#!/usr/bin/env python3 """ Interactive Financial Stress-Testing Dashboard Single-file web app that models: - Net worth projections with BTC scenarios + h-clock cycle trade - Cashflow and break-even analysis - Stress tests + Monte Carlo BTC outcomes - Cycle trade simulator - BTC-denominated scoreboard Run: python /home/ben/ava/fund-model/app.py CLI: --host 0.0.0.0 --port 8235 --log-level info """ from __future__ import annotations import argparse import json import logging from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer from urllib.parse import urlparse LOGGER = logging.getLogger("fund-model") DEFAULTS = { # Core portfolio defaults from current plan "btcCagr": 25, "btcStack": 22.19, "btcPrice": 97_000, "strdPosition": 500_000, "strdYield": 14.66, "cash": 100_000, # Income / expenses "salaryGross": 240_000, "salaryNet": 170_000, "expensesNeeds": 75_000, "expensesWants": 58_000, "monthlyDca": 500, # Projection controls "horizonYears": 7, "quitJob": False, # h-clock cycle trade assumptions "cycleBottomMin": 25_000, "cycleBottomMax": 60_000, "cycleTopMin": 150_000, "cycleTopMax": 400_000, "cycleCapital": 500_000, "tradeDurationMonths": 18, "taxRate": 33, # Monte Carlo controls "mcVolatility": 65, "mcPaths": 1000, } HTML_TEMPLATE = r""" Fund Model — Stress Dashboard

Financial Stress Dashboard

Interactive personal model (BTC + STRD + cashflow + cycle trade)

Core BTC / Portfolio

BTC CAGR (base)

BTC Stack (BTC)

BTC Price Now ($)

Cash Reserve ($)

Income & Expenses

Salary Net / Year ($)

Annual Needs ($)

Annual Wants ($)

Monthly DCA ($)

Quit job mode (salary = 0)

STRD Position

STRD Position ($)

STRD Yield % (annual)

Cycle Trade Inputs

Bottom Min ($)

Bottom Max ($)

Top Min ($)

Top Max ($)

Capital Deployed ($)

Trade Duration (months)

LTCG Tax Rate %

Projection / Monte Carlo

Projection Horizon

BTC Volatility % (ann.)

Monte Carlo Paths

Base NW (horizon)

Pessimistic NW

Optimistic NW

Base BTC Stack (horizon)

Net Worth Path with BTC Price Scenarios + h-clock Trade

Band = pessimistic to optimistic. Base uses your slider CAGR. Model applies STRD → IBIT cycle trade (sell Aug 2026, buy bottom window, sell late 2027 with LTCG tax).

Monthly Surplus

Annual Surplus

BTC Buy Capacity / Year

Passive Coverage (expenses)

Cashflow Breakdown

NW if BTC -50%

NW if BTC -70%

NW if BTC -80%

Runway if job loss

Cashflow if STRD = 0

Worst case (all 3)

Monte Carlo (N paths, 5 years)

Geometric Brownian Motion with drift from BTC CAGR and volatility input. Shows distribution of year-5 net worth.

Base BTC Bought

Base Net Profit (after tax)

STRD Hold Yield (same period)

Cycle Advantage vs STRD

Cycle Trade Scenarios

Scenario	Bottom	Top	BTC Bought	Gross Profit	Tax	Net Profit

Cycle Net Profit vs STRD Counterfactual

Real BTC (on chain / custody)

NW in BTC terms

Real / NW %

Sat accrual (salary, monthly)

Sat accrual (net, monthly)

BTC yield from cycle trade (base)

Real BTC vs Fiat-Equivalent BTC

""" def build_html() -> bytes: html = HTML_TEMPLATE.replace("__DEFAULTS__", json.dumps(DEFAULTS)) return html.encode("utf-8") class AppHandler(BaseHTTPRequestHandler): def _send(self, status: int, content_type: str, body: bytes = b"", head_only: bool = False) -> None: self.send_response(status) self.send_header("Content-Type", content_type) self.send_header("Content-Length", str(len(body))) self.end_headers() if not head_only and body: self.wfile.write(body) def do_GET(self) -> None: parsed = urlparse(self.path) if parsed.path in {"/", "/index.html"}: self._send(200, "text/html; charset=utf-8", build_html()) return if parsed.path == "/healthz": payload = json.dumps({"ok": True}).encode("utf-8") self._send(200, "application/json", payload) return self._send(404, "text/plain; charset=utf-8", b"Not Found") def do_HEAD(self) -> None: parsed = urlparse(self.path) if parsed.path in {"/", "/index.html"}: self._send(200, "text/html; charset=utf-8", build_html(), head_only=True) return if parsed.path == "/healthz": payload = json.dumps({"ok": True}).encode("utf-8") self._send(200, "application/json", payload, head_only=True) return self._send(404, "text/plain; charset=utf-8", b"Not Found", head_only=True) def log_message(self, fmt: str, *args) -> None: LOGGER.info("%s - %s", self.address_string(), fmt % args) def parse_args() -> argparse.Namespace: parser = argparse.ArgumentParser(description="Interactive fund model dashboard") parser.add_argument("--host", default="0.0.0.0", help="Host to bind (default: 0.0.0.0)") parser.add_argument("--port", default=8235, type=int, help="Port to bind (default: 8235)") parser.add_argument( "--log-level", default="info", choices=["debug", "info", "warning", "error", "critical"], help="Logging verbosity", ) return parser.parse_args() def main() -> None: args = parse_args() logging.basicConfig( level=getattr(logging, args.log_level.upper(), logging.INFO), format="%(asctime)s %(levelname)s %(name)s: %(message)s", ) server = ThreadingHTTPServer((args.host, args.port), AppHandler) LOGGER.info("Serving dashboard on http://%s:%s", args.host, args.port) try: server.serve_forever() except KeyboardInterrupt: LOGGER.info("Shutting down...") finally: server.server_close() if __name__ == "__main__": main()