We believe the most durable edge in markets belongs not to those with the best instincts, but to those who build the best systems—and have the discipline to follow them.
The efficient market hypothesis is an elegant abstraction. Reality is messier. Institutional mandates force selling at irrational levels. Behavioral biases create persistent dislocations. Regulatory shifts produce asymmetric information decay that the market prices in slowly, if at all.
We exploit these structural inefficiencies. Our thesis is straightforward: when capital is deployed with analytical rigor against empirically validated mispricings, the expected value is positive and repeatable. We are not in the business of predicting sentiment. We are in the business of measuring it, decomposing it, and positioning capital where the math says the crowd has it wrong.
This is not a discretionary shop. Conviction here is earned through data, stress-tested through backtesting, and executed with systematic discipline. We do not override the model on a hunch. The moment you start second-guessing the signal, you have already lost your edge.
Our quantitative infrastructure is purpose-built for alpha generation across commercial real estate, specialized REITs, and technology equities. We operate at the intersection of financial engineering and applied machine intelligence—deploying ensemble models that synthesize alternative data, fundamental factor decomposition, and real-time market microstructure signals into actionable positioning.
The pipeline is rigorous. Raw data ingestion spans traditional market feeds, macroeconomic releases, and proprietary alternative datasets. Feature engineering isolates predictive signals from noise. Walk-forward optimization eliminates look-ahead bias. Every strategy runs through Monte Carlo simulation and regime-conditional stress testing before a single dollar of live capital is allocated.
We sit on the bleeding edge of computational finance—leveraging GPU-accelerated backtesting, adaptive parameter tuning, and real-time risk attribution systems that institutional desks are only beginning to adopt. Our infrastructure is not a cost center; it is the alpha source. The technology does not support the strategy. The technology is the strategy.
Risk management is not a compliance function here—it is the operating system. Every position is sized algorithmically based on realized volatility, cross-asset correlation regimes, and maximum drawdown constraints that are non-negotiable regardless of signal conviction.
We employ dynamic hedging overlays calibrated to tail-risk distributions, not normal-distribution assumptions that blow up precisely when you need them most. Our portfolio construction process treats correlation as a variable, not a constant—because in a liquidation event, everything correlates to one.
The objective is asymmetric: participate in convexity when markets misprice risk, and protect capital ruthlessly when the vol surface signals regime change. We would rather miss upside than absorb a permanent impairment of capital.
For qualified family offices and principal investors
This website is for informational purposes only and does not constitute an offer to sell or a solicitation of an offer to buy any securities. Past performance, whether actual or backtested, is not indicative of future results. Khan Private Ventures, LLC does not provide investment advice to the general public. All investments involve risk, including loss of principal.