Monte Carlo · Equities

Where GOOGL could go

The same simulation as DCI's, run on one of its assets: each path replays GOOGL's real daily moves, picked at random, one after the other.

Annualized return
+31.5%
since 31 Oct 2022
Volatility
31.5%
annualized
Sharpe ratio
1.03
risk-free rate 0%
Daily moves
1,003
in the sample
0 / 2,000 paths · log scale
  • GOOGL so far
  • Median (P50)
  • P10 – P90
  • Sample paths
$100$200$500$1K$2K$5K20232025202720292031Today

Past performance is not indicative of future results. These paths only replay GOOGL's past daily moves; they are not a forecast or a promise of any return.

In 5 years

Low case (P10)
—
—
Median (P50)
—
—
High case (P90)
—
—
Paths that end higher
—
than today's $279.84
YearP10P50P90P50 a year
Oct 2027————
Oct 2028————
Oct 2029————
Oct 2030————
Oct 2031————

How it works

Yahoo Finance daily closes of GOOGL on trading days, adjusted for dividends and splits. Since 31 Oct 2022 that gives 1,003 daily moves, about 251 a year. A path starts at today's price, picks one of those moves at random, applies it, and repeats at the same pace until the horizon. 2,000 paths are drawn; P10, P50 and P90 are the prices that 10%, 50% and 90% of them stay below on each day.

Each move is drawn on its own, so streaks and changes of regime are not modelled. A short history means a rough picture. This is past behaviour replayed, not a forecast: past performance is not indicative of future results, and GOOGL can lose value.