Institutional-grade quant research, run on your own account.
The static 60/40 mix a robo-advisor drops you into and rebalances quarterly whether or not anything changed, and the asymmetry where institutions get factor models, risk parity, and statistical validation while everyone else gets an index tracker with a nice app. VenEdge replaces the passive engine with a validated multi-factor quantitative toolkit you run yourself, software, not a managed product. You bring your own broker and keep custody throughout; Vendra never holds your money or executes on your behalf.
VenEdge, formally registered as Quant Stack, is a private, self-hosted toolkit that blends several uncorrelated, academically-grounded return sources with institutional risk-budgeting, sizes every position by a volatility target, and routes every order through a multi-layer pre-trade risk system with an automatic drawdown kill switch. The same discipline AQR, Winton, and mid-tier quant funds run, operated on your own broker.
We publish the validation; the method stays proprietary. The full battery serious allocators demand, out-of-sample walk-forward, permutation testing, multiple-comparison correction, and deflated metrics, is on the page. The formula is not.
Four risk-tiered profiles driven by one multi-factor engine, what changes between them is the investable universe and the risk budget, not the machinery. The numbers below are out-of-sample walk-forward results (May 2025 – May 2026) shown against the 3-year in-sample backtest. For every profile, out-of-sample Sharpe is higher than in-sample, the single strongest signal a strategy is not overfit.
For every profile, out-of-sample Sharpe is higher than in-sample, the opposite of what overfit strategies show. The model was configured on 2023–2025 data and tested on data it had never seen; the unseen period performed better.
Backtest + walk-forward · not a live track record · USD · not MAS-licensed · illustrative
Fees matched to incumbents · independently validated · results published
Not overfit, robust across regimes, defensive when it counts, and above the passive frontier, each shown directly from the Quant Stack backtest and walk-forward data.
Parameters were configured on 2023–2025 data, then tested on May 2025 – May 2026 data the model had never seen. The unseen period produced a higher Sharpe for all four profiles. Overfit strategies show the opposite.
Returns across the 2018 correction, the 2020 COVID crash, the 2022 rate-shock, and the 2024–25 bull. In 2022, the worst year for passive 60/40 in two decades, SPY fell −17.85% while Leveraged Growth lost only −1.13%, a 16.7-point gap.
Stocks and bonds fell together. Every VenEdge profile (blue) lost less than SPY, Syfe, and Endowus.
Each profile (blue) plotted by out-of-sample volatility and return. All four sit above the Sharpe-1.0 ray, the shaded zone where passive 60/40 portfolios cluster.
VenEdge is private software you operate on your own broker, you keep custody and there is no management fee, because Vendra never manages your money. The chart benchmarks the engine's out-of-sample Sharpe against widely-used robo-advisors purely as a methodology reference; it is not a managed-product comparison or a solicitation.
All figures from the Quant Stack data · backtest + walk-forward · not a live track record · USD · not MAS-licensed · illustrative · incumbent Sharpe values indicative
VenEdge combines several independent, academically-grounded sources of return, each uncorrelated enough to smooth the others' rough patches across regimes. The specific factors, horizons, weights, and implementation are proprietary; what we publish is the validated outcome, not the formula. That is the line every serious quant manager draws.
Positions are blended and sized using the same risk-budgeting and volatility-targeting techniques institutional desks use, so each return source contributes balanced risk rather than whichever signal happens to be loudest that week. Alternative construction methods are available per profile for different market conditions.
Conservative (7 % vol target, defensive), Balanced (9 % vol, the flagship), Growth (13 % vol, equity-tilted), and Leveraged Growth (17 % vol, higher dollar exposure). Selecting a profile changes the investable universe and the risk budget; the underlying engine is identical across all four. Pick the one that matches your risk appetite.
A multi-layer pre-trade risk system sits between every signal and the broker: per-position and gross-exposure limits, long-only enforcement, post-loss cooldowns, and an automatic drawdown kill switch that halts trading before a bad streak compounds. Hardened so the kill switch can only ever fire on a real market move, never on a data-hygiene fault.
The framework is stress-tested with the same statistical defenses institutional allocators demand, out-of-sample walk-forward, permutation testing, multiple-comparison correction, multi-regime stress, and deflated performance metrics. Block-bootstrap permutation lands at p < 0.012; the Growth profile's deflated Sharpe is 0.96. Incumbents publish none of this; we publish the outcomes in full.
Upload your existing portfolio or connect a broker read-only; get institutional analytics for free: risk exposures, VaR and Expected Shortfall, drawdown-probability curves, Monte-Carlo forward simulation, beta vs the market, and a side-by-side comparison against all four profiles. No signup, no custody, no account linking. The X-Ray is open to anyone; the full toolkit is private and offered by enquiry.
VenEdge exposes a read-only API over your own account. You connect a broker, fetch your profile's current target allocation and the rebalance trade list, and execute on your own broker. How the weights are computed stays server-side, the API returns the destination, never the map.
# Fetch your profile's current target allocation
GET https://api.vendraholdings.com/v1/venedge/portfolio
Authorization: Bearer YOUR_SESSION_TOKEN
# Response, target weights + rebalance plan only.
# No factor scores, no model parameters, no signal internals.
HTTP/1.1 200 OK
{
"profile": "balanced",
"as_of": "2026-06-04T17:30:00+08:00",
"nav": 52340.18,
"currency": "SGD",
"target_weights": { /* per-instrument, sums to 100% */ },
"rebalance": [
{ "action": "buy", "qty": 12 },
{ "action": "sell", "qty": 5 }
],
"mode": "per_trade_approval"
}
# You receive the allocation. The methodology that produced
# it, the factor mix, horizons, and weighting, is not
# exposed through any public surface.Tell us about your venues, your strategies, and the governance gap you're trying to close. We respond within two business days, or not at all.