Know performance, backtest now
that day.
Backtested Gross Gains
This graph compares the Algo's best and worst performance over time, showing how returns can vary depending on when you start using the Algo.
Know performance, backtest now
Performance Summary
Hover to see parameter details.
Tap to see parameter details.
Avg Drawdown
--
Indicates the average decline the strategy experiences in downturns, revealing how deep its typical losses go.
Risk : Reward
--
Indicates how much the Algo typically earns for every rupee it risks. E.g., 1:3 means it targets ₹3 in reward for every ₹1 of risk.
Frequency of trade
--
Indicates how often the Algo trades on average.
Risk
--
Indicates the expected volatility of the Algo and is classified into levels like Low, Medium, and High.
Max Drawdown
--
Indicates the largest decline the Algo has faced so far, reflecting its most severe historical downturn.
Success Ratio
--
Indicates the percentage of trades that end in profit. E.g., 70% means 7 out of 10 trades are winners.
Avg Profit in Trade
--
Indicates the average gain the Algo earns on its winning trades.
Avg Loss in Trade
--
Indicates the average loss the Algo incurs on its losing trades.
Avg Time to Recovery
--
Indicates the average number of days the Algo took to bounce back after experiencing its average drawdown.
Max Time to Recovery
--
Indicates the number of days the Algo took in the past to recover from its worst drawdown to date.
Sharpe Ratio
--
Indicates how well an Algo balances risk and return, showing how effectively it manages volatility.
*Metrics/Analytics basis past data. Historical data does not guarantee future results.
Know performance, backtest now

Strategy Overview
This algorithmic trading strategy, named "Ratio-Weave Credit Spread Expiry," aims to identify and capitalize on short-term directional biases in the NIFTY 50 index by analyzing a combination of option chain data and technical indicators. The core of the strategy involves calculating a proprietary "alpha" signal derived from factors like implied volatility (IV) skew divergence between call and put options, entropy compression in at-the-money (ATM) options, and the momentum and correlation of ATM options. This alpha signal is then normalized using a time-series rank, providing a relative measure of the signal's strength. The algorithm triggers potential trades when the alpha signal exceeds a predefined threshold and when a significant IV skew is observed, suggesting a potential directional bias. This algorithm specifically focuses on trading credit spreads on NIFTY options, typically closer to the expiry date. Credit spreads involve simultaneously selling a near-the-money (NTM) option (either a call or a put) and buying a further out-of-the-money (OTM) option of the same type. The algorithm aims to profit from the time decay of the sold option, while the bought option acts as a hedge against adverse price movements. Specifically, it looks to establish credit call spreads when it anticipates market downside movement and credit put spreads when the expectation is upside movement. Credit spread strategies typically perform best when the market exhibits limited movement or moves in the anticipated direction, allowing the options to expire worthless and the trader to retain the initial premium received. The algorithm incorporates stop-loss and target levels to manage risk and potentially lock in profits.
This Algo is managed by
Stratzy
Stratzy is a place where you can get tailored guidance for your portfolio to help you make the right investments. Gain access to battle tested algos, automation of your investments and insights about the market, right in the palm of your hand. Your wealth generation begins here.
More algos by Stratzy









































































