1 dataset found
  1. Forex News Annotated Dataset for Sentiment Analysis

    • zenodo.org
    • data.niaid.nih.gov
    csv
    Updated Nov 11, 2023
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    Georgios Fatouros; Georgios Fatouros; Kalliopi Kouroumali; Kalliopi Kouroumali (2023). Forex News Annotated Dataset for Sentiment Analysis [Dataset]. http://doi.org/10.5281/zenodo.7976208
    Explore at:
    csvAvailable download formats
    Dataset updated
    Nov 11, 2023
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Georgios Fatouros; Georgios Fatouros; Kalliopi Kouroumali; Kalliopi Kouroumali
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset contains news headlines relevant to key forex pairs: AUDUSD, EURCHF, EURUSD, GBPUSD, and USDJPY. The data was extracted from reputable platforms Forex Live and FXstreet over a period of 86 days, from January to May 2023. The dataset comprises 2,291 unique news headlines. Each headline includes an associated forex pair, timestamp, source, author, URL, and the corresponding article text. Data was collected using web scraping techniques executed via a custom service on a virtual machine. This service periodically retrieves the latest news for a specified forex pair (ticker) from each platform, parsing all available information. The collected data is then processed to extract details such as the article's timestamp, author, and URL. The URL is further used to retrieve the full text of each article. This data acquisition process repeats approximately every 15 minutes.

    To ensure the reliability of the dataset, we manually annotated each headline for sentiment. Instead of solely focusing on the textual content, we ascertained sentiment based on the potential short-term impact of the headline on its corresponding forex pair. This method recognizes the currency market's acute sensitivity to economic news, which significantly influences many trading strategies. As such, this dataset could serve as an invaluable resource for fine-tuning sentiment analysis models in the financial realm.

    We used three categories for annotation: 'positive', 'negative', and 'neutral', which correspond to bullish, bearish, and hold sentiments, respectively, for the forex pair linked to each headline. The following Table provides examples of annotated headlines along with brief explanations of the assigned sentiment.

    Examples of Annotated Headlines
    
    
        Forex Pair
        Headline
        Sentiment
        Explanation
    
    
    
    
        GBPUSD 
        Diminishing bets for a move to 12400 
        Neutral
        Lack of strong sentiment in either direction
    
    
        GBPUSD 
        No reasons to dislike Cable in the very near term as long as the Dollar momentum remains soft 
        Positive
        Positive sentiment towards GBPUSD (Cable) in the near term
    
    
        GBPUSD 
        When are the UK jobs and how could they affect GBPUSD 
        Neutral
        Poses a question and does not express a clear sentiment
    
    
        JPYUSD
        Appropriate to continue monetary easing to achieve 2% inflation target with wage growth 
        Positive
        Monetary easing from Bank of Japan (BoJ) could lead to a weaker JPY in the short term due to increased money supply
    
    
        USDJPY
        Dollar rebounds despite US data. Yen gains amid lower yields 
        Neutral
        Since both the USD and JPY are gaining, the effects on the USDJPY forex pair might offset each other
    
    
        USDJPY
        USDJPY to reach 124 by Q4 as the likelihood of a BoJ policy shift should accelerate Yen gains 
        Negative
        USDJPY is expected to reach a lower value, with the USD losing value against the JPY
    
    
        AUDUSD
    
        <p>RBA Governor Lowe’s Testimony High inflation is damaging and corrosive </p>
    
        Positive
        Reserve Bank of Australia (RBA) expresses concerns about inflation. Typically, central banks combat high inflation with higher interest rates, which could strengthen AUD.
    

    Moreover, the dataset includes two columns with the predicted sentiment class and score as predicted by the FinBERT model. Specifically, the FinBERT model outputs a set of probabilities for each sentiment class (positive, negative, and neutral), representing the model's confidence in associating the input headline with each sentiment category. These probabilities are used to determine the predicted class and a sentiment score for each headline. The sentiment score is computed by subtracting the negative class probability from the positive one.

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Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Georgios Fatouros; Georgios Fatouros; Kalliopi Kouroumali; Kalliopi Kouroumali (2023). Forex News Annotated Dataset for Sentiment Analysis [Dataset]. http://doi.org/10.5281/zenodo.7976208
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Forex News Annotated Dataset for Sentiment Analysis

Explore at:
csvAvailable download formats
Dataset updated
Nov 11, 2023
Dataset provided by
Zenodohttp://zenodo.org/
Authors
Georgios Fatouros; Georgios Fatouros; Kalliopi Kouroumali; Kalliopi Kouroumali
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

This dataset contains news headlines relevant to key forex pairs: AUDUSD, EURCHF, EURUSD, GBPUSD, and USDJPY. The data was extracted from reputable platforms Forex Live and FXstreet over a period of 86 days, from January to May 2023. The dataset comprises 2,291 unique news headlines. Each headline includes an associated forex pair, timestamp, source, author, URL, and the corresponding article text. Data was collected using web scraping techniques executed via a custom service on a virtual machine. This service periodically retrieves the latest news for a specified forex pair (ticker) from each platform, parsing all available information. The collected data is then processed to extract details such as the article's timestamp, author, and URL. The URL is further used to retrieve the full text of each article. This data acquisition process repeats approximately every 15 minutes.

To ensure the reliability of the dataset, we manually annotated each headline for sentiment. Instead of solely focusing on the textual content, we ascertained sentiment based on the potential short-term impact of the headline on its corresponding forex pair. This method recognizes the currency market's acute sensitivity to economic news, which significantly influences many trading strategies. As such, this dataset could serve as an invaluable resource for fine-tuning sentiment analysis models in the financial realm.

We used three categories for annotation: 'positive', 'negative', and 'neutral', which correspond to bullish, bearish, and hold sentiments, respectively, for the forex pair linked to each headline. The following Table provides examples of annotated headlines along with brief explanations of the assigned sentiment.

Examples of Annotated Headlines


    Forex Pair
    Headline
    Sentiment
    Explanation




    GBPUSD 
    Diminishing bets for a move to 12400 
    Neutral
    Lack of strong sentiment in either direction


    GBPUSD 
    No reasons to dislike Cable in the very near term as long as the Dollar momentum remains soft 
    Positive
    Positive sentiment towards GBPUSD (Cable) in the near term


    GBPUSD 
    When are the UK jobs and how could they affect GBPUSD 
    Neutral
    Poses a question and does not express a clear sentiment


    JPYUSD
    Appropriate to continue monetary easing to achieve 2% inflation target with wage growth 
    Positive
    Monetary easing from Bank of Japan (BoJ) could lead to a weaker JPY in the short term due to increased money supply


    USDJPY
    Dollar rebounds despite US data. Yen gains amid lower yields 
    Neutral
    Since both the USD and JPY are gaining, the effects on the USDJPY forex pair might offset each other


    USDJPY
    USDJPY to reach 124 by Q4 as the likelihood of a BoJ policy shift should accelerate Yen gains 
    Negative
    USDJPY is expected to reach a lower value, with the USD losing value against the JPY


    AUDUSD

    <p>RBA Governor Lowe’s Testimony High inflation is damaging and corrosive </p>

    Positive
    Reserve Bank of Australia (RBA) expresses concerns about inflation. Typically, central banks combat high inflation with higher interest rates, which could strengthen AUD.

Moreover, the dataset includes two columns with the predicted sentiment class and score as predicted by the FinBERT model. Specifically, the FinBERT model outputs a set of probabilities for each sentiment class (positive, negative, and neutral), representing the model's confidence in associating the input headline with each sentiment category. These probabilities are used to determine the predicted class and a sentiment score for each headline. The sentiment score is computed by subtracting the negative class probability from the positive one.

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