48%
Net CAGR (2019-2025)
Wealthnomics deploys AlphaGod™, our proprietary systematic trading infrastructure, to capture alpha across US and Indian equity and derivatives markets through machine learning-driven, volatility-adaptive strategies.
Research-driven alternative asset management with institutional-grade systematic strategies across liquid US and Indian markets.
Wealthnomics is a research-driven alternative asset manager specializing in systematic, rules-based investment strategies across liquid US and Indian markets. Founded by practitioners with deep expertise in quantitative finance, machine learning, and risk management.
Our mandate is to deliver consistent, uncorrelated returns through our proprietary AlphaGod™ system—a multi-factor, volatility-adaptive trading infrastructure that has been rigorously validated across multiple market regimes.
500+ validation trials per strategy
Max DD under 1% all periods
Zero discretionary intervention
ML-driven regime detection
We optimize for Sharpe ratio, not absolute returns. Superior risk-adjusted performance compounds more efficiently over time.
Our systems are designed to perform better during volatility, not despite it. Market stress is an opportunity, not a threat.
Every hypothesis is tested on out-of-sample data. We reject strategies that show any signs of overfitting.
Institutional-grade infrastructure with independent custody, third-party audit, and segregated accounts.
Multi-layered systematic platform combining volatility-adaptive execution, machine learning regime detection, and rigorous risk management.
Dynamic position sizing and exit management calibrated to real-time market volatility.
Composite scoring combining orthogonal factors with ML-optimized weights.
Gradient boosting models evaluate factor importance and adapt to market regimes.
Tranche-based position management with dynamic rebalancing.
Focused exposure to liquid Indian equities, derivatives, and commodities.
Institutional-grade execution with smart order routing and real-time controls.
Audited results across multiple market regimes. All returns net of fees.
| Period | Market Condition | CAGR | Sharpe | Max DD | Win Rate | Trades |
|---|---|---|---|---|---|---|
| Full Period | All Regimes | 48.0% | 4.1 | -0.37% | 56.6% | 4,792 |
| Jan-Jun 2020 | COVID Crash | 61.7% | 3.9 | -0.37% | 54.6% | 337 |
| Jul 2020 - Dec 2021 | Post-COVID Bull | 89.0% | 4.7 | -0.19% | 62.6% | 984 |
| 2022 | Bear Market | 58.5% | 4.2 | -0.16% | 54.5% | 708 |
| 2023 | Recovery | 37.6% | 4.5 | -0.24% | 57.4% | 704 |
| 2024 | Consolidation | 38.2% | 4.9 | -0.15% | 58.8% | 711 |
Comprehensive examination of our systematic approach and the structural inefficiencies we exploit.
The US and Indian equity market presents a unique opportunity for systematic alpha generation due to structural inefficiencies arising from retail investor dominance, information asymmetries, and behavioral biases that create predictable patterns in price action.
AlphaGod™ is engineered to systematically exploit these inefficiencies through a multi-layered approach combining volatility-adaptive execution, machine learning-driven factor weighting, and rigorous risk management—validated across 6+ years of live market data including multiple stress scenarios.
The US and Indian market exhibits persistent inefficiencies that can be systematically captured by strategies optimized for local market microstructure.
Traditional fixed-parameter strategies underperform because they cannot adapt to the dynamic nature of market volatility.
Single-factor strategies are vulnerable to regime changes. Our composite scoring system combines orthogonal factors with ML-optimized weights.
The system benefits from volatility rather than suffering from it. Higher volatility increases trade frequency and profit potential.
Detailed examination of the AlphaGod™ system components and methodology
The AlphaGod™ signal engine processes market data through a multi-stage pipeline that transforms raw price and volume information into actionable trading signals.
Our ML layer employs gradient boosting models to continuously evaluate factor importance and adapt strategy weights based on detected market regimes.
Hidden Markov Models classify market into trending, mean-reverting, or volatile regimes in real-time.
Gradient boosting evaluates which factors are predictive in current regime, adjusting weights dynamically.
Isolation forests identify unusual market conditions that may require reduced position sizes.
Capital preservation is embedded at every level. The volatility-adaptive exit mechanism ensures losses are cut quickly while winners run.
All strategies undergo rigorous out-of-sample validation with 500+ parameter trials on data the model has never seen.
5-year training window, 2-year out-of-sample validation. Parameters must work on unseen data.
10,000 randomized trade sequences to validate robustness and estimate confidence intervals.
Performance validated across COVID crash, 2022 bear market, and other high-volatility periods.
Comprehensive risk framework with independent oversight and institutional governance.
Portfolio volatility maintained within 2-3% daily range through dynamic position sizing.
Maximum 23 concurrent positions with strict single-name and sector exposure caps.
All instruments meet minimum volume thresholds. Full liquidation possible within 24 hours.
Automatic position reduction at -0.5% daily, full deleverage at -1.0%.
Portfolio management, risk oversight, and operations operate independently.
All assets held with registered custodian. Fund never takes possession of investor assets.
Annual audit by Big 4 firm. Monthly NAV verification by independent administrator.
SOC 2 Type II compliant infrastructure. Multi-factor authentication throughout.
Systematic strategies can experience losses during regime changes or unprecedented conditions.
Use of up to 3x leverage amplifies both gains and losses.
Quantitative models may fail to capture unprecedented market dynamics.
System failures or connectivity issues could result in losses.
All strategy changes require IC approval. Committee meets weekly.
CRO reports directly to board with authority to halt trading.
Monthly performance reports, quarterly risk reviews, annual audited statements.
Full compliance with SEBI regulations. Regular compliance audits.
Multidisciplinary expertise in quantitative research, portfolio management, and technology.
Architect of AlphaGod™. Doctorate in quantitative finance with research in statistical modeling and applied computational methods.
Leads model development, data engineering, and signal research. Focus on robust statistical methods.
Oversees firm-wide market, liquidity, and operational risk. Independent reporting line to board.
Manages administration, finance, trade operations, and valuation frameworks.
Indicative terms for qualified investors.
We welcome inquiries from institutional investors, family offices, and qualified individuals.
Strategy deck, due diligence questionnaire, and offering documents available to qualified investors upon completion of onboarding procedures.
ayushman@wealthnomics.com
+91 8887365246
Wyoming, USA