Skip to content
View Vuong-Chu's full-sized avatar
🐳
Check your work a few times before submit.
🐳
Check your work a few times before submit.
Block or Report

Block or report Vuong-Chu

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
Vuong-Chu/README.md
Universe

Hi there, I am Vuong Chu Waving Hand


Click here to learn more about me!!!


- 💖 I’m interested in translating all methods in Financial Econometrics/Computational Finance to well-designed functions in C++, Python, and Java.

- 🌱 I’m currently targeting to Quant developer/ Quant analyst/ Quant researcher positions.

- 🔎 I’m looking to collaborate on projects related to financial time series data.

- 🔰 I love swimming, cycling and coding challenges.

- 📫 Feel free to reach out to me at minhvuong2992(at)gmail.com.

Github contributions: Pig

github contribution grid snake animation
Languages and Tools:

Python C++ C++ Java R PowerBI
GitHub Stats: Brain Party Popper

Pinned

  1. Calculate distance between Latitude/... Calculate distance between Latitude/Longitude points. All these formulas are for calculations on the basis of a spherical earth (ignoring ellipsoidal effects) – which is accurate enough for most purposes…
    1
    from math import radians, sin, cos, atan2, sqrt, tan, atan
    2
    
                  
    3
    def haversine_distance(long1, lat1, long2, lat2, degrees=False):
    4
      '''
    5
      The haversine formula determines the great-circle distance 
  2. Wallis_Pi.py Wallis_Pi.py
    1
    import math
    2
    
                  
    3
    def  Wallis_Pi(n):
    4
      '''
    5
      Compute the decimals of Pi using the Wallis formula:
  3. Multiple Columns Label Encoders Multiple Columns Label Encoders
    1
    import pandas as pd
    2
    from sklearn.preprocessing import LabelEncoder
    3
    
                  
    4
    class MultiColumnLabelEncoder:
    5
        '''
  4. This function is to remove outliers ... This function is to remove outliers in columns of a dataframe and ignore missing values that may be processed in following steps.
    1
    # Define function to detect outliers for numerical variables
    2
    import pandas as pd
    3
    
                  
    4
    def clean_outliers(data, types = "IQR", threshold = 3.0):
    5
        '''
  5. algs4 algs4 Public

    Algorithm practice following the Algorithm courses offered by Princeton University on Coursera

    Java

  6. Projects Projects Public

    This repository showcases my job market projects in quantitative finance. ⚡⚡⚡

    Jupyter Notebook