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Systematic Risk

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Before you can start the course, you'll have to complete a maths test. You can l earn about the program here. It's good if you want a risk modelling or model testing role, or if you want to be a quantitative developer building computer models for the quants who design banks' complex derivative products. Most 'front office quants' will have a PhD or an MSc. It's less well known in the worlds of data analysis and machine learning.

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The market value of fixed rate investments fluctuates from changes in market interest rates. Prepayment risk arises when borrowers redeem loans or borrowed funds before the maturity period to take advantage of a decline in interest rates. Extension risk arises when borrowers repay at a slower pace than expected when interest rates increase. Credit risk arises due to fluctuations in the value of investments resulting from issuer or borrower default or changes in the likelihood of default or recovery rates. Liquidity risk refers to the possibility of insufficient liquid resources to meet claims.

The frequency and magnitude of PC liquidity claims are more volatile compared to life or health insurance claims. Equity price risk results from the probable economic loss that results from adverse changes in stock prices.

Life and health insurers face equity price risk because of guarantees provided on variable life insurance and annuities. Equity price risks also arise for life insurance insurers as the fee income generated for managing AUM depends on portfolio sizes and performance of equity markets.

Aretina-Magdalena David-Pearson, in Econophysics , Market risk is defined as the risk that a financial position changes its value due to the change of an underlying market risk factor, like a stock price, an exchange rate, or an interest rate. Credit risk is defined as the risk that an obligor will not be able to meet its financial obligations toward its creditors. Under this definition, default is the only credit event. The weaker definition of credit risk is based on market perception. This definition implies that obligors will face credit risk even if they do not fail their financial obligations yet but the market perceives they might fail in the future.

Learning Outcomes

This is known as the mark-to-market definition of credit risk and gives rise to migration as well as default as possible credit events. Perception of financial distress gives rise to credit downgrade. Value at risk VaR is an estimate of the maximum loss that can occur for a portfolio under market conditions and within a given confidence level over a certain period of time. VaR has become an increasingly important measure for strategic risk management. Recent market events, including the Asian crisis and market collapse in Russia, have underscored the importance of complementing VaR analysis with a comprehensive stress-testing program.

New models and techniques for the trading book portfolios are needed to calculate the market risk.

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Credit is now playing a role in pricing—credit spreads are key factors for pricing many instruments. Specific risks arise from credit quality changes in the market place.

What is value at risk (VaR)? FRM T1-02

Thus the changes in credit risk affect market prices through spreads or credit ratings, infringing on the purity of the market risk estimation. As credit markets expand and deepen, information such as spreads and downgrades contributes directly, in an increased manner, to the positions' valuation in the corporate bond portfolios. Similarly, because market rates drive the value of fixed rate bonds, counterparty credit risk can only be assessed in such portfolios when exposures are evaluated under a variety of market conditions.

Non-fictie An Introduction To Value-at-risk By Moorad Choudhry paperback, 2013

Hence market risk factors are fundamental for a correct measure of credit risk. Credit risk modeling is one of the top priorities in risk management and finance. Common practice still treats market and credit risk separately. When measuring market risk, credit risk is commonly not taken into account; when measuring portfolio credit risk PCR , the market is assumed to be constant.

In this study, the focus is on integrated credit and market risk. There are two categories of credit risk measurement models: counterparty credit exposure models and PCR models. Counterparty credit exposure is the economic loss that will be incurred on all outstanding transactions if a counterparty defaults unadjusted by possible future recoveries. Counterparty exposure models measure and aggregate the exposures of all transactions with a given counterparty. They do not attempt to capture portfolio effects, such as the correlation between counterparty defaults.

PCR models measure credit capital and are specifically designed to capture portfolio effects, specifically obligor correlations. It accounts for the benefits of diversification. With diversification, the risk of the portfolio is different from the sum of risk across counterparties. Correlations allow a financial institution to diversify their portfolios and manage credit risk in an optimal way. However, PCR models either fix market risk factors to account for credit risk or fix credit risk drivers to account for market risk.

In this study, the portfolio credit risk engine PCRE is used, which is the first production solution for integrated market and credit risk, based on conditional probabilities of default.


Mark to future MtF is a concept where all financial instruments are valued across multiple scenarios developed on the underlying market and credit risk factors and across the time steps of interest. In the MtF concept, the calculations for pricing the instruments and VaR estimates are retrieved to deliver any combinations of results according to financial instrument, scenario, and time step.

If portfolio positions depend simultaneously on market and credit risk factors, the nature of the risk assessment problem changes. If market and credit risks are calculated separately, this is based on a wrong portfolio valuation and leads to a wrong assessment of true portfolio risk. A comprehensive framework requires the full integration of market and credit risk.

Basics of Investments

It is mandatory to model the correlations between changes of the credit quality of the debtors and changes of market risk factors. By combining an MtF framework of counterparty exposures Aziz and Charupat, and a conditional default probability framework Gordy, , one minimizes the number of scenarios where expensive portfolio valuations are calculated and can apply advanced Monte Carlo or analytical techniques that take advantage of the problem structure.

This integrated structure has the advantage of explicitly defining the joint evolution of market risk factors and credit drivers. Market factors drive the prices of securities and credit drivers are macroeconomic factors that drive the creditworthiness of obligors in the portfolio. Market risk covers a number of exposures.

We referred to collateral risk above, the risk of fall in value of collateral. This is a form of market risk. For repo market participants this can cover, as well as collateral risk, interest-rate risk and foreign exchange risk.