hard · Quantitative Finance

You compute the Delta of a digital (cash-or-nothing) option by bumping the spot and using a central finite difference on a Monte Carlo price, reusing the same random numbers (common random numbers) for the up- and down-bumps. As you shrink the bump size h at FIXED number of paths N, the variance of the estimated Delta is observed to BLOW UP rather than settle.

What is the precise reason?

  1. For the discontinuous payoff, only paths landing within h of the barrier differ between bumps, so the finite-difference increment is O(1)/h on an O(h)-probability set; its variance scales like 1/h and diverges as hto 0 at fixed N.
  2. Common random numbers break down for digital payoffs because the up- and down-bumped prices become independent as hto 0, so differencing adds rather than cancels variance.
  3. The central difference's O(h^2) truncation error dominates at small h, and squaring it in the variance estimate produces the observed blow-up.
  4. Round-off error in subtracting two nearly equal Monte Carlo prices dominates once h falls below machine epsilon, which is the sole source of the variance increase.

Sign up free to see the explanation and track your rank →

More Quantitative Finance practice

KomFi Academy — Stop doomscrolling. Get KomFi.

Build your intelligence, anytime, anywhere.

KomFi Academy is a curated training platform with 54,000+ practice questions, 20,000+ flashcards, on-demand video lectures, podcasts, and 4K slide decks across the topics serious professionals study: GMAT, LSAT, MCAT, Investment Banking, Private Equity (LBOs & PE math), Private Credit, Quantitative Finance, Financial Accounting, Asset- Backed Securities, Volume Profile Analysis, Order Flow Trading, Market Microstructure, Volume Spread Analysis, Elliott Wave Theory, Volume-Price Analysis, and Public Offering Frameworks.

What's inside

Topics

View pricing · Read testimonials