Logarithmic Utility in Statistics
A logarithmic utility function helps compare uncertain wealth choices. It is common in decision theory, economics, and applied statistics. The curve rises as wealth rises. Yet each extra unit gives less added utility. This pattern is called diminishing marginal utility. It matches many risk averse decisions. A person may prefer a sure moderate gain over a risky larger gain.
Why This Calculator Matters
This calculator estimates utility for two possible outcomes. It also returns expected utility, expected terminal wealth, certainty equivalent, and risk premium. These measures help explain choices under uncertainty. They can support portfolio reviews, insurance examples, business decisions, and classroom models. The shift value lets you keep every log input positive. The scale and vertical shift let you match a custom utility model.
Understanding the Outputs
Expected utility is the probability weighted average of outcome utilities. It is not the same as utility from expected wealth. That difference shows risk aversion. The certainty equivalent is the guaranteed wealth giving the same utility as the risky choice. When expected wealth is higher than the certainty equivalent, the gap is the risk premium. A larger gap means the risky option demands more compensation.
Advanced Interpretation
Marginal utility shows how much utility changes near the expected wealth point. For log utility, relative risk aversion is one. Absolute risk aversion falls as shifted wealth grows. This means the same cash risk matters less to someone with higher wealth. Base selection changes the utility scale, not the ranking, when scale is positive.
Practical Use
Use realistic probabilities and outcome values. Check that probabilities represent the same period. Enter losses as negative values. Add a shift only when wealth plus outcomes can reach zero or below. Review the certainty equivalent before making a final decision. The model is powerful, but it is still an assumption. Actual behavior may include taxes, liquidity needs, goals, and emotions.
Best Practice
Compare several cases. Change one input at a time. Watch how the risk premium moves. Save CSV results for audit trails. Use the report option for quick sharing. Keep notes beside each scenario. This makes future reviews easier and improves statistical judgement. Label each trial clearly before comparing final decisions across scenarios later.