Let the one-period riskless gross return be , with , and let the physical up probability be . The binomial market has risk-neutral probability
Under its equivalent martingale measure , successive multipliers are independent, taking with probabilities . The risk-neutral pricing function has the extension
For every fixed positive multiplier , the function is convex when is convex. Taking a positive weighted sum preserves convexity. More explicitly, for ,
Thus the pricing extension is convex, and so are its values on the attainable stock-price grid.
The replicating portfolio in a binomial market holds
shares over the next interval. If , put and . These are the secant slopes of on and , respectively. For a convex function, the slope of a secant on a later adjacent interval is no smaller than that on the earlier interval: apply the defining convexity inequality to the middle point , then rearrange. Hence . Using backward option pricing twice gives
The two coefficients are positive and sum to one. Therefore convex-payoff delta monotonicity in a binomial market yields
In particular an up move cannot reduce the stock holding. “Increases” here means nondecreases: an affine payoff gives equality, so strict increase cannot be claimed for every convex payoff.
For the expected utility maximization problem, let be the physical measure and on terminal paths. If a path has up moves, its binomial-market probability density is
Every terminal payoff is replicable in this complete market. Buying a positive payoff with initial wealth therefore imposes the state-price budget constraint . Since the utility function is increasing, the full budget is used. Its derivative and second derivative are
Put . The first-order condition for a positive multiplier gives . The budget determines uniquely. Independence of the successive moves gives
Thus the optimal claim, as a function of the number of up moves, is
Because uniquely determines , this is also a terminal-stock-price payoff, attainable by backward option pricing and claim replication. It rewards states relatively more probable under the investor's physical measure than under the pricing measure. If , the optimum is the riskless payoff .
To prove global optimality rather than merely assert a stationary point, use the tangent inequality for the strictly concave function :
Taking physical expectations makes the last term zero for any fully financed competing claim, and nonpositive for any claim costing less. Therefore , with equality only when almost surely. Finiteness causes no difficulty on the finite binomial tree, and in every terminal state.

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