From 5d10bb8071b16820057bf7499cf66ac0673f460c Mon Sep 17 00:00:00 2001
From: "Keith A. Lewis" April 23, 2024 April 25, 2024 This note assumes you are familiar with measure theory and stochastic
-processes, but are not necesarily an expert. We provide a mathematically
-rigorous model for any set of instruments that can be used to value,
-hedge, and understand how poorly risk-neutral pricing can be used for
-managing risk. It does not provide a solution, only an initial framework
-for for further research.Unified Model
-
Let T be the set of trading times, @@ -70,14 +92,14 @@
If {\mathcal{A}} is a finite algebra of sets on \Omega then the atoms of {\mathcal{A}}, \bar{{\mathcal{A}}}, form a partition of -\Omega. A function \underline{{\mathcal{A}}}, form a partition +of \Omega. A function X\colon\Omega\to\boldsymbol{R} is {\mathcal{A}} measurable if and only if it is constant on atoms of {\mathcal{A}} so X\colon\bar{{\mathcal{A}}}\to\boldsymbol{R} -is a function.
+class="math inline">X\colon\underline{{\mathcal{A}}}\to\boldsymbol{R} +is a function.If P is a probability measure on \Omega and X\colon\Omega\to\boldsymbol{R} is a random @@ -86,49 +108,30 @@
Price – X_t\colon\underline{{\mathcal{A}}}_t\to\boldsymbol{R}^I +market prices assuming perfect liquidity.
+Cash flow – C_t\colon\underline{{\mathcal{A}}}_t\to\boldsymbol{R}^I +dividends, coupons, margin adjustments for futures.
Trading Strategy – \tau_0 < +\cdots < \tau_n stopping times and trades \Gamma_j\colon\underline{{\mathcal{A}}}_{\tau_j}\to\boldsymbol{R}^I
+Position – \Delta_t = \sum_{\tau_j +< t}\Gamma_j = \sum_{s < t} \Gamma_s accumulate trades +not including last trades.
Value – V_t = (\Delta_t + +\Gamma_t)\cdot X_t mark-to-market existing positions and current +trades at current prices.
+Account – A_t = \Delta_t\cdot C_t +- \Gamma_t\cdot X_t receive cash flows proportional to position +and pay for current trades.
The Fundamental Theorem of Asset Pricing states there is no arbitrage if and only if there exist deflators, positive measures D_t\colon{\mathcal{A}}_t\to(0,\infty), {t\in T} on \Omega, with +class="math inline">D_t on {\mathcal{A}}_t, {t\in T}, with \tag{1} X_t D_t = (X_u D_u + \sum_{t < s \le u} C_s D_s)|{{\mathcal{A}}_t} - Note if cash flows are zero then deflated prices are a -martingale. If there are a finite number of cash flows then prices are -determined by deflated future cash flows.
+ A martingale measure satisfies M_t = M_u|{\mathcal{A}}_t for t \le u. Note if cash flows are zero then +deflated prices are a martingale measure. If X_u D_u goes to zero as u goes to infinity then prices are determined +by deflated future cash flows.Lemma. If X_t D_t = M_t - -\sum_{s\le t} C_s D_s where M_t = -M_u|{{\mathcal{A}}_t}, t \le u, -then there is no arbitrage.
+\sum_{s\le t} C_s D_s where M_t +is a martingale measue then there is no arbitrage.Lemma. For any arbitrage free model and any trading
strategy
\tag{2} V_t D_t = (V_u D_u + \sum_{t < s \le u} A_s
@@ -168,61 +174,61 @@ Suppose a derivative security specifies amounts \bar{A}_j be paid at times \bar{\tau}_j. If there is a trading strategy
-(\tau_j, \Gamma_j) with A_{\bar{\tau}_j} = \bar{A}_j for all j and A_t =
-0 otherwise (aka self-financing) then a “perfect hedge” exists\overline{A}_jArbitrage
Application
Note V_t D_t= (\sum_{\tau_j > t} -\bar{A}_j D_{\bar{\tau_j}})|{\mathcal{A}}_t can be computed from -the deriviative contract specification and the deflators D_t. Since V_t = -(\Delta_t + \Gamma_t)\cdot X_t we have \Delta_t + \Gamma_t, is the Frechet -derivative D_{X_t}V_t of option value -with respect to X_t.
+\overline{A}_j D_{\overline{\tau_j}})|{\mathcal{A}}_t can be +computed from the derivative contract specification and the deflators +D_t. Since we also have V_t = (\Delta_t + \Gamma_t)\cdot X_t the +Frechet derivative D_{X_t}V_t of option +value with respect to X_t is \Delta_t + \Gamma_t.If time T = \{t_j\} is discrete we can compute a possible hedge at each time, \Gamma_j = D_{X_j}V_j - \Delta_j, since \Delta_j is known at t_{j-1}. In general this hedge will not exactly replicate the derivative contract obligation.
+Note the Unified Model does not require Ito’s formula, much less a +proof involving partial differential equations and change of measure. +One simply writes down a martingale and deflator then uses equation (2) +to value, hedge, and manage the risk of realistic trading strategies. +The notion of “continuous time” hedging is a mathematical myth.
The Black-Scholes/Merton model uses M_t = (r, s\exp(\sigma B_t - \sigma^2t/2)P, where B_t is Brownian motion and P is Weiner measure The deflator is D_t = \exp(-\rho t).
-Note the Unified Model does not require Ito’s formula and a proof -involving partial differential equations. One just writes down a -martingale and deflator then uses equation (2) to value, hedge, and -manage the risk of trading strategies that can be performed. The notion -of “continuous time” hedging is a mathematical myth.
+class="math inline">B_t is Brownian motion, P is Wiener measure, and the deflator is +D_t = \exp(-\rho t)P.If repurchase agreements are available then a canonical deflator exists. A repurchase agreement over the interval [t_j, t_{j+}] is specified by a rate [t_j, t_{j+1}] is specified by a rate f_j known at time t_j. The price at t_j is 1 and -it has a cash flow of \exp(f_j(t_{j+1} - -t_j)) at time t_{j+1}. By -equation (1) we have D_j = \exp(f_j\Delta -t_j)D_{j+1}|{\mathcal{A}}_j. If {\exp(f_j(t_{j+1} - +t_j))} at time t_{j+1}. By +equation (1) we have {D_j = \exp(f_j\Delta +t_j)D_{j+1}|{\mathcal{A}}_j}. If D_{j+1} is known at time t_j then D_{j+1}/D_j = \exp(-f_j\Delta t_j) and D_j = \exp(-\sum_{i < j}f_i\Delta t_i) is -the canonical deflator.
+class="math inline">{D_{j+1}/D_j = \exp(-f_j\Delta t_j)} and +{D_j = \exp(-\sum_{i < j}f_i\Delta +t_i)} is the canonical deflator.The continuous time analog is D_t = \exp(-\int_0^t f(s)\,ds) where f -is the continuously componded instantaneous forward rate.
+is the continuously compounded instantaneous forward rate.A forward rate agreement with coupon f over the interval [u,v] having day count convention \delta has two cash flows: -1 at time t -and 1 + f\delta(u,v) at time u. The par forward coupon at time -t, F_t^\delta(u,v) is the coupon for which the -price is 0 at time t. By equation (1) -we have 0 = (-D_u + (1 + +class="math inline">\delta2 has two cash flows: +-1 at time t and 1 + +f\delta(u,v) at time u. The +par forward coupon at time t, +F_t^\delta(u,v) is the coupon for which +the price is 0 at time t. By equation +(1) we have 0 = (-D_u + (1 + F_t^\delta(u,v))D_v|{\mathcal{A}}_t so F_t^\delta(u,v) = \frac{1}{\delta(u,v)}\bigl(\frac{D_t(u)}{D_t(v)} - 1\bigr).
A swap is a collection of back-to-back forward rate
-agreements. The swap par coupon makes the price 0 at time (t_j). The
+swap par coupon makes the price 0 at time t so
F_t^\delta(t_0,\dots,t_n) = \frac{D_t(t_0) -
D_t(t_n)}{\sum_{j=1}^n\delta(t_{j-1},t_j)D_t(t_j)}.
@@ -271,20 +279,20 @@ Companies can default and may pay only a fraction of the notional
-owed on bonds they issued. A simple model for this is to assume the time
-of default is a random variable T and
-recovery R is a constant fraction
-between 0 and 1.2 The sample space for the default
-time is [0,\infty) indicating the time
-of default. The information available at time t is the partition consisting of singletons
-\{s\}, s <
+owed on bonds they issued. A simple model3 for
+this is to assume the time of default T
+and recovery R are random variables.
+The sample space for the default time is [0,\infty) indicating the time of default.
+The information available at time t is
+the partition consisting of singletons \{s\}, s <
t and the set [t, \infty). If
default occurs prior to t then we know
-exactly when it happend. If default has not occured by time t then we only know it can be any time after
-that.Forward Rate Agreement
Risky Bonds
The cash flows for a risky bond D^{T,R}(u) are 1 at time u if T >
@@ -292,13 +300,22 @@ Risky Bonds
class="math inline">T if T \le
t. For the model to be arbitrage-free we must have
- D_t^{R,T}(u) D_t = (D_u 1(T > u) + RD_t 1(T\le
-u)|{\mathcal{A}}_t.
- If the interest rate is 0 then D_t =
-1 and D_0^{R,T} = P(T > u) + RP(T\le
-u).
We need to extend the sample space to model the default time, \Omega' = \Omega\times [0,\infty).
+D_t^{R,T}(u) D_t = \bigl(1(T > u)D_u + 1(T\le u)R +D_T\bigr)|{\mathcal{A}}_t. + If the deflators are independent of the stopping time and +recovery is RD(T,u) at T\le u for some constant R then using D_T(u)D_T = D_u|{\mathcal{A}}_t for T \le u we have + D_t^{T,R}(u) D_t P(T > t) = \bigl(P(T > u) + R P(t < T \le +u)\bigr)D_u|{\mathcal{A}}_t. + The credit spread \lambda_t^{T,R}(u) is defined by {D_t^{T,R}(u) = D_t(u)\exp(-\lambda_t^{T,R}(u) (u - +t))}. Note if T = \infty or +R = 1 then the credit spread is +zero. +Perfect hedges never exist.↩︎
This is a very simplified model. The day count fraction \delta(u, v) is approximately v - u in years.↩︎
This is a very simplified model.↩︎