DERIVATIVES

The Binomial tree is a standard method for pricing American style options. Recall that, The Binomial options pricing model approach has been widely used since it is able to handle a variety of conditions for which other models cannot easily be applied. This is largely because the BOPM is based on the description of an…

Read More The Willow Tree Method, an Advanced Option Pricing Model

Convertible bonds are complex, hybrid securities. In finance, a convertible bond or convertible note or convertible debt (or a convertible debenture if it has a maturity of greater than 10 years) is a type of bond that the holder can convert into a specified number of shares of common stock in the issuing company or…

Read More Convertible Bond Arbitrage Using the Volatility Surface

Executive stock options usually have complex payoffs. To price them, we often use the binomial tree method or Monte Carlo simulations. … a lattice model can be designed to accommodate dynamic assumptions of expected volatility and dividends over the option’s contractual term, and estimates of expected option exercise patterns during the option’s contractual term, including…

Read More Valuation of Executive Stock Options Using a Closed-Form Formula

In a previous post, we presented a method for pricing a fixed-rate bond. In this post, we are going to discuss valuation of a callable bond. A callable bond (also called redeemable bond) is a type of bond (debt security) that allows the issuer of the bond to retain the privilege of redeeming the bond…

Read More Valuation of Callable Putable Bonds-Derivative Pricing in Python

A warrant is a financial derivative instrument that is similar to a regular stock option except that when it is exercised, the company will issue more stocks and sell them to the warrant holder. Warrants and options are similar in that the two contractual financial instruments allow the holder special rights to buy securities. Both…

Read More Valuation of Warrants-Derivative Pricing in Python

In a previous post, we wrote about Employee Stock Options, a form of financial compensation that a company uses to reward its employees. In this post, we are going to discuss another form of compensation, Performance Share Units. Performance share units (PSUs) are hypothetical share units that are granted to you based mainly on corporate…

Read More Performance Share Units-Derivative Valuation in Python

Employee Stock Option (ESO) is a form of compensation that a company uses to reward, motivate, and retain its employees. An employee stock option (ESO) is a label that refers to compensation contracts between an employer and an employee that carries some characteristics of financial options. Employee stock options are commonly viewed as a complex…

Read More Employee Stock Options-Derivative Pricing in Python

In a previous post, we presented the binomial tree method for pricing American options. Recall that an American option is an option that can be exercised any time before maturity. A drawback of the binomial tree method is that the implementation of a more complex option payoff is difficult, especially when the payoff is path-dependent.…

Read More Valuing American Options Using Monte Carlo Simulation –Derivative Pricing in Python

Just like any financial derivatives that were initially designed for risk management purposes, interest rate swaps are an effective tool for managing and transferring interest rate risks as long as those risks are well understood.  But as banks and financial institutions are constantly trying to invent new financial products to sell to their consumers, sometimes…

Read More Another Misuse of Financial Derivatives

In a previous post, we presented a methodology for pricing European options using a closed-form formula. In this installment, we price these options using a numerical method. Specifically, we will use Monte Carlo simulation. Recall that, A call option gives the buyer the right, but not the obligation to buy an agreed quantity of the…

Read More Valuing European Options Using Monte Carlo Simulation-Derivative Pricing in Python