Modern Portfolio Theory Does Not Consider Diversifiable Risk Relevant Because

Modern Portfolio Theory (MPT) is a foundational framework in finance that emphasizes the importance of portfolio diversification to optimize returns relative to risk. According to MPT, “modern portfolio theory does not consider diversifiable risk relevant because” it focuses on the concept of systematic risk, which affects the entire market and cannot be eliminated through diversification. Diversifiable risk, also known as unsystematic risk, is specific to individual assets or companies and can be mitigated by holding a well-diversified portfolio of assets.

The theory posits that investors can reduce diversifiable risk by including a variety of assets in their portfolio, thereby diminishing the impact of any single asset’s performance on the overall portfolio. However, MPT assumes that, once a portfolio is adequately diversified, the remaining risk is primarily systematic, or market risk, which is inherent and cannot be diversified away. This systematic risk is related to factors that affect the entire market, such as economic changes, political events, or financial crises.

Modern Portfolio Theory does not consider diversifiable risk relevant because it asserts that the risk of individual assets becomes negligible when combined into a diversified portfolio. The theory argues that investors should focus on systematic risk when making investment decisions, as this is the only type of risk that affects the portfolio’s performance and cannot be eliminated by diversification alone. By concentrating on optimizing the trade-off between risk and return at the portfolio level, MPT provides a structured approach to investing that aims to achieve the highest possible returns for a given level of risk, given that the diversifiable risk has been accounted for through diversification.

Modern Portfolio Theory (MPT) is a framework for constructing investment portfolios that aims to maximize returns for a given level of risk or minimize risk for a given level of return. Developed by Harry Markowitz in the 1950s, MPT emphasizes the importance of diversification to reduce portfolio risk. The theory operates under the assumption that investors are rational and risk-averse, seeking to optimize their portfolios by balancing risk and return.

MPT and Diversifiable Risk

Modern Portfolio Theory distinguishes between systematic risk and diversifiable risk. Systematic risk, also known as market risk, affects all securities and cannot be eliminated through diversification. Diversifiable risk, on the other hand, pertains to individual securities and can be reduced or eliminated by holding a diversified portfolio. MPT focuses on systematic risk because it is the component that affects the overall market and cannot be mitigated through diversification alone.

Risk Reduction through Diversification

In MPT, the primary goal is to construct a portfolio that lies on the efficient frontier, where expected returns are maximized for a given level of risk. By combining assets with low or negative correlations, investors can reduce the total risk of the portfolio. The efficient frontier is a graphical representation of the optimal portfolio combinations that offer the highest expected return for a given level of risk.

where:

• \( E(R_p) \) is the expected return of the portfolio,
• \( w_i \) and \( w_j \) are the weights of assets \( i \) and \( j \),
• \( \sigma_{ij} \) is the covariance between assets \( i \) and \( j \),
• \( \sigma_p^2 \) is the variance of the portfolio’s returns.

Efficient Frontier Visualization

The efficient frontier is typically plotted as a curve showing the highest return achievable for a given level of risk. This curve represents the optimal portfolio combinations for different risk levels.

Quote: “Modern Portfolio Theory demonstrates that diversifiable risk can be mitigated through careful portfolio construction, allowing investors to focus on systematic risk.”

Practical Implementation in Python

To construct and evaluate portfolios using MPT, you can use Python libraries such as NumPy and Pandas for data manipulation and calculations. The following code snippet illustrates how to compute the efficient frontier using historical returns data:

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

# Load historical returns data
returns = pd.read_csv('returns_data.csv')

# Calculate mean returns and covariance matrix
mean_returns = returns.mean()
cov_matrix = returns.cov()

# Define portfolio weights
weights = np.random.random(len(mean_returns))
weights /= np.sum(weights)

# Calculate portfolio return and risk
portfolio_return = np.dot(weights, mean_returns)
portfolio_risk = np.sqrt(np.dot(weights.T, np.dot(cov_matrix, weights)))

print(f"Expected Return: {portfolio_return}")
print(f"Portfolio Risk: {portfolio_risk}")

Modern Portfolio Theory provides a structured approach to portfolio management by focusing on the reduction of diversifiable risk and optimizing for systematic risk. This methodology remains a cornerstone of investment strategy and financial planning.