Quantitative Finance Expert Needed – Efficient Frontier (Python), CAPM, Options & Bonds (4 Questions) -- 2
Budget: ₹600 – ₹1,500 INR
Project description
I am looking for an experienced finance professional to prepare fully worked, step-by-step solutions for a set of four coursework-style questions in investments/derivatives. These solutions are for direct student submission, so clarity and explanation are very important.
The four question areas are:
Efficient Frontier with Python (Portfolio Theory)
Select 5 listed companies, download historical prices (2010-01-01 to 2022-12-31) from Yahoo Finance or Refinitiv.
Compute annualised returns and volatilities.
Use Python to simulate portfolios (around 2,000 simulations) and plot the efficient frontier.
Identify the maximum Sharpe ratio portfolio assuming a 3% risk-free rate; report the optimal weights and briefly discuss whether you would invest in this portfolio and why.
Equity CAPM – Theory + Regression Analysis
Clearly define CAPM, its purpose in asset pricing, and explain each component of the CAPM equation and what it means.
Choose 2 US companies from different industries, pull ~10 years of daily prices plus S&P 500 index and 10-year Treasury yield.
Run an OLS regression (Excel is fine) to estimate alpha and beta for each stock and interpret the coefficients.
Critically discuss CAPM’s assumptions, its real-world relevance, and limitations for both active and passive portfolio management.
Option Pricing & Strategies
Price a European call option using the Black–Scholes model with:
S₀ = 100, K = 110, T = 0.5 years, r = 5%, σ = 30%.
Re-price the option when volatility increases to 40% (due to positive news) and comment on the impact of volatility.
Draw and explain the P/L diagram of a short strangle, and state whether the position has positive/negative delta, gamma, theta and vega.
For a covered call strategy, explain the importance of time to expiry when choosing which call to short (all else equal).
Bond Valuation, YTM and DV01
Compute the dirty price of a US Treasury 2.5% coupon bond maturing 15-Aug-2030 trading at a given clean price on 2-Sep-2023 (semi-annual coupon, actual/actual).
For a hypothetical 10-year bond (2% annual coupon, face value $100m, given dirty price), calculate yield to maturity (YTM) and DV01, and explain the interpretation of DV01.
Evaluate a 1-year project that begins in one year, earning 10% at the end of the investment. Given current 1-year and 2-year interest rates (5% and 8%), show how to decide whether to undertake the project using bond/loan information.
Deliverables
A clearly written report (Word or PDF) with:
Full calculations shown step by step
Explanations in simple
Graphs/figures where required (efficient frontier, P/L diagram, etc.)
Python code (.py or .ipynb) for the efficient frontier and any data handling.
Excel file(s) for the CAPM regressions and bond/option calculations where relevant.
Requirements
Strong background in Finance / Financial Engineering / Quantitative Finance / Econometrics.
Solid knowledge of:
Portfolio theory & efficient frontier
CAPM and regression analysis
Black–Scholes option pricing & option Greeks
Bond pricing, YTM and DV01
Proficiency in Python (NumPy, pandas, etc.) and Excel/Regression tools.
Original work only – solutions must be written in your own words. I will check for plagiarism and AI-generated content.
How to apply
Please include in your bid:
A short summary of your relevant background (e.g. CFA, MSc in Finance, teaching/tutoring experience).
One example of similar quantitative finance work you have done (screenshots or brief description are fine).
Your fixed price quote for all 4 questions and estimated time to complete.
Looking forward to working with a reliable expert who can deliver clear, high-quality, step-by-step solutions.
I am looking for an experienced finance professional to prepare fully worked, step-by-step solutions for a set of four coursework-style questions in investments/derivatives. These solutions are for direct student submission, so clarity and explanation are very important.
The four question areas are:
Efficient Frontier with Python (Portfolio Theory)
Select 5 listed companies, download historical prices (2010-01-01 to 2022-12-31) from Yahoo Finance or Refinitiv.
Compute annualised returns and volatilities.
Use Python to simulate portfolios (around 2,000 simulations) and plot the efficient frontier.
Identify the maximum Sharpe ratio portfolio assuming a 3% risk-free rate; report the optimal weights and briefly discuss whether you would invest in this portfolio and why.
Equity CAPM – Theory + Regression Analysis
Clearly define CAPM, its purpose in asset pricing, and explain each component of the CAPM equation and what it means.
Choose 2 US companies from different industries, pull ~10 years of daily prices plus S&P 500 index and 10-year Treasury yield.
Run an OLS regression (Excel is fine) to estimate alpha and beta for each stock and interpret the coefficients.
Critically discuss CAPM’s assumptions, its real-world relevance, and limitations for both active and passive portfolio management.
Option Pricing & Strategies
Price a European call option using the Black–Scholes model with:
S₀ = 100, K = 110, T = 0.5 years, r = 5%, σ = 30%.
Re-price the option when volatility increases to 40% (due to positive news) and comment on the impact of volatility.
Draw and explain the P/L diagram of a short strangle, and state whether the position has positive/negative delta, gamma, theta and vega.
For a covered call strategy, explain the importance of time to expiry when choosing which call to short (all else equal).
Bond Valuation, YTM and DV01
Compute the dirty price of a US Treasury 2.5% coupon bond maturing 15-Aug-2030 trading at a given clean price on 2-Sep-2023 (semi-annual coupon, actual/actual).
For a hypothetical 10-year bond (2% annual coupon, face value $100m, given dirty price), calculate yield to maturity (YTM) and DV01, and explain the interpretation of DV01.
Evaluate a 1-year project that begins in one year, earning 10% at the end of the investment. Given current 1-year and 2-year interest rates (5% and 8%), show how to decide whether to undertake the project using bond/loan information.
Deliverables
A clearly written report (Word or PDF) with:
Full calculations shown step by step
Explanations in simple
Graphs/figures where required (efficient frontier, P/L diagram, etc.)
Python code (.py or .ipynb) for the efficient frontier and any data handling.
Excel file(s) for the CAPM regressions and bond/option calculations where relevant.
Requirements
Strong background in Finance / Financial Engineering / Quantitative Finance / Econometrics.
Solid knowledge of:
Portfolio theory & efficient frontier
CAPM and regression analysis
Black–Scholes option pricing & option Greeks
Bond pricing, YTM and DV01
Proficiency in Python (NumPy, pandas, etc.) and Excel/Regression tools.
Original work only – solutions must be written in your own words. I will check for plagiarism and AI-generated content.
How to apply
Please include in your bid:
A short summary of your relevant background (e.g. CFA, MSc in Finance, teaching/tutoring experience).
One example of similar quantitative finance work you have done (screenshots or brief description are fine).
Your fixed price quote for all 4 questions and estimated time to complete.
Looking forward to working with a reliable expert who can deliver clear, high-quality, step-by-step solutions.