Introduction
Financial institutions are subject to many sources of risk. Risk can be broadly defined as the degree of uncertainty about future net returns. A common classification reflects the fundamental sources of this uncertainty. Accordingly, the literature distinguishes four main types of risk. Credit risk relates to the potential loss due to the inability of a counterpart to meet its obligations. It has three basic components: credit exposure, probability of default and loss in the event of default. Operational risk takes into account the errors that can be made in instructing payments or settling transactions, and includes the risk of fraud and regulatory risks. Liquidity risk is caused by an unexpected large and stressful negative cash flow over a short period. If a firm has highly illiquid assets and suddenly needs some liquidity, it may be compelled to sell some of its assets at a discount. Market risk estimates the uncertainty of future earnings, due to the changes in market conditions. The most prominent of these risks in trading is market risk, since it reflects the potential economic loss caused by the decrease in the market value of a portfolio. Value at Risk (VaR) has become the standard measure that financial analysts use to quantify this risk. It is defined as the maximum potential loss in value of a portfolio of financial instruments with a given probability over a certain horizon. In simpler words, it is a number that indicates how much a financial institution can lose with probability θ over a given time horizon. The great popularity that this instrument has achieved among financial practitioners is essentially due to its conceptual simplicity: VaR reduces the (market) risk associated with any portfolio to just one number, which is the loss associated with a given probability.
VaR measures can have many applications, such as in risk management, to evaluate the performance of risk takers and for regulatory requirements. In particular, the Basel Committee on Banking Supervision (1996) at the Bank for International Settlements imposes to financial institutions such as banks and investment firms to meet capitalrequirements based on VaR estimates. Providing accurate estimates is of crucial importance. If the underlying risk is not properly estimated, this may lead to a sub-optimal capital allocation with consequences on the profitability or the financial stability of the institutions. From a statistical point of view, VaR estimation entails the estimation of a quantile of the distribution of returns. The fact that return distributions are not constant over time poses exceptional challenges in the estimation. While VaR is a very easy and intuitive concept, its measurement is a very challenging statistical problem. Although the existing models for calculating VaR employ different methodologies, they all follow a common general structure, which can be summarised in three points: 1) Mark-to-market the portfolio, 2) Estimate the distribution of portfolio returns, 3) Compute the VaR of the portfolio.
Methodology
The planned methodology is secondary research. The researcher will make use of published materials such as books, magazines and newspapers to collect data and information regarding the topic. The researcher will also make use of the internet to obtain information about the company such as its background and other related information. For the research, the researcher will mainly rely on secondary data in obtaining the information. Due to inaccessibility of the subject or the case study, other research methods are not applicable. Secondary data are data that have been collected for some other purpose. Secondary data can provide a useful source from which to answer the research question(s). Punch (1998) mentions several advantages of using existing data. Expenditure on obtaining data can be significantly reduced and data analysis can begin immediately, so saving time. Also, the quality of some data may be superior to anything the researcher could have created alone (Thomas, 2004, p. 191). On the other hand, the chosen research method also has several disadvantages. Data that have been gathered by others for their own purposes can be difficult to interpret when they are taken out of their original context. It is also much more difficult to appreciate the weak points in data that have been obtained by others. The data may be only partially relevant to the current research question (Thomas, 2004, p. 191).
0 comments:
Post a Comment