Identifying and Dealing with the Approach of Bears and their Departure
Thompson, James R.
Doctor of Philosophy
Based on the identification of market dynamics, capital allocation in long positions can be dynamically controlled by means of interrupting an otherwise strictly-long investment strategy allowing for an overall improved risk profile and faster response times during periods of persistent negative market returns. Herein, a portfolio selection methodology updating a reasonably diversified selection of competing S&P 500 constituents within and across various predefined industry groups and which produced above average long-term returns with minimized downside-risk, is proposed. Within the various predefined groups of stocks, Simugram methods are used to model and optimize on the distribution of returns up to and including a horizon of interest. Improvements to previous methods are focused toward calibrating the sampling distribution based on an empirical dataset within the various groups comprising the investor's portfolio, optionally allowing for a varying sampling frequency as dictated by the various group dynamics. By combining within-group optimization alongside with the capability of exiting aggressive long-strategies at seemingly riskier times, focus is on providing more frequent updates on a list of constituents with improved performance in both terms of risk and return.