Roboadvisor is a stock advisory service that takes inputs from the user in order to determine the user’s preferred diversification strategy and Investment goals
The goal of the project is to capture the user’s inputs through StreamLit to determine their goals and risk appetite, and provide recommendation on the stocks/cryptocurrencies that they can invest in. We do so by allowing the user to pick and choose between stocks/cryptocurrencies. Then, the machine learning robot will run it's code and use ML models to output a table of data detailing which stocks/cryptocurrencies in the portfolio will make money. Lastly, the buyer will then be asked if they want to buy/not buy the stock/cryptocurrency and orders will be placed. Minimum Viable Product(MVP): The Robotrader is a service that uses multiple Machine Learning models to recommend whether or not to buy a stock based on the following: Historical prices, Macroeconomic factors, and Company fundamentals. To acheive the MVp project objectives, we developed a model that will allow users to select a stock and provide their expectation of the macro economic and company fundamentals. Then, the machine learning robot will run it's code and use ML models to output a recomemndation detailing the closing price of the stock in question.
This project leverages python 3.8.8 with the following packages:
Python Pandas Jupyter Lab Alphavantage API Matplotlib Streamlit
Approach:
We followed the below steps in meeting the project objectives for the MVP
- Data Collection: Build APIs to gather data on specific stocks/cryptos and macro economic indicators. Source: Alpha Vantage Pulled historical data on the following indicators: EPS Stock Price (on top 50 stocks in the S&P 500) Cryptocurrency Price Inflation Consumer Sentiment
- Data Analysis: Analyze the data trends and the correlation between the indicators. Below is an analysis of the correlation between different features that make up the ctock price, and ana anlsysi of the closing price of the stocks.
a. Robotrader will recieve user input through streamllit
b. Robot will determine the price of the stock:
Next steps:
The next steps to further develop the product, to realize the complete project objectives, are provided below:
Further Details: Presentation https://docs.google.com/presentation/d/1rYWpFhiXFshuFSV1FPA2J8I28cMPgwta2fUc7Wr2Jbc/edit#slide=id.g125114ac3ca_0_0
import os
import requests
import json
import pandas as pd
from dotenv import load_dotenv
import alpaca_trade_api as tradeapi
from alpha_vantage.timeseries import TimeSeries
import matplotlib.pyplot as plt
import csv
from pathlib import Path
import numpy as np
import seaborn as sns
%matplotlib inline
We need also to import the relevant alpha vantage libraries :
from alpha_vantage.timeseries import TimeSeries
from alpha_vantage.cryptocurrencies import CryptoCurrencies
We need to import required modules for Classificatgion, Regression, Neural Networks, and Metrics:
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
from sklearn.metrics import precision_score
from sklearn.metrics import recall_score
from sklearn.linear_model import LogisticRegression
from sklearn.svm import LinearSVC
#from sklearn.preprocessing import GetDummies
from sklearn.linear_model import LogisticRegression
from sklearn.ensemble import RandomForestClassifier
from sklearn.discriminant_analysis import QuadraticDiscriminantAnalysis
#Linear Regression Library
from sklearn.linear_model import LinearRegression
from sklearn.metrics import r2_score
from sklearn.ensemble import RandomForestRegressor
from tensorflow.keras.layers import Dense
from tensorflow.keras.models import Sequential
```
Ram Atmakuri ram.atmakuri@outlook.com https://www.linkedin.com/in/ramatmakuri99
Amanda Hum amanda.m.hum@gmail.com https://www.linkedin.com/in/amandamhum
Enrique Viana j.enrique.viana@gmail.com https://www.linkedin.com/in/enriqueviana
Mohammed Amine Baite aminebaite@gmail.com https://www.linkedin.com/in/amine-baite-3972a71b8/
Alexis Rose Garcia Alexisg324@gmail.com https://www.linkedin.com/in/alexis-rose-garcia
Kyle Huber kyhuber@gmail.com https://www.linkedin.com/in/huberkyle/
license() A. HISTORY OF THE SOFTWARE ==========================
Python was created in the early 1990s by Guido van Rossum at Stichting Mathematisch Centrum (CWI, see http://www.cwi.nl) in the Netherlands as a successor of a language called ABC. Guido remains Python's principal author, although it includes many contributions from others.
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In May 2000, Guido and the Python core development team moved to BeOpen.com to form the BeOpen PythonLabs team. In October of the same year, the PythonLabs team moved to Digital Creations, which became Zope Corporation. In 2001, the Python Software Foundation (PSF, see https://www.python.org/psf/) was formed, a non-profit organization created specifically to own Python-related Intellectual Property. Zope Corporation was a sponsoring member of the PSF.
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0.9.0 thru 1.2 1991-1995 CWI yes 1.3 thru 1.5.2 1.2 1995-1999 CNRI yes 1.6 1.5.2 2000 CNRI no 2.0 1.6 2000 BeOpen.com no 1.6.1 1.6 2001 CNRI yes (2) 2.1 2.0+1.6.1 2001 PSF no 2.0.1 2.0+1.6.1 2001 PSF yes 2.1.1 2.1+2.0.1 2001 PSF yes 2.1.2 2.1.1 2002 PSF yes 2.1.3 2.1.2 2002 PSF yes 2.2 and above 2.1.1 2001-now PSF yes Footnotes:
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Financial Technology Bootcamp UCB-Coding-Bootcamp (2021-2022). Module 1-16. UC Berkeley Fintech Extension. https://courses.bootcampspot.com/
Alpha Vantage (API): Alpha Vantage (2022). www.alphavantage.co