Milestone Check 2 Presentation

Project Updates Presentation is a link to a powerpoint presentation showing what is completed and what the future plans are.

Professor Kaster suggests that I make the project more “embedded” as this is an embedded systems class. He gave the idea of creating something like a pocket forecaster for things such as gas or gold.

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Milestone Check 2

This week I have been learning and trying to implement some popular forecasting models such as the ARMA model. I have implemented the exponential MA model, that puts more weight on recent data compared to older data. I would like to make my own changes to this model to include other factors such as volume in deciding the weights.

The problem with the AR model is calculating the coefficients. I will ask Ali if there is a more efficient way in calculating these coefficients. If there is not, I will stick to using Perl’s matrix feature in calculating them.

I am keeping pace with the milestones I have created for myself. For the next two weeks I will be adding more parameters and tweaking this ARMA model my way to create a better fit for the data.

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Milestone Check 1

Written: 4/19/2011
Most of the milestones that were supposed to be completed by this time have been. As of now, the program is able to retrieve historical stock prices from the web and store them in a data structure. The program has the feature to calculate candlesticks and moving averages from this data, however, I did not calculate other technicals, as I wanted to spend more time finding long term trends. I have also retrieved the earnings of all companies since 2003, and stored them in an easy to read text file so that retrieving the data again will be more very quick. I will be consulting with Ali to figure out whether other information such as financials will be necessary.

After speaking to Ali on Wednesday, my track and milestones changed a little, but the overall goal remains the same. Firstly, I will use the historical stock prices and the moving averages to create a model to predict the stock prices for the next day, or the next couple days. After I have implemented this basic model, I will incorporate other pieces of data that I have gathered to create a more accurate model. As I do that, I will also evaluate whether using that data has a significant impact on the accuracy of the model with little impact on computation costs.

Here are the future corrected milestones for the next 6 weeks:

4/24/11 – Create a financial model to predict the next day using starting from something simple such as moving averages. (Follow the model shown in the book Ali gave)

5/8/11 – Make the model more accurate by involving other variables such as related stock prices, international markets, or other macroeconomic data

5/8/11 – Implement basic AI capabilities – keep track of probabilities as mentioned above in a separate file so the program gets smarter as more data is read
6/5/11 – Depending on how behind… build an alert system where an alert is txted/emailed when a stock is ideal to buy/short (from a list of stocks given by user).

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Introduction

The major goal of this project is to create a program that will forcast data, specifically the stock market. This will be done by analyzing how relevant data affects human behavior and finding a way to quantify it.

Milestones for the next 10 weeks:
4/3/11 – figure out how to retrieve data from the web so that it can be analyzed
4/10/11 – Use the data to calculate moving averages, candle sticks, and any other technicals that can be calculated with historical prices
4/17/11 – retrieve/parse/store financials and earnings data in some structure
4/24/11 – Use this information to forecast with Ali’s help on using the correct algorithms
5/8/11 – Implement basic AI capabilities – keep track of probabilities as mentioned above in a separate file so the program gets smarter as more data is read
6/5/11 – Depending on how behind… retrieve and analyze news to make predictions more accurate. And/Or build an alert system where an alert is txted/emailed when a stock is ideal to buy/short (from a list of stocks given by user).

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