Open projects for students
These projects are open and are waiting for students to pick them up. If you are interested or would like to apply please contact the respective project supervisor.
Supervisor:
László Varga
This opportunity is at the intersection of quantitative finance and machine learning. It offers gaining experience in AIML coding and understanding various financial products and models with the general goal of speeding up pricing and calibration calculations with neural networks.... More
Application deadline:
October 15, 2024
MSc
Open
Time series generation, prediction and classification with variational autoencoders
Supervisor:
László Varga
This opportunity is at the intersection of quantitative finance and machine learning. It offers gaining experience in AIML coding and understanding various financial products and models with the general goal of speeding up pricing and calibration calculations with neural networks.... More
Application deadline:
October 15, 2024
MSc
Open
Supervisor:
Gábor Fáth
This opportunity is at the intersection of quantitative finance and machine learning. It offers gaining experience in AIML coding and understanding various financial products and models with the general goal of speeding up pricing and calibration calculations with neural networks.... More
Application deadline:
September 30, 2024
MSc
Open
Replication of financial pricing models with neural networks
Supervisor:
Gábor Fáth
This opportunity is at the intersection of quantitative finance and machine learning. It offers gaining experience in AIML coding and understanding various financial products and models with the general goal of speeding up pricing and calibration calculations with neural networks.... More
Application deadline:
September 30, 2024
MSc
Open
Running projects
The following projects are currently in progress. Student application has been closed, but if you are interested in a discussion please contact the respective project team.
Bence Ónódy, Gábor Fáth
This project offers an exciting opportunity for students to delve into the intricate realm of finance and risk management. Participants will grapple with the challenge of determining the optimal hedging strategy in a volatile multi-factor market, where hedging instruments are... More
MSc
Running
Optimal hedging under constraints
Bence Ónódy, Gábor Fáth
This project offers an exciting opportunity for students to delve into the intricate realm of finance and risk management. Participants will grapple with the challenge of determining the optimal hedging strategy in a volatile multi-factor market, where hedging instruments are... More
MSc
Running
Márton Jakovác, Gábor Fáth
VAEs are cutting-edge generative models that excel in capturing complex data distributions and generating new samples that closely resemble the original data. Through hands-on experience, students will develop a deep understanding of VAEs' architecture, training methodologies, and their role in... More
BSc
Running
Generating synthetic data using Variational Autoencoders
Márton Jakovác, Gábor Fáth
VAEs are cutting-edge generative models that excel in capturing complex data distributions and generating new samples that closely resemble the original data. Through hands-on experience, students will develop a deep understanding of VAEs' architecture, training methodologies, and their role in... More
BSc
Running
Dalma Tóth-Lakits, Miklós Arató, András Ványolos
This research focuses on the parameter estimation and calibration of interest rate models allowing for negative rates. We work with different models from Kennedy's random Gaussian field to sufficiently altered HJM and Black's models to shifted SABR. We investigate how... More
PhD
Running
Models of negative interest rates
Dalma Tóth-Lakits, Miklós Arató, András Ványolos
This research focuses on the parameter estimation and calibration of interest rate models allowing for negative rates. We work with different models from Kennedy's random Gaussian field to sufficiently altered HJM and Black's models to shifted SABR. We investigate how... More
PhD
Running
Zoltan Udvarnoki, Gabor Fath
Ground state wave functions of one-dimensional quantum chains are equivalent to classical time series with nontrivial statistical properties. This equivalence allows us to simulate time series for specific financial applications in a quantum inspired way.
PhD
Running
Quantum time series
Zoltan Udvarnoki, Gabor Fath
Ground state wave functions of one-dimensional quantum chains are equivalent to classical time series with nontrivial statistical properties. This equivalence allows us to simulate time series for specific financial applications in a quantum inspired way.
PhD
Running
Daniel Boros, Ivan Ivkovic, Laszlo Markus
Our interest is stochastic processes with fractional properties and their applications in financial mathematics. We work on parameter estimation methods for fractional Brownian motion, the OU and CIR processes, and the Heston model with rough volatility. We place emphasis on... More
PhD
Running
Fractional processes and their financial applications
Daniel Boros, Ivan Ivkovic, Laszlo Markus
Our interest is stochastic processes with fractional properties and their applications in financial mathematics. We work on parameter estimation methods for fractional Brownian motion, the OU and CIR processes, and the Heston model with rough volatility. We place emphasis on... More
PhD
Running
Closed projects
The following projects has been closed. For reports, publications, and other related material click the project link below.
Nándor Tóth, Gábor Fáth
This opportunity offers hands-on experience at the intersection of AI and quantitative finance, enhancing coding and data manipulation skills and the understanding of the statistical properties of real financial time series data.
MSc
Closed
Generating synthetic financial data using GANs
Nándor Tóth, Gábor Fáth
This opportunity offers hands-on experience at the intersection of AI and quantitative finance, enhancing coding and data manipulation skills and the understanding of the statistical properties of real financial time series data.
MSc
Closed
Zoltan Udvarnoki, Gabor Fath, Norbert Fogarasi
We examine the advantage of quantum computing for pricing financial options using the Monte Carlo method. Quantum MC promises a quadratic speedup over the classical algorithm. Systematic and statistical errors are handled in a joint framework, and a relationship to... More
PhD
Closed
Quantum advantage of Monte Carlo option pricing
Zoltan Udvarnoki, Gabor Fath, Norbert Fogarasi
We examine the advantage of quantum computing for pricing financial options using the Monte Carlo method. Quantum MC promises a quadratic speedup over the classical algorithm. Systematic and statistical errors are handled in a joint framework, and a relationship to... More
PhD
Closed
Máté Kunsági-Sándor, Gábor Molnár-Sáska, István Csabai, Gábor Fáth
We build Variational Autoencoders (VAE) to compress high-dimensional implied volatility surfaces. and connect this with the Weighted Monte Carlo approach to create a dynamic pricing framework, which can price not just vanillas, but also exotic options on this compressed vol... More
PhD
Closed
Deep Weighted Monte Carlo
Máté Kunsági-Sándor, Gábor Molnár-Sáska, István Csabai, Gábor Fáth
We build Variational Autoencoders (VAE) to compress high-dimensional implied volatility surfaces. and connect this with the Weighted Monte Carlo approach to create a dynamic pricing framework, which can price not just vanillas, but also exotic options on this compressed vol... More
PhD
Closed