We investigated causal factors driving German hog-price dynamics with an innovative ‘diagnostic’ modeling approach. Hog-price cycles are conventionally attributed to randomly-generated behavior best modeled stochastically—most recently as randomly-shifting sinusoidal oscillations. Alternatively, we applied nonlinear time series analysis to empirically reconstruct a deterministic hog-price attractor from observed hog prices. Hog prices cycle aperiodically along this attractor as time evolves. The empirically diagnosed attractor indicates that causal factors driving the German hog-price cycle are endogenous to the hog industry itself. We next formulated a structural (explanatory) model of the pork industry to synthesize the empirical hog-price attractor and to determine causal factors generating it. Model simulations demonstrate that low price elasticity of demand contributes to aperiodic price cycling—a well know result—and further reveal two other important causal factors: the irreversibility of investment (caused by high specificity of technology), and the liquidity-driven investment behavior of German farmers.