Improving estimates of complex option-based employee compensation

Stock-based compensation allows employers and employees to share in the risks and rewards of their company’s success. In addition to intangible benefits such as team building and goal sharing, there can also be large financial rewards for employees and similar costs to employers. These costs must be reported in the company’s financial documents such as quarterly and annual reports. Current (and future) vesting rules for stock options are making them difficult to price, and this makes financial reporting difficult.

Scalability of an autonomous trading platform

This project will build on the work previously completed in the Mitacs project done by Dr. Michael Bauer, Omid Mola and Cyborg Trading Systems (CTS) – Integration of an Autonomous Trading Platform. The previous project formed the foundation of developing an autonomic system in an algorithmic trading application. The initial project was successful in determining that an autonomic system could be implemented by utilizing CTS’s proprietary framework.

Bootstrapping yield curves

Financial market’s stability depends on the accurate pricing of financial products traded in the market. This makes accurate pricing of products a top priority for the banks and financial instruments. Inaccurate prices can lead to instability in the market and formation of bubbles. This leads into market crashes such as the 2008 crash where the housing prices bubble caused the market crash. This project’s aim is to develop a tool for the bank to price financial products. This tool will provide the information required for pricing a product.

Engendering Dialogue and Meaningful Participation Among Constituencies Working Toward Ending Homelessness in Victoria, BC., Phase II

This work will build on the findings of the literature review conducted in Phase I. Phase II will focus on engaging people with experience of homelessness in vetting and refining inclusionary principles identified in Phase I and developing a draft inclusionary policy for the Greater Victoria Coalition to End Homelessness.The work is also highly relevant to Vancity. The Statement of Values and Commitments, developed in 2000, acts as a compass to guide Vancity’s business decisions and strategies to stay on course. One of the issues most important is addressing homelessness.

Optimization of Long Term Quantitative Market Predictions

Financial markets today are monitored and controlled by machine learning algorithms. The primary objective of this project is to further develop the algorithm for financial market analysis and prediction that the partner possesses at the moment. The algorithm currently demonstrates high accuracy, subject to certain constraints, among which: a small time interval between a prediction and the actual event and not highly efficient computation of indicators. In addition, the current algorithm is missing any form of analysis of the dynamics of distances to training clusters.

Risk minimizing hedging strategy of variable annuity guarantees under stochastic interest rates

A hedge is an investment position intended to offset potential losses, or in our case to pay off potential liabilities. Interest rates play an important role in hedging strategies and risk management for variable annuities and other long-term products. Financial institutions have an urgent need for practical and affordable dynamic hedging strategies. We propose a realistic interest rates model and the so-called risk minimization hedging strategy.

Measuring Sustainability in the Supply Chain at TD Bank Group

The purpose of this project is to develop an original model for evaluating TDBFG’s suppliers on the basis of environmental, social, and/or economic criteria. TDBFG has several initiatives to implement its corporate social responsibility (CSR) strategy. The research will focus on helping TDBFG align its CSR strategy with its supply chain management practices, particularly as it relates to evaluating its suppliers on the basis of sustainability criteria.

Development of an Agent-Based Market Simulator

Financial markets today are monitored and controlled by artificial intelligent algorithms. Developing these artificial intelligent algorithms requires a large amount of testing against complex patterns and phenomena observed in stock market. The main objective of the proposed project is the development of a market simulator. This is highly challenging and yet promising direction that will allow the partner to test some of its algorithms locally before running them in the live market.