Quantative_Analysis

In this Project, I focused on learning Financial Analysis covering many tools and techniques used by finance professionals daily .

I performed calculations on following Quantative Aspects and also learnt their theoretical concepts & Fundementals :

1.Rate of return of stocks
2.Risk of stocks
3.Rate of return of stock portfolios
4.Risk of stock portfolios
5.Correlation between stocks
6.Covariance
7.Diversifiable and non-diversifiable risk
8.Regression analysis
9.Alpha and Beta coefficients
10.Measuring a regression’s explanatory power with R^2
11.Markowitz Efficient frontier calculation
12.Capital asset pricing model
13.Sharpe ratio
14.Multivariate regression analysis
15.Monte Carlo simulations
16.Using Monte Carlo in a Corporate Finance context
17.Derivatives and type of derivatives
18.Applying the Black Scholes formula
19.Using Monte Carlo for options pricing
20.Using Monte Carlo for stock pricing

Tech Stack : Python , Panda , Numpy

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Name		Name	Last commit message	Last commit date
PART3_1_Running_Regression.ipynb		PART3_1_Running_Regression.ipynb
PART3_2_Computing_Alpha,_Beta,_and_R_Squared_.ipynb		PART3_2_Computing_Alpha,_Beta,_and_R_Squared_.ipynb
PART4_2_Obtaining_efficient_frontier.ipynb		PART4_2_Obtaining_efficient_frontier.ipynb
PART4_3_Obtaining_efficient_frontier.ipynb		PART4_3_Obtaining_efficient_frontier.ipynb
PART5_1_Calculating_beta_of_stock.ipynb		PART5_1_Calculating_beta_of_stock.ipynb
PART5_2_Calculating_the_expected_return_of_a_stock.ipynb		PART5_2_Calculating_the_expected_return_of_a_stock.ipynb
PART5_3_Estimating_the_sharp_Ratio.ipynb		PART5_3_Estimating_the_sharp_Ratio.ipynb
PART6_1_Running_a_Multivariate_regression.ipynb		PART6_1_Running_a_Multivariate_regression.ipynb
PART7_1_Monte_Carlo_Predicting_Gross_Profit.ipynb		PART7_1_Monte_Carlo_Predicting_Gross_Profit.ipynb
PART7_2_Monte_Carlo_Predicting_Gross_Profit_Part_II.ipynb		PART7_2_Monte_Carlo_Predicting_Gross_Profit_Part_II.ipynb
PART7_3_Monte_Carlo_Forecasting_Stock_Prices.ipynb		PART7_3_Monte_Carlo_Forecasting_Stock_Prices.ipynb
PART7_4_Monte_Carlo_Forecasting_Stock_Prices_Part_II.ipynb		PART7_4_Monte_Carlo_Forecasting_Stock_Prices_Part_II.ipynb
PART7_5_Monte_Carlo_Forecasting_Stock_Prices_Part_III.ipynb		PART7_5_Monte_Carlo_Forecasting_Stock_Prices_Part_III.ipynb
PART7_6_Monte_Carlo_Black_Scholes_Merton.ipynb		PART7_6_Monte_Carlo_Black_Scholes_Merton.ipynb
PART7_7_Monte_Carlo_Euler_Discretization_Part_I.ipynb		PART7_7_Monte_Carlo_Euler_Discretization_Part_I.ipynb
PART7_8_Monte_Carlo_Euler_Discretization_Part_II.ipynb		PART7_8_Monte_Carlo_Euler_Discretization_Part_II.ipynb
Part1_1_Calculating_security's_rate_of_return.ipynb		Part1_1_Calculating_security's_rate_of_return.ipynb
Part1_2__Calculating_a_Security’s_Return_in_Python–Logarithmic_Returns.ipynb		Part1_2__Calculating_a_Security’s_Return_in_Python–Logarithmic_Returns.ipynb
Part1_3_Calculating_a_Portfolio_of_Securities'_Rate_of_Return.ipynb		Part1_3_Calculating_a_Portfolio_of_Securities'_Rate_of_Return.ipynb
Part1_4__Calculating_the_Indices'_Rate_of_Return.ipynb		Part1_4__Calculating_the_Indices'_Rate_of_Return.ipynb
Part2_2_Calculating_Covariance_and_Correlation.ipynb		Part2_2_Calculating_Covariance_and_Correlation.ipynb
Part2_3_Calculating_Portfolio_Risk.ipynb		Part2_3_Calculating_Portfolio_Risk.ipynb
Part2_4_Calculating_Diversifiable_and_Non_Difersifiable_Risk_of_Portfolio.ipynb		Part2_4_Calculating_Diversifiable_and_Non_Difersifiable_Risk_of_Portfolio.ipynb
Part4_1_Obtaining_efficient_frontier.ipynb		Part4_1_Obtaining_efficient_frontier.ipynb
Part_2_1__Calculating_a_Security’s_Risk.ipynb		Part_2_1__Calculating_a_Security’s_Risk.ipynb
README.md		README.md

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