This section explores the benefits of using logarithmic returns in normalizing time series data for
analyzing Abbott Laboratories (Abbott), Pfizer Inc. (Pfizer), and Johnson & Johnson (J&J) stocks.
Normalized Price Paths of Healthcare Stocks
Each stock's daily adjusted closing prices were divided by the initial price to normalize the data.
The normalized stock prices were plotted to visualize their performance relative to their initial values
Sharpe Ratio Distribution
Random weights are assigned to each stock in the portfolio, meaning random weights are initialized to
distribute investment across the three stocks without any predetermined bias.
Normalizing Weights to Sum to 1.0. Weights are rebalanced to ensure they sum up to 1.0, representing a fully invested portfolio.
Expected Portfolio Return and Volatility. Calculate the expected portfolio return based on the mean log returns and assigned
weights as well as determining the expected volatility of the portfolio using the covariance matrix and assigned weights.
The Sharpe ratio quantifies the portfolio's performance relative to its risk. A higher ratio indicates better risk-adjusted returns.
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🏠 VAR Model: Housing Starts & Unemployment
Time Series Variables
Creating the VAR (Vector Auto-Regressive) Model
Multivariate Series Forecast
Forecast COMP, STARTS, and UNEM 24 periods ahead with optimal lag order 2.
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