FTAP History

Keith A. Lewis

June 10, 2025

Mathematical model.

T - trading times

I - instruments

\Omega - sample space of possible outcomes

(\mathcal{A}_t)_{t\in T} - information at time t is a partition of \Omega

X_t\colon\mathcal{A}_t\to\boldsymbol{{{R}}}^I - prices

C_t\colon\mathcal{A}_t\to\boldsymbol{{{R}}}^I - cash flows

\tau_0 < \cdots < \tau_n, \Gamma_j\colon\mathcal{A}_{\tau_j}\to\boldsymbol{{{R}}}^I - trading strategy

\Delta_t = \sum_{\tau_j < t} \Gamma_j = \sum_s < t} \Gamma_s - position

$V_t = (_t + _t)X_t - value

A_t = \Delta_t\codt C_t - \Gamma_t\cdot X_t - amount

X_t D_t = (\sum_{u > t} C_u D_u)|_{\mathcal{A}_t}

V_t D_t = (\sum_{u > t} A_u D_u)|_{\mathcal{A}_t}

1971

A. Beja

“The Structure of the Cost of Capital under Uncertainty”

The present study represents an attempt at a slightly different approach. We postulate the existence of equilibrium prices for capital assets under uncertainty, and then proceed to analyze the properties implicit in their definition. It is shown that some results can be derived without recourse to the way individuals make decisions, their detailed preferences or their subjective assessments of probabilities

Section II. T finite times. S state space, (e_t^i)_i partition of S at t\in T. Z = \boldsymbol{{{R}}}^{\cup_{t,i} e_t^i} is prospect space.