1 Introduction

1.1 Why quantifying market risk?

This ongoing project is made for all investors who want to dig deeper into their portfolio than just looking at the yearly profit or loss. Although most financial reports of more sophisticated brokers contain risk measures like standard deviations, the volatility alone cannot cover the risk inherent in non-linear financial products like options. Moreover, potential investors care about their portfolio values under certain market conditions, e.g. they want to compare their perceived personal stress levels during the financial crisis but with the financial instruments in their portfolio losses during stress scenarios.

If questions like

• What happens to the portfolio value, if the ECB increases the interest rate by 100bp?
• What is the least amount of money, a given portfolio will loose in one out of 100 events during the next year?
• How would a given portfolio perform, if a crash comparable to Black Friday 1987 takes place?

are of potential interest for you, then the OCTARISK market risk project might be satisfying your needs for a professional risk modelling framework.

Since most investors do not give excessive credits to debtors or bear operational or liquidity risks, the OCTARISK project focuses on market risk only - all remaining types of risk which are relevant for your investment portfolio: equity risk, interest rate risk, volatility risk, commodity risk, ...

For the assessment of these market risk types, a sophisticated full valuation approach with Monte-Carlo based value-at-risk and expected shortfall calculation is performed. The underlying principles are state-of-the-art in financial institutions and are used in internal models to fulfill the requirements set by regulators (for Basel III and Solvency 2). The important concepts are adopted, the unnecessary overhead was skipped - resulting in a fast, lightweight yet flexible approach for quantifying market risk.

1.2 Features

The OCTARISK quantifying market risk projects features

• a full valuation approach for financial instruments
• Monte-Carlo method for scenario generation of underlying risk factors
• simple input interface via static and dynamic files
• a processable report incl. graphical representation of portfolio profits and losses as well as an overview over the riskiest instruments and positions (see See Output files for examples)
• an easily customizable framework based on full implementation on Octave with compact source code

1.3 Prerequisites

The only requirement is GNU Octave (tested for versions > 4.0) with installed financial package and hardware with minimum of 4Gb of memory. Calculation time decreases significantly while using optimized linear algebra packages of OpenBLAS and LAPACK (or comparable). For automatic processing of the input data (e.g. to get actual market data from Quandl or Yahoo finance), to make the parameter estimation as well as process the report files, some programming language like Perl, Python and a running LaTeX environment are recommended, but not required.

Nevertheless, a basic understanding of a high level programming language like Octave is required to adjust the source code and to customize the calculation. Furthermore, a thorough understanding of financial markets, instruments and valuation will be needed in order to select appropriate models and to interpret results. The implemented models and the underlying concepts are explained in detail for example in following literature:

Risk Management and Financial Institutions, John C. Hull, 2015
Paul Wilmott on Quantitative Finance, 2nd Edition, Paul Wilmott, 2006
Options, Futures and other Derivatives, 7th Edition, John C. Hull, 2008

The next chapter contains the background and details needed for running the market risk valuation and aggregation software and understanding the risk measures.