Financial systems analysis: Opening the future to closed-end funds

This paper investigates a systematic quantitative investment strategy utilizing closed-end funds (CEFs). CEFs are advantageous to investors because they can be traded at a discount from their net asset value (NAV), as opposed to mutual funds which are traded at their exact NAV. The authors seek to explore different methods for taking advantage of this discount. They developed a program that exploits arbitrage opportunities from the fluctuating discount by utilizing a dynamic moving average and standard deviation. The program also fits an autoregressive integrated moving average (ARIMA) time series model to the data and attempts to predict the next price point. Using all of this information, the program decides to buy, sell, or hold a current position. Investors make many decisions using emotions and other biases that lead to the market mispricing a given stock or fund. Throughout the history of the stock market, and emphasized by the 2008 through 2009 economic crisis, brokers have been unable to correctly assess the risk in a trading decision. Automating the trading process through systematic quantitative methods removes the human element from the process by adding consistency to investing. In 1980, Thomas Herzfeld published groundbreaking research on CEFs; they are still a relatively small market and there is potential for more research and discovery in this field. The aim of this research is to develop an algorithm that will find above average returns while not accepting above average risk.