title: "Portfolio Risk Attribution & Scenario Analysis"
author: "Ruchi Malhotra"
date: "2025-08-06"
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📊 Portfolio Returns and Composition

knitr::opts_chunk$set(echo = FALSE, warning = FALSE, message = FALSE)
library(tidyverse)

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library(PerformanceAnalytics)

Loading required package: xts
Loading required package: zoo

Attaching package: 'zoo'

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library(quantmod)

Loading required package: TTR
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library(xts)
library(knitr)
library(corrr)

Warning: package 'corrr' was built under R version 4.3.3

[1] "SPY" "TLT" "VNQ"

[1] "AGG"

🗺 Correlation Map

📉 Performance Summary

🔍 Performance Comparison Table

                          Portfolio Benchmark
Annualized Return            0.0448    0.0628
Annualized Std Dev           0.1502    0.1149
Annualized Sharpe (Rf=0%)    0.2981    0.5461

📉 Drawdown Comparison

📦 Distributional View

🧮 Brinson-Style Risk Attribution (SPY/AGG Benchmark)

      SPY       TLT       VNQ 
 0.000528 -0.000204  0.000137 

     SPY      TLT      VNQ 
0.000528 0.000019      NaN 

Brinson-Style Attribution: Portfolio vs SPY/AGG Benchmark

Asset	Allocation	Selection	Total
SPY	0.000	0.0000	0.000
TLT	-0.001	-0.0281	-0.029
VNQ	NaN	NaN	NaN

📈 Scenario Analysis: Rate Shock Simulation

📊 Monte Carlo Simulation & 95% Value at Risk

🔐 Summary

This report demonstrates multi-asset portfolio analysis with risk attribution, scenario modeling, and Value at Risk simulation using real market data.

• Portfolio is a 3-asset blend of SPY (equity), TLT (bonds), and VNQ (REITs)
• Benchmark is a 50/50 SPY + AGG mix
• Compared performance, volatility, drawdowns, and 95% VaR
• Brinson attribution removed due to asset mismatch between portfolio and benchmark