kanwardusaj Goto Github PK

followers: 3.0 following: 1.0 repos: 17.0 gists: 0.0

Name: KD

Type: User

Bio: A software analyst with curiosity about Financial Engineering.

Location: Mumbai,India

Blog: https://kdsoftwarequality.wordpress.com/

KD's Projects

data_feeds_wqu

We will explore the use of C# and Excel to keep track of the pricing of various properties. We shall look to implement various useful statistical calculations which will allow you to gain further insight into the overall trends of the property market.

financial-data-structures

Create structured financial data in the form of time, tick, volume, and dollar bars from unstructured tick data. From Marcos Lopez de Prado's Advances in Financial Machine Learning textbook.

learn-python

📚 Playground and cheatsheet for learning Python. Collection of Python scripts that are split by topics and contain code examples with explanations.

learn-python3

Jupyter notebooks for teaching/learning Python 3

learngithub

A sample GitHub repo to help you learn and understand local and remote repo

machine_learning_and_deep_learning

machine_learning_gw2

This repo decide which features are helpful in predicting the target variable for time series data –serial correlation, momentum, technical analysis indicators (such as RSI), and signals from trend-following strategies (such as the moving average crossover)

modelling_strategy_dev

A small project on Financial Data Modeling and Strategy Development

project-based-learning

Curated list of project-based tutorials

python

All Algorithms implemented in Python

python-roadmap

Python Roadmap. Learn Python programming as your first programming language. Python for Absolute Beginners, Non-Tech Professionals, 15+ Projects, 30 Topics, 500+ Practice Questions, with Data Structures & Algorithms

scmrepo

For Coursera project

test_jenkins

This is for jenkins test SCM

time-tracker

Maven training - time tracker project

wqu_capstone_group20

This GIT report is for We have selected the Research Track (Capstone Research Paper) and the area of study chosen is to model the Efficient Market Hypothesis (EMH) and bring to light myths associated with the hypothesis that do not necessarily reflect the reality in the performance of investments on the market. Several myths are associated with the EMH which we seek to debunk in this project and also throw more light on the concept and other competitive concepts that operate contrary to established theories associated with the EMH. This choice has been informed by our keen interest as a group in the performance of investors on the market and how their very actions affect the performance of the entire market amidst changes in securities information. With this, we are looking forward to establish various myths associated with the EMH, debunking same and establish facts to add up to existing literature in addressing the competition on the market and how changes in information affect investors as well as their reactions to same.

wqu_data_feeds_pricing

wqu_machinelearning_finance

Create structured financial data in the form of tick, volume, and dollar bars from unstructured tick data. From Marcos Lopez de Prado's Advances in Financial Machine Learning textbook.

kanwardusaj Goto Github PK

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