Sonja Kokkonen

Posts from Sonja Kokkonen

Seeking Postdocs for Data Science in Finance

Would you like to get desired and prestigious EU funding for your Post-Doc? We are seeking talented  researchers in quantitative finance / financial data science for hosting and coaching them for EU-funding. The idea is to make a joint EU application for  2 year postdoc position at research group on Financial Computing and Data Analytics, […]

21.04.2023 Read more

Listening to the financial heartbeat with agent-based models

Time, as they say, is of essence in the financial world. Every second counts. But the reality is that the economic system in which the finance sector operates is not constricted by our traditional perceptions of time, nor is it a black-and-white world where price monitoring only can keep you afloat. In this article, Vladimir […]

29.08.2019 Read more

Portfolio credit risk: standard models won’t hit the mark in capturing default dependence

Portfolio credit risk models are concerned with potential losses due to defaults or deteriorations in credit quality. These models have applications ranging from regulatory and economic capital measurement to portfolio management and risk-adjusted pricing. Incorrectly specified models translate to insufficient capital buffers which, in turn, leave the financial system crisis-prone and in need of regular […]

20.08.2019 Read more

Using news for finding firm relations and implications on financial markets

Finding correlations between publicly traded companies is a topic of interest for a variety of actors on the financial markets. Many financial institutions use it to predict asset returns, while the regulators want to the know how the risk of default will spread through the market in times of crises. The classical approach towards building […]

14.08.2019 Read more

An introduction to sentiment analyses

The general idea behind sentiment analyses in finance is the existence of relevant but hard to quantify information in the textual data in addition to the objective statements of facts. This information could influence the sentiment of market participants which in turn could influence their actions. Therefore, quantifying sentiment is important to the extent that […]

12.08.2019 Read more

Financial Data Analysis: Machine Learning and Interconnections Between Stock Markets

Financial markets are complex, interconnected and deterministically chaotic systems in which the price of a stock may be influenced by the economic factors of other stock markets. Thus, a variety of methods that aim to analyze future market behavior have been developed. For example, technical analysis aims to identify, model, extrapolate and combine financial market […]

07.08.2019 Read more

Smart beta investing – How can big data help?

Smart beta is a relatively new term that has became ubiquitous in finance in the last few years, but the concepts behind it have been known for decades. It has its roots in factor investing, going back to the 1960s when risk factors were identified as the primary drivers of equity returns. Essentially, factors are […]

31.05.2019 Read more

Call for Papers

Please visit

06.05.2019 Read more

Large, Unstructured, Noisy Data in Finance

Large, unstructured, and noisy textual data sources have become readily available as the web has grown and become a household commodity. Millions of product reviews, resumes, legal and corporate filings, blogs, news articles, governmental releases, (and more) may be freely downloaded and offer tremendous opportunities for unlocking new business value, enabling more effective communities, and […]

09.04.2019 Read more

PhD dissertation of Giorgio Mirone

BigDataFinance Early stage Researcher Giorgio Mirone defended his PhD dissertation entitled “Measurement, assessment and forecast of integrated variance” on Friday 23 November 2018. Giorgio Mirone has been enrolled in the PhD programme in Economics and Business Economics. Professor Kim Christensen has been his supervisor and Professor Asger Lunde has been his co-supervisor. The dissertation can […]

11.12.2018 Read more

Big Data Finance: PhD Thesis in Three Minutes

BigDataFinance Early Stage Research Vladimir Petrov, based at University of Zürich, has made a video to introduce his research topic “High Frequency Trading Risk Management Tools Based on Scaling Law” and the Marie Skłodowska-Curie programme.

27.11.2018 Read more

Volatility seasonality of Bitcoin prices

“Learning properties of Bitcoin and other cryptocurrencies and confronting them to the features of traditional markets we contribute to the world where “finance” is a synonym of “democracy”.” BigDataFinance Early Stage Reasearch Vladimir Petrov, based at Univeristy of Zürich, and Anton Golub, Co-founder and Chief Science Officer at Lykke Corp, discuss Bitcoin’s seasonal volatility in their article […]

21.06.2018 Read more

BigDataFinance protagonist at the 6th Lindau Meeting in Economic Sciences

ESR Chiara Perillo from University of Zurich shared the stage with Nobel Prize Laureates Prescott, Diamond and Sims joining the panel discussion on new conditions for monetary and fiscal policy at the 6th Lindau Meeting on Economic Sciences by Sari Törmälä On 23-26 August 2017, the 6th Lindau Meeting on Economic Sciences took place in […]

08.03.2018 Read more