α	ALPHA: population linear projection ceofficient - probability of a Type I error
β	BETA: population regression coefficient - in the CAPM, the correlation between the expected return of a stock or portfolio and the return of the market as a whole - probability of a Type II error
γ	GAMMA: autocovariance matrix for vector process - autocovariance for scalar process - the rate of change in the delta
δ	DELTA: change in value of variable - coefficient on time trend - the sensitivity to changes in the price of the underlying asset
ε	EPSILON: a white noise variable
ζ	ZETA: constant term in ARCH specification
η	ETA: AR (∞) coefficient
θ	THETA: matrix of MA coefficient - scalar MA (q) coefficient - sensitivity to the passage of time
κ	KAPPA: kernel
λ	LAMBDA: matrix of eigenvalues - Lagrange multiplier - the percentage change in option value per change in the underlying price
μ	MU: population mean
ν	NU: degrees of freedom
ξ	XI: matrix of derivatives
π	PI: product - the number 3.14159...
ρ	RHO: autocorrelation - autoregressive coefficient - sensitivity to the applicable interest rate
σ	SIGMA: summation - long-run variance-covariance matrix - population standard deviation
τ	TAU: time index
υ	UPSILON: scaling matrix to calculate asymptotic distributions
φ	PHI: matrix of autoregressive coefficients - scalar autoregressive coefficient
χ	CHI: a variable with a chi-square distribution
ψ	PSI: matrix of MA coefficient for vector MA (∞) process - moving average coefficient for scalar MA (∞) process
ω	OMEGA: variance-covariance matrix - frequency