This study analyses the financial risk faced by representative mixed-enterprise farm businesses in four regions of south-eastern Australia. It uses discrete stochastic programming to optimise the ten-year cash flow margins produced by these farms operating three different farming systems. Monte Carlo analysis is used to produce a risk profile for each scenario, derived from multiple runs of this optimised model, randomised for commodity prices and decadal growing season rainfall since 1920. This analysis shows that the performance of the enterprise mixes at each site is characterised more by the level of variability of possible outcomes than by the mean values of financial outputs. It demonstrates that relying on mean values for climate and prices disguises the considerable risks involved with cropping in this area. Diversification into a Merino sheep enterprise marginally reduced the probability of financial loss at all sites. This study emphasises the fact that the variability, or risk, associated with all scenarios far exceeds the likely change in cash margins due to innovation and good management. It further shows that farm managers should give a higher priority to adopting innovations which reduce costs, rather than increase productivity, in order to reduce risk. Further analysis shows that the current static measures of financial performance (gross margins, profit and cash margins) do not characterise the risk-adjusted performance of the various farming systems and almost certainly result in a flawed specification of best-practice farm management in south-eastern Australia.