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    [CS 297 Proposal]

    [Paper Review]

    [MBS_BSF_linear regression Slides-PDF]

    [LSTM network explanation and walkthrough]

    [Linear Regression-PDF]

    [Deliverable 1]

    [Deliverable 2]

    [Deliverable 3]

    [Deliverable 4]

    [CS 297 Project Report-PDF]

    [CS 298 Proposal]

    [CS 298 Project Report-PDF]

    [CS 298 Slides-PDF]

CS297 Proposal

Housing Market Crash Prediction Using Machine Learning and Historical Data

Parnika De (

Advisor: Dr. Chris Pollett


The housing market bubble burst caused the financial crisis of 2008. One of the main reasons for that was Collateral Debt Obligations (CDO). For the 2008 housing crisis, sub-prime mortgages played a huge role. Loans were given to people at high-interest rates who did not have collaterals (sub-prime loans). Then came the rating agencies who gave “AAA” rating to CDOs, even to the subprime CDO’s. We all know what a disaster it created. But that was 2008, a decade passed and banks learned from their mistakes and the US did not have a financial crisis since the US economy is stronger than ever. But is it going to be all good forever? The answer is we don’t know. Therefore in this project, I aim to analyze US housing market data and other financial data to predict whether everything is good or are we heading south. To do this project, I would use a forecasting model to analyze the data and build an ML model that would help me predict “The future of the housing market”.


Week 1:08/27/19 - 09/03/19Ideation and Proposal
Week 2:09/03/19 - 09/10/19Restructured the proposal, read about MBS, Black-scholes Formula, Forcasting techniques
Week 3:09/10/19 - 09/17/19Work on deliverable 1 and read a research paper
Week 4:09/17/19 - 09/24/19Deliverable 1: Due
Week 5:09/24/19 - 10/01/19Read a research paper
Week 6:10/01/19 - 10/08/19Work on deliverable 2
Week 7:10/08/19 - 10/15/19Deliverable 2: Due
Week 8:10/15/19 - 10/22/19Learn Tensorflow
Week 9:10/22/19 - 10/29/19Work on deliverable 3
Week 10:10/29/19 - 11/05/19Deliverable 3: Due
Week 11:11/05/19 - 11/12/19Apply Linear Regression on the Housing dataset
Week 12:11/12/19 - 11/19/19Work on deliverable 4
Week 13:11/19/19 - 11/26/19Deliverable 4: Due
Week 14:11/26/19 - 12/03/19Work on the report
Week 15:12/03/19 - 12/10/19Work on the report
Week 16:12/10/19 - 12/17/19Deliverable 5: Due


The full project will be done when CS298 is completed. The following will be done by the end of CS297:

1. Data preparation(Cleaning of Data set)

2. Code HMM on a small dataset

3. Learn about Long short term Memory and code it

4. Apply Linear Regression on the Housing dataset

5. CS 297 report


[2017] The Great Recession: A Macroeconomic Earthquake. Lawrence J. Christiano. Federal Reserve Bank of Minneapolis. 2017.

[2011] The Role of ABS, CDS and CDOs in the Credit Crisis and the Economy. Robert A. Jarrow. 2011

[2016] The 2007–2009 Financial Crisis: An Erosion of Ethics: A Case Study. Edward J. Schoen. Journal of Business Ethics. 2016

[2009] Financial crises and bank failures: A review of prediction methods. Yuliya Demyanyk, Iftekhar Hasan . Elsevier Omega. 2009.