A comprehensive risk management review for financial instruments using different value at risk approaches: which methodology improves market risk valuation?
Trabajo Fin de Grado en Economía y Finanzas . Curso Académico 2019-2020In recent years, there has been an incrementing need within the financial industry to make
use of more sophisticated models to quantify the associated risk in any investment or financial
activity, with the goal of achieving an adequate risk management and control in decision-making
processes. Accordingly, throughout this academic research project, we present a review of the
different methodologies surrounding the Value at Risk framework, one of the most common tools
in financial risk analysis and quantification. We perform a deep analysis from standard approaches
for measuring VaR to the more complex techniques. We will also review some backtesting
procedures used to evaluate VaR models. Therefore, the main focus of this research will be to
implement a theoretical and practical analysis of several value at risk methodologies and discuss
their respective behaviour under real life scenarios including low but also high volatility periods,
such as the one fostered by the recent Covid-19 pandemic. To carry out the investigation, historic
data from the daily log returns of the Dow Jones Index will exploited through the open-source
software R. Results in this paper suggest that the GARCH (1,1) model parametric approach to VaR
is the best method for forecasting VaR, especially under the Student-T distribution assumption of
returns. The Historical Simulation non-parametric approach, as well as the Moving Average
Volatility model, also had promising results under relatively stable circumstances, but showed their
weaknesses when the situation changed and volatility in financial markets dramatically increased
as a consequence of the current health crisis. For its part, empirical literature highlights the lack of
accuracy of the traditional Riskmetrics methodology, fact that was also observed here, where we
obtained very discouraging results under such approach. Lastly, it seems that the Extreme Value
Theory significantly underestimated risk, resulting in a surprisingly bad performanc