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CAIA LEVEL 1 TEST PAPER 2025/2026 QUESTIONS WITH ANSWERS TAGGED A+

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CAIA LEVEL 1 TEST PAPER 2025/2026 QUESTIONS WITH ANSWERS TAGGED A+

Institución
CAIA - Chartered Alternative Investment Analyst
Grado
CAIA - Chartered Alternative Investment Analyst











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Institución
CAIA - Chartered Alternative Investment Analyst
Grado
CAIA - Chartered Alternative Investment Analyst

Información del documento

Subido en
27 de mayo de 2025
Número de páginas
34
Escrito en
2024/2025
Tipo
Examen
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CAIA LEVEL 1 TEST PAPER 2025/2026 QUESTIONS WITH
ANSWERS TAGGED A+
✔✔Standard VI(B) - Priority of Transactions - ✔✔Investment transactions for clients and
employers must have priority over investment transactions in which a Member or
Candidate is the beneficial owner.

✔✔Standard VI(C) Referral Fees - ✔✔Members and Candidates must disclose to their
employer, clients, and prospective clients, as appropriate, any compensation,
consideration, or benefit received from or paid to others for the recommendation of
products or services.

✔✔Traditional Investments - ✔✔include publicly traded equities, fixed-income
securities, and cash

✔✔Real Assets - ✔✔associated with investments that directly control non-financial
assets and represent actual rights to consumption rather than financial claims to cash
flows generated by the tangible and intangible assets of a firm. Examples:
1. Real Estate (land and permanent improvements to the land; land- raw land,
timberland and farmland)
2. Infrastructure investments (investments represent claims on the cash flows generated
by the assets)
3. intellectual property
4. Natural Resources
5. Commodities

✔✔Hedge Funds - ✔✔Private investment vehicles that typically use leverage,
derivatives, and long and short investment strategies. Minimal regulatory restrictions.

✔✔Private Equity - ✔✔Includes both debt and equity securities that are not publicly
traded. Examples:
1. Venture Capital
2. LBOs
3. Mezz debt
4. Distressed Debt

✔✔Structured Products - ✔✔segment the cash flows of traditional investments or link
the product's returns to one or more market values in order to achieve certain risk

✔✔Prime Broker - ✔✔Executes trades on behalf of an alternative investment manager,
lends securities to sell short, provides research data, produces account statements and
other documentation, and provides financing for leverage

✔✔Bank Structures - ✔✔1. US- Investment Banks and Commercial Banks are separate
in the US

,2. Germany- "Universal Banking"- institutions that allow both commercial and
investment banking
3. UK- similar to US, separates IB and CB
4. Japan- Multiple corporations are linked together via cross ownership structures
"Keiretsu"; reduces the number of public shareholders and allows banks to have
considerable authority

✔✔Securities Act of 1933 - ✔✔Governs new securities issues and requires the
company to disclose relevant information, to register new issues, and to disseminate a
prospectus

✔✔Investment Company Act of 1940 - ✔✔instituted to regulate investment pools
(mutual funds). Hedge funds use exemptions to avoid registering

✔✔Investment Advisors act of 1940 - ✔✔requires that investment advisors register with
the SEC. hedge funds use exemptions

✔✔Regulation T margin rule - ✔✔Fed rule conceding leverage- stipulates that only 50%
of the value of a security can be purchased on margin. HFs must avoid falling under this
rule bc leverage

✔✔Forward Contract - ✔✔A bilateral contract that obligates one party to buy and the
other to sell a specific quantity of an asset, at a set price, on a specific date in the
future;
No premium is paid to get into the contract ;
Used to hedge risk and speculate on prices;
Buyer has long position;
Seller has short position;
Can terminate a forward contract by entering into the opposite position in another trade

✔✔notional principal - ✔✔Face amount on the underlying asset upon which cash flows
on a derivative instrument are based (i.e. forward or swap)

✔✔return on notional principal - ✔✔Gain or loss on the derivative instrument divided by
the notional principle

✔✔Ex Post Pricing Model - ✔✔Describes "after the fact" historical returns. Focuses on
realized returns.

✔✔Ex Ante Pricing Model - ✔✔Describes "before the fact" expected future returns.

✔✔Skewness - ✔✔The extent to which the distribution data is not symmetric about its
mean
- Tails of a skewed distribution will be:
- Elongated to the right for a positively skewed distribution (also mean > median)

,- Elongated to the left for a negatively skewed distribution (median > mean)

✔✔Mesokurtic - ✔✔Distribution with zero excess kurtosis

✔✔Leptokurtic - ✔✔Distribution with a peak that extends above that of a normal
distribution and tails that are fatter than those of a normal distribution
- i.e. have a greater percentage of small deviations from the mean and a greater
percentage of extremely large deviations from the mean compared to a normal
distribution.
- Leptokurtic distributions have a higher probability of large loss versus otherwise
identical investments with normally distributed returns

✔✔Platykurtic - ✔✔Distribution with a peak that lies beneath that of a normal
distribution, implying a smaller % of small deviations from the mean compared to a
normal distribution

✔✔CAPM Model - ✔✔Describes the relationship between risk and expected return for
individual assets. Model assumes normal returns distributions and assets are liquid.
CAPM consists of three components:
1. Risk Free Rate
2. The stocks Beta coefficient
3. The expected market risk premium

✔✔Beta - ✔✔Measures the sensitivity of an asset's returns to changes in the broad
market return

✔✔Autocorrelation - ✔✔Correlation over time for an asset

✔✔Homoskedastic - ✔✔Variances of returns are constant over time

✔✔Jacque- Bera Test - ✔✔Used to test data for departures from the normal distribution
using a null hypothesis and an alternative hypothesis:
H(0)- data are normally distributed
H(A)- Data are not normally distributed

If data follows normal distribution Skewness =0 and Excess Kurtosis=0 and the JB stat
=0

✔✔Heteroskedastic - ✔✔Variances of financial data are not constant over time

✔✔Value at Risk (VaR) - ✔✔Measure of potential loss- interpreted as the worse case
possible loss under normal conditions over a specific period of time for a given
confidence level

, The VaR for a portfolio will be zero for a portfolio with individual assets that have non-
zero VaRs if the assets are perfectly negatively correlated. The portfolio VaR will equal
the sum of the individual VaRs if the assets are perfectly positively correlated. If the
assets are uncorrelated (i.e., correlation is zero), the portfolio VaR will lie between the
perfect positive and perfect negative correlation cases.

VaR assumes normally distributed returns and does not consider skewness in its
calculation. Calculating VaR requires four inputs:
-The portfolio's expected return.
-The historical volatility of portfolio returns.
-The significance level (probability of a loss greater than VaR).
-The desired time dimension.

Example- a one-day VaR of $20 million at a 95% confidence level implies that the one-
day loss will be greater than $20 million 5% of the time.

✔✔Monte Carlo Analysis - ✔✔Model that simulates values for risk factors (e.g. interest
rates) and estimates how changes in risk factors affect the fund's returns. Simulation
randomly generates thousands of possibly outcomes for the fund and those simulated
outcomes indicate what types of losses are possible.

✔✔Sharpe Ratio - ✔✔The expected excess return (defined as the difference between
the mean return for the portfolio and the RF rate) earned per unit of total risk (i.e.
standard deviation)

SR=[E(Rp)-Rf]/σp

E(Rp) = expected return for portfolio p
Rf = risk-free rate
σp = standard deviation of returns for portfolio p

✔✔Average Tracking Error - ✔✔Difference in mean returns between the portfolio and
the portfolio's benchmark.

Also know as active risk

✔✔Multifactor Asset Pricing Model - ✔✔Describes the relationship between expected
returns of assets and the assets' exposures to multiple risk factors- better explains
systematic risk than single factor models

✔✔Theoretical Models - ✔✔Use assumptions and logic that presumably capture
underlying investment behavior.

✔✔Empirical Models - ✔✔Based on historically observed behavior
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