For a random walk with drift, the best forecast of tomorrow's price is today's price plus a drift term. One could think of the drift as measuring a trend in the price (perhaps reflecting long-term ...

Let {Xk: k ≥ 1} be a sequence of independent, identically distributed random variables with $EX_{1} = \mu < 0$. Form the random walk {Sn : n ≥ 0} by setting S0 ...

We derive a perturbation expansion for general self-interacting random walks, where steps are made on the basis of the history of the path. Examples of models where this expansion applies are ...

For each indicator, the latest figure and its one-year, five-year, and 10-year changes are easy to understand in terms of raw data, but we need supplementary statistical analysis to determine whether ...