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In the context of a one-factor arbitrage pricing theory model, consider two assets (which represent the entirety of a small, two-asset economy). Asset one has an expected return of 10% and a factor sensitivity of 0.8 ; and asset two has an expected return of 8% and a factor sensitivity of 1.1. As a result of arbitrage action, which of the following is most likely to occur? A The price of asset one falls and the price of asset two rises B The price of asset one rises and the expected return on asset two falls C The expected return on asset two falls and the price of asset two falls D The price of asset two falls and the expected return on asset one falls E The expected return on asset one rises and the price of asset two falls

User Skyporter
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Final answer:

Arbitrage actions would likely cause the price of asset one to fall and the expected return on asset two to fall, as arbitrageurs correct market prices to align with the assets' factor sensitivities.

Step-by-step explanation:

In the context of a one-factor arbitrage pricing theory model, the assets in a market should have their prices such that no arbitrage opportunity exists. Given two assets in a small, two-asset economy with asset one having an expected return of 10% and a factor sensitivity of 0.8, and asset two having an expected return of 8% and a factor sensitivity of 1.1, arbitrageurs would seek to exploit any pricing inconsistencies. If the assets' expected returns do not align according to their factor sensitivities (also known as beta in the context of finance), arbitrage will occur, driving the prices and expected returns to an equilibrium.

The result most likely to occur due to arbitrage actions would be that the price of asset one falls and the expected return on asset two falls. This will happen because the higher expected return of asset one is not justified by its lower sensitivity compared to asset two. Thus, arbitrageurs would sell asset one and buy asset two until the expected returns are proportionate to their sensitivities or betas.

User Eric Wang
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