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.

Top 73 Backtests of Logistic strategy

Explore the most profitable cryptocurrency and stock backtests with Logistic Strategy (on TradingView).

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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

Total Trades

Bank of America Corporation (BAC)

+ Logistic strategy

@ 5 min

2.96

Risk Reward

25.10 %

Total ROI

Total Trades

Bloom Energy Corporation (BE)

+ Logistic strategy

@ Daily

2.62

Risk Reward

3,202.05 %

Total ROI

Total Trades

Hewlett Packard Enterprise Company (HPE)

+ Logistic strategy

@ 1 h

2.51

Risk Reward

1,216.71 %

Total ROI

165

Total Trades

Bloom Energy Corporation (BE)

+ Logistic strategy

@ 4 h

2.25

Risk Reward

11,394.49 %

Total ROI

122

Total Trades

Sandisk Corporation (SNDK)

+ Logistic strategy

@ 1 h

2.23

Risk Reward

954.38 %

Total ROI

Total Trades

ChainLink / TetherUS (LINKUSDT)

+ Logistic strategy

@ 5 min

2.03

Risk Reward

17.56 %

Total ROI

Total Trades

IREN LIMITED (IREN)

+ Logistic strategy

@ Daily

1.82

Risk Reward

682.33 %

Total ROI

Total Trades

Monero / TetherUS (XMRUSDT)

+ Logistic strategy

@ 4 h

1.82

Risk Reward

682.33 %

Total ROI

Total Trades

Zcash / TetherUS (ZECUSDT)

+ Logistic strategy

@ 4 h

1.78

Risk Reward

10,550.60 %

Total ROI

330

Total Trades

Spotify Technology S.A. (SPOT)

+ Logistic strategy

@ Daily

1.63

Risk Reward

310.87 %

Total ROI

Total Trades

CrowdStrike Holdings, Inc. (CRWD)

+ Logistic strategy

@ 2 h

1.61

Risk Reward

835.23 %

Total ROI

133

Total Trades

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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.

Backtests run

1.3

Avg profit factor

+786%

Avg net profit

+32%

Avg annualized return

58%

Avg max drawdown

0.16

Avg Sharpe ratio

On average, backtests of this strategy beat a buy-and-hold baseline by 647% over the same window.

Performance by asset class

Market	Backtests	Avg profit factor	Avg net profit	Avg max drawdown	Avg Sharpe
Crypto	68	1.2	+809%	70%	0.17
Stocks	727	1.5	+741%	49%	0.16

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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