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Logistic strategy

Script from: TradingViewSwingVolumeMomentum

The Logistic Strategy models price changes using a logistic function akin to those used for population growth. It leverages the z-score of net volume as the parameter influencing the exponential component, aiming to predict market movements with this unique approach. Ideal for traders seeking a novel perspective on utilizing volume data for trading analysis.

Premium users only

Premium users can access all backtests with a Risk/Reward Ratio > 3

@ 5 min

3.55

Risk Reward

22.53 %

Total ROI

16

Bank of America Corporation (BAC)

+ Logistic strategy

@ 5 min

2.96

Risk Reward

25.10 %

Total ROI

16

Hewlett Packard Enterprise Company (HPE)

+ Logistic strategy

@ 1 h

2.83

Risk Reward

1,470.76 %

Total ROI

168

Sandisk Corporation (SNDK)

+ Logistic strategy

@ 1 h

2.62

Risk Reward

1,256.81 %

Total ROI

56

Bloom Energy Corporation (BE)

+ Logistic strategy

@ Daily

2.25

Risk Reward

2,876.46 %

Total ROI

75

Zcash / TetherUS (ZECUSDT)

+ Logistic strategy

@ 4 h

2.23

Risk Reward

16,683.30 %

Total ROI

333

ChainLink / TetherUS (LINKUSDT)

+ Logistic strategy

@ 5 min

2.03

Risk Reward

17.56 %

Total ROI

17

Bloom Energy Corporation (BE)

+ Logistic strategy

@ 4 h

1.92

Risk Reward

9,807.71 %

Total ROI

123

Monero / TetherUS (XMRUSDT)

+ Logistic strategy

@ 4 h

1.82

Risk Reward

682.33 %

Total ROI

48

IREN LIMITED (IREN)

+ Logistic strategy

@ Daily

1.82

Risk Reward

682.33 %

Total ROI

48

CrowdStrike Holdings, Inc. (CRWD)

+ Logistic strategy

@ 2 h

1.67

Risk Reward

954.25 %

Total ROI

135

Spotify Technology S.A. (SPOT)

+ Logistic strategy

@ Daily

1.63

Risk Reward

310.87 %

Total ROI

50

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Active Trades

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Logistic strategy backtest statistics

Aggregated across every validated backtest TradeSearcher has run on this strategy. Figures update automatically as new backtests are added — they are not edited by hand. Classified as swing by holding period.

71
Backtests run
1.4
Avg profit factor
+906%
Avg net profit
+36%
Avg annualized return
58%
Avg max drawdown
0.17
Avg Sharpe ratio

On average, backtests of this strategy beat a buy-and-hold baseline by 733% over the same window.

Performance by asset class

MarketBacktestsAvg profit factorAvg net profitAvg max drawdownAvg Sharpe
Crypto671.2>1,000%70%0.18
Stocks7271.5+745%49%0.17

Backtests use the validated-universe filter: non-repainting scripts, over 15 trades, non-excluded. Per-market rows appear only when at least one backtest exists for that asset class.

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