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Project Proposal, Planning, Progress Reports!

https://docs.google.com/document/d/18xloM7lbhG3QRtfxHBbF_kxvIKcRuCrxDVNaTqSCuX0/edit?usp=sharing

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Yesterday, I finally was able to train my neural network with my economic indicators for the first time!

Today during class, I gave some minor touches to the training modules. I will work on coding the actual usage when I go back home!

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Stock price after 6 months
Stock price after 12 months

These are the value my neural network will predict for adjusting my investment portfolio

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Today, I finished answering "Product: ISTE-6A"

Next Steps:
1. Finish building system (May 20th)
2. Film video of explaining my product and turn in assignment (May 22)

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Date: May 12, 2020

I got some feedback about how I should use my research info and show it my final product. Mr. Goff told me that I will have to make meaning out of my research and he agreed that it is a great idea to create a video presentation of how I used my research (which are economic indicators) in my final product (algorithms, my system)

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Date: May 5, 2020

I reached out to Mr. Goff regarding the deadlines I have set during the weekend. Mr. Goff verbally gave me feedback through Google Meets during class time. Other than slight changes I might need to make while I go through the process, my deadlines were good to go and it was actually used as an example for our whole class!

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PLEASE! I have a detailed documentation of my research since I couldn't write everything in Padlet!!

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PLEASE! I have a detailed documentation of my research since I couldn't write everything in Padlet!!

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https://docs.google.com/document/d/1XFlKHu0AmFYs8q2dRa6idIDGQbB6E1Q2bOlaSuD7n8c/edit?usp=sharing

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WHAT is my product? What would I make, build, or create to share my ideas with the world? 

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WHAT is my product? What would I make, build, or create to share my ideas with the world? 

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My product is a command line app that will use artificial intelligence and analyze economic indicators to manage investment portfolios.

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HOW do I now use what I have gained from my research to produce my product?

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HOW do I now use what I have gained from my research to produce my product?

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Throughout my research, I was able to discover four economic indicators: inflation, gold, bond, and volatility. Because these indicators are accessible through databases and historical data, I could use their quantitative data to create an algorithm. This algorithm will analyze those data, and its output will be used as "training datasets" my artificial intelligence will learn.

Ultimately, I am expecting that my AI system can understand the correlations between multiple economic indicators to predict stock prices, which will be used to determine how to adjust values of investment portfolios.

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HOW do I convert these efforts into real-world purpose and impact? (WHO is my audience and what impact will my project have on them?)

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HOW do I convert these efforts into real-world purpose and impact? (WHO is my audience and what impact will my project have on them?)

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My final product is a command line (terminal) app that will manage investment portfolios, which will be uploaded in GitHub, an open source platform where developers share their projects and code. Well, it’s likely that no one will actually bother finding my account, BUT my project itself has a great potential to be used by personal investors because my product provides some financial algorithms and a functioning AI model, which are usually some resources that are kept as a secret by financial and investment companies. I can clearly say that not only my product will fit my use in investing, but systems like mine have a great potential of giving an impact to the investment world!

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So far, I created neural network, created two algorithms to analyze inflation and volatility, documented my research and building process.

Today during class, I added some more information about the "relevance" of my sources, re-organized my research notes.

Next Steps:
1. Finish creating an algorithm for detecting gold and bond trends!
2. Train my neural network for the first time with my economic datasets!

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BASED ON MY RESEARCH
Close Price
Inflation Rate
Gold Trend
Bond Trend
Short Term Volatility (Beta) Score
Long Term Volatility (Beta) Score

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1. Organized my documentation a little bit
2. Got some feedback from Mr. Goff regarding how I should use/show my research in my final product.

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1. Coded a module to read files for uploading data to my neural network

Next Steps:
1. code modules to save model parameters
2. FINISH BUILDING NEURAL NETWORK (DUE MAY 10th)

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https://www.investopedia.com/terms/r/rebalancing.asp
Rebalancing = strategy of investing by adjusting/weighting the assets of a portfolio

Process:

Set allocation percentages for each asset (ex: Google=30%, Gold=20%, S&P 500=25% ... )

Evaluate the actual possession percentage of every asset

Determine the amount of profit/loss of the asset

Determine the amount of shares to buy or sell

Do this process periodically

The periodic time of rebalancing is up to one's favor, but it is most conventionally done once a year.

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Finished reading my last source from Investopedia.

Next Steps: start coding my neural network before May the 10th!

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5 Essentials You Need To Know About Every Stock You Buy.

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5 Essentials You Need To Know About Every Stock You Buy.

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https://www.investopedia.com/financial-edge/0411/5-essential-things-you-need-to-know-about-every-stock-you-buy.aspx
Among the 5 essentials (price-earnings ratio, beta, dividend, the chart, the bottom line), I found beta the most interesting:

Beta = volatility of a stock  ⇒ measures the “risk” of growth

Usually calculating beta can be done by comparing stock indexes with other trustworthy indexes. Other than that, it seems like it is doable to evaluate a stock’s beta value from its chart.

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Completed moving my research into Padlet

Next Steps: complete taking notes from my final source; start building neural network (AI)!

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https://www.investopedia.com/investing/bond-advantages/
Along with gold, bonds seems to share same qualities as gold.

Key Findings:
Bonds are "loans" given to companies.

During a good economy, Steady amount of ups and downs ranges at a certain optimal level of volatility

During a bad economy, a rapid increase in value, extreme volatility occurs in gold prices. (Companies also pursue more loans during an economic struggle --> therefore, bond prices increase)

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https://www.investopedia.com/articles/basics/08/reasons-to-own-gold.asp

Gold indexes seems to be another important economic indicator that I could use in my investment system.

Key Findings:
Gold is a limited resource; therefore, its value is persistent unlike currencies

During a good economy, Steady amount of ups and downs ranges at a certain optimal level of volatility

During a bad economy, a rapid increase in value, extreme volatility occurs in gold prices. (When the economy is bad, investors usually buy gold in order to preserve the devaluing cash)

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Inflation, consumer prices (annual %) = DATABASE SOURCE!

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Inflation, consumer prices (annual %) = DATABASE SOURCE!

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https://data.worldbank.org/indicator/FP.CPI.TOTL.ZG
This database provides a graph/data spreadsheet of inflation rates of all countries around the globe. Using this database, I was able to compare its values with actual stock prices. This helped me to detect the correlations between inflation and the market, which is something I have to consider when building my algorithms.

My Observations:

When stock markets are growing, inflation rate experiences a low-volatile growth

When inflation rates experience rapid volatility, the economy is in risk

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https://www.investopedia.com/terms/i/inflation.as

Inflation: quantitative measurement of market demand and value of national currency

Key Findings: Inflation is a positive indicator of an accelerating economy. Nevertheless, its rate should be regulated through interest rates, monetary policies, and etc in order to prevent unexpected money circulation to cause currency devaluation, debt crisis, and other negative economic impacts.

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Book: Fundamentals of Deep Learning (Nikhil Buduma)

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Book: Fundamentals of Deep Learning (Nikhil Buduma)

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This book lays out the fundamental mathematics behind deep learning by showing and explaining equations in a friendly manner. Since I am challenging myself to build a neural network from scratch, learning these equations are essential when coding its optimization process.

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During our brainstorming process, I actively participated in giving feedback to my peer's inquiry questions.