Muhammad Rafay Aleem, Nandita Dwivedi, Kiran
1. Motivation and Background
Portfolio Management is the process of maximizing the return on a portfolio. Portfolio managers make trading decisions on behalf of their clients depending on their appetite for risk. They analyze different assets, their strengths and weaknesses before making a decision about which equities they should hold in a portfolio for balancing the risk and drawing maximum returns. This makes portfolio management a difficult process. We aim to make this process better and simpler by using predictive modeling and deep learning techniques. We generate stable portfolios on predicted stock prices for next quarter.
Related Work
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Is it possible to leverage your current Spark cluster to build Deep Learning models?
Can terabytes of data stored in HDFS, Hive, HBase be analyzed?
Muhammad Rafay Aleem, Nandita Dwivedi, Kiran
Diving into Intel’s BigDL
Apache Spark has rapidly gotten popular over the past couple of years. This comes from its simplicity, speed and support, also referred as 3 S’s of Spark. Many companies leveraged the Hadoop and Spark environments to build powerful data processing pipelines. These pipelines were built to pre-process huge volumes of data on distributed clusters and draw insights from it for business growth. As Deep Learning gained momentum for its…
