Algos by

SkewHunter

by StratzyNiftyBuyingDirectional

High risk option buying algo that carries trade till end-of-day.

Zen Credit Spread Overnight

by StratzyNiftyHedgedDirectional

Utilizing the principles of Hamiltonian mechanics, this algorithm identifies and executes optimal credit spread trades with precision.

Curvature Credit Spread Overnight

by StratzyNiftyHedgedDirectional

Utilizing the principles of Hamiltonian mechanics, this algorithm identifies and executes optimal credit spread trades with precision.

Fixed RR 1:3 (30% SL)

by StratzyNiftyBuyingDirectional

High risk, less frequent, un-hedged option buying trades that hunt for a fixed risk-reward of 1:3 with a 30% stop-loss.

Damper Credit Spread

by StratzyNiftyHedgedDirectional

Utilizing the principles of Hamiltonian mechanics, this algorithm identifies and executes optimal credit spread trades with precision.

SkewHunter TSL

by StratzyNiftyBuyingDirectional

High risk option buying algo with a trailing stop-loss that carries trade till end-of-day.

Delta-Rotation Credit Spread Expiry

by StratzyNiftyHedgedDirectional

This algorithm, named Delta-Rotation Credit Spread Expiry, aims to capitalize on short-term market inefficiencies by identifying potential credit spread opportunities in Nifty options. The core strategy revolves around analyzing various option chain parameters like implied volatility (IV), option greeks, market energy (Hamiltonian), entropy, and price action to gauge the overall market sentiment and identify potentially mispriced options. This is done by calculating an 'alpha' value, which is derived from a combination of IV, curvature, Hamiltonian, eigenvalues, entropy, and predicted volatility. The algorithm uses this alpha, in conjunction with its momentum and a related "alpha2" value based on spot returns and implied volatility curvature changes, to make informed decisions about initiating credit spreads. The signal generation logic triggers a trade when specific conditions related to the calculated 'alpha' values are met, indicating either a bullish or bearish sentiment. A bullish signal prompts the creation of a credit put spread by selling an at-the-money (ATM) put option and buying an in-the-money (ITM) put option to cap the potential loss. Conversely, a bearish signal triggers a credit call spread by selling an ATM call option and buying an out-of-the-money (OTM) call option. Risk management involves calculating the margin required for the trade and setting a stop-loss percentage based on this margin. Additionally, the algorithm sets a target profit level, aiming for 50% of the maximum potential profit from the spread, with a time-based expiry for the target, and will not trade if a similar trade has not yet closed. It checks the position and does not open a trade if one is open. The algorithm checks the current time to make sure that a trade is valid within testing time. The algorithm will check the expiry date to see if it should trade or not. It will also not trade when the market is closed or outside the testing hours.

Mathematician's Credit Spread Overnight

by StratzyNiftyHedgedDirectional

Utilizing the principles of Hamiltonian mechanics, this algorithm identifies and executes optimal credit spread trades with precision.

Delta-Leverage Credit Spread Overnight

by StratzyNiftyHedgedDirectional

Overnight credit spreads algo that uses intraday option chain data to identify opportunities for trade placement

Convex Credit Spread Overnight

by StratzyNiftyHedgedDirectional

Utilizing the principles of Hamiltonian mechanics, this algorithm identifies and executes optimal credit spread trades with precision.

Vacuum GRID (35% SL)

by StratzyNiftyBuyingDirectional

Uses the GRID risk management method to execute un-hedged options with deep-SL.

Settle-Down 40% TSL

by StratzyNiftyBuyingDirectional

A patient intraday strategy that focuses on quality opportunities over constant trading. Settle Down 40% is built for traders who prefer a measured approach instead of chasing every market move. Rather than reacting to every fluctuation, the strategy waits for conditions that align with its framework before taking a position. It generally participates using options slightly away from the current market price, helping balance opportunity with controlled exposure. As a trade begins to move in its favour, the strategy gradually shifts its focus from finding additional profits to protecting the gains already made. This disciplined approach helps reduce emotional decision-making and keeps the strategy focused on consistency over excitement. When market conditions don't offer a favourable setup, it is equally comfortable waiting for the next opportunity instead of forcing a trade.