Hello everyone,

Is it correct to say that **efficient frontier** itself is the expected returns for bearing **only systematic risk** at different levels?

Hello everyone,

Is it correct to say that **efficient frontier** itself is the expected returns for bearing **only systematic risk** at different levels?

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No.

Why is that? For a given level of expected return, we cannot reduce the risk anymore, can we? That means the total risk that weâ€™re bearing is essentially systematic risk. Otherwise, we can continue to diversify nonsystematic risk to find the better portfolio (lower total risk and the same expected return).

Is my reasoning correct?

How are you measuring risk?

Isnâ€™t it standard deviation (total risk) (x-axis)?

By the way, my assumption is that we only invest in risky assets. If our portfolio consists of risk-free assets, the efficient frontier should then be replaced by the optimal CAL â€¦ Iâ€™m not really sure â€¦

Yes: total risk.

Not systematic risk.

But the fact that for a given level of expected return, we **cannot reduce the total risk anymore**. That means **the total risk that weâ€™re bearing is essentially systematic risk**. Otherwise, we can continue to diversify nonsystematic risk to find the better portfolio (lower total risk but the same expected return) which is to the West of each efficient portfolio.

Is it correct?

Unless you add in the risk-free asset, in which case your efficient frontier becomes the CML.

If you donâ€™t have the risk-free asset, then total risk is not necessarily the same as systematic risk.

Hello Everyone,

I have the same question as raised by Bui_Manh_Khang. Since in the efficient frontier plot, all the assets on the frontier and below frontier are all well diversified, the risk plotted on the X-axis is in a way can be called as systematic risk only. Although we plot the total risk (std dev) but since we have already diversified, the total risk in a way represents the systematic risk only.

I am stucked with this particular thought. Could you anyone please help me out.

Thanks, Kaushik

Hi Kaushik (did you ask on our YouTube?): I think 2000magician is correct. You are correct in the sense that the efficient CML (i.e., straight line **after** introduction of Rf rate) is a coincident map to systemic risk; e.g., double the leverage by borrowing (on the CML) and you double the beta such that the CML x-axis is a proxy for the SMLâ€™s beta. But any portfolio below this CML does not map (or at best maps non-linearly without obvious visual interpretation). A key thing to keep in mind is that both efficiency and well-diversified have degrees; a portfolio is â€śmore diversifiedâ€ť as specific (idiosyncratic) risk tends to zero. Efficiency is also a relative concept. In CAPM theory (with it unrealistic assumptions), only the Market Portfolio is optimally well-diversified, many other portfolios are merely well-diversified (with negligible specific risk). This is why S2000magician make a GREAT point to write â€¦

Imagine a horizontal line slicing through the CML above the Market portfolio: on the CML is the same return as another portfolio on the PPC that has greater total risk (i.e., the points on the PPC are less efficient). Both have the same E(return) per beta (i.e., both plot on the SML) but the less efficient portfolio has greater risk because it has some specific risk. The SML plots all portfolio regardless of their efficiency; the after-Rf CML only plots the most efficient Market portfolio (albeit mixing in the zero-beta Rf asset). We have a learning spreadsheet that solves for the Market Portfolio (highest Sharpe); this is the only reason I understand your question, because Iâ€™ve had to implement the CML and SML in XLS and with data. Working with actual data helped me understand the profound difference between the CML and the SML. I would argue that the CML is empirical/practical while the SML is theoretical. Thanks,

Thank you very much for your help. Really appreciate the detailed explanation you always provide.

Yes, I was the one who asked you on youtube yesterday.

Thanks!

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