Westminster, California, United States
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"Data" is the most powerful word in today's industry. From data, we get information, and…

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Experience & Education

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Volunteer Experience

  • Head Coordinator and Mentor

    Rang dey Zindagi

    - 2 years 1 month

    Social Services

    • As the capacity of the head coordinator, I managed a team of 13 volunteers to promote child education in the backward areas of the city.
    • Also, in the capacity of the mentor of the Non-Profit Organization, I volunteered to mentor student of the government schools by teaching them Mathematics and English.
    • I guided them as to which career opportunities could be the best fit for them, and helped them prepare for the state level mathematics olympiads.

  • Bhumi Graphic

    Volunteer

    Bhumi

    Social Services

    • Being a part of Bhumi, I volunteered in various awareness drives in India.
    • Also during Daan Ustav, India's festival of giving also known as 'Joy of Giving' celebrated every year from October 2 to October 8.
    • The volunteering drives included cleanliness drive, plantation drive, traffic awareness drive and promotion of child education in the backward regions of the country.

  • Summer Intern

    Sunder Rang

    - 2 months

    Social Services

    • During my visit to the Chandelao Garh, a village in Rajasthan, I along with my colleague taught the art of handicraft to women residing there.
    • With the help of beads, threads and metal strings, different varieties of Jewellry were formulated and by selling those pieces of jewellry, the women earned their living.
    • To promote women empowerment, this initiative was taken and the women being the bread earner of the house does not need to be dependent on thier husbands for petty things.

Courses

  • Accounting for Decision Makers

    ACCT-603

  • Advanced Derivatives

    FINC - 774

  • Analyzing and Visualizing Data

    ITS 530

  • Business Intelligence and AI

    ITS-531

  • Computational Finance Experience

    FINC 795

  • Data Management and Analytics

    MGIS 725

  • Debt Analysis

    FINC - 773

  • Emerging Threats and Countermeasures

    ITS 834

  • Enterprise Risk Management

    ITS-835

  • Equity Analysis

    FINC - 772

  • Financial Analytics

    FINC-780

  • Human Computer Interaction and Usability

    ITS 536

  • Inferential Statistics

    DSRT 734

  • Information Governance

    ITS 833

  • Information Technology Importance in Strategic Planning

    ITS 831

  • Information Technology in a Global Economy

    ITS 832

  • Intro to Data Analytics and Business Intelligence

    MGIS 650

  • Intro to Data Mining

    ITS-632

  • Math of Finance - II

    MATH - 736

  • Math of Finance I

    MATH-735

  • Professional Writing

    DSRT-837

  • Statistical Softwares

    STAT 611

  • Survey of finance

    FINC-671

  • System Analysis and Design

    ITS 535

Projects

  • Bond Liquidity

    This project was made using Python.
    A large scale enhanced trace data for before and after the financial crisis was gathered through WRDS. Developed bond liquidity metrics and tested the hypothesis that the bond liquidity decreased after the crisis.

  • Trading Strategy

    This project is made using Python. Created a trading strategy using technical indicator in Jupyter Notebook to signal when to buy/sell a stock. Relative Strength Index was combined with exponentially weighted moving average to predict the status of the stocks.

  • Bond Valuation

    This project is made using Python. Calculated the bond prices, yield to maturity for semi-annual coupon bonds and asked yield based on invoice prices. Plotted a 3-dimensional graph for historical treasury yield curve in the past two decades.

  • Option Pricing using Monte Carlo Simulation

    This project is made using MATLAB. Priced the call and put options using Monte Carlo Simulation by getting the stock paths. European, Lookback, Barrier and Asian options were priced, and the validity of put-call parity was verified.

  • Give Me Some Credit (Kaggle)

    This project is made using Python. Analyzed the data from the Kaggle competition and correlated all the features of the data, cleaned the data. Regression models were used to fill in the missing values and to calculate the precision by which a person might experience serious deliquescence in the next two years.

  • Portfolio Optimization

    Using both R and Python, evaluated the stock means and covariance matrix of six companies using the data from yahoo finance for a set of period which is calculated on a daily basis. Also, anticipated and plotted the feasible set with identification of optimal portfolio.

  • Single Index Model Regression and 3 Factor Fama French model Regression

    This project is made using R language. A comparison data table of the prediction accuracy between the Single Index Model Regression and 3 Factor Fama French Model Regression was made. Summarized the results according to the values of alpha, R-squared, mean absolute prediction error, standard deviation of prediction error.

  • Stock returns

    The project included the calculation of stock return metrics of 30 companies, thereby estimating the monthly returns of these companies for a time period of 10 years, using R programming. The stock return information was summarized and then depicted in the form of a heat map.

    Other creators

  • Analysis of NBA Salaries

    -

    • This project was made using R, Tableau, MS Excel, MiniTab, Twitter.
    • Data sets of the upcoming NBA season was taken into consideration.
    • Determined on which factors does the salaries of the NBA players depend and to forecast salary cap implications.
    • Developed a code to generate the word cloud of NBA Salaries which were extracted from Twitter website.

  • Regression and Data Discovery

    -

    • This project was made using MS Excel, MiniTab, and Tableau.
    • Categorically grouped all the factors that affect the obesity rate and diabetes rate in the United States.
    • Using regression methods, dependent and independent variables were selected to maximize R-squared to 85.39%.
    • Factors were correlated with each other and obesity rates geographically in assorted graphical formats to bring statistics to life.

  • Lending Club Loan Stats

    -

    • This project is made using R programming language.
    • A descriptive analysis of the Lending Club loan data was done.
    • Using the statistical analysis, default behavior was modelled.
    • Different external variables were added to the data set to strengthen the analysis.
    • The new model was thus tested and compared to the previous models.
    • Logistic Regression and decision trees were used.

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