Library
Complete index of Sentivue's published surfaces — research, strategies, glossary, and audience pages. 45 pieces.
Research
Research (20)
Long-form analysis and frameworks for systematic traders, allocators, and quants.
- Methodology
Out-of-Sample Testing: Protocols That Actually Work
Most "out-of-sample" tests are contaminated by researcher iteration. The protocols that actually work share three features: pre-registration, hold-out segregation, and one-shot evaluation.
8 min read - Allocation
In-House vs Allocator-Managed Quant: A Total-Cost Analysis
Build a quant team in-house or allocate to an external systematic manager. The total-cost analysis usually favors allocation for sub-billion AUMs and in-house for sufficient scale.
6 min read - Methodology
Backtest vs Walk-Forward vs Paper Trading: When to Use Which
Three distinct evaluation regimes serve three distinct purposes. The mistake is treating them as alternatives rather than as a sequence.
6 min read - Metrics
Sharpe vs Sortino vs Calmar: Choosing the Right Metric
Three risk-adjusted return metrics; three different stories. Knowing which to lead with for a given strategy and audience is the difference between honest reporting and selective reporting.
6 min read - Methodology
Discretionary vs Systematic: A Hybrid Framework
The discretionary-vs-systematic debate is mostly false framing. The actual question is which decisions to systematize and which to leave human-judgment-driven.
6 min read - Allocation
Single Strategy vs Ensemble: The Diversification Math
Running one strong strategy or a portfolio of weaker strategies. The math favors ensembles in most cases — but only if the diversification is real.
6 min read - Methodology
Meta-Labeling: Filtering Primary Signals With a Secondary Model
Meta-labeling is a two-stage modeling pattern: a primary signal generator emits trade ideas, and a secondary model filters which ideas to act on. The technique improves precision at the cost of recall.
7 min read - Methodology
Monte Carlo for Strategy Validation: Walk-Throughs and Traps
Monte Carlo simulation is a useful sanity check on strategy robustness — and a popular tool for fooling yourself if applied carelessly. Three legitimate uses, two common traps.
7 min read - Risk
Correlation Decay: When "Uncorrelated" Strategies Converge in Stress
Strategy correlations are not stable. The strategies you diversified into during normal markets often co-move in crisis — exactly when you needed the diversification most.
7 min read - Methodology
From Backtest to Live: The Institutional Deployment Checklist
A working backtest is the start of deployment, not the end. The institutional checklist that separates strategies that survive their first live month from strategies that don't.
9 min read - Metrics
Sharpe Ratio: A Complete Guide for Algorithmic Traders
Sharpe is the default metric in systematic trading and the most often abused. The complete practitioner's guide to the math, the gotchas, and what Sharpe does and doesn't tell you.
9 min read - Methodology
What Is Walk-Forward Optimization (and Why It Beats Single-Period Backtesting)
Walk-forward optimization is the institutional standard for strategy validation. Here's the mechanics, the parameter choices, and why a single-period backtest is structurally incapable of catching overfitting.
9 min read - Position Sizing
Kelly Criterion in Practice: Half-Kelly, Fractional Kelly, and the Case Against Full Kelly
Full Kelly is mathematically optimal in expectation and operationally insane. Here's why fractional Kelly dominates institutional practice — and how to set the fraction.
7 min read - Execution
Slippage Modeling: The Difference Between Paper and Live P&L
Slippage is the largest single gap between backtest performance and live performance for most retail systematic strategies. Three escalating levels of realism — and why the conservative side is almost always the right call.
7 min read - Methodology
Why Most Retail Backtests Overfit — And the Institutional Fix
Most retail backtests beat the live performance by 2–5×. The reason is selection bias, and it is structural — not a discipline issue. Here's what institutional research does differently.
9 min read - Methodology
Statistical Significance in Trading: How Many Trades You Actually Need
Most retail backtests claim edge they cannot prove. Here's the math on minimum sample sizes for credible strategy validation — and why "looks profitable" usually doesn't pass the bar.
8 min read - Risk
Regime Detection: When to Turn a Strategy Off
Most strategies have a regime where they earn their backtest Sharpe and another where they hemorrhage. Real-time regime detection is the discipline that decides when to turn the strategy off.
8 min read - Risk
Drawdown vs Volatility: Which Actually Predicts Strategy Survival
Volatility is what statisticians measure; drawdown is what investors live through. The two metrics tell different stories — and the case for drawdown as a primary survival metric is stronger than the textbook implies.
8 min read - Position Sizing
The R-Multiple Framework: Position Sizing for Systematic Traders
The R-multiple framework expresses every trade in units of risk, not dollars. It is the cleanest position-sizing primitive for systematic strategies — and the one most often misused by retail.
7 min read - Allocation
Risk Parity vs Equal-Weight: Choosing a Strategy Allocator
Risk parity allocates equal volatility contribution; equal-weight allocates equal capital. They produce different portfolios with different failure modes — and the choice matters more than most allocators realize.
7 min read
Strategy
Strategies (10)
Implementation guides for systematic trading strategies — fit ranges, failure modes, and the math behind each.
- Directional
Momentum: Cross-Sectional vs Time-Series
Momentum strategies buy what's been winning and sell what's been losing. Two distinct implementations — cross-sectional and time-series — with different return drivers.
6 min read - Volatility
Volatility Arbitrage: VIX Term Structure Trades
Vol-arb harvests the volatility risk premium and the term-structure roll. The trade looks free for years and then loses two years of gains in a week.
6 min read - Cross-Asset
Carry Strategies: FX, Futures, Equities
Carry strategies earn the yield differential between long and short legs. The trade pays slowly and consistently, then occasionally gives back six months in a week.
6 min read - Directional
Trend Following: A Systematic Implementation Guide
Mechanics, fit ranges, and failure modes for trend-following strategies — the oldest profitable systematic style and the hardest to hold psychologically.
7 min read - Directional
Breakout Strategies: The Role of Volatility Filters
Breakout systems trade the resolution of consolidation patterns. The signal is straightforward; the volatility filter is what separates profitable breakouts from chop.
6 min read - Stat-Arb
Statistical Arbitrage: Signal Extraction & Risk Overlays
Stat-arb extracts cross-sectional alpha from a basket of mean-reverting relationships. The signals are usually weak; the risk overlays are what makes the portfolio investable.
7 min read - Stat-Arb
Pairs Trading: Cointegration, Half-Life, Exit Triggers
Pairs trading bets that two cointegrated instruments will revert to their long-run relationship. The math is elegant; the operational discipline is where most pairs strategies fail.
7 min read - Microstructure
Market Making: Quote Skew, Inventory Risk, Capital Efficiency
Market making earns the bid-ask spread in exchange for inventory and adverse-selection risk. The job is not quoting — it's managing inventory and fading adverse selection.
7 min read - Stat-Arb
Mean Reversion: Implementation, Fit Ranges, Failure Modes
Mean-reversion strategies bet on temporary price dislocations correcting toward equilibrium. Cousin of trend-following — opposite assumptions, opposite regime fit.
6 min read - Volatility
Options-Selling Overlays: Strangles, Condors, Risk Discipline
Options-selling overlays harvest the volatility risk premium with bounded position sizes and structured loss management. The discipline is the strategy.
6 min read
Glossary
Glossary (10)
Algorithmic trading, risk, and quantitative finance terms — defined the way practitioners actually use them.
- Metrics
Sortino Ratio
Risk-adjusted return measured against downside deviation only — penalizes losses while ignoring upside volatility. Often more honest than Sharpe for asymmetric strategies.
4 min read - Position Sizing
Kelly Criterion
Position-sizing formula maximizing geometric (compounded) growth. Mathematically optimal in theory, almost always too aggressive in practice.
4 min read - Risk
Maximum Drawdown
The largest peak-to-trough decline in an equity curve. The most behaviorally honest risk metric — what investors actually felt during the worst stretch.
4 min read - Risk
Regime Change
Persistent shift in the statistical properties of a market — volatility, correlation, mean return — that breaks the assumptions a strategy was designed under.
4 min read - Methodology
Walk-Forward Optimization
Out-of-sample testing protocol that rolls optimization and validation forward in time. The institutional standard against single-period backtest overfitting.
5 min read - Methodology
Backtest Overfitting
Selection of strategy parameters that fit historical noise rather than persistent edge. The single biggest reason backtests outperform live trading.
5 min read - Metrics
Sharpe Ratio
Risk-adjusted return measure: excess return per unit of total volatility. The default benchmark for systematic strategies — and the one most often abused.
4 min read - Metrics
Calmar Ratio
Return divided by maximum drawdown — the metric that maps cleanest to "how much pain to make this money." Underused outside CTA evaluation.
3 min read - Execution
Slippage
The difference between the expected fill price and the realized fill price. The largest single gap between paper backtests and live P&L for most retail strategies.
4 min read - Position Sizing
Volatility Targeting
Position-sizing rule that scales exposure inversely with realized volatility to hit a constant target risk level. Standard in CTA and systematic equity portfolios.
4 min read
Audience
Audience Pages (5)
How Sentivue works for different audiences — quants, allocators, prop firms, family offices, researchers.
- Audience
For Quants
Sentivue's Adapt program and Strategy Factory: how working systematic traders publish, validate, and scale strategies inside a research-grade infrastructure.
4 min read - Audience
For Prop Firms
Sentivue's prop-farming infrastructure: systematic strategies running on NinjaTrader VPS connectors with audited risk controls and clean-room reporting.
3 min read - Audience
For Researchers
Sentivue's public research surface: long-form methodology, KPI debriefs, and the working notes behind the firm's strategy stack — open by default.
3 min read - Audience
For Family Offices
Systematic, transparent, drawdown-aware allocation for single- and multi-family offices. Strategy-level attribution and direct quant team access.
3 min read - Audience
For Allocators
Sentivue Capital for accredited investors and institutional allocators: systematic, transparent, drawdown-aware allocation across the firm's strategy stack.
4 min read