Dual-Momentum-Trading-Bot

Publisher-claimed Trend strategy on Multi by johnhou13579. BotFinder score 37 out of 100.

A trading bot utilized on the TD Ameritrade platform written in python and utilizing tda-api API.

Source: github

Explorer/Multi/Dual-Momentum-Trading-Bot
37
Data index
MultiTrendMedium risk⚠ Publisher Claimed

Dual-Momentum-Trading-Bot

johnhou13579GitHub
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Net return
+93.96%
Max drawdown
—
Sharpe
—
Profit factor
—
Win rate
—
Track record
6.1y
⚠ Publisher-stated · not independently verified
BotFinder Analysis

BotFinder analysis pending.

About

Dual-Momentum-Trading-Bot

Long Term Momentum Trading on Tech Stocks What is this repository? A trading bot utilized on the TD Ameritrade platform written in python and utilizing tda-api API. Bot originally discovered, tweaked, and backtested on Quantopian. What strategy is used? We utilized Dual Momentum Strategy which focuses on weighted momentum based on the previous 1, 3, and 6 months. Portfolio rebalance happens bi-monthly. Risk lies in having entire portfolio within one stock and huge drawdown. However, since we would have held long term without rebalance, we would have expected similar drawdowns. Why we chose the stocks we used? Since our plan is to hold stocks we find value in long term, we decided to implement a momentum based strategy that would alternate between stocks that we would have held long term regardless. Since this backtest also shows tremendous spikes from Tesla and AMD, future results may not show as promising returns. Regardless, we find value in these companies and would have held them long term. Start date 2014-01-03 End date 2020-09-11 Total months 80 Backtest Annual return 93.96% Cu

PythonOpen-sourcepythonquantopiantda-apitdameritradetdameritrade-apitrading-algorithmstrading-bottrading-strategies
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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.

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Alerts on changes: coming soon

Prop-firm compatibility

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Source
johnhou13579
Since 2014 · 1 bots

Open-source maintainer on GitHub.

Trust 0Profile
Score & reliability37/100
Perf data7/35
Community0/25
Evidence20/20
Recency10/10
Verification0/10

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

Source facts
Stars62
Forks20
Net profit93.96%
Open issues0
LanguagePython
License—
Last update2020-10-05
Created2020-09-15
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