh aquatic environments, these robots conduct precise inspections of submerged structures like bridge piers, dams, and offshore platforms.

The paper also highlights the integration of sensor fusion, deep learning-based data analysis, and autonomous navigation technologies such as SLAM (Simultaneous Localization and Mapping) and Ultra-Wideband (UWB) positioning to improve detection accuracy and reliability in GPS-denied environments.

Despite their promise, intelligent inspection robots face technical challenges, including maintaining stability in complex environments, processing large-scale multi-source data in real time, and achieving fully autonomous decision-making. The authors suggest future research directions such as deeper integration of machine learning, optimization of multi-robot collaboration, and improvements in energy efficiency and lightweight design.

The author emphasizes: “By combining robotics, advanced sensors, and artificial intelligence, inspection robots are reshaping the future of structural health monitoring. These technologies will help prevent catastrophic accidents, reduce maintenance costs, and extend the lifespan of critical infrastructure.”

Journal

SmartBot

DOI

10.1002/smb2.70000

Method of Research

Literature review

Subject of Research

Not applicable

Article Title

A Review of Technical Advances and Applications of Intelligent Inspection Robots in Structural Health Monitoring

Frasky, a new robot for vineyard applications

Frasky is a robot designed to move autonomously through vineyards, performing tasks such as monitoring, manipulating grape clusters, and applying selective treatments.

Istituto Italiano di Tecnologia - IIT

Frasky, a new robot for vineyard applications — video:
Frasky is a robot designed to move autonomously through vineyards, performing tasks such as monitoring, manipulating grape clusters, and applying selective treatments. the project results from the collaboration with the partners involved in “JOiiNT LAB,” the joint lab aiming at creating a synergy between research and industry, thus comprising IIT and the industrial ecosystem in the Bergamo area.
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Credit: IIT-Istituto Italiano di Tecnologia

Bergamo/Genova (Italy), 18 September 2025 – A team of researchers from the Soft Robotics for Human Cooperation and Rehabilitation Lab at the Italian Institute of Technology (IIT-Istituto Italiano di Tecnologia) in Genova has conceived and developed Frasky, a new robotic prototype able to navigate and perform operations autonomously within vineyards. Coordinated by IIT researcher Manuel G. Catalano, the project results from the collaboration with the partners involved in “JOiiNT LAB,” the joint lab aiming at creating a synergy between research and industry, thus comprising IIT and the industrial ecosystem in the Bergamo area, including Consorzio Intellimech, Confindustria Bergamo, the University of Bergamo, and Kilometro Rosso Innovation District. Frasky’s main goal is to address the challenges that the agricultural sector is facing nowadays, such as environmental sustainability and labor shortages, by combining robotics and artificial intelligence.

“Integrating robotics and artificial intelligence in agriculture allows us to develop increasingly advanced models of precision farming,” says Manuel G. Catalano, IIT researcher and JOiiNT LAB coordinator. “For instance, it enables more efficient and targeted use of resources, reduces environmental impact, and offers concrete support to farmers and wine producers. These are important elements if we consider that the sector is affected by growing labor shortages and challenges posed by climate change. It is an ambitious goal, and it is possible thanks to the cooperation between research institutions, academia, and industry, where diverse perspectives and expertise play a role, which are essential to the success of this project.”

Frasky is a prototype robot intended for moving and interacting within agricultural environments. It is equipped with a robotic arm and a hand for manipulating plants and fruit. Within the arm, an integrated camera allows the system to map its surroundings and detect obstacles and specific objects, such as grape clusters, with precision. The setup is mounted on a commercially available mobile platform designed for outdoor navigation, with four motorized wheels. The complete system is modular and flexible in both hardware and software, enabling the integration of tools according to the needs of farmers. For instance, Frasky’s robotic hand includes a nozzle for applying selective treatments to the vineyard.

At the core of its operating abilities is software developed by the IIT team; it is divided into three main modules: navigation, which enables the robot to orient itself in space and reach points of interest while avoiding obstacles; perception, which permits environmental analysis and recognition of grapes clusters; and manipulation, which guides the movements of the robotic arm during its tasks. The data collected by the perception module can be used both for creating a map of the vineyard and supporting the manipulation module, enabling targeted actions such as grasping grape bunches, visual inspection, or application of treatments.

The software provides an intuitive graphical interface through which an operator can send commands and monitor in real time the robot’s operations, thus managing the entire system.

Frasky offers several advantages: more precise digital monitoring of crops; assistance to farmers with repetitive tasks; greater accuracy in treatment application in vineyards, reducing waste. All of this translates into tangible benefits for the environment and worker health, by limiting human exposure to potentially harmful chemicals.

Designing a robot capable of working in real-world agricultural environments presents significant technical challenges.

First, the terrain is uneven, and the environment is subject to changes, such as seasonal shifts, weather conditions, and plant growth. Foliage can become denser and more voluminous over time, reducing visibility, impeding access to plants and limiting the robot’s movement.

Moreover, the robotic system must be able to move autonomously, avoid obstacles and collect data on crop conditions, while performing interventions directly on the plants. The manipulation of fruit is an operation which requires dexterity and gentleness, because fruit is deformable and easily damaged.

In order to respond to all these challenges, Frasky was initially tested in the lab on an artificial vineyard and then validated through field demonstrations in a real vineyard in Bergamo: “Le Corne” vineyard in Grumello del Monte (Bergamo). These tests demonstrated the platform’s ability to move, map the environment, and autonomously apply treatments.

“We are currently working to make Frasky even more flexible, autonomous, and capable of adapting to various agricultural contexts, which present high complexity by their nature,” adds Francesca Negrello, IIT researcher and Technology Manager of JOiiNT LAB. “Our goal is to expand the robot’s perception and manipulation capabilities to other tasks beyond those already validated, so that it can operate alongside viticulturists, supporting them in production monitoring and in more repetitive and burdensome activities.”

“Collaboration between research and industry, as in JOiiNT LAB, is key to fostering technological innovation and nurturing new professional skills”, continues Fabio Previdi, Full Professor at the University of Bergamo. “Working closely with companies offers our students concrete interdisciplinary experiences, which are essential for developing the skills required to work in the industry and preparing them for the challenges of digital transformation. Our students, therefore, are directly involved in the projects, actively contributing to the development of advanced solutions in the labs and then transferring them outside the labs, generating benefits both for companies and the academic system.”

“The technologies that are developed for industry through joint work between research and industry have a cross-cutting impact which goes well beyond the manufacturing sector. Tangible outcomes are produced across the region”, concludes Stefano Ierace, Director of the Consorzio Intellimech. “Such projects promote new training experiences for students and young professionals, and offer real opportunities to explore innovative solutions, with benefits extending to the entire production chain and the local social system.”

Method of Research

Experimental study

Frasky was initially tested in the lab and then validated in a real vineyard in Bergamo: “Le Corne” vineyard in Grumello del Monte. These tests demonstrated the platform’s ability to move, map the environment, and autonomously apply treatments.
Credit
IIT-Istituto Italiano di Tecnologia

Purdue study uncovers why some hurricanes balloon in size and what that means for forecasting future storms

Purdue University

When people hear about hurricanes, they often focus on the category rating: Category 1 through 5, based on maximum wind speeds. But not all hurricanes with the same wind speeds are alike. Some are compact storms while others can span the size of entire states. Larger hurricanes bring far greater damage, generating wider footprints of high winds, heavier rainfall and more dangerous storm surge.

A new study led by Purdue University researchers has uncovered why some hurricanes grow significantly larger than others and why this growth occurs rapidly under certain ocean conditions. The research shows, for the first time, that hurricanes grow in size much faster when traveling over locally warm waters where the ocean surface is significantly warmer than the rest of the tropical oceans.

“This discovery can be put directly into use for daily forecasting of hurricane size and impacts,” said Danyang Wang, postdoctoral researcher in Purdue’s Department of Earth, Atmospheric, and Planetary Sciences (EAPS). “It can also be used to better model hurricane size in long-term risk models used by industry to evaluate property risks.”

The discovery, led by Wang with guidance from professor Dan Chavas of Purdue’s EAPS department, was published in the Proceedings of the National Academy of Sciences (PNAS).

Wang developed the underlying theory, extracted and analyzed data from historical records and climate simulations, and wrote the manuscript. Chavas provided high-level feedback on how to connect the theory to real-world storms.

They were joined by collaborator Ben Schenkel, a research scientist at the Cooperative Institute for Severe and High-Impact Weather Research and Operations at the University of Oklahoma. Schenkel provided a tropical cyclone size database used in the analysis and helped clarify results across multiple datasets.

Before this work, scientists knew that some hurricanes expanded significantly during their lifetimes while others stayed compact. But the factors behind that difference were not well understood. Wang and Chavas showed that the rapid growth of storms is tied to “hot spots” in the ocean. These are localized areas where the water is significantly warmer than the surrounding tropical waters.

The results also suggest a surprising silver lining in a warming world. The study found that hurricane size growth rates do not change much with global mean warming, though global temperatures continue to rise.

The 2024 Atlantic hurricane season gave a striking example of why storm size matters. Hurricane Helene expanded rapidly before making landfall, ballooning into one of the largest storms in U.S. history at an estimated width of over 400 miles and causing unprecedented damage.

“Two hurricanes with the same maximum wind speed can be two very different sizes,” Wang said. “But think of one doughnut the size of South Carolina and another the size of Texas.”

Chavas compared the process to popcorn kernels in a pan. “The hurricanes see the tropical ocean like popcorn heated on an uneven pan — turning up the heat everywhere may make them pop a little faster, but it’s over the hot spots where the hurricanes will pop the fastest.”

Modern satellites provide high-quality, daily estimated measurements of sea surface temperatures worldwide. By applying this new understanding of how hurricanes respond to local ocean hot spots, forecasters may be able to better predict how large storms will become at landfall.

“A larger storm has a larger footprint of damaging winds, generates higher storm surge and over a larger area, and produces more rainfall — all greater risks to society,” Wang said. “Better predictions of storm size at landfall translate to better predictions of the hazards that pose risks to life and property.”

The Chavas lab at Purdue specializes in understanding extreme weather, from tropical cyclones to severe thunderstorms and tornadoes. Wang focuses on the physics of hurricane structure, particularly storm size.

The team tapped into Purdue’s Rosen Center for Advanced Computing, which gave them the ability to analyze global data in fine detail and uncover patterns that would have been impossible to see otherwise. These resources helped ensure that their findings about tropical cyclone growth are both accurate and comprehensive.

They also used the National Center for Atmospheric Research’s Cheyenne and Derecho supercomputers, some of the fastest in the world, to run experiments that mimic how storms behave in different warming scenarios. This powerful combination of Purdue and NCAR computing resources let the researchers explore what-if questions about our climate and deliver insights that can improve forecasts and preparedness for future storms.

The findings pave the way for improvements in both daily storm forecasting and long-term risk assessment used by industries such as insurance and infrastructure planning. The research also highlights the importance of integrating theoretical science with high-resolution data and advanced computing power.

The work was supported by the National Science Foundation Division of Atmospheric and Geospace Sciences under grants #2431970 and #1945113.

About the Department of Earth, Atmospheric, and Planetary Sciences at Purdue University

The Department of Earth, Atmospheric, and Planetary Sciences (EAPS) combines four of Purdue’s most interdisciplinary programs: geology and geophysics, environmental sciences, atmospheric sciences, and planetary sciences. EAPS conducts world-class research; educates undergraduate and graduate students; and provides our college, university, state and country with the information necessary to understand the world and universe around us. Our research is globally recognized; our students are highly valued by graduate schools and employers; and our alumni continue to make significant contributions in academia, industry, and federal and state government.

Written by: David Siple, communications specialist, Department of Earth, Atmospheric, and Planetary Sciences at Purdue University