BTC_USDT_Trading_Model

Publisher-claimed ML strategy on Crypto by A-SOLO. BotFinder score 44 out of 100.

Algorithmic Trading Model Development for BTC/USDT Crypto Market. Crafting models that outperform benchmarks, balancing returns and risk management in the dynamic BTC/USDT market.

Source: github

Explorer/Crypto/BTC_USDT_Trading_Model
44
Data index
CryptoMLMedium risk⚠ Publisher Claimed

BTC_USDT_Trading_Model

A-SOLOGitHub
From
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Net return
+238%
Max drawdown
-6.28%
Sharpe
—
Profit factor
—
Win rate
—
Track record
2.6y
⚠ Publisher-stated · not independently verified
BotFinder Analysis

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About

BTC_USDT_Trading_Model

BTCUSDTTradingModel Algorithmic Trading Model Development for BTC/USDT Crypto Market. Crafting models that outperform benchmarks, balancing returns and risk management in the dynamic BTC/USDT market and generating 238% return along with the max drawdown of 6.28%. Dataset: The original data used in this project is historical BTC/USDT 4hrs data (January 1, 2018 to January 31, 2022). Preprocessing: - Feature Selection: The ‘opening price’ feature from the BTC/USDT dataset is used in training and testing the machine learning model. - Sequence ceartion: Considering the last 10 observations and forecasting the single fututre observation for each sequence. - Train-test split: Training Data :Jan 2018-Apr2021, Testing Data : Apr2021-Jan2022 Model Training: Random Forest Regressor Strategy 1 : Gap Trading Strategy Strategy 2 : Gap Trading strategy with Moving Average (FY 2023) Indicators: 1. Position: position = 1: Represents a long trade, indicating that the algorithm has bought an asset or security. position = 0: Denotes a neutral position, suggesting that there is no ongoing trade (neither

Jupyter NotebookApache-2.0Open-sourcealgorithmic-tradingbackbacktesting-trading-strategiesbtccrypto-marketmachine-learning-algorithmspythonrandom-forest-regressor
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Track record

⚠ No verified equity curve — no track-record source connected.

Risk

Drawdown profile

Max drawdown-6.28%
Recovery—
DD events—

No drawdown history is stored — only the maximum drawdown reported by the source.

Evidence

Verification ledger

Live-audited
Broker-verified
Capital-backed
Tamper-proof
Historical evolution

How the score has moved

Recalculated at each data collection. Transparency means showing the bad weeks too.

No score history is stored yet — only the current score is shown.

Reviews

Reviews & comments

No reviews collected from the source yet.

Live monitoring

⚠ No live verification account connected — ask for proof before buying.

Alerts on changes: coming soon

Prop-firm compatibility

Prop-firm compatibility not provided.

Source
A-SOLO
Since 2021 · 1 bots

Open-source maintainer on GitHub.

Trust 0Profile
Score & reliability44/100
Perf data14/35
Community0/25
Evidence20/20
Recency10/10
Verification0/10

Data-completeness & trust index (not a profitability rating)

Source facts
Stars20
Forks14
Max drawdown6.28%
Net profit238.0%
Open issues0
LanguageJupyter Notebook
LicenseApache-2.0
Last update2024-08-29
Created2024-03-01
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