Learn Data Skills
Beta
Nitiphong Nirachornkul

Nitiphong Nirachornkul

student

UNT

Technologies

My Portfolio Highlights

My New Course

Introduction to R

Quantitative chef, mixing variables and algorithms to create delectable insights.

My Work

Take a look at my latest work.

course

Exploratory Data Analysis in R

course

Supervised Learning in R: Classification

course

Introduction to R

DataCamp Course Completion

Take a look at all the courses I’ve completed on DataCamp.

My Work Experience

Where I've interned and worked during my career.

Bangkok Bank | Apr 2022 - Present

Portfolio Management Officer

Monitor Risk-adjusted return on capital (RAROC) to balance the risk and return of the portfolio. The RAROC components have return as a numerator and equity as a denominator. Thus, the bank loan comes from 2 parts. The first part is from deposits from clients which cannot take risks. The second part comes from equity which can take risk. Thus, the institution should find the probability of default of clients and rank the clients by Credit Risk Rating(CRR) or credit score to calculate the money that has risk or expected loss. The expected loss is the probability of default multiplied by clients Exposure At Default which is the amount of loss at the date that default minus the estimated collateral value. Moreover, the RORAC model also can apply to trading risk adjusted models. When the trading model that has constant stats results (the sample size should be large enough) should be able to calculate the probability of default. Thus, trading limit and probability of default can also find Exposure At Default and limit the leverage to maximize the profit.Monitor Risk-adjusted return on capital (RAROC) to balance the risk and return of the portfolio. The RAROC components have return as a numerator and equity as a denominator. Thus, the bank loan comes from 2 parts. The first part is from deposits from clients which cannot take risks. The second part comes from equity which can take risk. Thus, the institution should find the probability of default of clients and rank the clients by Credit Risk Rating(CRR) or credit score to calculate the money that has risk or expected loss. The expected loss is the probability of default multiplied by clients Exposure At Default which is the amount of loss at the date that default minus the estimated collateral value. Moreover, the RORAC model also can apply to trading risk adjusted models. When the trading model that has constant stats results (the sample size should be large enough) should be able to calculate the probability of default. Thus, trading limit and probability of default can also find Exposure At Default and limit the leverage to maximize the profit. Skills: RAROC · Banking Operations · Knowledge Acquisition · Analytical Skills · Investment Research · Money Market · Word Processing · Securities · Data Analysis · International Markets · Python (Programming Language) · Bonds · Financial Modeling · Microsoft Excel · Fixed Income Portfolio Management · Data Visualization · Financial Accounting · Financial Analysis · VBA Excel · Administrative Assistance · Thai · Derivatives · Finance · Fixed-Income Investing · Loss Given Default (LGD) · Net Present Value (NPV) · Quantitative Analytics · Communication · Economics · Investments · Equity Derivatives · Trade Credit · Accounting · Visual Basic for Applications (VBA) · Written Communication · Credit Rating · Funding
Show More

My Education

Take a look at my formal education

Msc Advance Data Analytics in Machine LearningUniversity of North Texas | 2021

About Me

Nitiphong Nirachornkul

Nitiphong hasn't filled in a bio text

Powered by

  • Work
  • Courses
  • Experience
  • Education
  • About Me
  • Create Your Data Portfolio for Free