Browsing Theses by Supervisor "Li, Yuying"
Now showing items 1-8 of 8
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Data-Driven Models: An Alternative Discrete Hedging Strategy
(University of Waterloo, 2023-08-16)Options hedging is a critical problem in financial risk management. The prevailing approach in financial derivative pricing and hedging has been to first assume a parametric model describing the underlying price dynamics. ... -
A General Neural Network Methodology for Multi-period Portfolio Optimization
(University of Waterloo, 2024-01-22)In this thesis, we propose a neural network methodology for solving the multi-period portfolio optimization problem. Our approach formulates the problem as a stochastic optimal control problem and uses a single neural ... -
Local Graph Clustering Using l1-regularized PageRank Algorithms
(University of Waterloo, 2020-05-05)Local graph clustering methods are used to find small- and medium-scale clusters without traversing the graph. It has been shown that the combination of Approximate Personalized PageRank (APPR) algorithm and sweep method ... -
Optimal Decumulation for Retirees using Tontines: a Dynamic Neural Network Based Approach
(University of Waterloo, 2023-09-19)We introduce a new approach for optimizing neural networks (NN) using data to solve a stochastic control problem with stochastic constraints. We utilize customized activation functions for the output layers of the NN, ... -
Optimization Methods for Semi-Supervised Learning
(University of Waterloo, 2018-05-17)The goal of this thesis is to provide efficient optimization algorithms for some semi-supervised learning (SSL) tasks in machine learning. For many machine learning tasks, training a classifier requires a large amount of ... -
A Robust Neural Network Approach to Optimal Decumulation and Factor Investing in Defined Contribution Pension Plans
(University of Waterloo, 2023-09-18)In this thesis, we propose a novel data-driven neural network (NN) optimization framework for solving an optimal stochastic control problem under stochastic constraints. The NN utilizes customized output layer activation ... -
Sentiment Lexicon Induction and Interpretable Multiple-instance Learning in Financial Markets
(University of Waterloo, 2020-09-28)Sentiment analysis has been widely used in the domain of finance. There are two most common textual sentiment analysis methods in finance: \textit{dictionary-based approach} and \textit{machine learning approach}. The ... -
Trust Region Methods for Training Neural Networks
(University of Waterloo, 2017-11-09)Artificial feed-forward neural networks (ff-ANNs) serve as powerful machine learning models for supervised classification problems. They have been used to solve problems stretching from natural language processing to ...