Cryptocurrency markets exhibit highly chaotic behaviour, differing substantially from securities. This research project looks at the cryptocurrency markets for data–aiming to answer if it possible to create mathematical models which track the overall behaviour of the Cryptocurrency Market, while minimizing risks. Through this research we expect to reconcile the theory developed above with the real life cryptocurrency exchanges and coins.
Within the aerospace sector, aftermarket services account for over 50% of revenue generated by aero engine manufacturers. Central to this is the ability to inspect and repair high unit cost components. Many processes are manual but given the ever-increasing quality, cost and delivery requirements, and the safety critical nature of these rotating parts, there is a strong drive towards process automation.
Machine learning (ML) is a method of training a computer to learn from data and predict future outcomes based on existing patterns in the data. This project aims to utilize various ML methods as new and potentially better analytics and predictive tools in the area of credit risk management for ATB. Given that data quality and flows change over time, a new framework built on Google Cloud Platform to update the machine learning models will also be developed.
Electronic exchanges are venues that provide immediacy for those who need to find a counterparty to their trades. Orders of various types arrive in the market at ever increasing speeds, and in this era of high-frequency trading (HFT), institutional investors are often disadvantaged because of their high-latency relative to faster traders.
The creative industry is one of the vital pillars of the Canadian economy. Furthering the careers of women in business, technical and creative roles in Vancouver can help promote the economic growth of BC creative industry and advancing women into higher roles. Our project is to track the real-time data of the female staff in animation and film studios in Vancouver and analyze the data. The methods for data collection include the traditional ways like making survey and doing interview, and the web-based way to make a database linked by a data collection website.
Risk aggregation is omnipresent in insurance applications. A recent example, borrowed from the modern regulatory accords, is the determination of the aggregate economic capital and its consequent allocation to risk drivers. A more traditional illustration of the importance of risk aggregation in insurance is the celebrated collective risk theory that dates back to the early years of the 20th century. This project will assist Sun Life Financial to build and implement an efficient quantitative framework to approximate the aggregate risk of its portfolio.
Asset allocation – the decision of how to divide a portfolio among the major asset classes such as cash, stocks and bonds – is a key determinant of portfolio performance. Because financial markets go through periods of strong and weak economies, the performance of an asset class varies with shifting economic conditions. These regime shifts pose a challenge to the asset allocation decision because they impact the portfolio’s return and risk.
The Research Group at CANNEX (formerly known as the QWeMA Group) develops solutions for the financial and insurance industry of North America. Our analytics play an important role in determining the value proposition of investment products. Our solutions help the financial community and public through their financial advisors to be able to make informed decisions. We work at the intersection of finance, mathematics, actuarial science, and computer science.
In recent years, the use of Mathematics and Statistics in Finance has become increasingly important, with the arrival of new software and investment methods. The notion of market efficiency, particularly the assumption that assets are always correctly priced, suffers from market anomalies which lead to potential arbitrage strategies in the short run. Therefore, this project aims to model portfolios using market anomalies and traditional finance methods. The goal is to develop a step-by-step procedure for portfolio selection and implement it in software.
When you load a page on the internet, or watch a video, or send an email, packets of information travel along a path from your computer to the destination. Where does this path go? If both you and your destination are located in the same country, does the path respect international boundaries? We propose a method for answering these questions that builds upon previous techniques. Our partner organization, CloudPBX Inc, develops and operates network infrastructure for telephonic communications.