<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Financial Engineering on gdpark.blog</title><link>https://gdpark.blog/tags/financial-engineering/</link><description>Recent content in Financial Engineering on gdpark.blog</description><generator>Hugo</generator><language>en</language><lastBuildDate>Sun, 18 Dec 2016 00:00:00 +0000</lastBuildDate><atom:link href="https://gdpark.blog/tags/financial-engineering/index.xml" rel="self" type="application/rss+xml"/><item><title>Call Options &amp; Put Options [Financial Engineering Programming #1]</title><link>https://gdpark.blog/posts/financial-engineering-01-call-options-put-options/</link><pubDate>Thu, 01 Sep 2016 00:00:00 +0000</pubDate><guid>https://gdpark.blog/posts/financial-engineering-01-call-options-put-options/</guid><description>A casual dive into call and put options — what they actually mean, why Black–Scholes blew the market wide open, and yes, there&amp;rsquo;s a dropped-class backstory involved.</description></item><item><title>Binomial Model: Two Period [Financial Engineering Programming #5]</title><link>https://gdpark.blog/posts/financial-engineering-05-binomial-model-two-period/</link><pubDate>Mon, 03 Oct 2016 00:00:00 +0000</pubDate><guid>https://gdpark.blog/posts/financial-engineering-05-binomial-model-two-period/</guid><description>We crank through the two-period binomial model one step at a time, build up the call price formula, and peek at how it naturally generalizes to n periods — heh heh.</description></item><item><title>Binomial Option Pricing Model: Basics [Derivatives I Studied #15]</title><link>https://gdpark.blog/posts/derivatives-15-binomial-option-pricing-model-basics/</link><pubDate>Wed, 14 Dec 2016 00:00:00 +0000</pubDate><guid>https://gdpark.blog/posts/derivatives-15-binomial-option-pricing-model-basics/</guid><description>A copy-paste deep dive into the binomial option pricing model — covering one-period basics, risk-free portfolios, and how to pin down a call option&amp;rsquo;s theoretical price.</description></item><item><title>Deriving the Black-Scholes Formula from the Binomial Model [Derivatives I Studied #16]</title><link>https://gdpark.blog/posts/derivatives-16-deriving-the-black-scholes-formula-from-the-binomial-model/</link><pubDate>Thu, 15 Dec 2016 00:00:00 +0000</pubDate><guid>https://gdpark.blog/posts/derivatives-16-deriving-the-black-scholes-formula-from-the-binomial-model/</guid><description>Turns out if you just crank n to infinity in the binomial model, the Black-Scholes formula pops right out — so let&amp;rsquo;s do exactly that instead of going the hard way.</description></item><item><title>Differentiation Fundamentals for Finite Difference Methods [Financial Engineering Programming #16]</title><link>https://gdpark.blog/posts/financial-engineering-16-differentiation-fundamentals-for-finite-difference-methods/</link><pubDate>Mon, 12 Dec 2016 00:00:00 +0000</pubDate><guid>https://gdpark.blog/posts/financial-engineering-16-differentiation-fundamentals-for-finite-difference-methods/</guid><description>Before we can tackle FDM and crack open the Black-Scholes PDE numerically, we need to get our differentiation fundamentals straight — so let&amp;rsquo;s run through it.</description></item><item><title>Black-Scholes Formula: Practice Problems [Derivatives I Studied #17]</title><link>https://gdpark.blog/posts/derivatives-17-black-scholes-formula-practice-problems/</link><pubDate>Fri, 16 Dec 2016 00:00:00 +0000</pubDate><guid>https://gdpark.blog/posts/derivatives-17-black-scholes-formula-practice-problems/</guid><description>Working through Chapter 13 Black-Scholes practice problems — from log-normal returns and Geometric Brownian Motion to actually pricing European call options.</description></item><item><title>Cholesky Decomposition &amp; Correlated Random Variables [Financial Engineering Programming #22]</title><link>https://gdpark.blog/posts/financial-engineering-22-cholesky-decomposition-correlated-random-variables/</link><pubDate>Sun, 18 Dec 2016 00:00:00 +0000</pubDate><guid>https://gdpark.blog/posts/financial-engineering-22-cholesky-decomposition-correlated-random-variables/</guid><description>A casual walkthrough of Cholesky decomposition — from real and Hermitian matrices to positive definite covariance matrices — and why it all matters in financial engineering.</description></item></channel></rss>