Mihai Ion
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  1. FIN 421
  2. Lectures
  3. L09: Review
  • Teaching
  • FIN 525
    • Lectures
      • L00: Jupyter basics
      • L01: Introduction
      • L02: Variables, types, operators
      • L03: Data structures
      • L04: Conditionals, loops
      • L05: Functions, packages
      • L06: Pandas intro
      • L07: Pandas I/O
      • L08: Pandas filtering
      • L09: Pandas data cleaning
      • L10: Merging, reshaping datasets
      • L11: Dates, lags, sorting
      • L12: Descriptive stats
      • L13: Conditional stats, outliers
      • L14: Conditional stats applied
      • L15: Linear regression intro
      • L16: Linear regression applications
      • L17: Panel regression intro
      • L18: Robust panel regression
      • L19: Robust timeseries regression
      • L20: Backtesting - data prep
      • L21: Backtesting - sumstats
      • L22: Backtesting -returns
      • L23: Backtesting - risk adjustment
  • FIN 421
    • Lectures
      • L01: Introduction
      • L02: Analyzing past returns
      • L03: Modeling future returns
      • L04: Portfolio theory intro
      • L05: Optimal capital allocation
      • L06: Tangency portfolios
      • L07_08: Optimal asset allocation
      • L09: Review
      • L10_11: Statistical models of returns
      • L12: CAPM
      • L13: Cost of equity
      • L14: Bond pricing
      • L15: Bond yields
      • L16: Bond risk
      • L17: Valuation data processing
      • L18_19: Multiples valuation
      • L20_21: Dividend discount models
      • L22_23: Discounted cash flow analysis
      • L24: Valuation sensitivity analysis
      • L25: Options intro
      • L26: Risk management with options

On this page

  • Lecture Overview
  • Real-World Application: performance of main asset classes
  • Cumulative returns
  • Sample statistics of individual assets
  • Tangency portfolio weights
  • Sample statistics of tangency portfolio
  • Optimal asset allocation weights

L09: Review

Lecture Overview

In this lecture we will work on an application that tries to incorporate most of the tools we learned so far.

Real-World Application: performance of main asset classes

From Yahoo Finance, download monthly data on the SPDR S&P 500 ETF, the SPRD Gold Shares ETF, and BlackRock’s long-term (20+ years) treasury ETF (tickers: SPY, GLD, TLT respectively).

  • Download monthly data from 2005 to 2022 and calculate monthly returns (use Adj Close)
  • Plot cumulative returns on these assets over time
  • Calculate Sharpe ratio for each asset
  • Calculate optimal tangency portfolio using these 3 assets
  • Calculate Sharpe ratio of tangency portfolio
  • Calculate optimal capital allocation if risk aversion is A = 4

Cumulative returns

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Sample statistics of individual assets

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Tangency portfolio weights

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Sample statistics of tangency portfolio

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Optimal asset allocation weights

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