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Price dispersion can be viewed as a measure of trading frictions (or, tautologically, as a violation of the law of one price). It is often attributed to consumer search costs or unmeasured attributes (such as the reputation) of the retailing outlets involved. There is a difference between price dispersion and price discrimination. The latter ...
where is the normal cumulative distribution function. The derivation of the formula is provided in the Talk page. The partial expectation formula has applications in insurance and economics, it is used in solving the partial differential equation leading to the Black–Scholes formula.
where (,) is the price of the option as a function of stock price S and time t, r is the risk-free interest rate, and is the volatility of the stock. The key financial insight behind the equation is that, under the model assumption of a frictionless market , one can perfectly hedge the option by buying and selling the underlying asset in just ...
In fact, the Black–Scholes formula for the price of a vanilla call option (or put option) can be interpreted by decomposing a call option into an asset-or-nothing call option minus a cash-or-nothing call option, and similarly for a put—the binary options are easier to analyze, and correspond to the two terms in the Black–Scholes formula.
A measure of statistical dispersion is a nonnegative real number that is zero if all the data are the same and increases as the data become more diverse. Most measures of dispersion have the same units as the quantity being measured. In other words, if the measurements are in metres or seconds, so is the measure of dispersion.
The marginal revenue function has twice the slope of the inverse demand function. [9] The marginal revenue function is below the inverse demand function at every positive quantity. [10] The inverse demand function can be used to derive the total and marginal revenue functions. Total revenue equals price, P, times quantity, Q, or TR = P×Q.
As the number of discrete events increases, the function begins to resemble a normal distribution. Comparison of probability density functions, () for the sum of fair 6-sided dice to show their convergence to a normal distribution with increasing , in accordance to the central limit theorem. In the bottom-right graph, smoothed profiles of the ...
In statistics, deviance is a goodness-of-fit statistic for a statistical model; it is often used for statistical hypothesis testing.It is a generalization of the idea of using the sum of squares of residuals (SSR) in ordinary least squares to cases where model-fitting is achieved by maximum likelihood.