Writing a 2 pages report related to finance

· Datasets are weekly, monthly and some annually – we will need to figure out how we can get them on same level. I think we can take weekly, monthly, quarterly data can move it to yearly. Going other way around is impossible.

· Some of datasets below are also available down to city and county level as different files on same website. Just need to search.

· I focused on only using datasets that show TREND BEFORE the rescissions to signs indications. And on Fred database you can see pretty good visualization to narrow down the trends.

· Credit score – due to hacks and people stealing credit of others, and fraudulent issues, I do not think we can reply on the scores for a forecast model.

· Per some recommendations from another professor who had groups in his class do a similar project by using python with machine learning, I think we should stick with Fred data. Z and myself found other sources, but issues has been getting data to same level from different sources can take months, while this site is more simple and you can look at one data with different units. Its already doing analytics for us.

DATASETS:

St. Louis Fed Financial Stress Index© (STLFSI) - measures the degree of financial stress in the markets and is constructed from 18 weekly data series: seven interest rate series, six yield spreads and five other indicators.

https://fred.stlouisfed.org/series/STLFSI

10-Year Treasury Constant Maturity Rate (DGS10) –INTEREST RATES

https://fred.stlouisfed.org/series/DGS10

- going up before the recession, but dropped several months before the recession.

-dropping during the recession

Mortgage Debt Outstanding, All holders (MDOAH)

https://fred.stlouisfed.org/series/MDOAH

Rest of Data Sets:

Real Median Household Income in the United States (MEHOINUSA672N) –

https://fred.stlouisfed.org/series/MEHOINUSA672N

-dropping before the recession

-dropping during the recession

Employed full time: Median usual weekly real earnings: Wage and salary workers: 16 years and over – weekly-hourly

https://fred.stlouisfed.org/series/LES1252881600Q#0

-dropping before the recession

-going up during the recession

Real Gross Domestic Product (GDPC1) –

https://fred.stlouisfed.org/series/GDPC1

- going up before the recession

-dropping during the recession

Bank Prime Loan Rate

https://fred.stlouisfed.org/series/MPRIME

-spikes right before the recessions

Net Percentage of Domestic Banks Reporting Stronger Demand for Subprime Mortgage Loans

https://fred.stlouisfed.org/series/DRSDSP

-demand is going up again

https://fred.stlouisfed.org/search?nasw=0&st=credit%20score%20manipulation&t=usa&ob=sr&od=desc

THIS RIGHT UP HERE IS THE HOLY GRAIL FUCKER!

U.S. National Home Price Index

https://fred.stlouisfed.org/series/CSUSHPINSA

9/19/17: DOW JONES AND S&P 500 HISTORICAL DATA

http://quotes.wsj.com/index/DJIA/historical-prices

The link above is for historical data of dow jones. You can set the range as far back as you want.

http://quotes.wsj.com/index/SPX/historical-prices

The link above is for historical data of s&p 500. You can set the range as far back as you want.

http://community.seattletimes.nwsource.com/archive/?date=19910310&slug=1270790

The link above goes into the details of how war affects the real estate market. This particular article focuses on the effects on cold markets after operation desert storm. Perhaps, recovery and rebuilding times after conflicts provide a need for more money to be put into the global economy thus pushing forth an aggressive real estate market.

https://soldnest.com/blog/how-natural-disasters-impact-real-estate

QUOTE: “How natural disasters impact real estate prices is certainly a local phenomenon rather than a nationwide trend. But the effects are very noticeable in that particular area, if only for a short time.”