We study the effect of variation in correlation on investment decision in an experimental two‐asset application. Comparison of allocations across problems suggests that subjects neglect probabilistic information on the joint distribution of returns and base their allocations on the observed return levels for the two assets. When asked to predict future returns, subjects try to replicate the historical distribution, thereby falling into the probability‐matching bias. Predictions drastically vary when correlations become negative, while allocations are not significantly affected by changes in sign of correlation. The observed allocation patterns contradict the predictions of standard models of choice; the inconsistency is attributed to common behavioral bias in financial decision. Field implications of the results are discussed.

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Fair value depends on an estimate of the both cash flow and risk, which is not an easy task when valuing startup firms. We present a measurement instrument for the future risk of small and risky firms that follows the major propositions in accounting and finance. It differs from other valuation instruments in looking simultaneously at the assets and liabilities. We test the VBB as a measure for value over time by using a database of VC backed innovative companies that oridary DCF valuation fails to capture their value. We show that the VBB is an effective way to capture the dynamics of the value of high risk firms.

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