Summary - Market Risk Flashcards
MARKET RISK
- explanation
Explanation:
Market risk is the risk of losses due to movements in prices of assets or liabilities. These include:
- Interest rates
- Equity prices
- Currency exchange rates
- Commodity prices
- Credit spreads (sometimes considered part of market risk)
It affects the valuation of assets and liabilities, especially those marked-to-market, and can also affect future cash flows.
MARKET RISK
- typical risk controls (7)
Risk limits: Set by asset class, duration, VaR thresholds, etc.
Diversification: Across assets, sectors, geographies, and currencies.
Hedging strategies: Using derivatives like swaps, options, or futures.
Scenario and stress testing: Especially to test tail events.
Asset-liability matching (ALM): Reduces mismatch exposure.
Governance: Investment committees, escalation protocols, front and back office seperation.
Use of risk-adjusted performance metrics: e.g. RAROC, Sharpe Ratio.
MARKET RISK
- Unique Factors to Watch For:
Procyclicality: Market risk can amplify in downturns due to forced selling or margin calls.
Correlation breakdown: Diversification benefits can vanish in crises (tail dependence)
Model risk: Heavy reliance on quantitative models (e.g. VaR, Black-Scholes).
Liquidity risk linkage: Difficulty in liquidating positions can worsen market losses.
Embedded options in liabilities: e.g., policyholder lapses tied to market conditions.
Market Risk
- Acronym
SHIELD
S – Scenario testing:
Simulate shocks to assess portfolio vulnerability.
H – Hedging:
Offset risk using swaps, options, or futures.
I – Investment limits:
Caps by asset type, duration, or exposure.
E – Embedded options:
Identify liability features sensitive to market conditions.
L – Liquidity linkage:
Market moves can trigger forced sales or losses.
D – Diversification:
Spread investments to reduce overall market impact.
Market Risk
- 6 Dimensions
6 Dimensions of market risk:
- Risk events - what causes risk events?
- Frequency - how often do prices change in unexpected ways?
- Duration - over what time can the price changes be?
- Severity - how large can the price changes be?
- Correlation - how interconnected are the unexpected price changes?
- Capital - how much additional funding do we need if prices unexpectedly drop?
Modelling market risk - issues
Lack of sufficient data to estimate parameters of model (such as mu and sigma) with credibility.
Market dynamics are constantly changing - past data might not be relevant any more.
Normal-based models underestimate volatility. Fat-tailed (or Levy with infinite variability) will be more appropriate.
Kurtosis of daily market change is higher than for normal distribution.
