Here is a selection of the research papers I’ve written during my two master’s programmes, all of which were awarded a first/distinction.
MSc dissertation under the supervision of Riccardo Rebonato:
Why is the slope a good predictor of excess returns? An overreaction explanation – The slope of the yield curve is an important factor in predicting excess bond returns, but why this is the case remains an open question. We provide statistical evidence that contrasts the classical explanation, suggesting that the excess returns are unlikely to be fully ascribable to ‘simple’ risk premia. Following in the footsteps of well-established behavioural finance research, in particular Shiller (1980), we propose a simple investor overreaction explanation instead.
MSc advanced module research projects:
The Gaussian Copula and the Financial Crisis: A Recipe for Disaster or Cooking the Books? – Was a complex mathematical model to blame for the Global Financial Crisis or was it the gaming of credit ratings based on incorrect correlation estimations; a so-called “cooking of the books”? In this paper the modelling of Collatarised Debt Obligations (CDOs) was investigated within the context of the Crisis.
Hedging Basis Risk Using Reinforcement Learning – This paper investigates the feasibility of using machine learning techniques, in particular reinforcement learning, to hedge basis risk. A linear, gradient-descent SARSA(λ) algorithm with binary features and an ε-greedy policy was implemented to investigate the optimal hedging strategy for a short put position on a non-traded asset by trading a portfolio of ∆t of a correlated but tradable asset, and cash.
Simulating Limit Order Book Models – Most of the world’s exchanges operate an order-driven trading system where all market participants are provided with a limit order book (LOB) that contains all currently outstanding limit orders. It is proposed that LOB dynamics are integral to the price-discovery process and that some statistical regularities emerge as a result of LOB structure and dynamics. In this paper two related zero-intelligence LOB models are discussed and compared with the behaviour of real LOBs.
MMath 4th year original research project under the supervision of Colm Connaughton:
Modelling Twitter Trends – This project researches and attempts to mathematically model the spread of popular topics on the popular social networking site Twitter. This modelling is based on the Susceptible Infected Recovered (SIR) epidemiological model, drawing parallels between the spread of infections and the spread of topics on Twitter, i.e. do things go “viral” mathematically like a disease.