Northwestern Mutual Fixed Income Project – cont’d (Student-Consulting)

Evaluating the performance of an active manager in institutional fixed income portfolios is often challenging due to the necessary customization of issuance-based benchmarks to meet specific investment objectives. These constraints can be related to risk limits including factors such as aggregate credit quality, issuer concentration, or asset type. Other constraints can be more liability-based such as duration, convexity, or minimum yield. Simply assessing a manager’s total returns relative to a broad-based index or peer group in isolation does not provide a complete representation of the quality of management. […]

The Herd Behavior Index and predicting market fear

The past has learned that stock prices tend to move together. Moreover, at moments of high market fear, this co-movement is stronger and stock prices move predominantly downwards. In such a market situation, diversification benefits dry up and stock picking does not help to protect an investment portfolio. In this project we implement the Herd Behavior Index, […]

Optimal Investment with Forward Preferences and uncertain parameters under binomial market model

Given a financial market environment, an agent aims to solve her optimal investment strategy. This project is a continuation of “forward and backward preferences” proposed in IGL and IRL last year. In the previous project, under the binomial market model, comparing to the classical backward approach, we showed substantial improvement in both computation time and […]

European-type basket option pricing: independence and comonotonicity approximations.

This project solves the European-type basket option pricing problem. Finding analytical solutions or stable numerical schemes for the corresponding high-dimensional PDE is still an open problem. Hanbali and Linders (2019) propose an approximation of the problem using the element of comonotonicity. Their theoretical results have been further strengthened by Ling (2019) using a modern machine […]

Implied Portfolio Value-at Risk: model-free and forward-looking risk estimates for investment portfolios

The Value-at-Risk (VaR) is one of the key risk measures to determine the risk levels of trading portfolios. The VaR gives information about the maximal future loss of the portfolio in a given time frame. However, determining a VaR for a given trading portfolio based on historical data of the stocks composing the portfolio results […]

Measuring intra-day systemic risk in high-frequency order books

Measuring the degree of co-movement between stock prices is of utmost importance when dealing with portfolio selection, risk measurement and multivariate derivative pricing/hedging. Daily stock price information is easily accessible for a large number of stocks and indices and allows to calibrate multivariate stock price models. Such a model can then be employed to investigate […]

P2P insurance: risk sharing of heterogeneous risks

The main objective of an insurance contract is to provide an adequate risk sharing scheme between insured and insurer. An insurance contract should allow the insured to make a risk bearable, which would be unbearable without an insurance contract (e.g. the risk of major damage to your house in case of fire). However, other risk […]

Model-free hedging via reinforcement learning

Under the complete market model assumption, risk neutral approach for pricing and hedging financial derivatives have been the standard solution for quite a while. With the rise of machine learning in the past decade, even in an incomplete market, efficient hedging of financial derivatives becomes feasible. This project aims to revisit the two recent groundbreaking […]

Holistic principle for risk aggregation and capital allocation: an extension to Solvency II standard

A novel holistic principle for risk aggregation and capital allocation has recently been proposed in [1], to remedy the issues of lack of consistency, negligence of cost of capital, and disentanglement of allocated capitals from standalone capitals in the state-of-the-art two steps procedure. Astonishingly, the proposed holistic principle provides a natural structural relationship among standalone […]

Cyber risk profile construction via individual cyber losses aggregation – continued

This project is a continuation of the IRisk Lab project, Cyber risk profile construction via individual cyber losses aggregation, in Fall 2019. Multivariate frequency model for cyber losses has been constructed, fitted, and tested, in the previous project. This project aims to further improve the multivariate frequency model, as well as construct the multivariate severity […]