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Research Paper | Computer Science | India | Volume 10 Issue 1, January 2021
Prediction of the Repo Rate of India Using Artificial Neural Network
Shivani Tinna | Uzma Siddiqui | Dhrumil Shah | Bharti Trivedi
Abstract: REPO signifies Re-Purchase Option, a variable benchmark through which the Reserve Bank of India lends money to other financial institutions – majorly banks. Financial institutions, in the time of liquidity crunch, can borrow from RBI against their pledged securities to overcome such crises. Banks further use repo rate as a measure to decide their lending rate (Rate of Interest on loans). Repo rate is used by monetary authorities to control inflation. It is very important to estimate the repo rate as it is a very important tool for the Reserve Bank of India (RBI) to control inflation trends. Raising or cutting the rates by the RBI will make borrowing more expensive or cheaper for commercial banks. This paper aims to predict the Repo Rate (Interest Rate) of India, where the input data set (predictors) consists of the Crude oil price in Indian Rupee (INR), Dollar price in INR, Gold price in INR and Bank rate of RBI India. As a data set, daily price and index values were used between January, 2015 to September, 2020 period. An Artificial Neural Network (ANN) with Regression to Multilayer Perceptron (MLP) in Keras is used to predict the repo rate.
Keywords: Artificial Neural Network ANN, Keras, Multilayer Perceptron MLP, Repo Rate
Edition: Volume 10 Issue 1, January 2021,
Pages: 1180 - 1186
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