easy · Quantitative Finance stochastic
Consider an It^o process dX_t = μ_t dt + σ_t dW_t. Under what condition is this process a martingale?
- The process is always positive.
- The drift coefficient μ_t is equal to zero for all t.
- The volatility coefficient σ_t is a constant.
- The drift μ_t equals the risk-free rate r.
Sign up free to see the explanation and track your rank →
More Quantitative Finance stochastic practice
- Under Girsanov's Theorem, what does a change of probability measure primarily alter in a s
- In the context of the HJM framework, what is the primary lesson regarding the drift of the
- In the Vasicek short-rate model dr_t = κ(θ - r_t) dt + σ dW_t, what happens to the drift w
- For a standard Brownian motion W_t, what is the expected value of W_t^2?
- Under the geometric Brownian motion model with μ = 0.12, σ = 0.30, and S_0 = 100, what is
- According to the lognormal property, what is the expected stock price at time T = 1 year i
- A stock follows geometric Brownian motion dS = μ S dt + σ S dW. Using Itô's Lemma, find th
- Under Girsanov's theorem, if a stock follows dS_t = μ S_t dt + σ S_t dW_t under the real-w