MarketML

Unverified ML strategy on Forex by tarasivashchuk. BotFinder score 18 out of 100.

Data science project with the goal of deploying a profitable market trading algorithm on the real stock and/or FOREX market with real money to generate passive income.

Source: github

Explorer/Forex/MarketML
18
Data index
ForexMLMedium risk⚠ Unverified

MarketML

tarasivashchukGitHub
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Free
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Net return
—
Max drawdown
—
Sharpe
—
Profit factor
—
Win rate
—
Track record
6.3y
BotFinder Analysis

BotFinder analysis pending.

About

MarketML

MarketML Data science project with the goal of deploying a profitable market trading algorithm on the real stock and/or FOREX market with real money to generate passive income. Plan Phase 1 (current) Development will start with getting a baseline solution working from start to finish, based on a fairly simple trading algorithm such as moving average crossover. This solution should allow for easily backtesting a provided trading strategy and returning back profitability and other performance metrics. Phase 2 The next phase will consist of applying more advanced techniques, in particular transformers, for the trading algorithm, potentially with a reinforcement learning component as well and testing its performance against the baseline. Phase 3 Once a trading algorithm which is consistently profitable is found, I will deploy the algorithm on a live market with real funds and track the returns, with the ultimate goal being of achieving returns that will cover a nice little passive side income. Structure TODO Author Taras Ivashchuk taras@tarasivashchuk.com License The MIT License (MIT) Co

Jupyter NotebookOpen-sourcealgorithmic-tradingdeep-learningmachine-learningpythonreinforcement-learningtimeseriestransformer
Track record

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

Risk

Drawdown profile

Data unavailable — contact the owner.

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
tarasivashchuk
Since 2018 · 1 bots

Open-source maintainer on GitHub.

Trust 0Profile
Score & reliability18/100
Perf data0/35
Community0/25
Evidence8/20
Recency10/10
Verification0/10

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

Source facts
Stars25
Forks11
Open issues2
LanguageJupyter Notebook
License—
Last update2021-01-14
Created2020-06-21
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