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Coding projects I have worked on, in R and Python. Predominantly includes utilizing code to recreate the Black Sholes Model, Greek Option calculator, Stochastic Process and Brownian Motion and other data science applications for finance. Python was also used primarily for machine learning applications in finance, using various functions from skl…

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FIN5615_Project_2 is one where I utlized a simple random walk in order to model stock prices, followed by comparing the random walk model with the Black-Shoeles model.

FIN5615_Project_3 is a continuation of the previous project.

FIN5615_Project_5 is an options pricing calculator built on Python, primarily showcasing the stochastic volatility of the greeks in the model.

FIN5615_Project_6 is a robust analysis on the returns of the S&P 500, by taking a dataset of the returns from Excel using read.csv to perform a variety of performance measures using functions from the numpy library inlcuding array, argmin/argmax and argsort.

FIN5622_Project_1 utlizes machine learning to predict the price of bitcoin using a fitted linear regression model.

FIN5622_Project_2 utlizes machine learning to build a model predicting the default probability of a loan using a fitted logistic regression model.

FIN5622_Project_3 is similar to project 2, however it utilizes random forests to predict default probability as apposed to a fited logistic regression model.

FIN5622_Project_4 uses clustering in order to detect regimes in the stock market.

FIN5622_Project_5 uses TensorFlow to construct a neural network that detects the probability of a loan being defaulted on.

FIN5622_Project_6 is a further application of TensorFlow to construct a neural network which predicts stock prices based on historical data and performance.

Project 1 Questions is a series of R questions (using RStudio as the IDE) that include using R to conduct a variety of tests on imported Excel data (primarily regression, T Test, and plotting) to deterime regression equations, chi values, T value/T Test scores, and P value.

Project 2 consists of two questions, with the first examining how firms’ stock returns (y) are affected by different independent variables using multiple linear regression models. Question 2 examines if attending an after-school program has a causal effect on the improvement of students’ exam scores (y) using a difference-in-difference model.

Financial Time Series Project (1) consists of using a variety of tests in R including ACF, Unit Root Test, and fitting data into a univariate time series model to determine if Excel imported data is stationary or not.

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Coding projects I have worked on, in R and Python. Predominantly includes utilizing code to recreate the Black Sholes Model, Greek Option calculator, Stochastic Process and Brownian Motion and other data science applications for finance. Python was also used primarily for machine learning applications in finance, using various functions from skl…

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