Algorithmic-Trading-In-Python

Unverified Other strategy on Multi by cengizozel. BotFinder score 18 out of 100.

Collection of 3 quantitative finance projects in Python that uses algorithmic trading.

Source: github

Explorer/Multi/Algorithmic-Trading-In-Python
18
Data index
MultiMedium risk⚠ Unverified

Algorithmic-Trading-In-Python

cengizozelGitHub
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Profit factor
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Win rate
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Track record
5.8y
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About

Algorithmic-Trading-In-Python

Algorithmic Trading In Python Collection of 3 quantitative finance projects in Python that uses algorithmic trading. I completed these projects by watching a full course by the software developer Nick McCullum on YouTube. The projects consist of instructions given on a Jupyter notebook from this repo and I did the coding part by following the course. Projects 1. Building An Equal-Weight SP 500 Index Fund 2. Building A Quantitative Momentum Investing Strategy 3. Building A Quantitative Value Investing Strategy All three projects use the sandbox version of IEX Cloud API. The free sandbox version is for testing purposes and gives random values. Building An Equal-Weight S&P 500 Index Fund View project The goal of this project is to build an equal-weight version of the S&P 500 index fund by taking the value of a portfolio as input and tell how many shares of each S&P 500 stock should be purchased. The script exports an excel file with the equal-weight version of the index fund as a result. Building A Quantitative Momentum Investing Strategy View project The goal of this project is to buil

Jupyter NotebookOpen-sourcefinancejupyterpythonsp500trading-algorithmstrading-strategy
Track record

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

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Source
cengizozel
Since 2010 · 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
Stars19
Forks15
Open issues0
LanguageJupyter Notebook
License—
Last update2021-01-20
Created2021-01-17
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