GARP FRM Part I Glossary

28 essential terms and definitions for GARP FRM Part I. Each definition is written for exam preparation, covering the concepts as they are tested on the 2026 syllabus.

28 Terms

16 Sections

2026 Syllabus

B

Beta: Beta is the sensitivity of an asset's returns to broad market returns, equal to the covariance with the market divided by market variance. A beta above one means the asset amplifies market moves, while a beta below one dampens them. $\beta_i = \frac{\text{Cov}(R_i, R_m)}{\text{Var}(R_m)}$
Basis Risk: Basis risk is the risk that the hedging instrument and the underlying exposure do not move in lockstep, leaving residual exposure even after the hedge is in place. It typically arises from mismatches in maturity, location, grade, or contract specifications.
Black-Scholes-Merton: Black-Scholes-Merton is the closed-form European option pricing model that treats the underlying as a lognormal diffusion under risk-neutral measure. Inputs are spot, strike, time to expiry, risk-free rate, dividend yield, and volatility; volatility is the only one that is not directly observable.

C

Convexity: Convexity measures the curvature of a bond's price-yield relationship, capturing the second-order effect that duration alone misses. Positive convexity means bond prices rise more for a yield drop than they fall for an equal-sized yield rise, helping hedgers refine their duration-based estimates.
Covered Interest Parity: Covered interest parity is the no-arbitrage condition stating that the forward exchange rate equals the spot rate adjusted for the interest rate differential between the two currencies. Persistent deviations are flagged as a cross-currency basis and watched closely after 2008. $F = S \cdot \frac{1 + i_d}{1 + i_f}$

D

DV01: Dollar value of an 01 (DV01) is the dollar change in a bond or portfolio's value for a one-basis-point parallel shift in yields. Trading desks use DV01 to size hedges and aggregate interest-rate exposure across instruments with very different cash-flow profiles.

E

Expected Loss: Expected loss (EL) is the average credit loss a portfolio is expected to incur over a defined horizon, calculated as the product of probability of default, loss given default, and exposure at default. It is treated as a cost of doing business and absorbed through pricing and reserves. $EL = PD \times LGD \times EAD$
Enterprise Risk Management: Enterprise risk management (ERM) is an integrated framework for identifying, measuring, and managing all material risks across a firm under a unified governance structure. It links risk appetite to strategy, aggregates exposures across silos, and reports residual risk to the board.
Expected Shortfall: Expected shortfall (ES), also called CVaR, is the average loss conditional on exceeding the VaR threshold. It is coherent, captures tail-risk shape, and is now the Basel-mandated market-risk measure under FRTB, replacing VaR for regulatory capital.
EWMA: Exponentially weighted moving average (EWMA) estimates volatility by weighting recent squared returns more heavily than distant ones using a single decay factor. RiskMetrics popularized lambda equal to 0.94 for daily data; it reacts faster than rolling windows but lacks GARCH's mean reversion. $\sigma_t^2 = \lambda \sigma_{t-1}^2 + (1-\lambda) r_{t-1}^2$

G

GARCH: Generalized autoregressive conditional heteroskedasticity (GARCH) is a model in which today's return variance depends on a long-run average, yesterday's squared return, and yesterday's variance. It captures volatility clustering and mean reversion observed in financial returns. $\sigma_t^2 = \omega + \alpha r_{t-1}^2 + \beta \sigma_{t-1}^2$
Greeks: Greeks are partial derivatives of an option's price with respect to its inputs: delta (spot), gamma (delta's slope), vega (volatility), theta (time), and rho (rate). Trading desks hedge each Greek separately to stay neutral to the dimension of risk they do not want to take.

H

Hypothesis Testing: Hypothesis testing is a statistical procedure for deciding whether sample evidence is strong enough to reject a null hypothesis in favor of an alternative. You compute a test statistic, compare it to a critical value, and weigh Type I and Type II error trade-offs.
Heteroskedasticity: Heteroskedasticity occurs in regression when the variance of residuals depends on the level of the explanatory variables, violating an OLS assumption. Coefficient estimates remain unbiased, but standard errors are wrong, so you correct them using White or Newey-West adjustments.

I

Information Ratio: Information ratio is the active return of a portfolio divided by its tracking error against a benchmark, measuring the consistency of excess return per unit of active risk. It is widely used to evaluate active managers running against an index. $\text{IR} = \frac{R_p - R_b}{\sigma(R_p - R_b)}$

J

Jensen's Alpha: Jensen's alpha is the portfolio return in excess of what CAPM would predict given its beta, isolating manager skill from passive market exposure. A positive alpha implies value added beyond what the chosen risk level would justify. $\alpha_J = R_p - [R_f + \beta_p(R_m - R_f)]$

M

Multicollinearity: Multicollinearity arises when two or more regressors are highly linearly related, inflating the standard errors of coefficient estimates. The model still fits in aggregate, but individual coefficients become unstable and hard to interpret. Detect it with the variance inflation factor.
Modified Duration: Modified duration is the percentage change in a bond's price for a one-percentage-point change in yield, expressed as a positive number. It is a first-order linear approximation that works best for small parallel shifts in the yield curve. $\text{ModDur} = \frac{\text{Macaulay Duration}}{1 + y}$

O

Optimal Hedge Ratio: Optimal hedge ratio minimizes the variance of the hedged position by setting the futures-to-spot ratio equal to the correlation between spot and futures returns scaled by their volatilities. The corresponding minimum-variance hedge tells you exactly how many futures to short. $h^* = \rho_{S,F}\,\frac{\sigma_S}{\sigma_F}$

P

Put-Call Parity: Put-call parity is a no-arbitrage relationship linking the prices of a European call, put, the underlying, and a risk-free bond with face equal to the strike. Violations imply an arbitrage opportunity once transaction costs are netted out. $C - P = S - K e^{-rT}$

R

RAROC: Risk-adjusted return on capital (RAROC) measures the profitability of a business or trade per unit of economic capital consumed, allowing you to compare activities with different risk profiles. It supports capital allocation by isolating risk-adjusted contribution to firm value. $\text{RAROC} = \frac{\text{Risk-Adjusted Return}}{\text{Economic Capital}}$

S

Stress Loss: Stress loss is the loss your portfolio would experience under a specific severe but plausible scenario, such as a recession or rate shock. Unlike statistical VaR, stress losses are scenario-driven and used to test whether capital and liquidity buffers survive tail events.
Sharpe Ratio: Sharpe ratio is the excess return per unit of total risk, calculated as portfolio return minus the risk-free rate divided by the portfolio standard deviation. It rewards both higher returns and lower volatility, making it a standard yardstick for absolute-return strategies. $\text{Sharpe} = \frac{R_p - R_f}{\sigma_p}$
Sortino Ratio: Sortino ratio refines the Sharpe ratio by replacing total volatility with downside deviation, penalizing only returns below a target threshold. It is preferred when return distributions are asymmetric and investors care primarily about losses rather than upside variability. $\text{Sortino} = \frac{R_p - R_T}{\sigma_d}$

T

Treynor Ratio: Treynor ratio measures excess return per unit of systematic risk, dividing portfolio return minus the risk-free rate by portfolio beta. It is appropriate for well-diversified portfolios where idiosyncratic risk has been eliminated and only market risk remains. $\text{Treynor} = \frac{R_p - R_f}{\beta_p}$
Tracking Error: Tracking error is the standard deviation of the difference between a portfolio's returns and its benchmark, quantifying how closely the portfolio follows the index. Index funds target very low tracking error, while active strategies accept higher tracking error in pursuit of alpha.

U

Unexpected Loss: Unexpected loss (UL) is the volatility of credit losses around the expected loss, representing the capital you must hold to absorb adverse deviations. It is typically measured as a standard deviation of loss and drives economic capital allocation rather than reserves.

V

Value-at-Risk: Value-at-risk (VaR) is the loss threshold that will not be exceeded over a given horizon at a stated confidence level, such as a 1-day 99% VaR of $5 million. It is intuitive but not coherent because it ignores tail shape beyond the cutoff and is non-subadditive.

GARP FRM Part I Glossary

B

C

D

E

G

H

I

J

M

O

P

R

S

T

U

V

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