Discover Algos by Risk Tolerance
Low Risk Algos
Capital-preserving algos with steady returns
Ratio-Fluxer Credit Spread Expiry
The "Ratio-Fluxer Credit Spread Expiry" algorithm seeks to capitalize on short-term imbalances and inefficiencies in the options market by identifying specific conditions related to implied volatility (IV) and price action to generate potential trading opportunities in NIFTY options. The strategy uses a combination of factors derived from option implied volatility, price action, and statistical analysis to generate a normalized "alpha" signal. This signal is then combined with other technical indicators to identify potential entry points for trades. The algorithm takes a contrarian approach, seeking to fade unsustainable market conditions which are quantified using ratios of IV entropy, imbalances in curvature, and skewness. The algorithm aims to identify opportunities where implied volatility might revert to a more sustainable level. It does this by analysing the "alpha" signals. This algorithm trades a credit spread on NIFTY options, specifically looking for opportunities to profit from the time decay of options contracts with a focus on expiry. The trades are triggered based on the calculated "alpha" and skewness of the implied volatility in the options chain. A credit spread involves selling a near-the-money option and buying a further out-of-the-money option of the same type (either puts or calls) with the same expiration date. This strategy benefits when the price of the underlying asset remains relatively stable or moves in a direction that allows the sold option to expire worthless, while the bought option limits potential losses. A credit spread benefits if there is low volatility in the market and it trades in a range-bound manner.
Foundation Portfolio Automated
A portfolio built with the foundational NIFTY etf. You need to have DDPI enabled account to be able to trade in this algo.
Medium Risk Algos
Balanced algos with risk-reward in check
Intraday Short Strangle
Daily strangle algo.
Lattice Short Straddles
A short straddle is an options strategy that involves selling both a call and a put option with the same strike price and expiration date.
Compressed Strangle
Executes overnight short strangles that capitalizes on correlation compression in the options market.
NIFTY Champions
Champions – Nifty 50 is a high-conviction, rules-based equity strategy that invests in the top 5 ranked stocks from the NIFTY 50 using the proprietary MOST framework. The portfolio is sector-agnostic, equally weighted, and dynamically rebalanced, making it suitable for long-term investors comfortable with concentration and active risk.
Moderately High Risk Algos
Aggressive trades with strategic protection
Intraday Short Strangle
Daily strangle algo.
Lattice Short Straddles
A short straddle is an options strategy that involves selling both a call and a put option with the same strike price and expiration date.
Compressed Strangle
Executes overnight short strangles that capitalizes on correlation compression in the options market.
NIFTY Champions
Champions – Nifty 50 is a high-conviction, rules-based equity strategy that invests in the top 5 ranked stocks from the NIFTY 50 using the proprietary MOST framework. The portfolio is sector-agnostic, equally weighted, and dynamically rebalanced, making it suitable for long-term investors comfortable with concentration and active risk.
High Risk Algos
High risk-high reward algos for brave traders
Zen Credit Spread Overnight
Utilizing the principles of Hamiltonian mechanics, this algorithm identifies and executes optimal credit spread trades with precision.
SkewHunter
High risk option buying algo that carries trade till end-of-day.
Curvature Credit Spread Overnight
Utilizing the principles of Hamiltonian mechanics, this algorithm identifies and executes optimal credit spread trades with precision.
Fixed RR 1:3 (30% SL)
High risk, less frequent, un-hedged option buying trades that hunt for a fixed risk-reward of 1:3 with a 30% stop-loss.
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Low Risk Algos
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Moderately High Risk Algos
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