Since the beginning of 2018, a well-known phenomenon in crisis period is observed on the market: the widening of the BOR-OIS spread. However, the reason is pretty different this time. Libor? OIS? Short reminder. Libor LIBOR, London Interbank Offer Rate is defined as: “The rate at which an individual Contributor Panel bank could borrow funds, … Continue reading What happened with the US BOR-OIS spread ?

# Financial Markets

# Build your own Bloomberg Launchpad

This short tutorial targets everyone who is either getting tired switching between numerous basic functions or would like to get an overview of various functions at the same time linked to a portfolio of tickers. I will explain how to create your launchpad and where you can find samples already done. Build your launchpad In your … Continue reading Build your own Bloomberg Launchpad

# How to Generate Correlated Assets and Why?

As soon as you will get into pretty complex derivatives, for example, you will need to generate correlated assets for pricing purposes. Example of such derivatives can be: Basket options Rainbox options Moutain ranges (created by Société Générale) The most complex amongst these derivatives cannot be priced using closed form formulae, Monte Carlo simulations are … Continue reading How to Generate Correlated Assets and Why?

# Speed Execution Benchmark on Monte Carlo

Today I will try to benchmark the execution speed of several programming languages on a Monte Carlo example. This benchmark involves VBA, C++, C#, Python, Cython and Numpy vectorization. I will try to add progressively other programming languages so that this article will be more thorough. Execution environment All the chunks of code have been … Continue reading Speed Execution Benchmark on Monte Carlo

# How to get Implied Volatility?

In this article, I will introduce what is implied volatility and several methods to find it. Here are the points I will try to cover: What is Implied Volatility? Dichotomy Method Newton Raphson Method Example in Python with a set of option prices Models Conclusion Implied Volatility Historical volatility and implied volatility, what is the … Continue reading How to get Implied Volatility?

# Relationship between Commodity Prices and the Dollar

In this short article, I will try to explain the relationship between commodity prices and both dollar. We typically see a negative correlation between them, why is that and is this always true? Relationship between commodity prices and dollar As I just said, there is a relationship between commodity prices and the dollar. It means … Continue reading Relationship between Commodity Prices and the Dollar

# Useful option pricing approximations

In this article, I will review some option pricing approximations that can be useful to verify the results given by the pricer you just implemented or to answer some interview questions. Here are the points I am going to tackle : Basic At-The-Money option approximation Examples Other approximations Negative volatility ?? Basic ATM approximation The … Continue reading Useful option pricing approximations

# Barrier option pricing with Monte Carlo

In this short article, I will apply Monte Carlo to barrier option pricing. Here are the points I am going to tackle: Quicker barrier options reminder Pros and cons of Monte Carlo for pricing Steps for Monte Carlo Pricing Up-and-Out Call pricing example Conclusion and ideas for better performance Barrier options Before entering in pricing … Continue reading Barrier option pricing with Monte Carlo

# How to be Gamma and Theta positive?

This is a question frequently asked during technical interviews. I will try to answer it through this short article giving examples and the logic behind them. Here are the main points I deal with here: Reminder: Gamma and Theta Black Scholes vs Real World Vertical Spread Conclusion - Smile skew Gamma Gamma is defined as … Continue reading How to be Gamma and Theta positive?

# Backtest a trading strategy in Python

In this article, I will introduce a way to backtest trading strategies in Python. All you need for this is a python interpreter, a trading strategy and last but not least: a dataset. A complete and clean dataset of OHLC (Open High Low Close) candlesticks is pretty hard to find, even more if you are … Continue reading Backtest a trading strategy in Python