Behind the Numbers: The Science of LSTM Forex Forecasting in India

Ready to dive into the world of data-driven forex forecasting for the Indian rupee?

Join me as I dive into analysis. I'm Pavan Kalyan, and I'm excited to welcome you to my blog!

Introduction about the topic Forex:

Forex, short for foreign exchange, involves trading one country's currency for another at prevailing exchange rates.

Objective: 

My objective is to develop a smart tool using LSTM technology to accurately forecast Indian forex rates for Euros. By analyzing historical data and employing advanced algorithms, my aim is to offer traders and investors valuable predictions and insights, empowering them to make informed decisions in the ever-changing forex market.

Data collection and Data Preprocessing: I obtained the data from Kaggle and ensured it was clean for analysis. After checking for duplicates, outliers, and missing values, I decided to retain outliers as forex rates naturally fluctuate.

Methodology: I constructed an LSTM model using TensorFlow, known for its efficacy in time series analysis. LSTM processes data sequentially through three gates, capturing temporal patterns. Specifying a sequence length of 10 allows the model to consider prior data points, enhancing its understanding of forex trends.

Analysis: forex rates among countries.

Here's a line plot illustrating the trends of exchange rates for Euro across different countries. In India, the exchange rate is around 90 Rs, while for Australia and the United States, it falls between 1.0. Sri Lanka stands out with an exchange rate of nearly 300. This indicates that the Sri Lankan currency is relatively high compared to the others when exchanging for 1 Euro.

Analysis: Exchanges happened on the date

The plot above displays the exchange rates that occurred over time. My dataset includes exchange rates for Indian Rupees, Australian Dollar, US Dollar, and Sri Lankan Rupee. We observe that exchanges have taken place at various rates from the mid-2005s to 2024.

Analysis: Exchanges rates fluctuations over time.

The plot showcases stable currency rates for Australia and the United States, whereas India and Sri Lanka experience more volatility. Notably, Sri Lanka exhibits significant fluctuations, especially from 2022 onward, possibly due to economic or political factors.

Analysis: Volatility of exchange rates

Exchange rates fluctuate annually, with Sri Lanka experiencing substantial changes in 2022. India saw relatively fluctuate rates from 2015 to 2024, with a sudden increase thereafter. Australia also witnessed fluctuations, influenced by economic and political factors.

Forecasting of the forex rate for INDIA:

Predicted forex rates are model estimates of future rates, compared to actual observed values in the market.

conclusion:

Advanced technologies like LSTM models are enhancing forex rate forecasting in India. By analyzing historical data and employing smart algorithms, we're improving our ability to predict future rates. Despite market fluctuations, our study offers promising insights for informed decision-making in forex trading.

Join me on this journey as I explore more exciting projects together and unlock new insights in the world of data science.