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Low Risk Algos
Capital-preserving algos with steady returns
Ratio-Ripple Credit Spread Exit-Early
This algorithmic trading strategy, named "Ratio-Ripple Credit Spread Exit-Early," aims to identify opportunities in the NIFTY 50 index options market by analyzing the relationship between implied volatilities (IV) of out-of-the-money (OTM) and at-the-money (ATM) options. The algorithm calculates a proprietary alpha signal derived from the difference between OTM and ATM implied volatilities and their rate of change, using time-series ranking to normalize the signal. Trades are triggered when the alpha signal exceeds a predefined threshold, indicating a potential mispricing in the options market. A secondary condition has been added that checks the rate of change of delta values. The algorithm factors in market open hours, expiry dates and tested time periods to find trading opportunities. The algorithm implements a credit spread strategy, specifically targeting the execution of credit call spreads or credit put spreads based on the signals generated. Credit spreads profit from a narrowing of the spread between the short and long options, which typically occurs when implied volatility decreases or when the underlying asset price moves in a favorable direction. The trades are executed by shorting a near-the-money (NTM) option and simultaneously buying a further out-of-the-money (OTM) option with the same expiration date and strike type, limiting potential losses. This strategy is typically favorable in sideways or moderately trending markets, where the expectation is for the underlying asset to remain within a defined range, allowing the options to expire worthless or with reduced value, thus generating profit.
Ripple-Return Credit Spread Expiry
The "Ripple-Return Credit Spread Expiry" algorithm is designed to identify and execute credit spread option strategies on the NIFTY 50 index, aiming to profit from the decay of option premiums as they approach their expiry date. The core strategy involves analyzing implied volatility (IV) across different strike prices to determine potential overpricing of options. It leverages technical indicators, specifically comparing the IV of out-of-the-money (OTM) options against at-the-money (ATM) options and their rate of change (delta), using a time-series rank to normalize the alpha signal. By identifying instances where OTM options are relatively overpriced compared to ATM options, the algorithm seeks to sell the overpriced options and simultaneously buy options further out-of-the-money to create a credit spread. The algorithm incorporates risk management techniques such as setting stop-loss and target levels based on a percentage of the margin required and/or spread premium, respectively. This algorithm trades credit spreads on NIFTY 50 index options, specifically targeting weekly expiry options. Credit spreads benefit from sideways or moderately directional market movements where the sold options expire worthless, allowing the trader to keep the premium received. The algorithm enters trades between 10:15 AM and 2:15 PM, avoiding trading on expiry days and outside of defined trading hours to align with backtested timeframes. The strategy aims to capitalize on the time decay of options close to expiry, while limiting potential losses through the purchase of further OTM options in the spread.
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.
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.
Medium Risk Algos
Balanced algos with risk-reward in check
Sahi-Nivesh Short Strangle Overnight
Imagine you're running a small shop and need to decide what to stock for the upcoming week. Instead of guessing, you look at a bunch of information: recent sales data (like past prices), general market trends, and even what's popular on social media (like implied volatility and sentiment). You use all this to figure out if there's a good opportunity to sell something everyone thinks will stay stable – like umbrellas before a predicted sunny week. The goal is to make a small profit if things go as expected, but be ready to quickly cut your losses if the weather suddenly changes. This algorithm does something similar, using market data and indicators to find opportunities where it believes things will stay relatively calm, so it can profit from that stability. This algorithm trades "short strangles" on the NIFTY 50 index, which is like betting that a stock's price won't move much. A short strangle strategy typically works best when the market is expected to be relatively stable. It sells options contracts that will only make money for the buyer if the price of the underlying asset moves a lot. The strategy aims to collect small profits from these options contracts expiring worthless if the market stays within a certain range. It works when the market prediction is stability, or low volatility.
Alpha Industries Automated
Invest in top sectoral ETFs.
Holonomy's Short Strangles
This Morning Short Strangle algo strategically sells both call and put options on the index in the morning, aiming to capitalize on premium decay or range-bound market conditions.
Foundation Portfolio Automated
An etf picking algo built with the foundational NIFTY etf.
Moderately High Risk Algos
Aggressive trades with strategic protection
Sahi-Nivesh Short Strangle Overnight
Imagine you're running a small shop and need to decide what to stock for the upcoming week. Instead of guessing, you look at a bunch of information: recent sales data (like past prices), general market trends, and even what's popular on social media (like implied volatility and sentiment). You use all this to figure out if there's a good opportunity to sell something everyone thinks will stay stable – like umbrellas before a predicted sunny week. The goal is to make a small profit if things go as expected, but be ready to quickly cut your losses if the weather suddenly changes. This algorithm does something similar, using market data and indicators to find opportunities where it believes things will stay relatively calm, so it can profit from that stability. This algorithm trades "short strangles" on the NIFTY 50 index, which is like betting that a stock's price won't move much. A short strangle strategy typically works best when the market is expected to be relatively stable. It sells options contracts that will only make money for the buyer if the price of the underlying asset moves a lot. The strategy aims to collect small profits from these options contracts expiring worthless if the market stays within a certain range. It works when the market prediction is stability, or low volatility.
Alpha Industries Automated
Invest in top sectoral ETFs.
Holonomy's Short Strangles
This Morning Short Strangle algo strategically sells both call and put options on the index in the morning, aiming to capitalize on premium decay or range-bound market conditions.
Foundation Portfolio Automated
An etf picking algo built with the foundational NIFTY etf.
High Risk Algos
High risk-high reward algos for brave traders
SkewHunter
A naked-options “Skew Hunter” algo that hunts extreme IV and volume-OI skew across strikes—entering directional options only when both volatility and flow signals align, with strict intraday risk controls.
SkewHunter TSL
A naked-options “Skew Hunter” algo with a TSL that targets extreme IV and flow skew, taking directional trades only when both signals align—then locking in gains through an adaptive trailing stop-loss.
Fixed RR 1:3 (30% SL)
An extremely high-risk naked-options algo that trades volatility-skew “energy,” going long calls or puts only when stress-imbalances and both alpha signals align—using a strict 30% SL, 90% target, and tightly filtered intraday entries.
Curvature Credit Spread Overnight
A credit-spread strategy that behaves like a market fluid-dynamics engineer—reading liquidity flow, viscosity, and curvature across strikes, and profiting when these flow patterns rebalance.
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