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SelmaNajih001ย 
posted an update 3 months ago
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How Financial News Can Be Used to Train Good Financial Models ๐Ÿ“ฐ
Numbers tell you what happened, but news tells you why.
Iโ€™ve written an article explaining how news can be used to train AI models for sentiment analysis and better forecasting. Hope you find it interesting!

Read it here: https://huggingface.co/blog/SelmaNajih001/llms-applied-to-finance

I would love to read your opinions! Iโ€™m open to suggestions on how to improve the methodology and the training
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SelmaNajih001ย 
posted an update 4 months ago
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Which is the best model to use as a signal for investment?
Here who is gaining the most:
SelmaNajih001/InvestmentStrategyBasedOnSentiment

The Space uses titles from this dataset:
๐Ÿ“Š SelmaNajih001/Cnbc_MultiCompany

Given a news title, it calculates a sentiment score : if the score crosses a certain threshold, the strategy decides to buy or sell.
Each trade lasts one day, and the strategy then computes the daily return.
For Tesla the best model seems to be the regression ๐Ÿ‘€
Just a quick note: the model uses the closing price as the buy price, meaning it already reflects the impact of the news.
SelmaNajih001ย 
posted an update 4 months ago
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Which is the best model to use as a signal for investment? ๐Ÿค”
Iโ€™ve created a Space where you can compare three models:
-Two available on my profile
- ProsusAI/finbert
You can try it here:
๐Ÿ‘‰ SelmaNajih001/InvestmentStrategyBasedOnSentiment
The Space uses titles from this dataset:
๐Ÿ“Š SelmaNajih001/Cnbc_MultiCompany

Given a news title, it calculates a sentiment score : if the score crosses a certain threshold, the strategy decides to buy or sell.
Each trade lasts one day, and the strategy then computes the daily return.

Just a quick note: the model uses the closing price as the buy price, meaning it already reflects the impact of the news.
If I had chosen the opening price, the results would have been less biased but less realistic given the data available.
SelmaNajih001ย 
posted an update 4 months ago
SelmaNajih001ย 
posted an update 4 months ago
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2300
Finally, I uploaded the model I developed for my masterโ€™s thesis! Given a financial event, it provides explained predictions based on a dataset of past news and central bank speeches.
Try it out here:
SelmaNajih001/StockPredictionExplanation
(Just restart the space and wait a minute)

The dataset used for RAG can be found here:
SelmaNajih001/FinancialNewsAndCentralBanksSpeeches-Summary-Rag
While the dataset used for the training is:
SelmaNajih001/FinancialClassification

I also wrote an article to explain how I've done the training. You can find it here https://huggingface.co/blog/SelmaNajih001/explainable-financial-predictions

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SelmaNajih001ย 
posted an update 4 months ago
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Introducing a Hugging Face Tutorial on Regression

While Hugging Face offers extensive tutorials on classification and NLP tasks, there is very little guidance on performing regression tasks with Transformers.
In my latest article, I provide a step-by-step guide to running regression using Hugging Face, applying it to financial news data to predict stock returns.
In this tutorial, you will learn how to:
-Prepare and preprocess textual and numerical data for regression
-Configure a Transformer model for regression tasks
-Apply the model to real-world financial datasets with fully reproducible code

Read the full article here: https://huggingface.co/blog/SelmaNajih001/how-to-run-a-regression-using-hugging-face
The dataset used: SelmaNajih001/FinancialClassification
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