
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-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.

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.

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.

Settle-Down 40% TSL
Imagine a savvy shopper at a bustling farmers market. They're not just grabbing the first apple they see; instead, they carefully scan the stalls, looking at the volume of shoppers around each vendor and comparing the quality and prices of the produce. This shopper is particularly interested in finding unusual deals where there are lots of sellers with fewer buyers, suggesting prices might be about to move. They’re not afraid to buy something cheap, but they set a firm stop-loss: if the apple starts to rot (the price drops too much), they quickly toss it to avoid a bigger loss. They also have a clever trick—if the apple starts to ripen nicely (price rises), they’ll adjust how quickly it has to rot (stop loss trails the price) before they toss it, locking in some profit. This algorithm trades options on the Nifty 50, a major Indian stock market index. It's looking for potential imbalances in the options market by comparing the trading volumes of different types of options (calls and puts, both in-the-money and out-of-the-money) to gauge market sentiment. It uses some complex calculations based on options data to determine if it should buy a call option (betting the market will go up) or a put option (betting the market will go down). Before acting, it makes sure it's the right time of day and not close to the expiry date of the options. If it decides to trade, it buys a single option and sets a stop-loss level to limit potential losses. It may also move the stop-loss as the price of the option changes, and takes the intiative to stop the trade to minimize losses.

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.

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.

Zen Credit Spread Overnight
An options trading algo that uses volatility and volume-based mean-reversion signals to create credit spreads. It sells ATM options and hedges with OTM/ITM strikes, operating between 10:15 AM–2:15 PM with strict risk management.

Delta-Ripple Credit Spread Overnight
The Delta-Ripple Credit Spread Overnight algorithm is designed to identify and capitalize on short-term directional movements in the NIFTY 50 index using a combination of implied volatility (IV) analysis and time series ranking. The core strategy revolves around identifying skews in the implied volatility of out-of-the-money (OTM) put and call options. The algorithm calculates an 'alpha' signal based on the relative IV of OTM puts and calls compared to at-the-money (ATM) options. This alpha is then ranked using a time-series rank to smooth the signal and identify potential trading opportunities. The algorithm leverages historical options data, calculates time to expiry, and incorporates checks for market open status and trading hours to ensure trades are executed under optimal conditions. Trades are only considered if certain time criteria with the underlying data are matched This algorithm specifically trades overnight credit spreads on the NIFTY 50 index options, aiming to profit from the decay of option premiums and directional biases. 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. The algorithm analyzes the alpha signal and, based on predefined thresholds, initiates a credit put spread (selling puts and buying further OTM puts) or a credit call spread (selling calls and buying further OTM calls). A credit spread strategy benefits from sideways or moderately directional markets, where the sold option expires worthless, allowing the trader to keep the premium received, less the cost of the long option. Stop-loss and target parameters are configurable to manage risk and potential profit.






