Type of Document Master's Thesis Author Kodra, Bledar Author's Email Address email@example.com URN etd-04232007-125139 Title Risk Analysis of Tilapia Recirculating Aquaculture Systems: A Monte Carlo Simulation Approach Degree Master of Science Department Agricultural and Applied Economics Advisory Committee
Advisor Name Title Taylor, Daniel B. Committee Chair Bosch, Darrell J. Committee Member McLean, Ewen W. Committee Member Keywords
- Risk Analysis
- Recirculating Aquaculture Systems
- Monte Carlo Simulation
Date of Defense 2007-04-06 Availability unrestricted AbstractRisk Analysis of Tilapia Recirculating Aquaculture Systems:
A Monte Carlo Simulation Approach
The purpose of this study is to modify an existing static analytical model developed for a Re-circulating Aquaculture Systems through incorporation of risk considerations to evaluate the economic viability of the system. In addition the objective of this analysis is to provide a well documented risk based analytical system so that individuals (investors/lenders) can use it to tailor the analysis to their own investment decisions—that is to collect the input data, run the model, and interpret the results. The Aquaculture Economic Cost Model (AECM) was developed by Dr. Charles Coale, Jr. and others from the department of Agricultural and Applied Economics at Virginia Tech. The AECM is a spreadsheet model that was developed to help re-circulating aquaculture producers make strategic business decisions. The model can be used by potential producers interested in investing in re-circulating aquaculture through development of a financial analysis that in turn will help them obtain funding for the enterprise. The model is also useful for current producers who want to isolate inefficient aspects of their operation. AECM model consists of three major sections which include the Data Entry, Calculations and Analysis. The first section requires that the producer conducts background research about their operation to ensure accurate calculation and analysis. The calculation section provides a great deal of information about the operation’s finances, while the analysis section provides information about the operation’s financial stability. While the AECM is a powerful model, it is based on single, usually mean, values for prices, costs, and input and output quantities. However, market, financial and production uncertainties result in fluctuating prices, costs and yields. An individual who is making management decisions for a re-circulating aquaculture system will be faced with some or all of these uncertainties. By adding simulation to the AECM model to account for these uncertainties individuals will be able to make better management decisions. Information of the varying likelihoods or probabilities of achieving profits will be of crucial interest to individuals who plan on entering into or modifying an existing aquaculture system. Risks associated with six variables were examined in this paper: feed cost, feed conversion, mortality rate, capital interest rate, final weight, and output price. Data for the Interest Rate and output price were obtained from the Federal Reserve System and NMFS website respectively. Expert opinion was the source of data for the other variables. After probability distributions were applied to the random variables to account for the uncertainty the model was simulated for ten thousand iterations to obtain expected returns for three years in advance that the model calculates an income statement. In addition to that, sensitivity analyses were carried out in order to inform the producer which factors are contributing the most to the profitability of the operation. In this way the producer will have a better idea as to which aspects of the operation to monitor closely and consider modifying. The analysis shows that the mean income for the three years will be negative and thus the business would be losing money. The simulated mean net incomes were: -$216,905, -$53,689, -$53,111 for year1 through year3 respectively. Sensitivity analysis confirmed that output price is by far the most significant input that makes the overall bottom line to fluctuate most. Output price was on top of the list for all the three years analyzed in this study. Feed cost and Feed conversion were the next most significant inputs. The other inputs were also significant in explaining the fluctuation of the bottom line; however both their regression and correlation coefficients were small.
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