Investment Models

Business Objective: Systemic Economic Development - Real Asset Focus

In collaboration with the Research Institute of the Finnish Economy, The Conference of Great Lakes and St. Lawrence Governors and Premiers, and the Global CleanTech Cluster Association, FinHub is focusing on fund design principles for industrial renewal.

Industrial renewal refers to the emergence of new or adapted industries or industry clusters, usually by integration of knowledge sectors and IT, or broadly as the result of technological advances. The challenge is how to organize and allocate investment assets from emerging industry clusters, given that they combine:

1. Startups seeking venture capital or corporate investment
2. Small and medium enterprises seeking debt or private equity investment
3. Infrastructure projects seeking bond, debt and/or private equity investment
4. Stocks and bonds

Big data-driven textual data mining, in combination with financial information tied to liquidity, profitability and efficiency, enable asset allocation strategies with risk and return profiles that are attractive to institutional investors such as pension funds and family offices.

Why is investment fund design a topic of academic research endeavor?

Industrial renewal is an expensive and long term value proposition, because it requires industry value chains to realign, expand and integrate as the result of technological innovation, such as IoT and big data analytics. This is where FinTech fits in: IT and AI efficiencies in finance result in the disintermediation of transactions. Algorithms are increasingly taking the place of humans, particularly as the result of deep learning and trend analytics offered by Watson, among others.

The research challenge is to develop the algorithms and uncover the trends, correlations, and investment opportunities in the area of asset risk aggregation and mitigation. Operational algorithmic fund (alg funds) designs capture years of data research.