Demo — Market Risk

Analysis Demos

EquityAAPL

CryptoBTCUSD

ForexEURUSD

Tools

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Portfolio

Tracking

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About

Disclosure

Equity Analysis · AAPL

Apple Inc.

18 analytical methods fire simultaneously. Stochastic DCF with sector routing, 5,000-path Monte Carlo, 4-factor regression against FRED macro data, automated stress testing, risk scoring, and 17 interactive charts — from one engine run.

You can already look up a stock's P/E ratio anywhere. This runs 18 computational methods and tells you the probability your investment makes money, what it's worth under 3,000 different assumptions, and exactly how much you could lose.

Engine Verdict

+18.4%

Expected Return

$234

Fair Value

8.2

Risk Score /25

62%

Prob. Profit

-14.2%

VaR 95%

0.89

Sharpe

15 Forecast Charts

01 · Monte Carlo Simulation

5,000 paths · GBM

5,000 simulated futures. 62% end above today's price. Median outcome $234 over 12 months.

Median$234.20

P10 – P90$168 — $312

Prob. Profit62.4%

Expected+18.4%

02 · Volatility Cone

Historical percentiles

Current vol is in the 40th percentile — normal, not stretched. The cone shows where vol typically sits at each horizon.

03 · Value at Risk

Parametric + Historical

Worst expected loss at 95% confidence. Everything left of the red line is the tail — the 5% of scenarios where things go wrong.

Ann. Vol24.8%

Sharpe0.89

Sortino1.24

Max DD-18.3%

04 · Stochastic DCF — Fair Value

3,000 sims · Sector-routed

3,000 DCF simulations with randomised growth, margins, and discount rates. Median fair value $234 (green) vs market $198 (red). Sector routing picks the right model — corporate FCF for tech, DDM for banks, NAV for REITs.

Fair Value$234.20

P25 – P75$208 — $268

Upside+18.0%

05 · Sensitivity Analysis (Tornado)

Top 6 factors

Which inputs move the price most. Revenue growth matters most — a 1% change swings fair value by $12. Discount rate is second.

06 · Factor Regression Betas

4-factor OLS · FRED data

AAPL moves 1.18× with SPY but only 0.3× with rates. Four-factor OLS regression against FRED macro data. R² shows how much of the variance is explained.

SPY Beta1.18

Rate Beta0.30

R²0.74

Alpha+2.1%

07 · Stress Test Scenarios

6 sector-specific scenarios

In a 2008-style crash, the model shows a -34% drawdown. Rate hike scenario: -12%. Dovish pivot: +18%. Six sector-specific scenarios from the template.

08 · Horizon Dashboard

3M – 5Y comparison

Short-term momentum is positive. Long-term mean reversion is neutral. Method weights shift automatically — 3M emphasises momentum, 5Y emphasises fundamentals.

09 · Risk Metrics Overview

Sharpe 0.89, Sortino 1.24, Calmar 0.67. Getting paid for the risk — Sortino confirms downside risk is well-compensated.

Sharpe0.89

Sortino1.24

Calmar0.67

Ann. Vol24.8%

10 · Price Projection — Fan Chart

12-month forward

Time-series fan showing the path, not just the destination. P25–P75 band over 12 months: $208–$268. Narrower than the MC histogram because paths are correlated over time.

11 · Drawdown Timeline

4 years of history

Worst drawdown in 4 years: -18.3%. Recovery took 4 months. Every peak-to-trough decline mapped. Deeper and longer drawdowns signal higher risk.

Max Drawdown-18.3%

Avg Recovery47 days

Current DD-1.2%

12 · Mean Reversion — Z-Score

200-day baseline

Z-score +0.4σ — slightly above the 200-day average. Not overextended. Crosses ±2σ (red zones) signal extreme stretch with high mean-reversion probability.

13 · Seasonality — Monthly Returns

4-year averages

Q4 is historically strongest (Oct–Dec green). February and September tend weakest. Based on 4 years of monthly return averages.

14 · Factor Correlation Matrix

Heatmap

AAPL correlates 0.82 with QQQ (bright) but only 0.31 with gold (dim). Bright squares = high correlation. Helps identify what's actually driving the stock.

15 · Scenario Tree

Probability-weighted

Bull case (35% prob): $268. Base (45%): $234. Bear (20%): $178. Probability-weighted outcomes from the sector template's scenario events.

Bull (35%)$268

Base (45%)$234

Bear (20%)$178

Plus

16 · Dividend Profile

Dividend history with growth trajectory. Current yield, 5-year growth rate, consecutive streak, safety score (0–100), best month to buy. Badges: Dividend King (50+ yr), Aristocrat (25+), Achiever (10+).

Yield0.52%

Growth (5Y)+5.2%

Streak12yr

Safety78

17 · Interactive Chart Workspace

TradingView LC · 9 timeframes

Candlestick, line, area, or bar charts with volume overlay. RSI and Bollinger Band sub-panels. 9 timeframes from 1W to Max. Independent from the analysis horizon — browse the chart while the engine runs.

Risk Assessment Matrix

5×5 Risk Matrix

8.2 / 25

Market

Operational

Financial

Regulatory

Strategic

Beyond the Forecasts — 6 Analysis Tabs

Overview Tab

Engine verdict with 6 key metrics. Cause-effect chain showing how sector dynamics flow through to the stock. Leading indicators to watch. Space for your own analyst notes — your research, organized alongside the engine output.

Risk Assessment Tab

Interactive 5×5 risk matrix. Likelihood × Impact scoring across 5 categories. The engine auto-scores from market data and financials — you can override any score. Composite risk number for cross-stock comparison.

Forecasts Tab

All 15 charts above. Each chart card is clickable — opens an insight overlay with "What This Tells You" (contextual analysis from THIS stock's data) and "How It Works" (methodology background).

Research Tab

Interactive chart workspace with candlestick, line, area, or bar charts. Volume, RSI, Bollinger Band overlays. 9 timeframes (1W to Max). Dividend profile with safety scoring. Independent from the analysis — browse while the engine runs.

Scenarios Tab

Stress scenarios from the sector template — rate hikes, recession, oil shock, specific sector risks. Each scenario shows factor shocks and expected portfolio impact. Scenario event trees with probability-weighted outcomes.

Factors Tab

The regression factors used for this sector — which FRED macro series drive the stock and how. DCF model structure showing revenue driver, cost driver, terminal approach, and key assumptions for this sector.

Data Collected Per Analysis

Market Data

4 years of daily price history. Current quote with price, volume, market cap. 52-week range. Sector classification (GICS). All from Financial Modeling Prep (FMP).

Fundamentals

5 years of annual + 8 quarters of financial statements: income statement, balance sheet, cash flow. Key metrics: PE, PS, PB, EV/EBITDA, dividend per share, payout ratio, book value.

Macro Factors

FRED economic data: Treasury yields (2Y, 10Y), yield curve spread, Fed Funds rate, VIX, crude oil, gold, USD index, CPI, consumer sentiment, housing starts, manufacturing employment.

Sector Intelligence

20 sector templates (11 GICS equity + 5 crypto + 2 forex + 2 base). Each template defines: regression factors, DCF model structure, stress scenarios, risk factor descriptions, leading indicators, cause-effect chains.

Crypto Analysis · BTCUSD

Bitcoin

Crypto-native analysis: Student-t fat-tailed Monte Carlo with regime switching, NVT proxy valuation, momentum regime detection. No DCF — crypto has no cash flows.

The same GBM model that works for Apple will give you garbage for Bitcoin. Crypto has fat tails and regime switches — quiet months interrupted by 40% moves. We model that.

How crypto analysis differs

Monte Carlo uses Student-t distributions (fat tails, df=4.5) with regime-switching volatility (quiet ×1, volatile ×2.5). No DCF — replaced by NVT proxy and momentum regime detection. Risk categories swap to: Volatility, Liquidity, Protocol, Regulatory, Concentration.

Engine Verdict — Crypto

+42.1%

Expected Return

$2.1T

Market Cap

Bull

Regime

58%

Prob. Profit

24%

Prob. 2×

Prob. ½

Monte Carlo — Student-t Fat Tails

5,000 paths · Regime switching

Wider fan than equity MC — fat tails capture extreme moves. 10th percentile drops to $58K, 90th reaches $248K. Regime switching models quiet vs volatile crypto periods.

14 Forecast Charts for Crypto

02 · Volatility Cone

Crypto vol is in the 85th percentile — elevated but not extreme for BTC. The cone is wider than any equity because crypto's vol range is 40%–120% annualised vs equity's 15%–40%.

03 · Value at Risk

VaR 95% is -8.4% daily for BTC. That's 3× worse than AAPL. The left tail is fatter — Student-t captures this. Maximum drawdown -72% in 4 years. This is the price of asymmetric upside.

06 · Factor Regression

BTC/ETH/DXY factors

BTC beta to ETH: 0.72 (they move together). DXY beta: -0.31 (dollar up = BTC down). VIX beta: -0.18. R² = 0.41 — crypto is harder to explain with macro factors than equities. That's the point.

07 · Stress Tests

Crypto-specific scenarios

Exchange collapse scenario: -55%. Regulatory ban: -42%. Risk-off shock: -38%. But dovish pivot: +65%. Crypto stress tests are asymmetric — the upside scenarios are as extreme as the downside.

08 · Horizon Dashboard

3M momentum: bullish. 12M trend: positive. But 5Y mean reversion says BTC is above its long-term growth trajectory. Short-term signals and long-term signals disagree — that's useful information.

09 · Risk Metrics

Sharpe 0.52, Sortino 0.78. Lower than AAPL — crypto gives you more return but demands more volatility. Calmar 0.31 — the max drawdown is brutal relative to the annualised return.

10 · Fan Chart

Much wider fan than equity. The P10–P90 range for BTC over 12 months: $58K–$248K. That's a 4× spread. For AAPL it's $168–$312 (1.9× spread). This is what 70%+ annualised vol looks like.

11 · Drawdown Timeline

Worst drawdown: -72%. Recovery: 14 months. This is normal for crypto. The question isn't whether it draws down — it will. The question is whether you can hold through it.

12 · Mean Reversion Z-Score

BTC Z-score +1.2σ above the 200-day average. Stretched but not extreme. Crypto Z-scores regularly hit ±3σ during bull/bear cycles. At ±2σ, mean reversion probability increases significantly.

13 · Seasonality

Q4 and Q1 historically strongest for BTC. September weakest. But crypto seasonality is less reliable than equities — sample size is smaller and regime changes matter more than calendar effects.

14 · Correlation Matrix

BTC–ETH: 0.85 (practically the same trade). BTC–SPY: 0.42 (moderate, increasing over time). BTC–Gold: 0.12 (the "digital gold" narrative doesn't show up in the data).

15 · Scenario Tree

Bull (30%): $248K. Base (40%): $152K. Bear (30%): $58K. The probabilities are more evenly split than equities — crypto genuinely has higher uncertainty in both directions.

17 · Chart Workspace

Same interactive candlestick/line/area workspace. Crypto volume patterns matter — look for volume spikes confirming price moves. Low-volume rallies are suspect.

Crypto Risk Matrix

Risk Matrix

14.6 / 25

Volatility

Liquidity

Protocol

Regulatory

Concentration

Crypto Data Collected

Price & Volume

4 years of daily OHLCV data. Volume profile for liquidity assessment. Market cap tracking.

Crypto Factors

Regression against BTC, ETH, SOL, DOGE, LINK, BNB. Plus DXY, VIX, Treasury yields from FRED. 5 crypto sector templates: L1, DeFi, Exchange, Infrastructure, Meme.

Forex Analysis · EURUSD

EUR/USD

Rate-driven analysis: interest rate differentials between ECB and Federal Reserve, Ornstein-Uhlenbeck mean-reverting Monte Carlo, PPP deviation, REER Z-score.

Currencies don't trend — they revert to equilibrium. The standard Monte Carlo assumes a random walk. We use Ornstein-Uhlenbeck because that's actually how forex behaves.

How forex analysis differs

Monte Carlo uses Ornstein-Uhlenbeck mean-reverting process — currencies snap back to equilibrium, they don't random walk like equities. Analysis centers on interest rate differentials from FRED (ECB vs Fed, BOE vs Fed, BOJ vs Fed). No DCF. Risk categories: FX Volatility, FX Liquidity, Macro Divergence, Central Bank, Geopolitical.

Engine Verdict — Forex

2.00%

ECB Rate

4.50%

Fed Rate

-2.50%

Differential

USD

Carry Favours

1.0920

Equilibrium

54%

Prob. Above

Monte Carlo — Mean Reverting (OU)

5,000 paths · θ=0.05

Fan pulls toward equilibrium at 1.0920. Narrower than equity MC — forex majors revert, they don't trend. The OU process models mean-reversion speed (θ=0.05 for majors).

14 Forecast Charts for Forex

02 · Volatility Cone

EUR/USD vol at the 30th percentile — quiet. Forex major pair vol is typically 7–12% annualised, far lower than equities. But central bank meetings create discrete jumps that the cone doesn't capture.

03 · Value at Risk

VaR 95% is -0.9% daily for EUR/USD. Sounds small — but leveraged forex positions amplify this. The return distribution is tighter and more symmetric than equities. Max drawdown -8.2% over 4 years.

06 · Factor Regression

DXY / Rates / VIX

DXY beta: -0.92 (EUR/USD moves almost 1:1 inverse to dollar index). 2Y yield beta: -0.28 (higher US rates = stronger dollar = EUR/USD down). VIX beta: -0.15 (risk-off = dollar strength). R² = 0.86 — forex is highly macro-driven.

07 · Stress Tests

Forex scenarios

Fed hawkish pivot: EUR/USD -4%. Risk-off shock: -3% (dollar strengthens). BOJ intervention: ±5% on JPY pairs. Dovish pivot: EUR/USD +5%. Oil spike: EUR weakens (energy importer).

08 · Horizon Dashboard

Short-term: USD momentum fading. Medium-term: rate differential still favours USD. Long-term: PPP suggests EUR is undervalued. Different horizons tell different stories — that's why we show all of them.

09 · Risk Metrics

Sharpe 0.18 for EUR/USD. Low — but forex returns are low because vol is low. Sortino 0.24. The key metric for forex is the carry return vs the vol — are you getting paid to hold the position?

10 · Fan Chart

Narrow fan — forex majors don't move as much as equities. The P25–P75 band over 12 months for EUR/USD: 1.05–1.12. The fan pulls toward equilibrium because of the OU mean-reverting process.

11 · Drawdown

Max drawdown -8.2% over 4 years. Shallow compared to equities — but forex positions are often leveraged 10–50×, so a -8% move at 20× leverage is a -160% account wipeout. Context matters.

12 · Mean Reversion Z-Score

EUR/USD Z-score -0.6σ below the 200-day average. Modestly undervalued relative to recent history. Forex Z-scores are more reliable than equity Z-scores because currencies actually mean-revert.

13 · Seasonality

December: EUR weakens (year-end dollar demand, repatriation flows). January: EUR strengthens (new allocation cycles). Forex seasonality is driven by institutional flow patterns, not earnings cycles.

14 · Correlation Matrix

EUR/USD–GBP/USD: 0.78 (both move inverse to dollar). EUR/USD–USD/JPY: -0.55 (opposite dollar exposure). EUR/USD–Gold: 0.38 (both anti-dollar). The dollar index drives everything.

15 · Scenario Tree

ECB catches up to Fed (40%): EUR/USD 1.14. Status quo (35%): 1.09. US recession (25%): EUR/USD 1.18. Note: all scenarios are above current — the rate differential is expected to narrow.

17 · Chart Workspace

Same interactive workspace. Forex charts benefit from the 1W and 2W timeframes — short-term forex moves are driven by news flow and positioning, not fundamentals.

Forex Risk Matrix

Risk Matrix

7.4 / 25

FX Volatility

FX Liquidity

Macro Divergence

Central Bank

Geopolitical

Forex Data Sources

Rate Data (FRED)

ECB Deposit Facility Rate, SONIA (Bank of England), Japan 3M Interbank, Fed Funds Rate, 2Y/10Y Treasury yields. Live from the Federal Reserve Economic Data API.

Forex Factors

Regression against USD Index (DXY), 2Y/10Y yields, yield curve spread, VIX, crude oil. 2 forex templates: Major pairs and Exotic pairs with tailored scenarios.

Dividend Tools

Dividend Hunter & Capture

Screen S&P 500 by yield, safety, growth, and payout. Identify capture opportunities with scored ex-date calendars. Track streaks, find aristocrats, project income.

Most dividend screeners show you yield and nothing else. We score safety — because a 6% yield that gets cut to 0% isn't a dividend, it's a trap. AT&T taught that lesson.

Dividend Hunter

Screen the S&P 500 by yield, safety score, streak, 5-year growth, and payout ratio. Sort by any column. Filter by sector, minimum yield, minimum streak. Every stock gets a composite safety score (0–100) based on payout ratio, free cash flow coverage, debt levels, earnings stability, and consecutive payment streak.

Capture Calendar

Monthly calendar showing every ex-dividend date in the S&P 500. Click a date to see which stocks go ex that day. Each opportunity scored by yield, volatility, and historical recovery pattern. Filter by universe: All S&P 500, Blue Chip (>$100B), High Yield (>3%), or by sector.

Safety Scoring

Composite 0–100 score. Factors: payout ratio (lower = safer), free cash flow coverage (can they afford the dividend?), debt/equity (are they borrowing to pay?), earnings stability (consistent or volatile?), streak length (how long have they paid?). Badges: King (50+ yr), Aristocrat (25+), Achiever (10+).

Capture Signals

For each stock near its ex-date: ex-date drop behaviour (does price drop the full dividend?), recovery speed (how fast does it bounce?), volatility context (is the stock calm or choppy?), yield vs risk tradeoff. Scored as good / neutral / caution.

Sample · Dividend Hunter

Safety Score

3.3%

Yield

25yr

Streak

+7.2%

5Y Growth

Top Dividend Picks

Ticker

Name

Yield

Safety

Streak

Growth

JNJ

Johnson & Johnson

3.3%

62yr

+5.8%

Procter & Gamble

2.4%

68yr

+6.1%

Coca-Cola

3.0%

62yr

+3.4%

ABBV

AbbVie

3.8%

52yr

+8.2%

AT&T

6.2%

0yr

-47%

Portfolio Analysis

Growth Portfolio

Correlated Monte Carlo with Cholesky decomposition, efficient frontier, correlation heatmap, aggregated stress tests, sector exposure, and per-holding P&L tracking.

Analysing stocks individually misses the point. Your AAPL and MSFT are 0.85 correlated — you don't have two positions, you have one big tech bet. Portfolio analysis shows you what you actually own.

Correlation Matrix

Heatmap showing how every holding moves relative to every other. High correlation (>0.7) means your diversification is weaker than you think. Helps identify redundant positions.

Efficient Frontier

500 random portfolio weights plotted on a risk-return chart. Your current allocation shown as a dot. If you're below the frontier, you can get more return for the same risk by rebalancing.

Correlated Monte Carlo

Cholesky decomposition preserves inter-stock correlations during simulation. The portfolio fan chart is more realistic than running MC on each stock independently and summing.

Aggregated Stress Tests

How the PORTFOLIO (not individual stocks) responds to scenarios like rate hikes, recession, oil shock. A portfolio of tech + energy may hedge a scenario that kills tech alone.

Sector Exposure

Pie chart showing concentration by GICS sector. If 60% of your portfolio is technology, you know your fate is tied to one sector.

Diversification Ratio

Weighted average of individual vols / portfolio vol. Above 1.2 = good diversification benefit. Below 1.05 = your holdings are so correlated you barely benefit from having multiple positions.

Sample Portfolio

+14.2%

Expected Return

18.4%

Portfolio Vol

-12.1%

VaR 95%

0.77

Sharpe

1.34×

Diversification

59%

Prob. Profit

Holdings · $147,200

+$11,380 · +12.4%

Ticker

Name

Weight

Value

P&L

P&L %

AAPL

Apple

28.5%

$41,668

+$5,210

+14.3%

MSFT

Microsoft

24.2%

$35,581

+$3,840

+12.1%

JNJ

J&J

16.8%

$24,676

-$1,240

-4.8%

XOM

Exxon

14.1%

$20,772

+$2,160

+11.6%

Thesis Tracker

Tracking

Lock the price the day you spot an opportunity. Set buy and sell flags. Configure your chart with custom indicators. Come back in a week, a month, a year — see if your analysis held up.

You ran the analysis. You spotted the opportunity. But three weeks later, you forgot what price you saw it at and whether your thesis is playing out. Tracking locks the price the day you flagged it and shows you the answer every time you open the page.

Locked price

The market price at the moment you click "Track This." Immutable — it never changes. This is your anchor point. Every time you open the page, you see how far price has moved from where you started watching.

Buy & sell flags

Set optional price levels where you'd be interested in buying or selling. Green and red dashed lines on the chart. Not triggers, not orders — just your thinking made visible. Editable anytime as your thesis evolves.

Custom chart config

Each tracked stock gets its own indicator setup. AAPL with trend indicators (SMA 50/200, ADX), BTCUSD with momentum (EMA 12/26, MACD), JNJ with volatility (Bollinger, ATR). Or use presets: Momentum, Trend, Volatility, Mean Reversion.

Thesis accountability

"I tracked AAPL at $198, set a buy flag at $180, sell flag at $260. It's $234 now, up 18% in 79 days." One glance and you know if your analysis was right. No other platform anchors to YOUR decision point.

Sample tracking grid

AAPLApple

+18.0%

$198.42 · Mar 12 · 79 days

$234.20+$35.78

▽ Buy $180△ Sell $260

Viewed 2h ago · SMA 50 · SMA 200 · RSI · Vol

BTCUSDBitcoin

-14.9%

$108,240 · Apr 3 · 57 days

$92,100-$16,140

▽ Buy $85,000△ Sell $130,000

Viewed 3d ago · EMA 12 · EMA 26 · MACD · Vol

Chart builder

11 overlays

SMA 20/50/100/200, EMA 12/26/50, Bollinger Bands, VWAP, Envelope Channel, Ichimoku Cloud. Toggle any combination. Each saved per-stock.

7 sub-panels

Volume, RSI, MACD, Stochastic %K/%D, ADX (trend strength), OBV (on-balance volume), ATR (average true range). All computed client-side — no API delay.

4 presets

Momentum (EMA 12/26 + RSI + MACD). Trend (SMA 50/200 + ADX). Volatility (Bollinger + Envelope + ATR). Mean Reversion (SMA 200 + Bollinger + RSI + Stochastic). One click to apply, then customise.

Sort & monitor

Sort by best/worst performing, recently/least viewed, oldest tracked, alphabetical. Grid view (2× or 3×) or list. Expand any card to full-screen. Refresh all quotes in one click.

Not a watchlist — a thesis tracker

A watchlist is a list of tickers. Tracking is a list of theses. Each card answers one question: "I flagged this stock at this price — was I right?" The locked price never moves. The buy and sell flags are your thinking made visible. Come back in a month and the chart tells the story.

Index Analysis

S&P 500 + IPO Calendar

Every stock in the S&P 500, analysed by the engine once a month. Bear, Base, and Bull scenarios with traffic light scoring. Plus upcoming and recent IPOs.

Running the engine on 500 stocks one at a time would take you days. We do it automatically on the first Monday of every month. Sort by probability of profit and the top opportunities surface instantly.

Monthly batch engine

The same engine that runs when you analyse a single stock — Monte Carlo, stochastic DCF, risk scoring — runs automatically on all 500 S&P stocks. Results stored and sortable.

Bear / Base / Bull

Three traffic lights per stock. Bear ratio (how bad could it get), Base ratio (is it cheap or expensive), Bull ratio (how good could it get). Green / yellow / red at a glance.

Trend arrows

Month-over-month comparison. ↑ means the engine is more bullish than last month. ↓ means less bullish. → means unchanged. Spot momentum shifts across the index.

Excel export

Download all 500 stocks with 25 columns of data: ratios, scenarios, risk scores, Sharpe, Sortino, VaR, individual risk categories, fair value, market cap. Build your own models on top.

Sample · S&P 500 Batch

Traffic light system

3 dots per stock

TickerBearBaseBullProbRisk
NVDA0.691.32 ↑1.7584%11.2
AAPL0.901.18 →1.3562%8.2
JNJ0.961.10 ↑1.2159%4.2
INTC0.500.79 ↓1.3638%16.8

IPO Calendar

Upcoming IPOs

See what's coming to market in the next 3 months. Company name, ticker, exchange, expected price range, shares offered, and estimated valuation.

Recent IPOs

What listed in the last 3 months and how they priced. Track new listings from day one by adding them to your Tracking page.

Disclosure

What This Is. What It Isn't.

These are not legal boilerplate. They are statements about what the tool does and does not do. Full disclosure page →

×REF-01Not Financial Advice

Market Risk runs quantitative models on market data. It does not tell you what to buy, sell, or hold. Models are built on assumptions and historical data — both can be wrong. A Monte Carlo simulation showing 62% probability of profit means there is a 38% probability of loss.

×REF-02Not a Guarantee

Every number produced by this platform is an estimate derived from a model. Models simplify reality — that is their purpose and their limitation. Monte Carlo paths are probability distributions, not predictions.

×REF-03Analysis Can Be Wrong

All analysis can be wrong. Historical volatility may understate future volatility. Factor relationships may break down during crises. The engine does not claim to predict the future.

×REF-04Your Research, Your Risk

Every analysis you run is private. We don't share it, sell it, or trade on it. What you do with the analysis is entirely your responsibility.

×REF-05Data Sources & Limitations

Market data from FMP. Macro indicators from FRED. Data may be delayed, incomplete, or contain errors. Price history capped at ~4 years. Not real-time.