MAISNER

Ref.	Mode	Note	Timestamp	Assets	Value	Status
Loading...

Member	Role	Today	This Week	Total	Top Feature	Last Active
Loading…

Start

Overview

Quick Start

Tools

Analyzer

Optimizer

Multi-Asset

Stress Test

Advanced Stress

Frontier

Research

Tax Harvesting

Constrained Optimizer

Leverage Analyzer

Stop Loss

Attribution

Portfolio Monitor

Long/Short Opt.

Long/Short Anal.

Hedging Optimizer

PRIIPs KID

Alert System

Visualizers

Portfolio Chart

Options Risk

News Globe

Metrics

Risk Metrics

Factors

Backtesting

Welcome to MAISNER

A personal Bloomberg terminal for portfolio intelligence. Built for independent wealth managers and serious private investors.

◈

Analyzer

Enter your current holdings and get a full optimization with rebalancing plan.

◎

Optimizer

Build an optimal portfolio from scratch using Markowitz + RMT covariance.

◈

Multi-Asset

Mix stocks, options, bonds, futures, and crypto in one optimized portfolio with Greeks and CVaR.

◉

Stress Test

Replay 2008, 2020, 2022 crises — or build custom macro scenarios with sector and ticker shocks.

◌

Frontier

Interactive efficient frontier — move sliders and watch your portfolio shift in real time.

◧

Research

Factor Explorer, Strategy Builder, and Signal Analysis for systematic quant research.

◫

Tax Harvesting

Identify loss positions for tax harvesting with wash-sale warnings and substitute suggestions.

◩

Constrained Optimizer

Lock positions, set per-ticker bounds, define sector floors/ceilings — optimize the remaining free budget.

◎

Portfolio Chart

TradingView-style historical performance chart with SPY benchmark. Open via Chart button in the header.

◈

Options Risk

3D P&L and Greeks surfaces for any option in your portfolio. Theta decay and delta profile charts included.

◌

News Globe

Financial news geo-located on a 3D interactive globe. Click any dot to read the full story.

◫

Metrics

Understand every number — Sharpe, Sortino, Max Drawdown, Calmar and more.

How MAISNER works

MAISNER pulls 10 years of monthly price history and fundamentals for every ticker in your database. When you run an analysis, it builds a covariance matrix cleaned with Random Matrix Theory (Marchenko-Pastur filter), then runs a Markowitz Mean-Variance optimisation tilted toward quality factors — ROE, margins, and debt coverage.

The result is not just optimal weights — it's a full rebalancing plan with exact share counts, Monte Carlo projections, sector exposure, and correlation maps.

⚠ Beta Notice

MAISNER is in closed beta. All outputs are for informational purposes only and do not constitute investment advice. Always verify results independently before making any financial decision.

Quick Start

From zero to your first optimized portfolio in under 3 minutes.

Option A — Analyze an existing portfolio

Go to the Analyzer tab. Click + Add position for each stock you hold.

Enter the ticker symbol (e.g. AAPL, MSFT, ASML) and the number of shares you own.

Choose an optimization mode: Conservative, Balanced, Aggressive, or Dividend.

Click Run Analysis. Wait 30–60 seconds while the system fetches data and computes.

Review your results: current vs optimal weights, rebalancing plan with exact share counts, risk metrics, and Monte Carlo projection.

Click Save Portfolio to store the result for future reference or stress testing.

Option B — Build from scratch

Go to the Optimizer tab. Enter a list of tickers you want to consider — or leave empty to use all available tickers.

Select optimization mode and click Run Optimization.

The system returns the maximum Sharpe ratio portfolio, a minimum variance alternative, and an equal-weight benchmark for comparison.

Supported tickers

US tickers work out of the box (AAPL, MSFT, NVDA…). European tickers are auto-resolved: just type the base symbol (e.g. SAP, ASML, ENI) and the system will find the right exchange suffix (.DE, .MI, .L, .PA etc.).

ETFs are fully supported and get a combined 50% sector cap to prevent over-indexing.

Weight formats — Stress Test, Leverage, Stop Loss, Advanced Stress

When entering portfolio weights manually in Stress Test, Leverage Analyzer, Stop Loss Calculator, or Advanced Stress Test, always enter weights as percentages (0–100), not fractions.

            AAPL   35   ← correct (35%)

            MSFT   25   ← correct (25%)

            NVDA   40   ← correct (40%)

            ──────────────────

            AAPL   0.35   ← wrong — interpreted as 35% also due to auto-detection, but ambiguous for values < 1%

When loading a saved portfolio into these tools, weights are converted automatically — no manual entry needed.

Analyzer uses shares (not percentages). Optimizer uses tickers only — the system finds the optimal weights.

Portfolio Analyzer

Takes your real holdings (ticker + shares), runs full Markowitz optimization, and produces a precise rebalancing plan.

Optimization Modes

Conservative

Maximizes risk-adjusted return (Sharpe) with a quality tilt — favours high ROE, low debt, strong margins. Best for long-term wealth preservation.

Balanced

Sharpe maximization with a volatility cap you set manually. Useful when you need growth but want to bound portfolio risk.

Aggressive

Maximizes expected return regardless of volatility. Higher risk, higher potential upside. Not suitable for capital preservation.

Dividend

Maximizes dividend yield weighted by quality score. Designed for income-focused portfolios. Filters out low-yield positions.

What the results show

Weights Table

Curr % — your current allocation based on market value of shares held.

Opt % — the mathematically optimal allocation for your selected mode.

Δ Shares — exact number of shares to buy (+) or sell (−) to reach optimal weights.

Monte Carlo Projection

10,000 simulated paths over 10 years based on the portfolio's expected return and volatility. Shows the 5th percentile (pessimistic), median, and 95th percentile (optimistic) outcomes.

Use the median as a rough planning number, not a guarantee.

Correlation Matrix

Shows pairwise return correlations between positions. Low correlation means better diversification. High correlation (>0.8) means two positions move together and you're not getting real diversification benefit.

Portfolio Optimizer

Builds an optimal portfolio from a list of candidate tickers. No shares required — weights only.

The math behind it

RMT Covariance Cleaning

Standard covariance matrices contain noise — random correlations that look real but aren't. MAISNER applies Random Matrix Theory (Marchenko-Pastur filter) to separate signal from noise before optimization.

When there are too few observations, it blends RMT with Ledoit-Wolf shrinkage to ensure the matrix is stable and invertible.

Quality Tilt

The optimizer doesn't purely maximize Sharpe. It applies a quality tilt: tickers with higher ROE, stronger margins, and lower debt get a small expected return bonus. This biases the result toward fundamentally strong companies.

Sector Constraints

No single sector can exceed 40% of the portfolio. ETFs have a combined cap of 50%. This prevents the optimizer from concentrating everything in one hot sector.

For portfolios with fewer than 8 tickers, sector caps are disabled to avoid infeasibility.

Three portfolios returned

Max Sharpe

Highest risk-adjusted return. This is the primary output.

Min Variance

Lowest possible portfolio volatility. Use this if capital preservation is priority.

Equal Weight

Benchmark. All tickers weighted equally. Useful to compare optimizer's added value.

Stress Test

Replays historical crisis periods against your portfolio to measure how it would have behaved.

Available Scenarios

2008 GFC

Global Financial Crisis. Sep 2008 – Mar 2009. S&P 500 fell ~57% peak to trough. Tests exposure to financials and leverage.

2020 COVID

Pandemic crash. Feb–Mar 2020. Fastest bear market in history — 34% drop in 33 days. Tests liquidity and sector exposure.

2022 Rate Shock

Fed rate hike cycle. Jan–Dec 2022. Growth and tech sold off heavily. Tests duration sensitivity and valuation risk.

Custom Scenario

Advanced Stress Test tab lets you define custom shocks to equities, rates, FX, and sectors simultaneously.

What to look for

Good result

Optimized portfolio drawdown significantly smaller than current portfolio. Recovery time shorter. Max loss within acceptable range for your risk tolerance.

Warning sign

Optimized portfolio performs similarly to current during a crisis — means concentration risk is still present. Consider adding uncorrelated assets (bonds, gold, low-vol stocks).

Interactive Efficient Frontier

The efficient frontier shows every possible portfolio you can build from a set of assets. Points on the curve are optimal — nothing better exists at that risk level.

How to read the chart

X-axis — Annualized Volatility (risk). Lower is safer.

Y-axis — Annualized Expected Return. Higher is better.

The curve is the efficient frontier — portfolios on it cannot be improved (you can't get more return for the same risk). Portfolios below the curve are suboptimal.

Your current portfolio dot shows where you sit relative to the frontier. The optimizer moves you onto it.

Sliders

Each ticker has a slider that lets you manually override its weight. As you move sliders, your portfolio dot moves on the frontier in real time — you can see exactly what trade-off you're making.

Use this to understand how much return you sacrifice by constraining a position (e.g. "I want at most 10% in NVDA").

Research Tab

Three quantitative research tools: Factor Explorer, Strategy Builder, and Signal Analysis. Designed for systematic investors.

Factor Explorer

What it does

Computes 11 quantitative factors for every ticker and analyzes their predictive power. Shows which factors historically predicted returns best in your universe.

Mean IC

Information Coefficient — rank correlation between factor score and future returns. IC > 0.05 is considered meaningful.

ICIR

IC divided by IC standard deviation. Measures consistency. ICIR > 0.5 is good.

Quintile Spread

Return of top quintile minus bottom quintile. Larger spread means factor discriminates better.

IC Decay

How fast the factor loses predictive power over time. Momentum decays fast; value decays slowly.

Strategy Builder

DSL Syntax

Write a simple strategy in plain text, then run a full walk-forward backtest against 10+ years of price history.

select top(5) by momentum_12m
weight equal
rebalance monthly

select top(6) by score(value_composite * 0.5 + quality_composite * 0.5)
weight factor(quality_composite)
rebalance quarterly

IS/OOS split: results are split into In-Sample (training) and Out-of-Sample (test). A strategy that only works IS is overfit. Good strategies maintain Sharpe OOS.

Signal Analysis

Tests each factor as a trading signal. Shows hit rate (% of times a top-ranked stock actually outperformed), long/short spread, statistical significance (T-stat), and turnover cost estimate.

The Ensemble section finds optimal weights to combine all signals using OLS regression — giving you a composite score that's better than any single factor alone.

Risk & Performance Metrics

Every number MAISNER produces, explained clearly.

Return Metrics

Ann. Return (CAGR)

Compound Annual Growth Rate. The geometric average return per year. A portfolio that grew 100% over 5 years has CAGR ≈ 14.9%.

Volatility (Ann.)

Standard deviation of monthly returns, annualized (×√12). Measures how much the portfolio fluctuates. Lower is more stable.

Risk-Adjusted Metrics

Sharpe Ratio

Excess return above risk-free rate (3.8%) per unit of volatility. >1.0 excellent 0.5–1.0 good <0.5 poor

Sortino Ratio

Like Sharpe, but only penalizes downside volatility. Better for asymmetric strategies. A Sortino of 2× the Sharpe means the portfolio has low downside risk.

Calmar Ratio

Annual return divided by Max Drawdown. Measures return per unit of worst-case loss. >1.0 strong

Beta (vs SPY)

Sensitivity to S&P 500 moves. Beta 0.6 means if SPY falls 10%, your portfolio is expected to fall ~6%. Beta >1 means more volatile than market.

Drawdown

Max Drawdown

The largest peak-to-trough decline in portfolio value over the period. The single most important risk metric for most investors.

Recovery Time

How many months it took to recover from the max drawdown. A long recovery time means capital was tied up at a loss.

Benchmark Comparison

MAISNER uses a beta-adjusted benchmark for fair comparison. If your portfolio has Beta 0.6, comparing against raw SPY is unfair — the benchmark becomes:

Benchmark = 0.6 × SPY + 0.4 × AGG (bond index)

This means you're compared against a portfolio with the same market exposure as yours — not against a fully-invested equity benchmark.

Portfolio Construction Constraints

Max Weight

No single position exceeds 35% of the portfolio. Prevents extreme concentration in one stock.

Sector Cap

No single sector exceeds 40%. Prevents tech or finance from dominating the entire portfolio.

Transaction Cost

0.10% assumed on each trade. Applied to the rebalancing plan to show true net-of-cost impact.

Risk-Free Rate

3.8% annually (approximate 3M T-bill rate). Used as the baseline for Sharpe and Sortino calculations.

Factor Definitions

The 11 quantitative factors used in Research and Quality Tilt optimization.

Momentum

Momentum 1M / 3M / 6M / 12M

Price return over the respective lookback period. Ranked cross-sectionally. High score = strong recent performer. 12M momentum is also called "52-week momentum".

Value

Value Composite

Blends P/E (30%), P/B (20%), P/S (20%), EV/EBITDA (30%). Lower multiples = higher value score. Rank-normalized to [0,1].

Quality

Quality Composite

Blends ROE (25%), ROA (20%), Gross Margin (20%), Operating Margin (15%), Interest Coverage (20%). Higher = better quality business.

Low Leverage

Inverse of Debt/Equity ratio. High score = low financial leverage = lower bankruptcy risk.

Other Factors

Low Volatility

Inverse of 1-year realized volatility. Counterintuitively, low-vol stocks historically outperform on a risk-adjusted basis.

Growth Composite

Blends Revenue Growth (50%) and EPS Growth (50%). Captures fundamental business momentum.

Dividend Yield

Trailing dividend yield from the database. Used in Dividend optimization mode.

FCF Yield

Free Cash Flow divided by Market Cap. Measures how much real cash a company generates relative to its price.

Backtesting & Walk-Forward

How the Strategy Builder tests strategies without cheating.

Walk-Forward Methodology

MAISNER uses a strict IS/OOS (In-Sample / Out-of-Sample) split. The default is 60/40: 60% of history is used to calibrate the strategy, 40% is held out as a true test.

A strategy that looks great IS but collapses OOS is overfit to historical noise. Good strategies maintain meaningful Sharpe ratios on data they've never "seen".

IS vs OOS Metrics

IS Sharpe

Sharpe ratio in the in-sample training period. Strategies optimize for this — it's expected to look good.

OOS Sharpe

Sharpe in the hold-out period. This is the real test. OOS Sharpe > 0.5 suggests the strategy has genuine alpha.

Degradation %

How much Sharpe dropped from IS to OOS. <30% good 30–60% acceptable >60% overfit

PSR

Probabilistic Sharpe Ratio (Bailey & López de Prado, 2012) — probability that the OOS Sharpe is above zero given its estimation error. PSR ≥ 0.95 = high confidence; PSR < 0.75 = OOS Sharpe may be noise.

Weighting Methods

weight equal

Selected tickers get equal weight. Simple, low turnover, hard to beat consistently.

weight factor(x)

Weight proportional to factor score. Tickers with stronger signal get larger allocation.

Constrained Optimizer

Lock specific positions, set per-ticker bounds, and define sector constraints — then let the optimizer allocate the remaining budget optimally.

What it does

Partial Optimization

Standard MVO optimizes all positions freely. The Constrained Optimizer lets you pin certain assets and only optimize what's left. This is how institutional managers handle client mandates, regulatory requirements, or high-conviction positions they don't want touched.

The engine uses the same RMT-cleaned MVO as the standard optimizer — locked positions are included in the full covariance structure, they just aren't moved.

Three types of constraints

Locked Weight

Fix a position at an exact percentage. e.g. "AAPL must be exactly 15%." The optimizer cannot change this. Use when a client mandates a specific allocation.

Locked Shares

Fix a position by number of shares instead of percentage. The weight is derived from the current market price and locked. Useful for positions held for tax reasons.

Min / Max Bounds

Set a floor and/or ceiling on a position. e.g. "MSFT must be between 5% and 20%." The optimizer picks the best value within that range.

Sector Floor

Force a minimum allocation to a sector. e.g. "Healthcare must be at least 10%." Useful for mandate compliance or strategic allocation requirements.

Sector Ceiling

Cap total allocation to a sector. e.g. "Technology cannot exceed 30%." Applied to the entire portfolio including locked positions.

How the math works

Free Budget

All locked weights are summed first. The remainder — the free budget — is what gets optimized. For example, if you lock AAPL at 15%, MSFT at 20%, and BRK.B at 10%, the remaining 55% is distributed by the optimizer across all free positions.

Sector constraints apply to the full portfolio, including locked positions. If AAPL (locked at 15%) + MSFT (locked at 20%) already puts Technology at 35%, the sector cap of 40% leaves only 5% more for free tech positions.

Important behaviors

Locked positions affect optimization metrics

Adding a locked position — even at zero weight — changes the covariance matrix size and the T/N ratio used by the RMT filter. This means metrics like Sharpe Ratio will shift slightly compared to running the same portfolio without that asset. This is mathematically correct, not a bug.

Infeasibility

If your constraints are impossible to satisfy — for example, locked weights sum to more than 100%, or a sector floor conflicts with a sector ceiling — the optimizer will return an error message specifying which constraint is violated. It will never silently relax your constraints.

When to use it

Client mandates

A client insists on holding their TSLA position. Lock it, optimize everything else around it.

Tax constraints

A position can't be sold without triggering a large capital gain. Lock shares, optimize the free capital.

Regulatory limits

A fund mandate limits any single sector to 25%. Set a sector ceiling and let the optimizer work within it.

Conviction overweights

You want at least 10% in a specific stock regardless of what the optimizer would say. Set a min bound of 10%.

Constrained vs Standard Optimizer

The Standard Optimizer gives the mathematically unconstrained optimal portfolio — useful for discovering what the model produces with no human input.

The Constrained Optimizer gives the best portfolio achievable within your real-world requirements. The Sharpe Ratio will typically be lower than the unconstrained solution — the difference tells you exactly how much you are paying for your constraints in risk-adjusted return terms.

Multi-Asset Optimizer

Build portfolios combining stocks, ETFs, options, bonds, futures, and crypto in a single optimization.

Supported Asset Types

Stocks & ETFs

Standard equity positions. Enter ticker, direction (long/short), and optional allocation hint. Type is auto-detected.

Options

Calls and puts. Enter underlying ticker, strike, expiry, and market price. Greeks are computed via Black-Scholes (BAW for American). Convexity correction applied if delta error >5%.

Bonds

Enter face value, coupon, maturity, and credit rating. Duration computed via Vasicek model. Incorporated into portfolio duration and CVaR.

Futures & Crypto

Futures use underlying equity proxy for correlation. Crypto capped at 15% of portfolio. Futures capped at 20%.

Portfolio Greeks

When options are present, MAISNER computes portfolio-level Greeks — the net Delta, Gamma, Theta, Vega, and Rho of all option positions combined. This tells you the portfolio's aggregate sensitivity to price, time, and volatility moves.

Options max allocation is capped at 30% of total portfolio by default.

CVaR Optimization

For portfolios with options, standard Mean-Variance Optimization is replaced with CVaR optimization using 5,000 Monte Carlo scenarios. This correctly handles the non-linear payoff structure of options — Markowitz cannot.

CVaR (95%) = Expected loss in the worst 5% of scenarios

Advanced Stress Test

Define fully custom macro scenarios — combine equity shocks, rate moves, sector shocks, and individual ticker shocks simultaneously.

Custom Scenario Builder

Market Shock

A broad S&P 500-like shock applied to all equity positions. Enter as a percentage (e.g. −30 for a crash scenario, +15 for a bull run).

Sector Shocks

Apply additional shocks to specific sectors on top of the market shock. Use + Add sector to add rows. E.g. a banking crisis might apply −50% to Financials while the broad market falls −20%.

Ticker Shocks

Override any individual position with a precise shock. E.g. you expect AAPL to fall −40% in a specific scenario — add a ticker shock to override the sector result.

Duration (years)

How long the shock plays out. Affects bond mark-to-market and recovery path estimates.

Volatility

Annual portfolio volatility assumption during the stress period. Higher vol = wider confidence intervals.

Spillover

Cross-asset contagion effect. Positive means assets become more correlated during the shock (realistic during crises).

Tax Loss Harvesting

Identifies positions with unrealized losses that can be sold to generate tax deductions, while maintaining market exposure through substitute securities.

How it works

Enter your positions (ticker, shares, purchase price, purchase date). The system fetches the current market price, calculates your unrealized P&L, and identifies positions with losses that qualify for tax-loss harvesting.

For each candidate, it suggests a substitute security — a highly correlated but legally distinct asset you can buy immediately to maintain market exposure while the wash sale clock runs.

Country Tax Configs

Netherlands

Box 3 wealth tax system. Harvesting is less impactful than income-tax countries but still relevant for timing crystallization of losses.

Germany

25% Abgeltungsteuer on capital gains + solidarity surcharge. Losses can be carried forward indefinitely within the same asset class.

30-day wash sale rule applies. You cannot buy back the same or substantially identical security within 30 days before or after the sale.

Switzerland / UK / France / Belgium

Country-specific rules applied. Check local regulations — the tool provides guidance but not tax advice.

Wash Sale Warning

MAISNER flags positions that may trigger wash sale rules and marks them clearly. The tool does not execute trades — always confirm with your tax advisor before acting.

Portfolio Chart

Interactive historical performance chart powered by TradingView Lightweight Charts. Click Chart in the top bar to open it over any tab.

How the chart is built

Buy-and-Hold Performance

The chart reconstructs historical portfolio performance assuming you held the current weights from the start of the selected period. Each day, it computes the weighted return of all positions and chains them into a cumulative index starting at 100.

Portfolio Return(t) = Σ weight_i × Return_i(t)

This is a static-weight backtest, not rebalanced. The actual past performance of a rebalanced portfolio would differ — use the Backtest module for that.

Controls

Optimal / Current

Toggle between the optimized weights and your current (pre-rebalancing) holdings.

vs SPY

Overlay the S&P 500 ETF as a benchmark. Both series normalized to 100 at the start of the period for fair comparison.

Period

1M to MAX. Longer periods use price_history.xlsx (10 years monthly data) supplemented by Yahoo Finance daily data.

Stats Strip

Return

Total cumulative return over the selected period.

vs SPY

SPY's total return over the same period for direct comparison.

Volatility

Annualized standard deviation of daily returns over the period.

Max DD

Largest peak-to-trough decline within the period.

Sharpe

Risk-adjusted return, rf=3.8%. Computed on the historical data shown.

Auto-refresh: while the panel is open, the chart updates automatically every 5 minutes with the latest prices. Drag to scroll history, scroll to zoom.

Options Risk Visualizer

3D surface charts showing how an option's P&L and Greeks change across all combinations of spot price and time to expiry. Available in the Portfolios tab for any saved portfolio containing options.

The 3D Surface

What you're looking at

X-axis: Underlying price (±30% from current spot)
Y-axis: Days to expiry (1 day → current DTE)
Z-axis / Color: The selected value (P&L, Delta, or Gamma)

Two reference planes are drawn: ■ Gold = strike price, ■ Green = current spot. You can rotate and zoom the 3D chart freely.

Surface Views

P&L Surface

Shows profit/loss relative to entry price at every (spot, time) combination. Green = profitable zone, red = loss zone. The "mountain" shape shows where and when the trade makes money.

Delta Surface

How sensitive the position is to spot price moves at each combination. Delta approaches 1 (for calls) as spot rises and time decreases — option behaves like stock.

Gamma Surface

Rate of change of delta. Peaks sharply at-the-money near expiry — this is "gamma risk". High gamma means delta changes rapidly with small spot moves.

Supporting Charts

Theta Decay

Option price vs days remaining at current spot. Shows how time erosion accelerates — options lose value faster in the last 30 days. Red line = your entry price.

Delta Profile

Delta across the full range of spot prices at current DTE. S-curve shape for calls, inverse for puts. Shows where delta transitions from 0 to 1.

Greeks Strip

Displays current Greeks computed at the live spot price and current DTE using Black-Scholes. If a market price was stored with the option, Implied Volatility is back-solved via Brent's method before computing all Greeks.

News Globe

A 3D interactive globe that places financial news stories geographically. Find the Globe tab inside the News section.

How news is geo-located

Each news item is matched against a library of 23+ geographic regex patterns (company names, index names, central banks, currencies) and a map of 35+ regional ETF tickers. Matches place a glowing dot on the corresponding country or region.

Stories that don't match any pattern are distributed across 24 known financial city locations worldwide — so the globe stays populated even with mixed news feeds.

Interaction

Drag

Rotate the globe to any angle. Globe auto-rotates slowly when idle.

Scroll

Zoom in and out to focus on specific regions.

Hover

Tooltip shows region name and headline preview without clicking.

Click

Opens a news card with publisher, source info, summary, and link to the full article. Globe pauses auto-rotation for 20 seconds while you read.

Dot Colors

Green

US / Americas

Red

China / Energy Markets

Blue

Europe (country-specific or broad EU)

Amber

Asia-Pacific, Middle East, Crypto

Orange

Emerging markets, LatAm, Africa

Silver

Global / Macro stories

Leverage Analyzer

Quantifies the risk-reward trade-off of using margin. Shows Kelly-optimal leverage, margin call distance, and Monte Carlo liquidation probability.

What it answers

Is my leverage safe?

The Leverage Analyzer translates your portfolio's return and volatility into three concrete outputs: how much leverage Kelly theory suggests (f*), how far the market has to fall before a margin call, and the probability of being liquidated within the simulation horizon — computed from 5,000 GBM paths.

Key outputs

Kelly f*

Theoretically optimal leverage = (μ − r_f) / σ². Full Kelly is aggressive — practitioners use ½ Kelly or ¼ Kelly. Shown in all three variants.

Margin Call Level

The portfolio decline that triggers a margin call. US maintenance = 25% (so 37.5% drop at 2× leverage). EU maintenance = 50%.

Liquidation Probability

Monte Carlo: fraction of 5,000 GBM paths that cross the margin threshold within the horizon. The key risk number.

Vol Decay

−½(L²−L)σ² per year. Measures the drag that volatility applies to leveraged compound returns. Increases quadratically with L.

Stress Scenarios

Five historical crises applied at your leverage ratio: GFC 2008, COVID 2020, Rate Shock 2022, Dot-com 2000, Black Monday 1987.

Modes

Simple

Stocks and ETFs only. Available for all plan tiers.

Multi-Asset

Options, bonds, and futures included. Professional/Admin only. Options are mapped to their underlying for price resolution.

Stop Loss Calculator

Derives volatility-calibrated stop prices for each position using Paleologo's Advanced Portfolio Management framework. Both long and short positions are supported.

The core idea

Stops as statistical inference

Rather than picking stops arbitrarily, MAISNER sizes them to the position's own daily volatility: stop = k × daily_σ × √T where k is your multiplier (1.5–2.5×) and T is the horizon. A tighter stop at k=1.5 catches real losses quickly but generates more false exits; k=2.5 is wider and tolerates noise.

For short positions, the stop is placed above the entry price (stock rising hurts a short). The barrier probability formula is also inverted — the engine uses the upper-barrier GBM formula automatically.

Position-level outputs

Stop Price

Long: entry × (1 − stop%). Short: entry × (1 + stop%). Precise level to place your stop order.

Barrier Probability

Analytical probability that the stock touches the stop within the horizon. GBM first-passage formula with log-space drift correction.

Re-entry Price

Level to re-enter after a stop-out: slightly below stop (long) or above (short), accounting for a 5-day noise band at 0.5σ.

Dollar Risk

Notional loss at the stop: |weight| × portfolio value × stop%. Useful for position-sizing checks.

Portfolio-level outputs

Portfolio Drawdown Limit

k × portfolio_daily_σ × √T — the combined loss threshold for the entire book.

VaR

Parametric Value at Risk at your chosen confidence level (90/95/99%) over the horizon.

Sharpe-Adjusted Stop

Paleologo's adjustment: high-Sharpe strategies get slightly tighter stops because they have real edge — the adjustment reduces false exits while still catching real losses.

Kelly Connection

Checks if total stop-level risk is consistent with Kelly-optimal position sizing. Oversized positions show here.

Performance Attribution

Decomposes active return into allocation, selection, and interaction effects using the Brinson-Hood-Beebower model vs an SPY sector benchmark.

What it answers

Where did my alpha come from?

Attribution breaks the gap between your portfolio return and the benchmark into three effects: did you outperform because you over-weighted the right sectors (allocation), because your stock picks beat the sector ETF (selection), or from a combination of both (interaction)? The three always sum exactly to active return.

The three effects

Allocation

(wₚ − wᵦ) × (R_sector_bench − R_bench_total). Value from over/under-weighting sectors vs the benchmark.

Selection

wᵦ × (R_sector_port − R_sector_bench). Value from picking stocks that outperformed the sector ETF.

Interaction

(wₚ − wᵦ) × (R_sector_port − R_sector_bench). Combined effect of active weight AND active security selection in the same sector.

Benchmark

SPY sector blend

Benchmark = SPY sector weights (Technology 30%, Financials 13.2%, Healthcare 12.8%, …) applied to sector ETF returns (XLK, XLF, XLV, XLY, XLI, XLC, XLP, XLE, XLB, XLU, XLRE). SPY actual return is shown as a reference. Sector classification uses FMP profile data as the primary source.

How to use it

Load Portfolio

Select any saved optimizer or analyzer portfolio from the dropdown. Weights load automatically from either flat_weights or weights_table format.

From Monitor

Click "Attribution" in the Monitor bar to prefill using current position values as weights (value / total portfolio value).

Period

6M / 1Y / 2Y / 3Y. Returns fetched from Yahoo Finance for both your tickers and the sector ETFs.

Portfolio Monitor

Real-time P&L tracking for your actual holdings. Supports stocks, ETFs, bonds, options, futures, and crypto. All plan tiers.

What it does

Live P&L and currency exposure

The Monitor fetches live prices from FMP Professional (with Yahoo Finance fallback) and computes cost basis, current value, and P&L for each position. Currency is inferred from the ticker suffix — .DE/.PA → EUR, .L → GBP, .ST → SEK, no suffix → USD — and converted to USD at current FX rates.

Managing portfolios

New Portfolio

Click "+ New", enter positions manually (ticker, quantity, purchase price, date, type), then click Save.

Load from Optimizer

Use the "Load from saved portfolio" dropdown to pre-fill tickers and quantities from any saved optimizer result. Update the purchase prices before saving.

Live Refresh

Click "⟳ Live" to fetch current prices and update P&L for all positions. Prices are from FMP with Yahoo fallback.

Attribution

Click "Attribution" to send position weights (by current value) directly to the Performance Attribution tab.

Options in Monitor

Approximate option valuation

Live option values are estimated as intrinsic value + time value (simplified Black-Scholes with 25% assumed vol). Expired options (past expiry date) are marked to zero with an EXPIRED badge and shown in red. For precise option analytics, use the dedicated Options Pricing engine.

Long/Short Optimizer

Extends the standard MVO framework to allow short positions. Same Sharpe objective, same RMT covariance — negative weights represent shorts, with borrow cost automatically deducted.

Portfolio modes

Long/Short (net=1)

Σw = 1. Standard fully-invested portfolio with some short positions. Shorts reduce exposure to overvalued names while longs carry the portfolio.

Market Neutral (net=0)

Σw = 0. Long gross equals short gross. Pure alpha — uncorrelated with broad market direction. Lower Sharpe than long/short in bull markets, but hedged against market drawdowns.

Objective modes

Standard

Maximise (μ_eff − r_f) / σ. Identical to the standard optimizer but with borrow cost subtracted from short-position returns.

Conservative

Minimise portfolio variance wᵀΣw. Produces fewer and smaller short positions. Lowest volatility.

Balanced

Maximise Sharpe subject to vol ≤ vol_cap. If the cap is tighter than the minimum achievable volatility, falls back to min-variance.

Aggressive

Maximise expected return. Uses wider bounds (1.5× max_short and max_long). High gross exposure, high concentration.

Dividend

Maximises dividend yield on the long leg with a light vol penalty. Shorts low-yield names. Useful for income-focused L/S strategies.

Key parameters

Max Short

Maximum short weight per stock (default 30%). The optimizer cannot short any single name more than this.

Max Long

Maximum long weight per stock (default 35%). Same cap as the standard optimizer.

Borrow Rate

Annual cost to borrow shares for shorting (default 0.5%). This rate is subtracted from each shorted stock's expected return. A high borrow rate naturally discourages shorting when the alpha is insufficient.

Vol Cap

Balanced mode only. Maximum allowed portfolio volatility. The optimizer will not exceed this even if it means sacrificing Sharpe.

Reading the results

Positive weights = long positions (green in the table). Negative weights = short positions (red). Gross exposure is the sum of absolute weights — values above 1.0 mean leverage. Net exposure is the algebraic sum — 1.0 for long/short mode, 0.0 for market neutral.

The optimizer may decide not to short any position if the borrow cost exceeds the expected alpha — in that case it returns an all-long portfolio and the L/S ratio shows as "Long only".

Long/Short Analyzer

Evaluates an existing long/short portfolio given your actual positions. Enter each holding with ticker, quantity, direction (LONG or SHORT), and purchase price — live prices are fetched automatically.

Inputs

Ticker

Stock or ETF symbol. Live price is fetched from FMP (yfinance fallback).

Qty

Number of shares. Must be positive regardless of direction.

Direction

LONG = you own the shares. SHORT = you have sold the shares short and owe them back to the broker.

Purchase Price

Your entry price per share. Used to compute realised P&L vs current live price.

Borrow Rate

Annual cost to borrow shares for shorting (default 0.5%). Deducted from expected return of short positions in the risk calculation.

P&L calculation

How P&L is computed

Long: P&L = qty × (live_price − purchase_price). Positive when price rose.

Short: P&L = qty × (purchase_price − live_price). Positive when price fell.

The position detail table shows P&L in dollars and as a percentage of the initial cost.

Exposure metrics

Gross Value

Sum of all position values at live prices — longs + |shorts|. Represents total capital at risk.

Net Value

Long value minus short value. Positive = net long, zero = market neutral.

L/S Ratio

Long gross ÷ short gross. A ratio of 2.0 means you have twice as much long exposure as short exposure.

Net Exposure

Net value ÷ gross value, as a %. 100% = fully long, 0% = market neutral, negative = net short.

Risk metrics

Expected Return

Weighted expected return from Stocks.xlsx, minus borrow cost on short positions.

Volatility

Portfolio volatility σ_p = √(wᵀΣw) using RMT-cleaned covariance. Negative short weights reduce portfolio vol if they are negatively correlated with longs.

Sharpe

(Expected Return − 3.8%) / Volatility. Annualised.

VaR 95% (1yr)

Parametric Value at Risk: σ × 1.645. The 1-year loss not exceeded in 95% of scenarios.

CVaR 95%

Conditional VaR (Expected Shortfall): σ × 2.063. Average loss in the worst 5% of scenarios.

Stress scenarios

Each historical scenario (GFC 2008, COVID 2020, Rate Shock 2022, Dot-com 2000–02, Black Monday 1987) applies a market-level shock adjusted by each stock's beta. Short positions profit from market declines — the table shows the hedge effectiveness of your short book.

Impact_i = sign_i × β_i × market_return × live_value_i

Hedging Optimizer

Finds the jointly optimal put option strike K* and futures hedge ratio H* that minimise Expected Shortfall of your commodity or equity position. Based on Yu & Sun (2017).

What it answers

How should I hedge my position?

If you hold Q units of a commodity or equity at spot price P₀, you face two risks: the price falling (price risk) and an additional source of volatility unrelated to price — crop yield, weather, operational risk — called background risk. The Hedging Optimizer tells you exactly how many put options to buy (at what strike) and how many futures contracts to sell to minimise the Expected Shortfall of your terminal wealth at the horizon.

Inputs

Ticker / Load Defaults

Enter a ticker (e.g. CL for crude oil, GLD for gold, AAPL for a stock) and click Load Defaults to auto-fill spot price from FMP and estimate σ_spot from price_history.xlsx.

Spot Price P₀

Current market price of the asset you hold. The model treats this as the starting price for simulating future prices.

Futures Price F₀

Current futures contract price. Typically slightly above spot due to cost of carry: F₀ ≈ P₀·e^(r·τ). The futures gain/loss from holding H contracts is (F₀·e^(rτ) − F_T)·H·Q.

Quantity Q

Number of units you hold. The initial wealth is W₀ = P₀·Q. All ES/VaR results are expressed as a percentage of W₀.

Horizon τ

90 / 180 / 365 days. The model simulates the spot and futures prices at this horizon and computes the hedged terminal profit.

μ Spot / μ Futures

Annualised expected return of the underlying asset and futures contract. Affects the risk-neutral drift in the lognormal simulation.

σ Spot / σ Futures

Annualised volatility. σ_spot drives simulation variance; σ_futures is also used for Black-Scholes put pricing (the put is written on the futures contract).

ρ₁ (spot–futures)

Correlation between spot and futures. Typically 0.80–0.99 for a same-commodity hedge. Lower ρ₁ means futures hedge is less effective and H* tends to be larger.

ρ₂ (spot–background)

Correlation between spot price and background risk. Positive: high price and high background risk co-occur (amplifying losses). Negative: background provides a natural hedge.

σ Background (σ_z)

Standard deviation of the background risk term Z_T ~ N(0, σ_z²). Larger σ_z increases the importance of the β mixing parameter.

β (background mix)

Slider from 0 to 1. β=0: background risk is purely additive — it adds a fixed dollar amount to the profit/loss regardless of price. β=1: purely multiplicative — the background shock scales the entire hedged profit. Real-world commodities are typically β=0.3–0.7.

Budget d

Fraction of position value P₀·Q to spend on put options. d=0.10 means you budget 10% of position value. This determines h = d·P₀/Φ — more budget buys more puts.

α (ES confidence)

Tail probability for Expected Shortfall. α=0.05 means ES is the average of losses in the worst 5% of scenarios. Higher α is more conservative.

Outputs

Optimal H* (futures ratio)

Optimal number of futures contracts to short, per unit of underlying held. H*=1 = fully hedged. H*>1 = over-hedge (can be optimal with multiplicative background risk — flagged in amber).

Optimal K* (put strike)

Optimal put option strike. Values below F₀ = OTM put (cheap, less protection). Values near F₀ = ATM (expensive, strong protection). Searched over [0.7·F₀, 1.3·F₀].

Optimal h* (option units)

Number of put options to hold per unit of Q. Determined by the budget constraint: h* = d·P₀/Φ(K*).

ES_α (% wealth)

Expected Shortfall of the hedged position's normalised loss. Lower is better. Compare the three scenarios to quantify how much risk the hedge removes.

VaR_α (% wealth)

Value at Risk — the (1−α) quantile of the loss distribution. The ES is always ≥ VaR.

Charts

Loss Distributions

Histogram overlay for all three scenarios (no hedge / options only / optimal). The optimal distribution should be shifted left (lower losses) and tighter.

ES vs H (diagnostic)

ES curve across H ∈ [0,2] at the fixed optimal K*. The minimum is H* (annotated). A flat curve means futures add little marginal benefit. A steep left side means even a small futures position sharply reduces tail risk.

Sensitivity: β

ES with vs without futures across background mix β. If the gap between the two lines is large, futures are essential. At β=0 (pure additive), futures may be less important.

Sensitivity: Budget d

ES vs option budget fraction. Diminishing returns are typically visible — doubling the budget from 10% to 20% buys less ES reduction than going from 1% to 10%.

Sensitivity: α

ES across tail levels. The hedge should reduce ES at all α, but the relative benefit may change — a hedge optimised for α=5% may be suboptimal for α=1%.

Sensitivity: σ_spot

Hedge effectiveness across volatility regimes. High-volatility environments (σ≥40%) typically show the largest absolute ES reduction from hedging.

Interpreting the over-hedge badge

An amber badge appears when H* > 1. This is not an error — it is a mathematical result of the Yu & Sun (2017) model under certain parameter configurations. It occurs when: (a) β is close to 1 (multiplicative background risk causes correlated amplification of losses), (b) ρ₁ is low (futures are a poor hedge, requiring more contracts), or (c) σ_futures > σ_spot (the futures contract is more volatile than the spot). In practice, check margin requirements before over-hedging.

PRIIPs KID Generator

Generates a regulatory Key Information Document under EU Regulation 1286/2014 using Method 1 (historical bootstrap). Produces EN / NL / DE PDFs in minutes from any saved portfolio. Professional and Admin plans only.

What it answers

Does my portfolio need a KID, and what does it say?

Under PRIIPs, any portfolio offered to EU retail investors requires a standardised Key Information Document covering risk classification, performance scenarios, costs, and holding-period recommendations. MAISNER computes all required numbers from your portfolio's price history and produces a print-ready PDF draft in three languages.

The document is a draft — the manufacturer bears final legal responsibility for accuracy and distribution. The red disclaimer box on the last page makes this explicit.

Risk Indicator (SRI)

VEV

Value-at-Risk Equivalent Volatility = σ_monthly × √12. The annualised volatility of the portfolio's monthly log-returns. This is the PRIIPs Method 1 market risk proxy.

MRM

Market Risk Measure, 1–7, derived from VEV. Thresholds: VEV ≤ 0.5% → MRM 1; ≤ 1.2% → 2; ≤ 2.0% → 3; ≤ 3.0% → 4; ≤ 8.0% → 5; ≤ 16% → 6; above → 7. Most equity portfolios land at 5–6.

CRM

Credit Risk Measure, 1–6. Default = 1 (securities held directly, custodian ring-fencing). Increase only if the product carries issuer credit risk (structured notes, bonds below investment grade).

SRI

Summary Risk Indicator = max(MRM, CRM−1) per PRIIPs Annex IV Table 4. For most equity portfolios with CRM=1, SRI = MRM. Displayed as the coloured 1–7 bar on the PDF cover and in the on-screen results.

Performance Scenarios (Method 1)

Bootstrap with replacement, 10,000 paths

MAISNER draws random monthly return sequences from the portfolio's historical monthly log-returns (price_history.xlsx, minimum 24 months required). For each of the four scenarios — stress (1st percentile), unfavourable (10th), moderate (50th), favourable (90th) — it simulates 10,000 paths over 1 year, the mid-point, and the full RHP, and reports the final portfolio value as a euro amount and annualised percentage.

The bootstrap respects the actual return distribution including fat tails. No normality assumption is imposed.

Stress (P1)

1st percentile of simulated terminal values. Regulatory worst-case. Reflects a severe but historically plausible outcome.

Unfavourable (P10)

10th percentile. Below-average outcome in a weak market environment.

Moderate (P50)

Median outcome. What the investor might expect under typical historical conditions.

Favourable (P90)

90th percentile. Strong market environment. Not a guarantee.

Costs and RIY

Entry / Exit Fee

One-time costs in % of invested amount. Default 0%. Charged in year 1 (entry) or at the RHP (exit).

Ongoing / TER

Annual management fee or total expense ratio. Applied as a compound drag each year. Default 0.50%.

Performance Fee

Annual performance-linked fee in % of invested amount. Default 0%.

RIY

Reduction in Yield — total cost as an annualised drag on returns. Regulatory disclosure number shown in the Costs table for each holding period.

Inputs

Portfolio

Enter tickers and weights manually, or load any saved portfolio from the dropdown. For multi-asset portfolios, options are mapped to their underlying equity; bonds/futures are included if price history is available.

Product Name

Name printed on the KID cover and in the PDF filename. Use the fund or portfolio name as it appears in legal documentation.

Manufacturer

Legal entity distributing the product. Printed in the "Who is responsible for this KID?" section and PDF footer.

RHP

Recommended Holding Period in years (3 / 5 / 7). Determines the time columns shown in the scenario table and in the cost calculations.

Reference Investment

Amount in euros for which scenario values are shown (default €10,000). Regulatory standard is €10,000 for most retail products.

Language

English, Nederlands, or Deutsch. All section headings, labels, risk descriptions, and legal text are fully translated. The PDF filename includes the language code.

PDF Branding

When you click DOWNLOAD PDF, the branding dialog appears. Enter your firm name (printed in the page footer) and optionally upload a logo (PNG/JPG, max 10 MB — placed in the top-right of page 1). Leave both blank for a plain MAISNER-branded draft.

Legal Notice

This tool generates a draft KID for review purposes. The manufacturer / PRIIP maker is solely responsible for the accuracy, completeness, and regulatory compliance of the final KID distributed to retail investors. This output does not constitute legal, tax, or investment advice. Always have the final document reviewed by qualified legal counsel before distribution.

Alert System

Rule-based monitoring that fires notifications when your portfolio crosses a defined threshold. Seven alert types cover weight drift, sector concentration, P&L, price levels, option expiry, and VaR. All plans.

Alert Types

Drift

Fires when a position weight drifts more than the threshold % from its target. Useful for rebalancing triggers — e.g. alert when AAPL drifts >5% from target 20%.

Sector

Fires when the combined weight of a sector exceeds the threshold. Monitors concentration risk — e.g. alert when Technology >40% of portfolio.

P&L (position)

Fires when a single position's unrealised P&L crosses the threshold %. Direction: above (profit target), below (loss limit), or either. e.g. alert when TSLA P&L <−15%.

Portfolio P&L

Same as P&L but for the total portfolio (sum of values vs sum of costs). Fires when total P&L crosses threshold %.

Price

Fires when a ticker's live price crosses an absolute level. e.g. alert when SPY >600, or when VIX >30. Direction: above, below, or either.

Expiry

Fires when an option position is within the threshold number of days of expiration. Helps avoid accidental exercise or missed roll decisions.

VaR

Fires when the portfolio's 1-day 95% parametric VaR exceeds the threshold % of portfolio value. Risk-limit monitoring.

Creating a Rule

Bell icon → Manage Rules → + New Rule

Select the rule type, the portfolio to monitor (saved portfolio or Monitor portfolio), the ticker or sector if required, a threshold value, direction (above / below / either), and the cooldown window in hours. Enable the rule and click Save. Rules are evaluated when you click Check Now or automatically via the daily scheduled check.

Notifications

Bell badge

Unread alert count shown on the bell icon in the top bar. Turns amber when alerts are present.

Cooldown

Once a rule fires, it will not fire again until the cooldown period (default 24 hours) has elapsed — even if the condition remains true. Prevents alert fatigue on persistent breaches.

Mark as read

Click an alert to mark it read, or use "Mark all read" in the dropdown. Read alerts are dimmed but not deleted — they remain visible in the history panel.