The general terms of use of the FTI app : https://play.google.com/store/apps/details?id=com.hstrading.fti
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Updated
Sep 17, 2017
The general terms of use of the FTI app : https://play.google.com/store/apps/details?id=com.hstrading.fti
Run SMA backtesting in Java
Extracts financial statements from a public company, outputs financial ratios in a nice table.
Two applications to load data (financial analysis or polling) into a Python script to print summary data tables in text files.
Студенческие работы в рамках прохождение курсов в Финансовом университете при Правительстве РФ на направление "Прикладная информатика".
DL projects( Boltzmann-Machines, Recurrent Neural Networks, Self_Organizing_Maps)
Here you will find the metrics that I use in my files.
A full-stack application for people that want to build positive financial habits by tracking their expenses.
Personal finance and retirement planner which utilises Alpaca API and Alternative Free Crypto API. Monte Carlo Simulations are used to project future retirement investment performance.
Python financial analysis of company profit/loss records.
This app helps you determine the fund with the most investment potential based on key risk-management metrics: the daily returns, standard deviations, Sharpe ratios, beta, etc.
Hi, I'm Irbaz a professional qualification student and it is my financial analysis portfolio.
Analysis of fund portfolios and the S&P 500 to identify ideal portfolios for a firm's suite of fund offerings.
This repository presents an algorithm for analyzing financial instruments based on the correlation coefficient. The algorithm allows to calculate the degree of the relationship.
Financial Markets AI that gives real-time financial market analysis, metrics, and can perform hypothesis testing; written on a Asp.NET, EC2, RDS stack.
Using Python to analyse distinct datasets. Through financial analysis, we aim to extract essential metrics like total months, net "Profit/Losses," average changes, and significant profit fluctuations. Through election analysis, we aim to extract total votes, candidates' performance percentages and counts, revealing the winner by popular vote.
This finance project aimed to use data science and machine learning techniques to analyze and predict stock prices.
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