CAIA L2 - 5.3 - Liquidity and Funding Risks Flashcards
List and Describe
Three terms that are
used to describe value
(for futures)
5.3 - Liquidity and Funding Risks
Trading level = funding + notional funding
* Trading level: the amount of capital traded in an active risk account, as well as the denominator used to calculate leveraged returns. Management and incentive fees are also calculated based on trading level. The trading level determines the size of the positions the CTA takes in futures markets and is the account value used to translate profits and losses into percentage returns (PnL).
* Funding level: the total cash or collateral posted by the investor to support the trading level. The minimum funding level is the required total margin collateral.
* Notional funding: the added exposure beyond the trading level that is allowed by the CTA. Investors use notional funding to leverage their managed futures account to higher trading levels. This amount is not deposited or borrowed, but rather, it is a good-faith deposit and is therefore considered a low cost means of utilizing leverage.
5.3 - Liquidity and Funding Risks
Define
Cross-margin benefit
5.3 - Liquidity and Funding Risks
Benefit of less margin requirement
It exists when a CTA has many positions in futures contracts that are traded on the same exchange so that the total amount of margin required is less than the sum of the margins required on the individual contracts
5.3 - Liquidity and Funding Risks
Define
Capital at risk (CaR)
5.3 - Liquidity and Funding Risks
total loss incurred if each position in a trader’s portfolio hits its stop-loss price level on a particular day
5.3 - Liquidity and Funding Risks
Formula
Parametric VaR
5.3 - Liquidity and Funding Risks
VaR’α’=(α × σ’t’)+ μ
α = critical Value (<0)
σ = volatility ; standard deviation
μ = average return
Pr{Z≤α}=1– confidence level
α => z=1.28 / 1.65 / 2.33 1-tail 90% / 95% / 99%
5.3 - Liquidity and Funding Risks
Define
Scenario analysis
(or stress test)
5.3 - Liquidity and Funding Risks
Simulation
used to estimate how a portfolio will perform
under various market situations
- combination of actual historical events and events that would come from simulated financial stress
Stress test
can simulate highly adverse scenario (5+ sigma price movement)
5.3 - Liquidity and Funding Risks
Define
Omega Ratio
5.3 - Liquidity and Funding Risks
Ω = (upper partial moment) / (lower partial moment)
Ω = [∑max(Ri–T,0) / N] / [∑max (T– Ri,0) / N]
average of differences of returns > target return / average of differences of returns < target return. Or total of all upper partial moments divided by total of all lower partial moments.
ômega = 1 => likely output for a symmetrical distribution with a target return equal to the mean.
A portfolio’s omega will be reduced by:
* higher volatility,
* higher kurtosis, and
* lower skewness
* or increasing the target return
5.3 - Liquidity and Funding Risks
Define
Two reasons
a smoothed return series
may not be unsmoothed by arbitrageurs
5.3 - Liquidity and Funding Risks
1. True trading opportunities may not exist. Appraisals are price indicators that do not represent either bids or offers to buy or sell.
2. Substantial transaction costs or barriers to arbitrage may prevent arbitrageurs from taking advantage of these opportunities. These costs include sales commissions, transfer taxes, financing costs, inspection costs, legal costs, et cetera. Barriers such as redemption fees on short-term positions are helpful in reducing potential arbitrage opportunities.
Unsmoothing may not be needed for assets with:
* minimal trading barriers,
* low transaction costs, and
* tradable prices
because of the potential for arbitrage opportunities
5.3 - Liquidity and Funding Risks
Explain
Price Smoothing Problems
5.3 - Liquidity and Funding Risks
Price smoothing
=>
lower standard deviations (volatilities), correlations with the market, and reported betas
=>
risk is understated
=>
higher fund allocations
=>
appropriate hedge ratios ,
diversification , and
risk management strategies may be negatively impacted
‘–
Obs:
Long-term mean returns are one statistic that should not be substantially impacted by price smoothing
5.3 - Liquidity and Funding Risks
Formula
Real data as a function of Smoothed data:
- True price as a function of reported prices
- True Returns as a function of reported returns
- True Variance as a function of reported variance
- True Beta as a function of reported beta
5.3 - Liquidity and Funding Risks
P’t,true’ = P’t–1,reported’ +
[(1/⍺) × (P’t,reported’ – P’t–1,reported’)]
R’t,true’ ≈ (R’t,reported’ – ρ R’t–1,reported’) / (1–ρ)
⍺ = Decay parameter
ρ = autocorrelation
R’t, true’ = estimated true return in period t
R’t, reported’ = reported returns in period t
R’t–1, reported’ = reported returns in period t – 1
σ’true’^2 = σ’reported’^2 ×[ (1+ρ)/(1–ρ) ] or true volatility = smoothed volatility X √(1+p)/(1-p)
β’true’ = β’reported’ / (1– ρ)
⍺ - decay function in a model is used to assign less weight to old valuations and more weight on recent valuations
5.3 - Liquidity and Funding Risks
List
Reasons for Delayed Price Changes and Smoothed Prices (first-order autocorrelation) with price indices
5.3 - Liquidity and Funding Risks
1. ‘Mix” with not traded recently - A price index is based on prices from recent transactions for index components, and older prices may be used for some components that have not traded recently.
2. Appraisers’ anchoring - Appraisers may be vulnerable to anchoring, where people tend to rely too heavily on previous observations.
3. Biased prices - An efficient market can still produce transaction prices that are biased and result in lagged price responses.
4. Lag between transaction and reporting - There is often a lag between when the price is set on a transaction (such as a house sale) and when the transaction closes and is reported.
5.3 - Liquidity and Funding Risks
Identify
3 steps
of unsmoothing
5.3 - Liquidity and Funding Risks
- Specify the form of the autocorrelation
- Estimate the parameters of the assumed autocorrelation process
- Two reported returns must be inserted into the model, along with the estimated correlation coefficient in place of ρ
Dica:
Remember the unsmoothed return formula, which has the returns and ρ
5.3 - Liquidity and Funding Risks
List the different types of margin used in the marketplace
- Initial margin: This is the amount of cash or risk-free securities (like U.S. Treasury Bills) that must be deposited to trade a specific futures contract.
- Maintenance margin: This margin is the required amount that must be in an account to carry futures positions that were previously initiated. If the margin account falls below this level, funds must be added to restore the balance back up to the initial margin amount.
- Variation margin: This is the daily settlement of gains and losses in futures markets.
- Margin-to-equity ratio: Expressed as a percentage, this ratio is the amount of assets held for margin, relative to the net asset value (NAV) of the investment account. This ratio has a close correlation to the volatility of the overall fund, as higher margin-to-equity ratios imply greater leverage, and therefore, greater fund volatility.
Provide the formula for estimating volatility and for estimating with unequal weightings
how will positive autocorrelation effect the true beta vs the reported beta
Assuming positive autocorrelation, the true beta will exceed the reported beta, and the smoothed return series will re lect understated systemic risk.
LO 5.3.7
What are the key takeaways from analyzing the NPI and NAREIT indices
- The NPI exhibited less volatility than the NAREIT Index when comparing smoothed returns and unsmoothed returns.
- Estimated risk increases signi icantly for the NPI when the data is unsmoothed,which speaks to the importance of the asset allocation process.
- Positive autocorrelation can create significant long-term losses even when volatility over a shorter time frame appears insignificant.
- Correlations of smoothed returns to other asset class returns is also understated by smoothing. Correlations are critical to asset allocation and diversification decisions.
- The risk-adjusted returns for private equity real estate investments tend to be high, which may be a result of using smoothed returns, and therefore, overestimating risk-adjusted performance.
