learning-market-maker

Unverified ML strategy on Multi by phelps-sg. BotFinder score 18 out of 100.

Python implementation of the basic model described in Chan, Nicholas Tung, and Christian Shelton. "An electronic market-maker."

Source: github

Explorer/Multi/learning-market-maker
18
Data index
MultiMLMedium risk⚠ Unverified

learning-market-maker

phelps-sgGitHub
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Max drawdown
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Sharpe
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Profit factor
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Win rate
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Track record
7.0y
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About

learning-market-maker

Electronic market-making using reinforcement-learning This repo contains a Python implementation of the basic model described in Chan, Nicholas Tung, and Christian Shelton. "An electronic market-maker." (2001). Example usage: ~~~python from chanandshelton import import matplotlib.pyplot as plt learner, results = learningexperiment() print("Greedy policy is ", learner.greedypolicy()) print("Q table: ", learner.asDataFrame()) pf, pmm, imb, r, a = results plt.figure() plt.plot(pf) plt.plot(pmm) plt.show() ~~~

PythonOpen-sourcealgorithmic-tradingcomputational-financefinancereinforcement-learning
Track record

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

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Verification ledger

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

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

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Source
phelps-sg
Since 2019 · 2 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
Stars17
Forks3
Open issues0
LanguagePython
License—
Last update2023-08-27
Created2019-10-24
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