The expected utility of the above bet (with a 50% chance of receiving 100 and a %50 chance of receiving 0) is
E(u)=u(0)+u(100)2E(u)=\frac{u(0)+u(100)}{2} E(u)=2u(0)+u(100)​
and if the person has the utility function with u(0)=0,u(40)=5,u(100)=10u(0)=0,\;u(40)=5,\;u(100)=10u(0)=0,u(40)=5,u(100)=10 then the expected utility of the bet equals 5, which is the same as the known utility of the amount 40. Hence the certainty equivalent is 40.

The risk premium is ($50 minus $40) = $10, or in proportional terms :
KaTeX parse error: Can't use function '$' in math mode at position 10: \frac{$̲50-$40}{$40}
or 25% (where $50 is the expected value of the risky bet). This risk premium means that the person would be willing to sacrifice as much as $10 in expected value in order to achieve perfect certainty about how much money will be received. In other words, the person would be indifferent between the bet and a guarantee of $40, and would prefer anything over $40 to the bet.

In the case of a wealthier individual, the risk of losing $100 would be less significant, and for such small amounts his utility function would be likely to be almost linear, for instance if u(0)=0u(0)=0u(0)=0 and u(100)=10u(100)=10u(100)=10, then u(40)u(40)u(40) might be 4.00014.00014.0001 and u(50)u(50)u(50) might be 5.00015.00015.0001.

The utility function for perceived gains has two key properties:

  • an upward slope

    The upward slope implies that the person feels that more is better: a larger amount received yields greater utility, and for risky bets the person would prefer a bet which is first-order stochastically dominant over an alternative bet (that is, if the probability mass of the second bet is pushed to the right to form the first bet, then the first bet is preferred)

  • concavity

    The concavity of the utility function implies that the person is risk averse: a sure amount would always be preferred over a risky bet having the same expected value; moreover, for risky bets the person would prefer a bet which is a mean-preserving contraction of an alternative bet (that is , if some of the probability mass of the first bet is spread out without altering the mean to form the second bet, then the first bet is preferred).

  • Measures of risk aversion under expected utility theory

    There are multiple measures of the risk aversion expressed by a given utility function. Several functional forms often used for utility functions are expressed in terms of these measures.

    • Absolute risk aversion

      The higher the curvature of u(c)u(c)u(c), the higher the risk aversion.

      Arrow-Pratt measure of absolute risk aversion (ARA), after the economists Kenneth Arrow and John W.Pratt, also known as the coefficient of absolute risk aversion :
      A(c)=−u′′(c)u′(c)A(c)=-\frac{u^{''}(c)}{u^{'}(c)} A(c)=−u′(c)u′′(c)​
      u′′u^{''}u′′ : the second derivatives with respect to ccc of u(c)u(c)u(c);

      u′u^{'}u′ : the first derivatives with respect to ccc of u(c)u(c)u(c);

    • Relative risk aversion

      Arrow-Pratt measure of relative risk aversion (RRA) or coefficient of relative risk aversion is defined as :
      R(c)=cA(c)=−cu′′(c)u′(c)R(c)=cA(c)=-\frac{cu^{''}(c)}{u^{'}(c)} R(c)=cA(c)=−u′(c)cu′′(c)​
      RRA is a dimension-less quantity.

    • Portfolio Theory

      In MPT, risk aversion is measured as the additional expected reward an investor requires to accept additional risk.

      Here risk is measured as the standard deviation of the return on investment, i.e. the square root of its variance.

      In advanced portfolio theory, different kinds of risk are taken into consideration. They are measured as the n-th root of the n-th central moment.

      The symbol used for risk aversion is AAA or AnA_nAn​ :
      A=dE(c)dσA=\frac{dE(c)}{d\sigma} A=dσdE(c)​

      An=dE(c)dμnA_n=\frac{dE(c)}{d{\sqrt\mu_n}} An​=dμ​n​dE(c)​

lambda=dE(c)dσordE(c)dσ里面包含着lambdalambda=\frac{dE(c)}{d\sigma} \\ or\\ \frac{dE(c)}{d\sigma}里面包含着lambda lambda=dσdE(c)​ordσdE(c)​里面包含着lambda

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