Intraday Trading and Analysis and Monitoring Trader Behavior

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.

Statistical Analysis of Women’s Representation in the Animation and Visual Effects Industry in Vancouver

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 beyond the normal limits

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.

Modeling regime changes to improve portfolio diversification and performance

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.

Retirement income and wealth management analytics

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.

Portfolio optimization and risk analysis

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.

A weighted graph approach to IP geolocation

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.

Aboveground Storage Tank (AST) tightness testing using statistical approach

The industry partner, Cantest is establishing a new leak detection procedure for analyzing data sources in aboveground storage tanks and statistical learning models to monitor AST shell dynamics and product activity over time. This is an important problem as identifying leak detection is usually associated with various environmental data and records collected from sensitive sensors attached to the ASTs. Current testing procedure for leak detection uses simple statistical rules and thresholds to detect anomalies. These methods are failing for preventing AST related environmental incidents.

Developing statistical methods to discover genetic variants underlying longitudinal decline in lung function

COPD is a common inflammatory lung condition that is characterized by airflow limitation and symptoms of cough and shortness of breath. Globally, it affects 384 million people and is responsible for ~4-7% of all deaths. Longitudinal genome-wide association studies (GWAS) are needed to unravel the molecular determinants of dynamic quantitative traits underlying COPD, such as decline in lung function over time.
Analysis of longitudinal GWAS to find biomarker of lung function decline was unsuccessful in the past. None of the discovered biomarkers were replicable.

Prediction models for pain volatility and engagement patterns of mobile pain app users

Pain is among the top 3 most common reasons for seeking medical help. ManagingLife has developed a mobile-based app, called Manage My Pain, to help chronic-pain patients by providing a simplistic, customizable and comprehensive interface to track pain symptoms and pain experience at a frequency chosen by the users. ManagingLife is interested in understanding the benefits of the app use on its 27,000 and constantly growing user base by identifying user cohorts that ultimately experience improvement in pain experience given self-disclosure tracking behaviours.

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