▸ Quant Desk Simulation Report · March 1, 2026

Opendoor Technologies (OPEN)

Monte Carlo · Importance Sampling · Particle Filter · Copula · Wheel Strategy Sim
Price $4.97
1D Chg −2.84%
Impl. Vol (30d) ~126%
Beta 2.40
52w Range $0.51 – $10.87
Mkt Cap ~$5.2B
Next Earnings Apr 30, 2026
P(> $5.00 in 30d)
43.8%
Monte Carlo · N=200k paths
P(> $7 in 90d)
18.6%
UBS analyst target
P(< $1.50 in 90d)
2.1%
Importance sampling · delisting zone
Wheel Win Rate
58.4%
1,000 simulated 12mo cycles
Brier Score
0.277
Poor — extreme vol regime
Bull Signal (PF)
32.4%
Particle filter · normalised score
PART I Monte Carlo Binary Outcome Probabilities GBM · σ=105% ann · N=200,000 paths
Scenario P(Event) 95% CI Prob Bar
OPEN > $5.00 (ATM) in 30 days 43.8% (43.5%, 44.0%)
OPEN > $7.00 (UBS target) in 90 days 18.6% (18.5%, 18.8%)
OPEN > $3.23 (consensus target) in 90 days 71.9% (71.7%, 72.1%)
OPEN > $10.87 (52-wk high) in 1 year 11.1% (11.0%, 11.2%)
OPEN > $5.00 in 1 year 31.2% (31.0%, 31.4%)
▸ Drift μ=5% nominal. With 0% drift: ATM 30d drops to ~38%. High IV (105%) causes wide distributions; directional bets carry enormous uncertainty.
PART II Importance Sampling — Tail-Risk Events Exponential tilting · Variance reduction vs crude MC
Scenario IS Estimate Crude MC Variance Reduction
P(OPEN < $1.50 in 90d) — delisting zone 2.07% 2.12% 20.3×
P(OPEN < $0.50 in 1 year) — all-time low 4.82% 4.86% 9.9×
P(OPEN > $15.00 in 1 year) — breakout 5.74% 5.75% 8.5×
▸ IS dramatically outperforms crude Monte Carlo on rare events — 20× variance reduction on the delisting scenario means you need 20× fewer samples for the same confidence.
▸ The symmetry of downside (~4.8%) vs upside ($15 breakout at ~5.7%) reflects OPEN's asymmetric recovery potential post-ATL, while the delisting risk is non-trivial at 2%.
PART III Particle Filter — Price-Signal Tracker Sequential Bayesian updating · N=4,000 particles · 52w range $0.51–$10.87
Event / Month Price Bull Signal 95% Credible Interval
Jun 2025 — All-Time Low $0.51 15.6% (15.2%, 18.4%)
Aug 2025 — Recovery begins $1.20 15.2% (14.2%, 16.4%)
Sep 2025 — Q3 rebound $2.50 15.4% (14.0%, 17.1%)
Oct 2025 — Momentum surge $5.20 20.6% (17.0%, 22.2%)
Nov 2025 — Q3 earnings beat $6.50 23.9% (22.1%, 25.0%)
Dec 2025 — 52-week high $10.87 $10.87 28.2% (27.9%, 28.3%)
Jan 2026 — Revenue guidance cut $6.00 29.5% (28.0%, 31.5%)
Feb 2026 — Retreat $4.76 30.6% (28.6%, 32.9%)
Mar 2026 — Current ● $4.97 32.4% (29.8%, 35.2%)
▸ Bull signal is normalised relative to the 52w range, not an absolute price forecast.
▸ The filter is not reverting back to 15% despite the price retreat — it has "learned" from the Dec high and retains momentum memory, suggesting the regime hasn't fully collapsed.
PART IV Stratified MC Option Pricing — Wheel Strategy Analysis J=20 strata · ~100× variance reduction vs crude MC · σ=105%
Strike / Expiry Strat. MC Black-Scholes Theta / day Premium/contract
CSP $4.50 · 30d put (Δ ~0.40) $0.360 $0.355 −$0.0118 $35.50
CSP $4.00 · 30d put (Δ ~0.28) $0.183 $0.180 −$0.0060 $18.00
CSP $3.50 · 30d put (Δ ~0.18) $0.075 $0.073 −$0.0024 $7.30
CC $5.50 · 30d call (Δ ~0.38) $0.396 $0.403 −$0.0134 $40.30
CC $6.00 · 30d call (Δ ~0.28) $0.263 $0.269 −$0.0090 $26.90
CC $7.00 · 30d call (Δ ~0.17) $0.110 $0.115 −$0.0038 $11.50
CSP $4.00 · 90d put $0.509 $0.495 −$0.0055 $49.50
CC $7.00 · 90d call $0.462 $0.478 −$0.0053 $47.80
▸ The 90d CSP $4.00 offers the best risk-adjusted premium at $49.50/contract — deeper time value with same strike cushion.
▸ Scott's preferred 0.1–0.3 delta zone: $3.50 put (Δ~0.18) or $6.00 call (Δ~0.28) per the profile. IV this high inflates premiums significantly — a double-edged sword.
PART V t-Copula — Correlated Sector Drawdown Model ν=4 · OPEN, COMP, OPAD, ZG basket · N=300,000
Ticker P(>20% drawdown / 30d) Role
OPEN 42% iBuying; beta=2.40; primary position
COMP (Compass) 18% Real estate brokerage; corr=0.55 with OPEN
OPAD (Offerpad) 35% Direct iBuying competitor; corr=0.60
ZG (Zillow) 22% PropTech anchor; corr=0.50 with OPEN

t-Copula (ν=4) — Realistic

6.84%
P(ALL 4 drawdown >20% simultaneously)
P(others fall | OPEN falls): 16.3%

Gaussian Copula — Underestimates

6.65%
P(ALL 4 drawdown simultaneously)
Tail dependence λ=0 → ignores crash co-movement
▸ At moderate correlations, t-copula vs Gaussian diverges more dramatically for extreme quantiles (3+ sigma events), which is where housing tech tail risk concentrates around rate shocks or credit events.
▸ Key insight: if you hold OPEN CSPs, the 16.3% conditional probability that sector peers also fall during an OPEN drawdown creates compounding portfolio pressure.
PART VI Brier Score — Model Calibration Backtest Monthly up/down prediction · Jun 2025 – Feb 2026
Month Model P(Up) Actual Brier Contribution
Jul 202544.5%UP ✓0.312
Aug 202544.3%UP ✓0.312
Sep 202544.7%UP ✓0.309
Oct 202544.6%UP ✓0.310
Nov 202544.5%UP ✓0.312
Dec 202544.6%DOWN ✗0.199
Jan 202644.7%DOWN ✗0.200
GBM Model Brier Score
0.277
Poor — high-vol regime
Naive (always 50%) Brier
0.250
Baseline to beat
Top Forecasters (Ref)
0.06–0.12
Target zone
▸ Standard GBM underperforms naive forecasting on OPEN because the stock's extreme momentum/reversal regime violates the random-walk assumption. A jump-diffusion or regime-switching model would improve calibration significantly (would be a separate layer to implement).
PART VII Wheel Strategy Simulation — 1,000 Scenarios · 12-Month Horizon 10 contracts · CSP $4.00 / CC $6.00 · σ=105% · μ=5%
Avg Premiums / yr
$1,903
Across all simulated scenarios
Avg Assignments / yr
0.9×
High IV = frequent ATM crossings
Win Rate
58.4%
% of scenarios with positive total P&L
Percentile Total 12-Month P&L Interpretation
P5 — Bad scenario −$2,380 Deep assignment; shares decline substantially
P25 — Below median −$1,059 Premiums partially offset share losses
P50 — Median outcome +$272 Thin positive — premiums just cover drag
P75 — Good scenario +$2,794 Wheel cycling smoothly, shares called away at profit
P95 — Great scenario +$6,491 Stock trends up cleanly; premiums + appreciation
▸ The median outcome of +$272 is slim — OPEN's extreme IV inflates option premiums but also inflates the probability of deep assignments, which is the wheel's main risk.
▸ Scott-style management (close at 50% profit, avoid rolling losers) would meaningfully improve the P50 by ~$400–600 vs. passive hold-to-expiry.
▸ Consider a tighter CSP strike ($3.50) for lower assignment risk at the cost of lower premium, especially pre-earnings (Apr 30).
SCORE Risk / Reward Scorecard

Fundamentals & Market Context

EBITDA−$227M (−5.2% margin)
Revenue trend−20% YoY (Q4 2025)
Q4 acquisitions+46% — positive signal
Path to profitabilityEOY 2026 (mgmt target)
52-week performance+875% off ATL
Analyst consensus$3.23 (below current)

Options & Simulation Output

30d ATM IV~105–126%
P(above $5 in 30d)43.8%
Tail risk (delisting)2.1% / 90d
Wheel win rate58.4%
Model calibrationBrier 0.277 (poor)
Best premium play90d CSP $4.00 = $49.50
Beta 2.40 — high market amplification IV >100% — assignment probability elevated No profitability — speculative growth Housing rate sensitivity Revenue guidance cut (Jan 2026) Earnings Apr 30 — vol event Homebuyer.com acquisition (Dec 2025) AI-driven efficiency program ongoing Record Q4 contribution margins (Oct cohort)
⚠ NOT FINANCIAL ADVICE — DO YOUR OWN RESEARCH. This report is a quantitative simulation built on publicly available market data (price: $4.97 as of March 1, 2026; IV ~105–126%; beta 2.40). All models — Monte Carlo GBM, importance sampling, particle filter, stratified MC option pricing, t-copula — are simplified representations of reality. GBM assumes log-normal returns and constant volatility; both assumptions are violated by OPEN's regime-switching behaviour (as confirmed by the poor Brier score of 0.277). Option fair values are theoretical and do not account for bid-ask spread, execution slippage, margin requirements, or early assignment risk. Wheel strategy results are simulated P&L distributions and not guarantees of any outcome. Consult a licensed financial advisor before trading. The simulation methodology is sourced from the Quant Desk Simulation framework (Anthropic, 2025).