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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.
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Performance Summary
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Avg Drawdown
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Indicates the average decline the strategy experiences in downturns, revealing how deep its typical losses go.
Risk : Reward
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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
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Indicates how often the Algo trades on average.
Risk
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Indicates the expected volatility of the Algo and is classified into levels like Low, Medium, and High.
Max Drawdown
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Indicates the largest decline the Algo has faced so far, reflecting its most severe historical downturn.
Success Ratio
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Indicates the percentage of trades that end in profit. E.g., 70% means 7 out of 10 trades are winners.
Avg Profit in Trade
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Indicates the average gain the Algo earns on its winning trades.
Avg Loss in Trade
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Indicates the average loss the Algo incurs on its losing trades.
Avg Time to Recovery
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Indicates the average number of days the Algo took to bounce back after experiencing its average drawdown.
Max Time to Recovery
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Indicates the number of days the Algo took in the past to recover from its worst drawdown to date.
Sharpe Ratio
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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.
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Strategy Overview
Imagine you're a shopkeeper deciding what to stock on your shelves for the next day, but you're not selling groceries—you're selling investment contracts. This algorithm is like that shopkeeper, carefully analyzing market trends, historical data, and a bit of financial "weather forecasting" to decide whether to place orders to sell certain combinations of options contracts. The goal is to make a small profit from the price difference when these contracts either expire or when the market believes there is little chance of the price of an asset moving beyond a specific high or low range. The algorithm only considers making these decisions during a specific window of the trading day. This algorithm trades a "short strangle" on the NIFTY 50 index options. A short strangle strategy typically performs well when the market is expected to stay relatively calm or move within a narrow range. It profits if the index price remains between two pre-defined price points (the "strikes") until the option contracts expire. The algorithm aims to capitalize on the expectation that the market won't make any sudden large price swings overnight.
This Algo is managed by
Stratzy
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