Simple by Default • Deep on Demand • Mathematical when Requested
IntelligenceFor Modern Finance
A transparent, educational, and institutional financial intelligence platform. Analyze equities, control downside risk, and master quantitative finance—without Wall Street jargon, hidden black boxes, or misleading simulations.
Whether you are a beginner exploring your first stock, an active investor safeguarding a portfolio, or a quant developing systematic algorithms, RISKOS adapts to your experience level.
Beginner • Research
Explore Markets
Search 5,000+ Indian (NSE/BSE) and US (NYSE/NASDAQ) equities with clear, plain-English company summaries, valuation metrics, and sector indicators.
Construct mathematically resilient portfolios that prioritize downside capital preservation using Conditional Value-at-Risk (CVaR) and Black-Litterman allocations.
Deterministic exchange calendar synchronization. Zero fake simulated ticks outside official trading hours. When NSE or NYSE closes, price feeds halt and display exact final timestamps.
Layer 2: Deep on Demand
Institutional Capabilities Without Black Boxes
Every model, indicator, and calculation on RISKOS includes a one-click "Explain This" breakdown detailing plain-English intuition, exact mathematical formulas, and regulatory research citations.
Dual-Market Intelligence
Unified surveillance across Indian (NSE/BSE) and US (NYSE/NASDAQ) equities with synchronized market clocks, atomic tick timestamps, and automatic currency normalization.
Downside Tail Risk (CVaR)
Replaces flawed Gaussian VaR with sub-additive Conditional Value at Risk (Expected Shortfall) at 99% confidence, capturing fat-tailed market crash distributions.
41 Bots
Sector Quantitative Bots
41 autonomous strategy bots named after Egyptian mythology (Horus, Anubis, Osiris, Ra, Thoth) deployed across Indian and US sectors with strict SEC 15c3-5 risk limits.
Macro Regime Detection
Unsupervised 3-state Gaussian Hidden Markov Models automatically classify market weather into Bull, Bear, or Sideways regimes to adapt strategy parameters dynamically.
Gamma Exposure & Volatility
Tracks options market maker inventory hedging pressures, gamma flip thresholds, and conditional volatility forecasting via EWMA and GARCH(1,1).
75 Interactive Quant Labs
Comprehensive quantitative curriculum: from portfolio variance and Sharpe ratio to Black-Litterman, Merton credit default, and Combinatorial Purged Cross-Validation.
Layer 3: System Pipeline
Interactive System Pipeline Architecture
See exactly how raw exchange feeds transform into audited quantitative decisions across the RISKOS pipeline.
Step 1
Ingestion
NSE, BSE, NYSE Feeds • Calendar Clock
Step 2
Truth Gate
Tick Hygiene • Zero Out-of-Hours Ticks
Step 3
Risk Engines
CVaR • GARCH Vol • Ledoit-Wolf
Step 4
41 Bots
Egyptian Strategy Signals • Barra Factor
Step 5
Provenance
Immutable Audit Trail • SEBI/SEC
ESC
INTENT: COMPANY ANALYSISGenerating structured research canvas for Reliance Industries Ltd...
Beta measures how strongly this stock has historically moved compared to the broader stock market (NIFTY 50).
2. WHY IT MATTERS TO AN INVESTOR
A beta of 1.17 means when the NIFTY 50 rises 1%, this stock historically rose about 1.17%. In market downturns, it has tended to fall slightly more than the index.
3. CALCULATION WITH ACTUAL DATA
Source:NSE Daily Log Returns (252 Trading Days)
Data Status:VERIFIED HISTORICAL
Limitation:Past price sensitivity does not guarantee future co-movement in structural regime shifts.
End-to-End Decision Architecture (Click any node to inspect math)
01MARKET DATANSE / US tick streams
02FEATURE ENGINELog returns & variance
03RISK MODELGARCH & Ledoit-Wolf
04PORTFOLIO ENGINECVaR minimization (SLSQP)
05SCENARIO ENGINEMacro shocks & stress tests
06FINANCIAL INSIGHTExecution boundary
PIPELINE NODE 01: MARKET DATA
Raw Tick Ingestion & Log Returns
Continuous ingestion of multi-asset high-frequency price and quote time-series from NSE/BSE and US exchanges. Prices are converted to continuous compounding log-returns \( r_t = \ln(P_t / P_{t-1}) \) ensuring additivity and normality properties for downstream estimators.
ANALYTICAL ATTRIBUTION
Why This Portfolio Allocation? (Model Output)
RETURN CONTRIBUTION41%
Equities allocation drives the primary alpha component under the current interest rate regime.
RISK CONTRIBUTION28%
Fixed income and gold dampen tail variance, keeping portfolio volatility under 10%.
DIVERSIFICATION BENEFIT87%
Negative equity-bond correlation yields significant variance reduction over single-asset exposure.