The correct option is this Weighted average.
In Finance MCQs, understanding portfolio risk is a core concept in modern investment theory. When multiple assets are combined into a portfolio, many students initially assume that the portfolio’s risk is simply the weighted...
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The correct option is this Weighted average.
In Finance MCQs, understanding portfolio risk is a core concept in modern investment theory. When multiple assets are combined into a portfolio, many students initially assume that the portfolio’s risk is simply the weighted average of the individual asset risks. However, in reality, portfolio risk is usually less than the weighted average of individual risks. The weighted average serves as a comparison benchmark, but diversification often reduces overall risk below this level.
The concept of weighted average means multiplying each asset’s risk by its respective portfolio weight and then summing the results. If asset A has a weight of 50% and asset B also has 50%, the simple weighted average of their risks would be the midpoint between their individual standard deviations. However, this calculation ignores a critical factor: the relationship between asset returns.
In portfolio management, risk is measured using variance or standard deviation. The formula for portfolio variance includes not only the weighted individual variances but also the covariance terms between assets:
σp² = Σ wi² σi² + ΣΣ wi wj Cov(Ri, Rj)
This formula shows that portfolio risk depends on how assets move relative to each other. The covariance term captures the interaction between asset returns. If assets are not perfectly positively correlated, these covariance terms reduce total portfolio risk. This is why diversification works.
When assets are less than perfectly positively correlated, their returns do not move exactly together. Some assets may rise while others fall, partially offsetting losses. This interaction lowers total portfolio volatility compared to the simple weighted average. Only in the extreme case of perfect positive correlation (correlation = +1) does the portfolio risk equal the weighted average of individual risks. In all other realistic cases, portfolio risk is lower.
It is important in Finance MCQs to distinguish weighted average from other terms. Mean refers to the average expected return, not risk. Mean correlation measures the average relationship among assets but does not directly measure portfolio risk. Negative correlation describes assets moving in opposite directions, which can significantly reduce risk, but the general principle of risk reduction applies whenever correlation is less than +1. The weighted average is the correct baseline comparison when analyzing how diversification affects risk.
From a practical perspective, this concept forms the foundation of modern portfolio theory (MPT). Investors and financial managers rely on diversification to reduce volatility without lowering expected returns. For example, suppose a stock has a standard deviation of 20% and a bond has a standard deviation of 10%. A 50-50 portfolio would have a weighted average risk of 15%. However, if the stock and bond are not perfectly correlated, the actual portfolio risk may be significantly lower than 15%. This is the true benefit of diversification.
Understanding this principle is essential in competitive exams such as CFA, CSS, PMS, MBA finance papers, and banking certifications. Questions often test whether students recognize that portfolio risk is generally less than the weighted average due to diversification effects. Some questions require numerical calculations, while others test conceptual clarity about correlation and covariance.
In conclusion, in finance, portfolio risk is typically smaller than the weighted average of individual asset risks because of diversification benefits. Recognizing this principle strengthens conceptual understanding of risk management, asset allocation, and efficient portfolio construction. Mastery of this topic not only helps in solving Finance MCQs accurately but also builds a strong foundation for real-world investment decision-making and portfolio optimization.
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