The Black-Scholes-Merton model is one of the earliest option pricing models that was developed in the late 1960s and published in 1973 [1,2]. The most important concept behind the model is the dynamic hedging of an option portfolio in order to eliminate the market risk. First, a delta-neutral portfolio is constructed, and then it is adjusted to stay delta neutral as the market fluctuates. Finally, we arrive at a Partial-Differential Equation for the value of the option.
This equation is also called a diffusion equation, and it has closed-form solutions for European call and put options. For a detailed derivation and analytical formula, see Reference .
In this post, we focus on the implementation of the Black-Scholes-Merton option pricing model in Python. Closed-form formula for European call and put are implemented in a Python code. The picture below shows the prices of the call and put options for the following market parameters:
We compare the above results to the ones obtained by using third-party software and notice that they are in good agreement.
In the next installment, we will price these options using Monte Carlo simulation.
 Black, Fischer; Myron Scholes (1973). The Pricing of Options and Corporate Liabilities. Journal of Political Economy. 81 (3): 637–654
 Merton, Robert C. (1973). Theory of Rational Option Pricing. Bell Journal of Economics and Management Science.
 Hull, John C. (2003). Options, Futures, and Other Derivatives. Prentice Hall
Follow the link below to download the Python program.
Originally Published Here: Black-Scholes-Merton Option Pricing Model-Derivative Pricing in Python
A derivative is a financial instrument whose price is derived from an underlying asset. Thus, in very simple words, the price and value of a derivative stem from its underlying asset. The underlying asset can be anything that has some value. The most common forms of derivatives are forwards, futures, options, and swaps. Although other derivatives also exist, known as exotic derivatives, in this article we will focus on these four types of derivatives.
Although the pricing models differ for each type of derivative, the underlying principle is the same: financial derivatives are priced based on non-arbitrage principle, or the law of one price.
A forward contract is a private agreement between two parties giving the buyer an obligation to purchase an asset, and the seller an obligation to sell an asset at a set price at a future point in time. The underlying asset can be anything of value. In order to understand this better, let us look at a simple example.
Let us assume that the underlying asset here is a 10 kg bag of apples that have not been harvested yet. Technically, the underlying asset does not even exist, so it has no financial value. However, it is still possible to assign a price to it. Suppose that a farmer enters into a forward contract to sell the 10 kg bag of apples at a price of $20 in 3 months' time when the apples will be harvested. The farmer does this because he fears that the price of apples may go down in the future, resulting in a loss for him. So in order to set off or hedge the potential loss, the farmer enters into a forward contract with a buyer who agrees to buy the 10 kg bag of apples at the $20 price determined today. This means that 3 months from now, the forward contract will be executed at $20 regardless of the price in the future. In this manner both the buyer and seller transfer the risks to each other.
Forward contracts are often customized and trade over the counter.
A futures contract is a legal agreement to buy or sell a particular commodity, or security at a predetermined price at a specified time in the future. Futures contracts are standardized for quality and quantity in order to facilitate trading on an organized exchange. In addition, unlike forwards, the profit and loss of a futures contract is settled daily.
Despite the differences, the underlying principles for both futures and forwards are the same. The parties enter into a contract to buy or sell a particular underlying asset at a fixed price in the future, and the value of the contract is determined as the underlying asset is realized.
An options contract is an agreement between a buyer and seller that gives the buyer of the option the right but not the obligation to buy or sell a particular asset at a later date at an agreed-upon price. Options contracts are often used in securities, commodities, and real estate transactions.
In principle, options are similar to forwards and futures but the difference is its holder has a right, but not an obligation to buy or sell the underlying asset. A call option gives the buyer the right to buy the asset at a predetermined price at or before maturity. A put option allows the holder to sell at a predetermined price at or before expiration.
Going back to our original example, suppose that the farmer has bought a put option that allows him to sell apples at $20. Three months later, if the price of 10 kg bag of apples becomes $24, then in this situation the farmer would have the option of not executing the contract at $20 and instead of selling the 10 kg bag of apples at the market price of $24. However, if the price of the apples falls down to $15, then the farmer can exercise the put option and sell the apples at the contractual price of $20.
Black-Scholes option pricing model
There are different models for valuing options. The earliest model is called the Black-Scholes option pricing model which provides an analytical, closed-form formula for valuing a European option. The model requires 5 important input parameters: spot price, strike price, volatility, risk-free rate, maturity.
Binomial option pricing model
Binomial option model is used to value American style options. The model relies on the assumption that for the next time period, a stock can move up, or down with certain probabilities. The major advantage of the binomial model is that it’s relatively simple. To value an option using this method, a tree of possible values of the underlying assets is built first. Then the option value is determined by calculating its payoffs at maturity and rolling back to time zero.
A swap is a derivative contract through which two parties can exchange the cash flows or liabilities from two different financial instruments. The most common type of swap is interest rate swap, however, there exist other types such as commodity and currency swaps.
Interest rate swaps are used to manage and transfer interest rate risks. Let’s take a look at an example, a parent company operating in the USA has a subsidiary in Europe. The parent in the USA has to pay a fixed-rate loan in dollars whereas the subsidiary based in Europe has to pay a variable rate loan in Euro. The parent wants to pay a variable rate based on its cash flow situation whereas the subsidiary wants the fixed-rate loan because of the certainty of payments. Thus, both the parent and subsidiary will enter into an interest rate swap where the parent will end up paying the variable-rate euro loan and the subsidiary will end up paying the fixed-rate dollar loan.
An interest rate swap can be valued by decomposing it into fixed-rate and floating-rate bonds. Essentially, the value of each leg is determined by calculating the Net Present Value of future cash flows. An alternative way to value an interest rate swap is to view it as a series of Forward Rate Agreements.
Article Source Here: Derivative Pricing and Valuation
In a previous post, we discussed the risks of Collateralized Loan Obligations, a type of complex credit derivatives. Since then, the trend in securitizing loans is still upward. Nowadays, not only performing loans but also non-performing loans are being securitized and sold to investors.
A non-performing loan is a loan that is in default or close to being in default. Depending on the terms of the contract, a loan can become non-performing after being in default for 90 days. Recently, independent.ie reported
Non-banks - including vulture funds - that have amassed billions of euro of non performing loan (NPL) portfolios are likely to securitise some of those loan either to lower their own financing costs or simply to raise cash...This trend already appears to be underway, with Scope noting a €419.8m deal by Lone Star in the third quarter of last year when it raised funds by borrowing against the value of portfolio of performing and non-performing loans. Read more
Securitization is a proactive measure that allows a financial institution to transfer the risks of a portfolio of non-performing loans.
The massive bad-loan sales in recent years began with boom era commercial property and developer loans that have now largely been removed from bank balance sheet. Lenders here now have what the agency called “relatively granular NPL stock” mainly of SME loans and residential mortgages. These are significantly easier to securitise than CRE portfolios, and if the “No Consent, No Sale” bill became law, so called synthetic securitisation remains a viable risk-transfer mechanism. Synthetic securitisation involves banks buying complex financial derivatives to insure against the risk of borrower defaults.
However, there are many issues associated with managing the risks of these non-performing loans, notably the lack of standard definitions and valuation methodology. A solid regulatory framework should be developed to ensure market transparency and to facilitate risk management.
Originally Published Here: Are Collateralized Loan Obligations the New Debt Bombs? Part Two