Econ-Dashboard

A centralized dashboard for screening and downloading Stock/ETF/FX/Economic Data, as well as viewing Forex, Metal, Energy, and Crypto Calendars. Apart from being a one-stop data provider, Econ-Dashboard is also equipped with sentiment classifier trained on financial/economic sentiment. Time-series forecasting is armed with two LSTM models distinguished for different market capitalization constraints.

The sentiment classification model is available at my huggingface repository

Model Implementation

The model is equipped with a pre-trained embedding layer(Universal-Sentence-Encoder), therefore, the model deployment requires a customized kerasmodel class.

# Define the custom layer
class USEEncoderLayer(tf.keras.layers.Layer):
    def __init__(self, **kwargs):
        super(USEEncoderLayer, self).__init__(**kwargs)
        self.use_layer = hub.KerasLayer("https://tfhub.dev/google/universal-sentence-encoder/4",
                                        input_shape=[],  # check the important notes
                                        dtype=tf.string,
                                        trainable=False,
                                        name="USE_encoder")
    def call(self, inputs, **kwargs):
        return self.use_layer(inputs)
# Register the custom layer
custom_objects = {"USEEncoderLayer": USEEncoderLayer, "KerasLayer": hub.KerasLayer}
# Load the model with custom layer
with tf.keras.utils.custom_object_scope(custom_objects):
    best_use_model = tf.keras.models.load_model(r"WRITE_MODELS_PATH")

Available Features

Stock Screener

• Stock screener is equipped with yfinance API. You can select time frame and data interval, and download the data
• If you're not sure about which ticker/symbol format, head over to yahoo finance to check the ticker/symbol

Data Provider

• Data Provider is powered with various economic and financial data, including economic calendar, FX , Stock , Earnings, Commodities, Bonds, Crypto market data.

Sentiment Analysis

Sentiment Classification model is trained on Phrasebank's agreeall Financial sentiment dataset.

Time-Series Forecasting

Forecasting model is a fine-tuned LSTM model that is trained on 7-days look-back period to forecast 1-day forward window value. The model inputs are; last available Volume and 7 consecutive daily close data. You have option to either upload your own data, or write the required data inputs on your own. The time-series feature is armed with two models that are specifically trained for both Large and Small Cap Stocks. You May Select The Model For Your Stock