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In this project, I had backtested the cross-over trading strategy on Google Stock from Jan 2016 to June 2020. By using historical time-series data, I had tested the Moving Average(MA) cross-over strategy and Relative Strength Index (RSI) strategy with a stop loss at a price that closes 2% or more below 10-day MA. I had plotted the equity curve w…

A walk through the frameworks of Python in Finance. The repository is currently in the development phase. The finalized version will include a full-fledged integration and utilization of Quantopian, GS-Quant, WRDS API and their relevant datasets and analytics.

Using a dataset of hedge fund indices, I had computed various risk parameters, explicitly Value at risk (VaR), drawdown and deviation from normality with Python. Using different models, I had computed non-parametric VaR, Parametric Gaussian Model VaR and Cornish-Fisher VaR, as well as plotted the VaR of all hedge fund indices.

The concentration of five tech giants, namely Facebook, Amazon, Microsoft, Apple and Google in the S&P500 have increased significantly. It is a common view on the street that the concentration level has surpassed that during the Dot-com bubble in 1999. Thus, extracting the time series data set for cumulative stock price of the above tech stocks …

Python for Finance (O'Reilly)