Primary Chart

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Project Scope

Pattern Recognition for Financial Time Series

The objective of this project is to explore how time-frequency signal processing and deep learning can be combined to predict stock prices. Financial variables are treated as non-stationary signals, transformed via Short-Time Fourier Transform (STFT), and fed into a Convolutional Neural Network (CNN) for regression modeling.

Multivariate Signal Vector

X(t) =[p(t),r(t),g(t),s(t),d(t)]
p: Stock Pricer: Revenueg: Profits: Sensexd: USD-INR

System Pipeline

Time Series Data
STFT
Spectrogram
CNN Model
Prediction