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interactive-corporate-report

Automated machine learning company report in an interactive 'PDF style' from four dimensions: employees, customers, shareholders (owners) and management.

interactive-dashboard-r

Creating interactive dashboards using R markdown

interactive-reporting-in-jupyter-notebook

This sample shows how to create a Jupyter Notebook with the interactive pivot table and pivot charts components. This approach can be used for data analysis and data visualization purposes.

interactive-tutorials

Interactive Tutorials

interbank-lending-systemic-risk

interest-rate-modeling-for-counterparty-risk

Simulating Interest Rate curves for modeling the CVA charge for an Interest Rate Swap

intradaytop10

Intra-Day top 10 share to take trade on the basis of Volatility. Indian Market. Uses python code to and freely available data on NSC india website.

intro

Why another database for macroeconomic data?

intro-regression_rmd

R Markdown files to generate slides for Introduction to Regression webinars.

intro-shiny-rmarkdown

Materials for the "Intro to Shiny and R Markdown" 2-day workshop at rstudio::conf 2018

intro-to-xlwings

intro_to_stats_in_r

Course notes for E3 DTP. Part 2 - Introduction to R Markdown and Basic Statistics.

introduction-to-data-science-in-python

This repository contains Ipython notebooks of assignments and tutorials used in the course introduction to data science in python, part of Applied Data Science using Python Specialization from University of Michigan offered by Coursera

introduction-to-finance---valuation-and-investing

This Specialization builds on the success of the Introduction to Finance course and provides a rigorous introduction to core topics in financial valuation, including time value of money, cash flow analysis, asset pricing, and risk and return. In the final Capstone Project, you’ll apply your skills to research, analyze, and value a real-world enterprise.

introduction-to-highcharter-visualizations

High Charter is a Premium package available for R programming Language Interface. It is a Expensive and Paid package and cannot be used for commercial and government use without payment. What makes it so special is the custom designing to the plots and endless options for different plots. There are more than 100 different types of plot available in High Charter. It basically supports Markdown.

introduction-to-time-series-forecasting-python

Introduction to time series preprocessing and forecasting in Python using AR, MA, ARMA, ARIMA, SARIMA and Prophet model with forecast evaluation.

introneuralnetworks

Introducing neural networks to predict stock prices

inventory-management-system-using-r

This is a Inventory Management System created using R and Shiny package that forecasts next month sales demand and also calculates safety stock and reorder point.

investment-dashboard-builder

Produce clear dashboards showing your investments' performance over time

investment-portfolio-performance-attribution

The purpose of this project is to measure how much of the performance of a diversified quantitative investment portfolio is significantly impacted by random market behavior, if at all. If successful, the results of this analysis will lay the groundwork for a broader analysis pertaining to the separation of alpha and beta across the investment portfolio. If the "luck" portion of the portfolio can be measured dynamically (accounting for lags etc) then a hedging tool could potentially eliminate random market risk without eroding portfolio returns in times of erratic market behavior. The methodology is to obtain historical performance data from 11 different trading models (mean reversion, pairs, market making, momentum, statistical arbitrage, etc) that together form a diversified investment portfolio over a particularly volatile trading period. I will explore the data by analyzing the distribution of performance across symbols and across time periods to reveal the structure of the performance data and how it relates to and is impacted by market behavior. I will then model the data to measure how much of the performance is explained by the market and market volatility, its clustering tendencies and its correlation to the predictor variables. Finally, I will interpret the results and reconcile the results with my original hypothesis to determine if it makes sense to continue work to create a hedging instrument for the portfolio.

investment-research

Investigation into different trading strategies for personal use. Machine learning using TensorFlow and Keras, data sourced from Quandl and Quantopian.

investmentperformance

Show the performance of an investment. Compares contributions to market value

investmentsim

Simulates investment performance using either historical returns or simulated returns.

investor-flow-of-funds-us

Monthly net new cash flow into various mutual fund investment classes (equities, bonds etc).

investor-portfolio

Stock Recommendation and Management System - A Python Web Application developed to analyse, report and consult an investor

investr

Collection of Shiny apps written in R for analyzing investment data.

ioanalysis

Input-Output Analysis

ipp-macro-series-parser

Parser for various series of macroeconomics variables and aggregates

ipython_notebooks

Set of Jupyter (iPython) notebooks (and few pdf-presentations) about things that I am interested on, like Computer Science, Statistics and Machine-Learning, Artificial Intelligence (AI), Financial Engineering, Optimization, Stochastic Modelling, Time-Series forecasting, Science in general... and more.

ipythonscripts

Tutorials about Quantitative Finance in Python and QuantLib: Pricing, xVAs, Hedging, Portfolio Optimisation, Machine Learning and Deep Learning