CDT’s approach to risk management is rooted in the principles of conventional enterprise risk management strategies employed in the banking and insurance industries. Our proprietary insider activity research in concert with market valuation and economic datapoints drive our probability of risk model (“PBM”) that leverages decades of data to support its conclusions. In real time, we update our PBM to calculate the size of our risk reserve which is capital allocated to cash and cash equivalent securities. The purpose of this reserve is twofold, to anchor returns and opportunistically deploy capital during periods of market turbulence.

Our process is akin to the way an insurance company underwrites risk. For example, car insurance in rural Montana costs significantly less than insuring a car on the congested and expensive streets of Manhattan. At a high level, insurance companies investigate several outside factors that influence premium rates in a specific location such as, population density, historical cost of repairs and crime rates among other datapoints. Our quantitative probability of risk model does much of the same by measuring risk (increasing or decreasing our reserve) based on how crowded the market is, the sentiment of the executives and the health of the economy.