Backtest Returns
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Backtest Snapshot

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Combine other Algos and compare portfolio stability.

Combine other Algos and compare portfolio stability.

Algo
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Algo Score - It's a single number that summarizes an Algo's overall performance by combining returns, risk, volatility, drawdowns, and consistency. A higher score indicates stronger, more stable, and better risk-adjusted performance.

Score
Correlation
Algo
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Algo Score - It's a single number that summarizes an Algo's overall performance by combining returns, risk, volatility, drawdowns, and consistency. A higher score indicates stronger, more stable, and better risk-adjusted performance.

Score
Correlation
Only-Calls 40% TSL
-- 1.00
Settle-Down 40% TSL
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SkewHunter
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SkewHunter TSL
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Wise-Move 25% TSL
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Fixed RR 1:3 (30% SL)
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Vacuum GRID (35% SL)
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Seed-Fund 40% SL FixedRR 1:3
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Thrifty 40% TSL
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Index Sniper
-- --
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Why is less correlation so important in Algotrading?
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At Stratzy, we align strictly with SEBI’s risk management framework by prioritizing uncorrelation in our strategy curation. In algorithmic trading, uncorrelation ensures that our strategies do not react identically to market volatility; if one strategy faces a drawdown due to specific market conditions, others are designed to remain unaffected or perform differently. This statistical diversification acts as a crucial internal hedge, reducing the risk of simultaneous losses and ensuring portfolio stability. By avoiding concentrated risk, we uphold the regulatory mandate to prioritize investor safety and maintain market integrity.

Backtested Gross Gains (₹)

Backtested Returns Snapshot

PeriodReturns
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Backtest Best & Worst Holding Periods
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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

Hover to see parameter details.

Click to see parameter details.

Drawdown Icon

Avg Drawdown

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Indicates the average decline the strategy experiences in downturns, revealing how deep its typical losses go.

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Risk Reward Icon

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.

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Win Rate Icon

Avg Trade

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Indicates how often the Algo trades on average.

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high Risk

Risk

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Indicates the expected volatility of the Algo and is classified into levels like Low, Medium, and High.

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Max Drawdown

Max Drawdown

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Indicates the largest decline the Algo has faced so far, reflecting its most severe historical downturn.

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Success Ratio

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.

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Avg Profit

Avg Profit in Trade

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Indicates the average gain the Algo earns on its winning trades.

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Avg Loss

Avg Loss in Trade

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Indicates the average loss the Algo incurs on its losing trades.

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Avg Time to Recovery

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.

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Max Time to Recovery

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.

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Sharpe Ratio

Sharpe Ratio

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Indicates how well an Algo balances risk and return, showing how effectively it manages volatility.

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*Metrics/Analytics basis past data. Historical data does not guarantee future results.

Overview

NiftyBuyingDirectional

Imagine a savvy shopper at a bustling farmer's market, but with a very specific agenda. This shopper isn't browsing leisurely. Instead, they're intensely focused on a few select stalls selling unique, handcrafted goods. They've done their homework, tracking the stall owners' recent pricing and sales patterns. They're looking for a rare combination: a product that's both unusually cheap compared to its past prices, and from a stall owner whose overall sales are showing strong potential. If they spot this sweet spot, they'll quickly buy a small quantity, always keeping a close eye on the price in case they need to quickly cut their losses. This algorithm trades NIFTY options, specifically aiming to buy "naked" call or put options. It's constantly crunching data, looking for a specific blend of signals derived from option prices, implied volatility, and trading volume. The algorithm waits for a potent combination of factors to align—basically, it wants to see a call or put option that looks unusually cheap based on its own volatility metrics, and also sees a pattern suggestive of overall buying or selling strength. If this combination shows up, the algorithm buys a single lot, setting a stop-loss order to limit potential losses. It's designed to be selective and risk-conscious, only entering trades when specific conditions are met and quickly exiting if things go south.

This algo is managed by...

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Stratzy

INH000009180 SEBI registered algo provider

Algos in market
Algos in market79
Active since
Active since5 Years
Deployed by
Deployed by12.5K users

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.

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