Backtesting Var Models

The idea of “risk” is used in many fields and industries. There has been large efforts made towards the understanding of risk. Since, risk varies so much depending on the field of study, the need for learning about it is warranted. As can be imagined, the importance of risk in a market economy is crucial. In the 1990s, JP Morgan made the Value at Risk (VaR) a central component of its work efforts (Cecilia-Nicoleta, Anne-Marie, & Carmen-Maria, 2011).

increasing w by a small amount. Therefore, Marginal VAR (value at risk) allows risk managers to study the effects of adding or subtracting positions from an investment portfolio. Since value at risk is affected by the correlation of investment positions, it is not enough to consider an individual investment's VAR level in isolation. Rather, it must be compared with the total portfolio to determine what

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Cernauskas, D., & Tarantino, A. (2011). Essentials of Risk Management in Finance. Hoboken: John Wiley & Sons, Inc.

When we measure risk per unit of return, Collections, with its low expected return, becomes the most risky stock. The CV is a better measure of an asset’s stand-alone risk than because CV considers both the expected value and the dispersion of a distribution—a security with a low expected return and a low standard deviation could have a higher chance of a loss than one with a high but a high .

| Based on explicit knowledge and this can be easy and fast to capture and analyse.Results can be generalised to larger populationsCan be repeated – therefore good test re-test reliability and validityStatistical analyses and interpretation are

Since the onset of the financial crisis 2008, the sovereign debt crisis in western economies and the new financial regulation with Basel III coming up, the financial industry faces the challenge of reinventing itself. The ring-fence for Commercial and Investment Banking, and new economic and regulatory capital requirements will determine the kinds of products banks will be able to distribute. It will have a huge impact in the Investment Banking business, which will suffer tough regulation and supervisory procedures. At the same time, credit risk models will be reviewed because they have failed to predict the crisis of 2008. The current financial and economic crisis doesn’t have any precedent in the past.

• Interest rate risk: Evaluating management of interest rate risk including the ability to accurately identify and quantify interest rate risk in assets and liabilities under varying model

A combination of business risk and financial risk shows the risk of an organization’s future return on equity. Business risk is related to make a firm’s operation without any debt whereas financial risk requires that the firm’s common stockholders make a decision to finance it with debt. Business risk can be evaluated volatility in earnings and profits (coefficient of variation of returns on assets and of operating profits). A measure of business risk is also asset beta or unlevered beta. In case of AHP, it is 1.2 (βa) which is very low signifying low business risk for the firm.

Systematic risk is the only relevant measurement, according to CAPM. Undiversified shareholder and bankruptcy can complicate this form of measurement. It means the measurement could not work. In addition to the systematic risk measurement, we could also use the contribution to firm risk measure.

The success of the model is attributed to Yale’s ability to combine both quantitative analysis (mean-variance analysis) with market judgments to structure its portfolio. In addition, Yale also uses statistical analysis to actively test their models with factors affecting the market, therefore understanding the sensitivity of their portfolio in response to various market changes. Yale also follows and forecasts the cash flow of private equity and real assets in its portfolio to decide the need for hedging.

As indicated by the case study S&P 500 index was use as a measure of the total return for the stock market. Our standard deviation of the total return was used as a one measure of the risk of an individual stock. Also betas for individual stocks are determined by simple linear regression. The variables were: total return for the stock as the dependent variable and independent variable is the total return for the stock. Since the descriptive statistics were a lot, only the necessary data was selected (below table.)

Secondly, the balance between using Model and exercising judgment was conductive to risk management. Before crisis, Medigan and Zhikharev did not believe VAR was good enough to measure risks and only worked for normal distributed assets. They came up with a new tool called Global Access Risk Factor Model. The new risk tool enhanced the judgment and helped make some wise decisions in managing risk. The model helped to keep everyone honest. In the summer 2008, the Model performed as expected. It made sure the portfolios were adjusted accordingly with their views of macro environment. In March 2009, the Model suggested to add more risk in order to get higher return. However, the Global Access team still believed the market was not going to recover yet. They did not count on the Model and decided to take cautious steps. On one side, they had downside-protected trades by limit premium and quickly took gain and cut loos. On the other side, they carefully chose trades with strong fundamental value. For the year 2009, they portfolios behaved significantly well.

As a result, many different factors have been tested across different markets. Historically, most studies have relied on general economic theories or empirical observations in selecting Factors. Benaković and Posedel (2010) emphasize Interest rates, oil prices, and industrial production. Chen, Roll and Ross (1986) use industrial production growth, inflation, bonds spread, NYSE stock market returns, oil prices, interest term structure, and consumption to decompose returns of a portfolio with general securities. Bodurtha, Cho and Senbet (1989) even uses international factors. Most of literatures have focused on applying different factors with a portfolio of many securities, as it is widely known that idiosyncratic risks diversifies away as the number of

In their research study, Souder & Myles (2010) identify that risk is chiefly fundamental to investing. Böhringer & Löschel (2008) further add that there is no discussion of returns or performance that is deemed meaningful in the absence of at least some mention of the involved risk. However, the trouble for investors, who have just entered into the marketplace, involves the process of figuring where risk really lies, as well as what the difference between the various levels of risks. Relating to the manner, in which risk is fundamental to investments, a significant number of new