The MSc project is a substantial component of the programme, occupying around 4 months. It is a piece of original work undertaken by the students under the supervision of an academic researcher and, in most cases, also with an external supervisor. Most projects are carried out in association with a bank, hedge fund, consultancy, or systems provider in the finance industry, and we endeavour to arrange suitable placements.
You will find below a large sample of past theses, covering wide range of topics.
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- 19 November 2020- Goldman Sachs-Imperial MSc Flash Talk Series
- Past and Current Project Partners
- 2022-23
- 2021-22
- 2020-21
- 2019-20
- 2018-19
- 2017-18
- 2016-17
- 2015-16
We are proud to partner with Goldman Sachs for a Flash Talk series of 2019-2020 MSc Math Finance Theses.
Event type : Zoom Webinar
Date: Thursday, 19 November
Time: 4:30-6pm GMT
Alcazar | Bainbridge Partners |
Bank of America | Barclays |
BNP Paribas | Beekin |
Blackrock | Citigroup |
Credit Suisse | Deutsche Bank |
EBRD | Ernst & Young |
Goldman Sachs | HSBC |
IHS Market | IXIS-CIB |
JP Morgan | Janus Henderson |
Jetstone Asset Management | Lloyds TSB |
Marney Capital | Mazars |
Mitsubishi Group | Morgan Stanley |
Natwest Markets | Norges Bank |
Quod Financial | Rogge Global Partners |
Santander | Swiss Re |
Synergis | Toronto Dominion Securities |
UBS | Velador Associates |
XSOR Capital |
- George Coxon: Optimal execution with intraday liquidity changes and transient no
- Minyuan Li: Simulations of calibrated local stochastic volatility models
- David Malone: Methods of pricing cross-currency Bermudan swaptions
- Ilia Sobakinskikh: Optimizing transformer neural network for real-time outlier d
- James Mc Greevy: Detecting multivariate market regimes via clustering algorithms
- Victoria Xing: Liquidity saving mechanisms and mixed-integer linear programming
- Changan Qian: Transformer-based probabilistic forecasting model for intraday for
- Anthea He: Reservoir Computing in alpha forecasting of foreign exchange market
- Thomas Simon: Evaluating approaches for estimating the Day-Ahead price and Water
- Jeroen Nelis: Detecting and repairing arbitrage: from European to American optio
- Martin Weirich: Fokker-Planck calibration of one-factor stochastic local volatil
- Valentin Blanda: FX barrier option pricing
- Zhihao Xu: Harvest Volatility Risk premia using deep reinforcement learning
- Andrea Iannucci: Machine learning for directional movement prediction of US corp
- Weiqing Cao: LMM to FMM: an illustration of SONIA cap pricing
- Félix Eychenne: Correctly pricing continuous barrier contracts
- Alberto Moreno de Vega Garcıa: Deep solvers
- Callum Rough: The rough Bergomi model: from motivation to implementation
- Yuchen Yan: Financial bubble prediction with neural networks
- George Akerman: Empirical Bond Pricing with Affine Models
- Yuvraj Anand: Algorithmic Market-Making for Options
- Xingyu Du: Predicting Economic Recessions Using Signature Kernels
- Jan Jasper Eckstein: Low Latency Finance
- Konstantinos Evangelides: Backward Stochastic Differential Equations
- Chun Hei Fan: Application of Schrodinger's Bridge in Volatility Models
- Yijun Fu: Dynamic Portfolio Optimisation under Multiscale Stochastic Structures
- Zhenya Grigoriev: General Signature Kernel for Time Series Modelling
- Tom Ham: Actor-Critic Reinforcement Learning Methods for Electronic Market Making
- Yizhe He: CIR++ vs Shifted Squared Vasicek in Interest Modelling
- Jay Jethwa: Uncertain Volatility Model with Applications to Cliquets
- Balint Zoltan Keresztfalvi: Pricing of Bermudan Swaptions in the Cheyette Model
- James Leach: Dividend Modelling and the Particle Method
- Tianyu Luo: Deep Hedging with Transaction Costs and Risk Preferences
- Manola Meconcelli:
- Nilesh Ramnarain: Harvesting Volatility Risk Premia using Deep Reinforcement Learning
- Bassam Sinan: Deep hedging of Autocallables with rough Bergomi model
- Etienne Wallerich: Arbitrage Detection with Quantum Annealing
- Tianhao Wang: Reinforcement Learning Provides Free-Lunch, but at What Cost?
- Kexin Xie: Ranking of Covariance Forecasts by Robust Loss Functions
- Jiaxin Xu:Delta Hedging Convertible Bonds with Credit Risk
- Junwei Yuan: Deep learning for unconstrained Markov regime-switching quadratic utility maximisation
- Bo Yuan: Deep learning interpretability of the parameters to smile map in a rough volatility model
- Jing Zhang: Machine Learning in Credit Risk
- Zihui Zhao: Random Matrix Theory: Moment expansions, algebra and combinatorics
- Andrew Alden: NLP for Financial Chat Message Classification
- Hinrik Bergs: Neural Rough Differential Equations for Long Time Series and Classification of D
- Arvid Bertermann: Reinforcement learning trading strategies with limit orders and high-frequency signals
- Joseph Burrin: Implementing an IR-FX Model for CVA Calculation
- Millie Deng: Study of the Conformance Anomaly Detection Algorithm on Streamed Data
- Jingxuan Dong: Efficient Methods for Dynamical Initial Margin Modelling
- Wiam El Mouden: Deep intensity-based CVA with Wrong Way Risk
- Sami Farih: A Risk Methodology for Cross-Asset Volatility Trading Strategies
- Si Cheng Fong: Distributional Prediction of Foreign Exchange Rates with Mixture Density Network
- Kian Hatamieh: European Government Bond Volume Prediction Using Dealer to Client Flow
- Jonah Humphreys: ML and Artificial Neural Networks Applied to Forecasting Energy Commodity Prices
- Jiarou Li: Utility Maximizastion in Regime-Switching Markets with Full and Partial Informat
- Minghao Li: Uncertain Volatility Model for Option Pricing
- Viola Pu: Pricing Options using Deep Neural Networks from a Practical Perspective
- Winter Shi: Deep Hedging under Reweighted Asset Measure
- Xiaofu Tang: Use of Kernel Methods for Dynamic Hedging in Incomplete Markets
- Jiajie Tao: Semilinear PDEs for Valuation under Credit, Collateral and Funding
- Tzyy Tong: Reinforcement Learning with Continuous Controls for Foreign Exchange Trading
- Marianne Toscano: Deep Structural-based CVA with Wrong Way Risk
- Konstantinos Tsoulias: Bitcoin Trading Strategies Based on Twitter Sentiment Analysis
- Lidan Xing: Fx Trading Strategy Using Rough Path Signature
- Baofeng Ye: Discrete Dynamic Risk Constraints for Controlling Tail-risk Seeking Traders
- Tao Yu: Bootstrapping Past Inflation Returns
- Kaixuan Zhou: Connecting Caplets and Swaptions in the Displace Diffusion Market Model
- Xingyao Zhu: Improvements on Target Risk Portfolio in Strategic Asset Allocation
- Hendrik Zimmermann: Intraday Trading with Neural Networks and Deep Reinforcement Learning
- Nassim Amer-Ouali: Calibrability of first-to-default correlation structure
- Pierre-Alexis Corpechot: Study of the joint S&P 500/VIX smile calibration problem within rough volatility
- Hicham El Jerrari: Robust option pricing: the uncertain volatility model
- Qingxin Geng: Dynamically controlled kernel estimation for XVA pricing and options replication
- Thomas Hengstberger: Increasing Venture Capital Investment Success Rates Through Machine Learning
- Xiaoshan Huang: Interpretability in Deep Learning for Heston Smile Modeling Calibration
- Chenhao Jin: Truncated Order Decision for Signature Least Square Regression Model Under the P
- Haoyin Lin: Dynamic convex duality and backward stochastic differential equations in utility
- Chenyu Liu: Deep Reinforcement Learning and Electronic Market Making
- Shibo Lu: Harvesting Volatiltiy Risk Premium
- Conor McIndoe: A data driven approach to market regime classification
- Jeremy Marc: Prediction of financial bubbles and backtesting of a trading strategy
- Clea Morand: Predicting US Stock Returns Using Closing Auction Imbalance Data
- Peixuan Qin: Pricing and Hedging of Derivatives by Unsupervised Deep Learning
- Umor Sami: Discrete Hedging and Pricing of European Options using Reinforcement Learning
- Francesco Sciacovelli: Interest Rate Prediction with Twitter Sentiment
- Viraj Shah: Optimal Stopping Problems: Autonomous Trading Over an Infinite Time Horizon
- Jianxiong Sun: Stochastic control problem with constrained condition and random drift
- Hafsae Tabti: Utility Maximisation
- Hugues Thorin: Artificial Neural Networks for SABR model calibration & hedging
- Yuchen Tu: Predicting High-Frequency Stock Market by Neural Networks
- Niklas Walter: A Jump-Diffusion Model for Credit Risk with Endogenous Contagion
- Toby Weston: Distributional Reinforcement Learning for Optimal Execution
- Ruizhe Xia: An Automated Approach on Generating Macro-Economic Sentiment Index Through Centr
- Xinyu Yan: Forecasting Cryptocurrency pricing
- Chenyu Yang: Dual control methods for tight bounds of value function when the drift following
- Yaozhang Wang: Unconstrained utility maximization problem via four methods
- Yifan Zheng: Robust Option Pricing
- Jietao Zhou: Constrained quadratic risk minimization problem via four different approaches
- Tara Aghajani: Solving high-dimensional non-linear PDE using deep learning
- Majd Agoumi: Hedging Dividend Futures
- Benyamin Azoulay: Iceberg orders and shapes of the limit order book
- Apolline Bonnerre: Automated valuation platform for vanilla products
- Lewis Brown: A Machine Learning Approach to Cardinality Constrained Portfolio Optimisation
- Sahil Chadha: Classification-based Prediction of Gadget Time Series Using Machine Learning
- Zuming Gao: Optimal Trading strategy and trading behaviour
- Xinnan Gu: Machine Learning For Foreign Exchange Rate Forecasting
- Justin Gwee: Stochastic Optimisation under Probability Distortion
- Ghada Hamieh: LIBOR Discontinuation
- Elissa Ibrahim: Constant Maturity Swap Pricing
- Ruizhi Kong: Alpha in Short and Long Term Bond Market
- Francois Le Dain: Trading volume forecasting in the equity market using machine learning
- Thomas Leygonie: Reinforcement learning for derivatives pricing and uncertain volatility model
- Justin Li: A Machine Learning Approach to Improve the Pegging Algorithm
- Remi Mouzayek: Extraction of relation-objects from documents using a weakly supervised setting
- Mohamed Taik: Robust Option Pricing, Taik
- Xiyu Yang: Optimal Investment with discretionary stopping and trading constraints
- Jonathas Castello Branco: ETF Market Making
- Francois Cluzeau: Hazard rate surface model and its implication to SouthernEuropean sovereign bond
- Antoine Collas: Option and CVA Greeks with adjoint algorithmic differentiation
- Jason de La Borie De La Batut: Advanced methods in portfolio optimisation for trading strategies and smart beta
- Alexander Done: Static and Dynamic Execution Strategies
- Laurids Gert Nielsen: Machine Learning For Foreign Exchange Rate Forecasting
- William Goldberg: An assessment of the validity of linear propagator models
- Kees Groeneweg: On the class of modulated volterra stochastic volatility processes
- Marjorie Grootenboer: Model risk management for market risk
- Kanstantsin Kulak: Performance improvements for risk balances portfolios
- Haibo Li: Gaussian process regression: a machine learning approach to derivatives pricing
- Yilang Lu: Application of clustering method to trading strategy in the US equity market
- James McIndoe: Tactical asset allocation strategies derived using sentiment analysis
- Nelson Okou: Fractional Brownian motion and machine learning for variance prediction
- Luis Eduardo Pavon Tinoco: Application of Stochastic Control in Optimal Execution Algorithms
- Zhentian Qiu: Classify Neural Networks in Credit Scoring area based on the financial ratios
- Henry Sorsky: Factor Investing in the Automotive Sector
- Ghali Tadlaoui: Intelligent Portfolio Construction: Machine Learning enabled
- Turker Temel: Rough stochastic volatility and applications of the rough Bergomi model
- Mehdi Tomas: Pricing and calibration of stochastic models via neural networks
- James Edbooke: Time Series Modelling Technique Analysis for Enterprise Stress Testing
- Inass El Harrak: An Application of Importance Sampling to the Evaluation of the Economic Capital
- Jessy Hu: Liquidity Risk Arising from Margin Requirements
- Shijun Liu: A Mathematical Solution to Seeking Arbitrage Opportunity in M&A
- Alexandre Maraval: Indicators of Risk Appetite and Applications on Trading
- Fei Wang: Forward Variance Dynamics: Bergomi Model and its Applications in Pricing Cliquet
- Yafan Wang: Applications of Recurrent Neural Network on Financial Time Series
- Haixia Zhong: Malliavin Calculus Applied to Monte Carlo Methods in Mathematical Finance
- Cheng Luo: On the Calibration of the SABR Model and its Extensions
- Kyriacos Neocleous: Longevity Risk: An Intensity-Based Approach
- Nadya Patricia: Approximation Error in Dependence Iteration for Default Modelling
Scholarships
MSc Maths Finance News
- Msc Mathematics and Finance ranks 1st in the 2024 QuantNet Ranking of Best UK Quant Programs
- MSc Mathematics and Finance ranks 5 highest UK-based programme in the 2022 Quant Guide
Congratulations!
- Ranitea Gobrait for receiving the JP Morgan Scholarship New J.P. Morgan Scholarship creates Quantitative Finance study opportunities | Imperial News | Imperial College London
- Cécilia Auburn (Class of 2020) for the award of First laureate of the "CFM Women in quantitative finance" grant.
Terms and conditions
Important information that you need to be aware of both prior to becoming a student, and during your studies at Imperial College: