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Illegal insider trading of stocks is based on releasing non-public information (e.g., new product launch, quarterly financial report, acquisition or merger plan) before the information is made public. Detecting illegal insider trading is difficult due to the complex, nonlinear, and non-stationary nature of the stock market. In this work, we present an approach that detects and predicts illegal insider trading proactively from large heterogeneous sources of structured and unstructured data using a deep-learning based approach combined with discrete signal processing on the time series data. In addition, we use a tree-based approach that visualizes events and actions to aid analysts in their understanding of large amounts of unstructured data. Using existing data, we have discovered that our approach has a good success rate in detecting illegal insider trading patterns. My research paper (IEEE Big Data 2018) on this can be found here: https://arxiv.org/pdf/1807.00939.pdf

  • Updated Jan 8, 2019
  • Python

This project will walk you through the importance of Fast Fourier Transform (FFT) which is one of the major computation techniques in the world of Digital Signal Processing (DSP). It also explains how 'Filter Design Toolbox' can be made use of in MATLAB to design desired filters on the go.

  • Updated May 16, 2020
  • MATLAB

An Expert system is a software capable of making complex decisions which only an expert it a particular field can make. Those decisions are accurate and prefect by considering specific set of rules. This project also aims to do the same thing. This is an Expert system capable of assisting user in order to invest or buy from the stock market of a particular asset present. The whole project is prepared in MATLAB.

  • Updated Apr 18, 2018
  • MATLAB

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