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Balance Sheet Complexity

Data Feed by Optimum Complexity

Added as Candidate: Oct. 15, 2019

Candidate Product
Candidate Definition
This product is in the review and/or onboarding process towards full availability. It is not currently available for purchase via FactSet.
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Highlights
  • Make more informed investment decisions. Quantitative Complexity Theory pinpoints when a company moves from 'too big to fail' to 'too complex to survive' and helps investors identify the true drivers of risk in the Balance Sheet. In a world dominated by turbulence and inter-dependency, fragility and complexity can significantly impact company profitability.
  • Gain deeper insight into complexity risks embedded in your portfolio companies. Complexity is a fundamental physical property of any system, and increasing uncontrolled complexity is a major threat to all businesses and the global economy. Take advantage of Optimum’s Balance Sheet Complexity Indicator to identify such risks in your portfolio.
  • Leverage a theory with origins in quantum mechanics, systems theory and image analysis. Optimum uses Quantitative Complexity Theory to extract all linear and non-linear relationships between the tradeable components of a system (e.g. an index or investment universe) to construct investment portfolios. It requires no models and accounts for the nonlinearities and dispersion of data using entropy concepts, as opposed to standard deviations.
Feed Coverage
Region CountTypeStart Date
Global 44,000Public Companies1990
North America 5,000Public Companies1990
Europe 1,000Public Companies1990
Feed Details
Evaluate the complexity of portfolio companies based on Quantitative Complexity Theory (QCT). Using at least 12 quarters of company data, Optimum calculates the current complexity and a complexity interval. The upper bound (critical complexity) is the level of complexity above which the company becomes unmanageable, as too much entropy can arise from the Balance Sheet. The lower bound (minimum complexity) is the minimum level of complexity created by the company. Balance sheet items are also ranked according to their contribution to the overall company complexity. Items at the top are the main drivers of complexity and should be addressed by the executive management to reduce the complexity (and increase the manageability) of the company.
Firm Information
Created in 2016, Optimum is the first company to measure complexity based on a proven model-free approach and to launch complexity-based investment strategies. Optimum uses proprietary technology and Quantitative Complexity Theory (QCT), a model-free measure of correlation created by company Co-founder & CTO Dr. Jacek Marcyk, to trade investment portfolios. Optimum also offers risk management advisory services to financial companies.