SARVIS ALGO

Quantitative Indian Index Trading

Data-driven algorithmic strategies built on mathematical indicators — no guesswork, only proven rules.

Human vs Quantitative Trading
Why we chose algorithms over intuition
Aspect Human Trading Quantitative Trading
Decision Making Gut feeling & emotions Mathematical rules & data
Emotions Fear & greed drive exits/entries Zero emotion — rules execute as coded
Speed Seconds to minutes per decision Milliseconds — instant reaction
Consistency Varies daily with mood & fatigue Same rules, every single trade
Backtesting Can't test “feelings” on past data 129M+ combinations tested on 11+ years
Risk Management Often ignored under pressure Hard-coded stop-loss & daily limits
Screen Time 6+ hours glued to charts daily Runs 24/7 on server — check anytime
Multiple Indices Hard to track 3+ indices at once NIFTY + BANKNIFTY + SENSEX simultaneously
Overnight Bias News & social media cause panic Only reacts to price & indicators
Revenge Trading Common after losses — doubles down Daily loss limit hit → stops trading
Scalability One person, one screen, limited Add more strategies & indices easily
Long-term Edge 90% of retail traders lose money Proven rules with statistical edge
Our Trading Philosophy
7+ years of painful lessons distilled into unbreakable rules

The Hard Truth About Trading

After 7+ years of manual trading, the reality was clear — consistent profit was impossible. At one point, every single day was a loss. The market isn't random chaos, but it's designed like a double-edged blade — sharp on both sides. Index options punish hesitation and reward discipline, but human psychology works against us. We get trapped by noise, react to panic, revenge-trade after losses, and override our own rules. The only way forward was to remove the human from the equation.

Rules Never Bypassed

No manual entries allowed — ever. Only manual exit is permitted to keep the system pure quantitative. Every entry and every exit is indicator-driven. No overrides, no exceptions, no “just this once.”

No Panic, No Aggression

The system never enters or exits on panic spikes or aggressive market movements. These are the #1 loss-making events in manual trading — our algorithms simply ignore them and wait for confirmed indicator signals only.

Multi-Timeframe, Every Second

Multiple timeframes with different indicators, each with its own custom configuration — tracked and evaluated every single second. Not random indicators; each one is fully backtested with optimized settings preserved across 10+ years of historical data.

Indicator-First Exits

Our primary strategy uses pure indicator-based exits — no fixed stop-loss that gets hunted by market noise. Supporting strategies use adaptive trailing stops to protect against option premium decay. Every exit is systematic, never panic-driven.

Custom Optimized Settings

Every indicator period, phase, and power setting is custom-tuned — not textbook defaults. All parameters are backtested and optimized across 10+ years of NIFTY/BANKNIFTY/SENSEX historical data through 129M+ test combinations.

Battle-Tested Through Major Events

This system has survived every major market event in the last decade of backtesting — COVID crash, budget days, election results, RBI surprises, global crises. The rules held. The edge survived.

The Win Rate Myth

Most trading systems claim 70%+ win rate. Here's what they don't tell you — to achieve that, the take-profit is kept tiny and the stop-loss is kept too large. So the 30% of losing trades wipe out all the gains from the 70% winners.

The reality of a genuinely profitable system: 25–40% win rate. 60–80% of trades will be losses — because we take every opportunity the market offers. But when we win, the winners are significantly larger than the losers. That's the real edge. Risk-reward matters, not win rate.

Realistic Returns — No False Promises

80–100%
Year-on-Year Returns
Following quantitative rules strictly
10–15%
If Targeting 100% Green Months
After all broker & exchange costs

Not every day, week, or month will be green — and that's by design. Market noise exists at every timeframe and every indicator. It arrives like an unwelcome guest, always. But by following quantitative procedures and never reacting to noise, the edge compounds over time. Patience is the strategy. The system trades on real movements only.

Understanding the Market

The market never repeats the same pattern. No timeframe, no indicator is free from noise. Index options are designed like a double-edged blade — you must learn to hold it without getting cut. That's not easy, and it's not something manual trading can consistently achieve. The only sustainable approach is systematic, rule-based, emotionless execution — and that is exactly what SARVIS ALGO does.

No Speed, No Thrills — Just Discipline

Think of this system as an autonomous driver on a highway with a strict speed limit. It doesn't race. It doesn't swerve. It doesn't chase. It watches every signal, every second — across multiple timeframes and indicators — and acts only when conditions are right. No adrenaline, no excitement, no heroic trades. Just calm, calculated, rule-bound execution that compounds over time. Boring is profitable.

Disclaimer: Past backtested performance does not guarantee future results. Trading in index options involves substantial risk of capital loss. All strategies and returns mentioned are based on historical backtests and simulations. Actual trading results may vary due to market conditions, slippage, and execution differences. Please consult a SEBI-registered investment advisor before making trading decisions.

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The Journey
From manual trading to systematic, data-driven decisions

The Problem

After 7 years of manual option trading, one truth became clear: emotions destroy profits. The same patterns that worked on paper fell apart under live pressure. The market needed a system, not a person.

The Obsession

Over 2+ years, every known technical indicator was tested. Not just applied, but dissected across multiple timeframes, market regimes, and volatility conditions. 186 indicators. 12 timeframes. 129 million combinations.

The Elimination

Most strategies fail in live markets. Through 3,680+ backtests and 933 unique strategy variations, the weak were eliminated. Only strategies that survived across trending, ranging, and volatile regimes made the cut.

The Result

What remains is not a single strategy, but a multi-strategy system that adapts to market conditions. Custom indicator-based signals, spread strategies, adaptive risk management, and real-time market regime detection working together.

Research Depth
What it took to find what actually works
📊

Technical Indicators

EMA, SMA, Proprietary MA, RSI, MACD, ADX, Bollinger, SuperTrend, VWAP, ATR, Ichimoku, Heikin Ashi, KAMA, ZLEMA, TEMA, HMA, ALMA, CCI, Stochastic, Williams %R, Donchian, Keltner, Pivot Points, and more.

186 Indicators Tested
🤖

ML/AI Models

XGBoost, Random Forest, LSTM, Gradient Boosting, Neural Networks, Deep Reinforcement Learning (PPO, DQN, A2C), CatBoost, LightGBM, SVM, KNN, Decision Trees, AdaBoost, and Logistic Regression.

22 Model Types Evaluated
🔍

Strategy Discovery

Systematic strategy hunting across trend following, mean reversion, momentum, breakout, scalping, swing trading, OI analysis, PCR, IV surface modeling, VIX regime detection, and gap trading approaches.

933 Strategies Tested

Multi-Timeframe Analysis

Every indicator tested across 5-second, 15-second, 1-minute, 2-minute, 3-minute, 5-minute, 15-minute, 30-minute, 1-hour, 2-hour, 3-hour, and daily timeframes.

12 Timeframes
💹

Option Chain Analysis

Real-time option chain EMA tracking, IV skew analysis, OI-based entry/exit, spread strategies (debit spreads), premium decay modeling, and synthetic option pricing for backtesting.

NIFTY, BANKNIFTY, SENSEX
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Risk Management

Adaptive stop loss, trailing stop loss, premium-based exits, time-based exits, VIX regime sizing, conviction decay engine, and smart cooldown periods. No single trade can break the system.

Multi-Layer Protection
Technology
Production-grade infrastructure built for reliability
Python 3.13
Flask
WebSocket
XGBoost
Scikit-Learn
NumPy
Pandas
SQLite
Zerodha Kite API
Proprietary Moving Average
Real-time Option Chain
VPS Deployed
SSL/HTTPS
Adaptive Market Override
Multi-Strategy Engine
Saravanan G
Algo Trader & Developer

Started trading options in 2019. Spent years learning what doesn't work before building what does. Every line of SARVIS ALGO is written from real market experience, not theory.

The goal was never to build the most complex system. It was to build one that survives real markets, real slippage, and real emotions.

7+
Years Trading
2+
Years Building
64
Versions
129M+
Combinations
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