// Investor Presentation · 2025

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portfolio_optimizer.py — Optivya

portfolio_optimizer.py

risk_manager.py

config.ini

Python UTF-8 LF Spaces: 4 Ln 1, Col 1 main ●

import numpy as np from optivya.engine import BacktestRunner class MomentumBacktest: self.risk = RiskManager(max_drawdown=0.035) def generate_signals(self, data): z = ret / vol return np.where(z > 1.5, 1, 0) # AUM: ₹25Cr | CAGR: 36.09% engine.run(live=True) from optivya.options import VolSurface edge = fair - market self.broker.place_order(strike, qty) import numpy as np from optivya.engine import BacktestRunner class MomentumBacktest: self.risk = RiskManager(max_drawdown=0.035) def generate_signals(self, data): z = ret / vol return np.where(z > 1.5, 1, 0) # AUM: ₹25Cr | CAGR: 36.09% engine.run(live=True) from optivya.options import VolSurface edge = fair - market self.broker.place_order(strike, qty)