Absorbing floor and terminal-wealth distribution¶
Probability decomposition¶
At horizon \(T\), total probability is split into:
survived wealth above the floor;
an atom at the floor from diffusion paths that hit the absorbing barrier; and
wealth below the floor from crash jumps that overshoot the barrier.
The three masses should reconcile to one within numerical integration tolerance.
Public functions¶
Function |
Output |
|---|---|
|
probability of remaining above the absorbing barrier |
|
regime-conditional bounded transition densities |
|
exponentially tilted survival transform used in moments |
|
density of jump distance beyond the barrier |
For a terminal gap process, integrate compute_density on the positive gap grid and
compute_overshoot_density on the overshoot grid. The floor atom is the residual
\(1-S-O\) after survival mass \(S\) and overshoot mass \(O\) are computed. Use a grid that is wide and
fine enough for the desired tolerance; do not clip a negative residual silently without checking
integration error.
Units and interpretation¶
Density grids are in the log-gap or overshoot coordinate expected by the corresponding API, not directly in wealth units.
Wealth mapping requires the target wealth and buffer from the same Riccati solution.
A positive overshoot mass is expected in a jump model and is economically different from the diffusion floor atom.
Runnable source¶
examples/terminal_wealth_distribution.py
constructs the full decomposition and overlays an independent Monte Carlo histogram. It saves one
PNG. For regression tolerances, see validation.
Failure modes¶
Root-finding failure when Laplace characteristic roots are not separated cleanly.
An inversion/grid range that truncates material tail mass.
Mixing an asset specification with a gap process produced by another Riccati solution.
Confusing the exponential jump rate with its reciprocal mean.