Hello, Being a beginner of lyx (no knowledge of latex), I have this lyx-generated latex source (lyxout.txt attached) When doing view / PDF (PDFLatex), latex run 1, I get a few "Missing ... inserted" and these errors:
>>>>>LaTeX Error: \begin{tabular} on input line 90 ended by \end{eqnarray*}. ... & = & d_{1}-\sigma\sqrt{T}\end{eqnarray*} Your command was ignored. Type I <command> <return> to replace it with another command, or <return> to continue without it. >>>>>Too many }'s. \end{tabular} \begin{tabular}{|c|c|c||c|} You've closed more groups than you opened. Such booboos are generally harmless, so keep going. >>>>LaTeX Error: \begin{document} ended by \end{tabular}. \end{tabular} \begin{tabular}{|c|c|c||c|} Your command was ignored. Type I <command> <return> to replace it with another command, or <return> to continue without it. No pdf is generated. The lyx doc contains tables, and a lot of math formulae. Any ideas? Rds, ________________________________ This e-mail is confidential and may contain legally privileged information. It is intended only for the addressees. If you have received this e-mail in error, kindly notify us immediately by telephone or e-mail and delete the message from your system.
% Preview source code %% LyX 1.5.2 created this file. For more info, see http://www.lyx.org/. %% Do not edit unless you really know what you are doing. \makeatletter [EMAIL PROTECTED]"C:/BlackScholes/\string"/}} \makeatother \documentclass[english]{article} \usepackage[T1]{fontenc} \usepackage[latin9]{inputenc} \usepackage{esint} \makeatletter %%%%%%%%%%%%%%%%%%%%%%%%%%%%%% LyX specific LaTeX commands. %% Bold symbol macro for standard LaTeX users \providecommand{\boldsymbol}[1]{\mbox{\boldmath $#1$}} %% Because html converters don't know tabularnewline \providecommand{\tabularnewline}{\\} %%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Textclass specific LaTeX commands. \newenvironment{lyxlist}[1] {\begin{list}{} {\settowidth{\labelwidth}{#1} \setlength{\leftmargin}{\labelwidth} \addtolength{\leftmargin}{\labelsep} \renewcommand{\makelabel}[1]{##1\hfil}}} {\end{list}} \usepackage{babel} \makeatother \begin{document} \title{Black Scholes Merton} \maketitle The standard Black-Scholes framework is extended to cope with time-dependency of the risk-free rate, dividend and volatility parameters. In the following, \begin{lyxlist}{00.00.0000} \item [{$V$}] is the value of the option being priced, \item [{$c$}] the price of a European call \item [{$p$}] the price of a European put \item [{$X$}] the option's strike \item [{$T$}] the option's time to expiration date \item [{$S$}] the price of the contract underlying the option \item [{$\sigma$}] the standard deviation of the continuously compounded log returns, per sqrt of annum, can be constant or time-dependent $\sigma(t)$ \item [{$D$}] the present value of the dividends during the life of the option, discounted at the risk-free rate, in case the underlying contract pays discrete dividends \item [{$q$}] the continuously compounded dividend yield, can be constant or time-dependent $q(t)$ \item [{$r$}] the continuously compounded risk-free rate, can be constant or time-dependent $r(t)$ \item [{$N(.)$}] the cumulative standard normal distribution function \item [{$n(.)$}] the standard normal distribution density function \end{lyxlist} \section{Partial differential equation} $V$ value of the option \[ \frac{\partial V}{\partial t}+\frac{1}{2}\sigma^{2}S^{2}\frac{\partial^{2}V}{\partial S^{2}}+\left[r-q\right]S\frac{\partial V}{\partial S}=rV\] or its time-dependent equivalent\[ \frac{\partial V}{\partial t}+\frac{1}{2}\sigma^{2}(t)S^{2}\frac{\partial^{2}V}{\partial S^{2}}+\left[r(t)-q(t)\right]S\frac{\partial V}{\partial S}=r(t)V\] In general, usual greek formulae remain valid with these replacements $rT$ by $\int_{0}^{T}r(\tau)d\tau$ $qT$ by $\int_{0}^{T}q(\tau)d\tau$ $\sigma^{2}T$ by $\int_{0}^{T}\sigma^{2}(\tau)d\tau$ see Wilmott \section{European call and put (upfront premium)} \subsection{Price} \begin{tabular}{|c|c|c||c|} \hline const $\sigma$ & Discrete dividends $D$ & Continuous dividend yield $q$ & time-dependent $q$\tabularnewline \hline \hline $r$ & \begin{eqnarray*} c & = & (S-D)N(d_{1})-Xe^{-rT}N(d_{2})\\ p & = & Xe^{-rT}N(-d_{2})-(S-D)N(-d_{1})\\ d_{1} & = & \frac{\ln\frac{S-D}{X}+rT+\frac{1}{2}\sigma^{2}T}{\sigma\sqrt{T}}\\ d_{2} & = & d_{1}-\sigma\sqrt{T}\end{eqnarray*} & \begin{eqnarray*} c & = & Se^{-qT}N(d_{1})-Xe^{-rT}N(d_{2})\\ p & = & Xe^{-rT}N(-d_{2})-Se^{-qT}N(-d_{1})\\ d_{1} & = & \frac{\ln\frac{S}{X}+\left(r-q\right)T+\frac{1}{2}\sigma^{2}T}{\sigma\sqrt{T}}\\ d_{2} & = & d_{1}-\sigma\sqrt{T}\end{eqnarray*} & \begin{eqnarray*} c & = & Se^{-\int_{0}^{T}q(\tau)d\tau}N(d_{1})-Xe^{-rT}N(d_{2})\\ p & = & Xe^{-rT}N(-d_{2})-Se^{-\int_{0}^{T}q(\tau)d\tau}N(-d_{1})\\ d_{1} & = & \frac{\ln\frac{S}{X}+rT-\int_{0}^{T}q(\tau)d\tau+\frac{1}{2}\sigma^{2}T}{\sigma\sqrt{T}}\\ d_{2} & = & d_{1}-\sigma\sqrt{T}\end{eqnarray*} \tabularnewline \hline $r(t)$ & \begin{eqnarray*} c & = & (S-D)N(d_{1})-Xe^{-\int_{0}^{T}r(\tau)d\tau}N(d_{2})\\ p & = & Xe^{-\int_{0}^{T}r(\tau)d\tau}N(-d_{2})-(S-D)N(-d_{1})\\ d_{1} & = & \frac{\ln\frac{S-D}{X}+\int_{0}^{T}r(\tau)d\tau+\frac{1}{2}\sigma^{2}T}{\sigma\sqrt{T}}\\ d_{2} & = & d_{1}-\sigma\sqrt{T}\end{eqnarray*} & \begin{eqnarray*} c & = & Se^{-qT}N(d_{1})-Xe^{-\int_{0}^{T}r(\tau)d\tau}N(d_{2})\\ p & = & Xe^{-\int_{0}^{T}r(\tau)d\tau}N(-d_{2})-Se^{-qT}N(-d_{1})\\ d_{1} & = & \frac{\ln\frac{S}{X}+\int_{0}^{T}r(\tau)d\tau-qT+\frac{1}{2}\sigma^{2}T}{\sigma\sqrt{T}}\\ d_{2} & = & d_{1}-\sigma\sqrt{T}\end{eqnarray*} & \begin{eqnarray*} c & = & Se^{-\int_{0}^{T}q(\tau)d\tau}N(d_{1})-Xe^{-\int_{0}^{T}r(\tau)d\tau}N(d_{2})\\ p & = & Xe^{-\int_{0}^{T}r(\tau)d\tau}N(-d_{2})-Se^{-\int_{0}^{T}q(\tau)d\tau}N(-d_{1})\\ d_{1} & = & \frac{\ln\frac{S}{X}+\int_{0}^{T}\left(r(\tau)-q(\tau)\right)d\tau+\frac{1}{2}\sigma^{2}T}{\sigma\sqrt{T}}\\ d_{2} & = & d_{1}-\sigma\sqrt{T}\end{eqnarray*} \tabularnewline \hline \end{tabular}\begin{tabular}{|c|c|c||c|} \hline $\sigma(t)$ & Discrete dividends $D$ & Continuous dividend yield $q$ & time-dependent $q$\tabularnewline \hline \hline $r$ & \begin{eqnarray*} c & = & (S-D)N(d_{1})-Xe^{-rT}N(d_{2})\\ p & = & Xe^{-rT}N(-d_{2})-(S-D)N(-d_{1})\\ d_{1} & = & \frac{\ln\frac{S-D}{X}+rT+\frac{1}{2}\int_{0}^{T}\sigma^{2}(\tau)d\tau}{\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}\\ d_{2} & = & d_{1}-\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}\end{eqnarray*} & \begin{eqnarray*} c & = & Se^{-qT}N(d_{1})-Xe^{-rT}N(d_{2})\\ p & = & Xe^{-rT}N(-d_{2})-Se^{-qT}N(-d_{1})\\ d_{1} & = & \frac{\ln\frac{S}{X}+\left(r-q\right)T+\frac{1}{2}\int_{0}^{T}\sigma^{2}(\tau)d\tau}{\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}\\ d_{2} & = & d_{1}-\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}\end{eqnarray*} & \begin{eqnarray*} c & = & Se^{-\int_{0}^{T}q(\tau)d\tau}N(d_{1})-Xe^{-rT}N(d_{2})\\ p & = & Xe^{-rT}N(-d_{2})-Se^{-\int_{0}^{T}q(\tau)d\tau}N(-d_{1})\\ d_{1} & = & \frac{\ln\frac{S}{X}+rT-\int_{0}^{T}q(\tau)d\tau+\frac{1}{2}\int_{0}^{T}\sigma^{2}(\tau)d\tau}{\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}\\ d_{2} & = & d_{1}-\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}\end{eqnarray*} \tabularnewline \hline $r(t)$ & \begin{eqnarray*} c & = & (S-D)N(d_{1})-Xe^{-\int_{0}^{T}r(\tau)d\tau}N(d_{2})\\ p & = & Xe^{-\int_{0}^{T}r(\tau)d\tau}N(-d_{2})-(S-D)N(-d_{1})\\ d_{1} & = & \frac{\ln\frac{S-D}{X}+\int_{0}^{T}r(\tau)d\tau+\frac{1}{2}\int_{0}^{T}\sigma^{2}(\tau)d\tau}{\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}\\ d_{2} & = & d_{1}-\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}\end{eqnarray*} & \begin{eqnarray*} c & = & Se^{-qT}N(d_{1})-Xe^{-\int_{0}^{T}r(\tau)d\tau}N(d_{2})\\ p & = & Xe^{-\int_{0}^{T}r(\tau)d\tau}N(-d_{2})-Se^{-qT}N(-d_{1})\\ d_{1} & = & \frac{\ln\frac{S}{X}+\int_{0}^{T}r(\tau)d\tau-qT+\frac{1}{2}\int_{0}^{T}\sigma^{2}(\tau)d\tau}{\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}\\ d_{2} & = & d_{1}-\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}\end{eqnarray*} & \begin{eqnarray*} c & = & Se^{-\int_{0}^{T}q(\tau)d\tau}N(d_{1})-Xe^{-\int_{0}^{T}r(\tau)d\tau}N(d_{2})\\ p & = & Xe^{-\int_{0}^{T}r(\tau)d\tau}N(-d_{2})-Se^{-\int_{0}^{T}q(\tau)d\tau}N(-d_{1})\\ d_{1} & = & \frac{\ln\frac{S}{X}+\int_{0}^{T}\left(r(\tau)-q(\tau)\right)d\tau+\frac{1}{2}\int_{0}^{T}\sigma^{2}(\tau)d\tau}{\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}\\ d_{2} & = & d_{1}-\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}\end{eqnarray*} \tabularnewline \hline \end{tabular} \subsection{Delta} \begin{tabular}{|c|c||c|} \hline Discrete dividends $D$ & Continuous dividend yield $q$ & time-dependent $q$\tabularnewline \hline \hline \begin{eqnarray*} \Delta_{c} & = & N(d_{1})\\ \Delta_{p} & = & N(d_{1})-1\end{eqnarray*} & \begin{eqnarray*} \Delta_{c} & = & e^{-qT}N(d_{1})\\ \Delta_{p} & = & e^{-qT}\left[N(d_{1})-1\right]\end{eqnarray*} & \begin{eqnarray*} \Delta_{c} & = & e^{-\int_{0}^{T}q(\tau)d\tau}N(d_{1})\\ \Delta_{p} & = & e^{-\int_{0}^{T}q(\tau)d\tau}\left[N(d_{1})-1\right]\end{eqnarray*} \tabularnewline \end{tabular} \subsection{Gamma} \begin{tabular}{|c|c|c||c|} \hline & Discrete dividends $D$ & Continuous dividend yield $q$ & time-dependent $q$\tabularnewline \hline \hline $\sigma$ & \begin{eqnarray*} \Gamma_{c}=\Gamma_{p} & = & \frac{n(d_{1})}{(S-D)\sigma\sqrt{T}}\end{eqnarray*} & \begin{eqnarray*} \Gamma_{c}=\Gamma_{p} & = & e^{-qT}\frac{n(d_{1})}{S\sigma\sqrt{T}}\end{eqnarray*} & \begin{eqnarray*} \Gamma_{c}=\Gamma_{p} & = & e^{-\int_{0}^{T}q(\tau)d\tau}\frac{n(d_{1})}{S\sigma\sqrt{T}}\end{eqnarray*} \tabularnewline \hline $\sigma(t)$ & \begin{eqnarray*} \Gamma_{c}=\Gamma_{p} & = & \frac{n(d_{1})}{(S-D)\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}\end{eqnarray*} & \begin{eqnarray*} \Gamma_{c}=\Gamma_{p} & = & e^{-qT}\frac{n(d_{1})}{S\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}\end{eqnarray*} & \begin{eqnarray*} \Gamma_{c}=\Gamma_{p} & = & e^{-\int_{0}^{T}q(\tau)d\tau}\frac{n(d_{1})}{S\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}\end{eqnarray*} \tabularnewline \end{tabular} \subsection{Vega} Only defined when the volatility is constant. \begin{tabular}{|c|c||c|} \hline Discrete dividends $D$ & Continuous dividend yield $q$ & time-dependent $q$\tabularnewline \hline \hline \begin{eqnarray*} \upsilon_{c}=\upsilon_{p} & = & (S-D)n(d_{1})\sqrt{T}\end{eqnarray*} & \begin{eqnarray*} \upsilon_{c}=\upsilon_{p} & = & Se^{-qT}n(d_{1})\sqrt{T}\end{eqnarray*} & \begin{eqnarray*} \upsilon_{c}=\upsilon_{p} & = & Se^{-\int_{0}^{T}q(\tau)d\tau}n(d_{1})\sqrt{T}\end{eqnarray*} \tabularnewline \end{tabular} \subsection{Theta} We will demonstrate for the most general case: \begin{eqnarray*} c & = & Se^{-\int_{0}^{T}q(\tau)d\tau}N(d_{1})-Xe^{-\int_{0}^{T}r(\tau)d\tau}N(d_{2})\\ p & = & Xe^{-\int_{0}^{T}r(\tau)d\tau}N(-d_{2})-Se^{-\int_{0}^{T}q(\tau)d\tau}N(-d_{1})\\ d_{1} & = & \frac{\ln\frac{S}{X}+\int_{0}^{T}\left(r(\tau)-q(\tau)\right)d\tau}{\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}+\frac{1}{2}\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}\\ d_{2} & = & \frac{\ln\frac{S}{X}+\int_{0}^{T}\left(r(\tau)-q(\tau)\right)d\tau}{\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}-\frac{1}{2}\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}\end{eqnarray*} \[ \Theta_{c}=-\frac{\partial c}{\partial T}=-S\frac{\partial}{\partial T}\left[e^{-\int_{0}^{T}q(\tau)d\tau}N(d_{1})\right]+X\frac{\partial}{\partial T}\left[e^{-\int_{0}^{T}r(\tau)d\tau}N(d_{2})\right]\] \[ =-S\left[-q(T)e^{-\int_{0}^{T}q(\tau)d\tau}N(d_{1})+e^{-\int_{0}^{T}q(\tau)d\tau}n(d_{1})\frac{\partial d_{1}}{\partial T}\right]+X\left[-r(T)e^{-\int_{0}^{T}r(\tau)d\tau}N(d_{2})+e^{-\int_{0}^{T}r(\tau)d\tau}n(d_{2})\frac{\partial d_{2}}{\partial T}\right]\] \[ =Sq(T)e^{-\int_{0}^{T}q(\tau)d\tau}N(d_{1})-Xr(T)e^{-\int_{0}^{T}r(\tau)d\tau}N(d_{2})-Se^{-\int_{0}^{T}q(\tau)d\tau}n(d_{1})\frac{\partial d_{1}}{\partial T}+Xe^{-\int_{0}^{T}r(\tau)d\tau}n(d_{2})\frac{\partial d_{2}}{\partial T}\] \[ \frac{\partial d_{1}}{\partial T}=\frac{\left[r(T)-q(T)\right]\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}-\left[\ln\frac{S}{X}+\int_{0}^{T}\left(r(\tau)-q(\tau)\right)d\tau\right]\frac{\sigma^{2}(T)}{2\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}}{\int_{0}^{T}\sigma^{2}(\tau)d\tau}+\frac{1}{2}\frac{\sigma^{2}(T)}{2\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}\] \[ \frac{\partial d_{2}}{\partial T}=\frac{\left[r(T)-q(T)\right]\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}-\left[\ln\frac{S}{X}+\int_{0}^{T}\left(r(\tau)-q(\tau)\right)d\tau\right]\frac{\sigma^{2}(T)}{2\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}}{\int_{0}^{T}\sigma^{2}(\tau)d\tau}-\frac{1}{2}\frac{\sigma^{2}(T)}{2\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}\] \[ n(d_{1})=\frac{1}{\sqrt{2\pi}}e^{-\frac{d_{1}^{2}}{2}}=\frac{1}{\sqrt{2\pi}}\exp\left[-\frac{\left[\ln\frac{S}{X}+\int_{0}^{T}\left(r(\tau)-q(\tau)\right)d\tau\right]^{2}}{2\int_{0}^{T}\sigma^{2}(\tau)d\tau}\right]\exp\left[-\frac{1}{8}\int_{0}^{T}\sigma^{2}(\tau)d\tau\right]\exp\left[-\frac{1}{2}\left[\ln\frac{S}{X}+\int_{0}^{T}\left(r(\tau)-q(\tau)\right)d\tau\right]\right]\] \[ n(d_{2})=\frac{1}{\sqrt{2\pi}}e^{-\frac{d_{2}^{2}}{2}}=\frac{1}{\sqrt{2\pi}}\exp\left[-\frac{\left[\ln\frac{S}{X}+\int_{0}^{T}\left(r(\tau)-q(\tau)\right)d\tau\right]^{2}}{2\int_{0}^{T}\sigma^{2}(\tau)d\tau}\right]\exp\left[-\frac{1}{8}\int_{0}^{T}\sigma^{2}(\tau)d\tau\right]\exp\frac{1}{2}\left[\ln\frac{S}{X}+\int_{0}^{T}\left(r(\tau)-q(\tau)\right)d\tau\right]\] \[ =n(d_{1})\exp\left[\ln\frac{S}{X}+\int_{0}^{T}\left(r(\tau)-q(\tau)\right)d\tau\right]=n(d_{1})\frac{S}{X}e^{^{\int_{0}^{T}r(\tau)d\tau}}e^{^{-\int_{0}^{T}q(\tau)d\tau}}\] \[ \Theta_{c}=Sq(T)e^{-\int_{0}^{T}q(\tau)d\tau}N(d_{1})-Xr(T)e^{-\int_{0}^{T}r(\tau)d\tau}N(d_{2})\] \[ -Se^{-\int_{0}^{T}q(\tau)d\tau}n(d_{1})\frac{\partial d_{1}}{\partial T}+Xe^{-\int_{0}^{T}r(\tau)d\tau}n(d_{2})\frac{\partial d_{2}}{\partial T}\] \[ =Sq(T)e^{-\int_{0}^{T}q(\tau)d\tau}N(d_{1})-Xr(T)e^{-\int_{0}^{T}r(\tau)d\tau}N(d_{2})\] \[ -Se^{-\int_{0}^{T}q(\tau)d\tau}n(d_{1})\frac{\partial d_{1}}{\partial T}+Xe^{-\int_{0}^{T}r(\tau)d\tau}n(d_{1})\frac{S}{X}e^{^{\int_{0}^{T}r(\tau)d\tau}}e^{^{-\int_{0}^{T}q(\tau)d\tau}}\left[\frac{\partial d_{1}}{\partial T}-\frac{\sigma^{2}(T)}{2\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}\right]\] \[ =Sq(T)e^{-\int_{0}^{T}q(\tau)d\tau}N(d_{1})-Xr(T)e^{-\int_{0}^{T}r(\tau)d\tau}N(d_{2})\] \[ -Se^{-\int_{0}^{T}q(\tau)d\tau}n(d_{1})\frac{\partial d_{1}}{\partial T}+n(d_{1})Se^{^{-\int_{0}^{T}q(\tau)d\tau}}\left[\frac{\partial d_{1}}{\partial T}-\frac{\sigma^{2}(T)}{2\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}\right]\] \[ \Theta_{c}=Sq(T)e^{-\int_{0}^{T}q(\tau)d\tau}N(d_{1})-Xr(T)e^{-\int_{0}^{T}r(\tau)d\tau}N(d_{2})-Se^{-\int_{0}^{T}q(\tau)d\tau}n(d_{1})\frac{\sigma^{2}(T)}{2\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}\] Similarily, the theta for a european put is \[ \Theta_{p}=-Sq(T)e^{-\int_{0}^{T}q(\tau)d\tau}N(-d_{1})+Xr(T)e^{-\int_{0}^{T}r(\tau)d\tau}N(-d_{2})-Se^{-\int_{0}^{T}q(\tau)d\tau}n(d_{1})\frac{\sigma^{2}(T)}{2\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}\] \subsection{Rho} Only defined when the riskfree rate is constant. \begin{tabular}{|c} \hline \begin{eqnarray*} \rho_{c} & = & XTe^{-rT}N(d_{2})\\ \rho_{p} & = & -XTe^{-rT}N(-d_{2})\end{eqnarray*} \tabularnewline \end{tabular} \subsection{DDiv} Only defined when the dividend yield is a constant. \begin{tabular}{|c} \hline \begin{eqnarray*} \left.\frac{\partial}{\partial q}\right\rfloor _{c} & = & -STe^{-qT}N(d_{1})\\ \left.\frac{\partial}{\partial q}\right\rfloor _{p} & = & STe^{-qT}N(-d_{1})\end{eqnarray*} \tabularnewline \end{tabular} \section{European call put (futures-style margining)} Note that all exchange-listed options where the premium is handled with futures-style margining are american. However, we can consider the European case. Let $c$and $p$ be the upfront premium options, and $C$ and $P$ the equivalent margined options. \subsection{Price} $C=e^{rT}c$ or $C=e^{\int_{0}^{T}r(\tau)d\tau}c$ , the same for puts. \subsection{Delta, Gamma, Vega, ddiv} All these are derivatives w.r.t. a parameter that is neither $r$ nor $T$. So: \[ \Delta_{C,P}=e^{\int_{0}^{T}r(\tau)d\tau}\Delta_{c,p}\] \[ \Gamma_{C,P}=e^{\int_{0}^{T}r(\tau)d\tau}\Gamma_{c,p}\] \[ \upsilon_{C,P}=e^{\int_{0}^{T}r(\tau)d\tau}\upsilon_{c,p}\] \[ \left.\frac{\partial}{\partial q}\right\rfloor _{C,P}=e^{\int_{0}^{T}r(\tau)d\tau}\left.\frac{\partial}{\partial q}\right\rfloor _{c,p}\] \subsection{Theta\[ \theta_{C,P}=-\frac{\partial C,P}{\partial T}=-\frac{\partial\left[e^{\int_{0}^{T}r(\tau)d\tau}c,p\right]}{\partial T}\] \[ \theta_{C,P}=-r(T)e^{\int_{0}^{T}r(\tau)d\tau}c,p+e^{\int_{0}^{T}r(\tau)d\tau}\theta_{c,p}\] \[ \theta_{C,P}=-e^{\int_{0}^{T}r(\tau)d\tau}\left[r(T)c,p-\theta_{c,p}\right]\] \[ \theta_{C}=-e^{\int_{0}^{T}r(\tau)d\tau}\left[r(T)\left[Se^{-\int_{0}^{T}q(\tau)d\tau}N(d_{1})-Xe^{-\int_{0}^{T}r(\tau)d\tau}N(d_{2})\right]-Sq(T)e^{-\int_{0}^{T}q(\tau)d\tau}N(d_{1})+Xr(T)e^{-\int_{0}^{T}r(\tau)d\tau}N(d_{2})+Se^{-\int_{0}^{T}q(\tau)d\tau}n(d_{1})\frac{\sigma^{2}(T)}{2\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}\right]\] \[ =-e^{\int_{0}^{T}r(\tau)d\tau}\left[Sr(T)e^{-\int_{0}^{T}q(\tau)d\tau}N(d_{1})-Xr(T)e^{-\int_{0}^{T}r(\tau)d\tau}N(d_{2})-Sq(T)e^{-\int_{0}^{T}q(\tau)d\tau}N(d_{1})+Xr(T)e^{-\int_{0}^{T}r(\tau)d\tau}N(d_{2})+Se^{-\int_{0}^{T}q(\tau)d\tau}n(d_{1})\frac{\sigma^{2}(T)}{2\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}\right]\] \[ =-e^{\int_{0}^{T}r(\tau)d\tau}\left[S\left[r(T)-q(T)\right]e^{-\int_{0}^{T}q(\tau)d\tau}N(d_{1})+Se^{-\int_{0}^{T}q(\tau)d\tau}n(d_{1})\frac{\sigma^{2}(T)}{2\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}\right]\] \[ \theta_{C}=-S\left[r(T)-q(T)\right]e^{\int_{0}^{T}(r(\tau)-q(\tau))d\tau}N(d_{1})-Se^{\int_{0}^{T}(r(\tau)-q(\tau))d\tau}n(d_{1})\frac{\sigma^{2}(T)}{2\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}\] \[ \theta_{P}=-e^{\int_{0}^{T}r(\tau)d\tau}\left[r(T)\left[Xe^{-\int_{0}^{T}r(\tau)d\tau}N(-d_{2})-Se^{-\int_{0}^{T}q(\tau)d\tau}N(-d_{1})\right]+Sq(T)e^{-\int_{0}^{T}q(\tau)d\tau}N(-d_{1})-Xr(T)e^{-\int_{0}^{T}r(\tau)d\tau}N(-d_{2})+Se^{-\int_{0}^{T}q(\tau)d\tau}n(d_{1})\frac{\sigma^{2}(T)}{2\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}\right]\] \[ =-e^{\int_{0}^{T}r(\tau)d\tau}\left[Xr(T)e^{-\int_{0}^{T}r(\tau)d\tau}N(-d_{2})-Sr(T)e^{-\int_{0}^{T}q(\tau)d\tau}N(-d_{1})+Sq(T)e^{-\int_{0}^{T}q(\tau)d\tau}N(-d_{1})-Xr(T)e^{-\int_{0}^{T}r(\tau)d\tau}N(-d_{2})+Se^{-\int_{0}^{T}q(\tau)d\tau}n(d_{1})\frac{\sigma^{2}(T)}{2\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}\right]\] \[ =e^{\int_{0}^{T}r(\tau)d\tau}\left[S\left[r(T)-q(T)\right]e^{-\int_{0}^{T}q(\tau)d\tau}N(-d_{1})-Se^{-\int_{0}^{T}q(\tau)d\tau}n(d_{1})\frac{\sigma^{2}(T)}{2\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}\right]\] \[ \theta_{P}=S\left[r(T)-q(T)\right]e^{\int_{0}^{T}(r(\tau)-q(\tau))d\tau}N(d_{1})-Se^{\int_{0}^{T}(r(\tau)-q(\tau))d\tau}n(d_{1})\frac{\sigma^{2}(T)}{2\sqrt{\int_{0}^{T}\sigma^{2}(\tau)d\tau}}\] } \subsection{Rho} Only defined when the riskfree rate is constant. \begin{tabular}{|c} \hline \begin{eqnarray*} \rho_{C}=\frac{\partial C}{\partial r}=\frac{\partial}{\partial r}\left[e^{rT}c\right]= & re^{rT}\left[Se^{-qT}N(d_{1})-Xe^{-rT}N(d_{2})\right]+e^{rT}XTe^{-rT}N(d_{2})= & rSe^{(r-q)T}N(d_{1})+(T-r)XN(d_{2})\\ \rho_{P}=\frac{\partial P}{\partial r}=\frac{\partial}{\partial r}\left[e^{rT}p\right]= & re^{rT}\left[Xe^{-rT}N(-d_{2})-Se^{-qT}N(-d_{1})\right]-e^{rT}XTe^{-rT}N(-d_{2})= & (r-T)XN(-d_{2})-rSe^{(r-q)T}N(-d_{1})\end{eqnarray*} \tabularnewline \end{tabular} \end{document}