Financial Correlation plays a major part in financial marketswhich is a statistical tool to measure the relationship between changes of twoor more financial variables over time. Linear correlation, Pearson product-moment correlation coefficient, copulacorrelations and many others are various statistical measures to find thedegree of financial correlation. It is vital to understand if there are anycorrelations between stocks for example, in a portfolio, as this gives a strongindication about the various risks associated in the portfolio and volatility.
The goal of financial correlation is to combine assets with lowcorrelation, for example, stocks in a portfolio to lower the portfoliovolatility and risk. Hence, it is vital to understand how assets are correlatedin a portfolio in order to understand how to balance the portfolio with variousassets and equity by combining them with correct proportions. This is becausethe instability of the portfolio is decreased by setting low correlation ornegatively correlated investments in a portfolio. For example, by combining asset classes such as stocks/equity orbonds that have low correlation decreases the overall volatility andinstability and therefore allows an investor to invest more. Thus, in order for an investor to earn a highinvestment return on a particular portfolio, the latter will have to takecertain amount of risk. Hence, understanding thoroughly how assets arecorrelated can lead to huge rewards provided the portfolio of assets iscombined with non-correlated assets which will lower the overall volatility ofthe portfolio.
Moreover, the GARCH model is also a useful model to adopt tounderstand any volatility in assets and portfolios. The model builds onadvances in the understanding and modelling of volatility in the last ten years.The GARCH model is advantageous as it takes into consideration any surpluskurtosis (that is fat tail behaviour) and volatility clustering, two essential characteristicsof financial time series. It is beneficial as it also provides exact forecasts ofcovariances and variances of asset returns as the model is able to model time-varyingconditional variances.
Thus, the GARCH model is very beneficial as it can beapplied to a wide range of fields such as risk management, option pricing,portfolio management and asset allocation, foreign exchange and the termstructure of interest rates.