Conventional wisdom holds that financial markets are informationally efficient—that stocks are always priced and traded at the intrinsic value of their underlying assets. Thus, investors cannot expect to achieve returns consistently in excess of average returns, given information that is publicly available at the time, without taking on large economic risks akin to gambling risks. In other words, one can only obtain higher returns by purchasing riskier investments, and not through expert timing or speculative stock selection. There are three major interpretations of this efficient market hypothesis: Weak Efficient Market Hypothesis (EMH), which holds that current prices for assets, such as stocks, bonds, and property, reflect all past prices, Semi-strong EMH, which argues that prices change instantly to reflect all new public information (such as news of a take-over or a change in fiscal policy), and Strong EMH, which claims that prices adjust perpetually to reflect hidden, insider information not yet made public.
Weak EMH holds that technical analysis, the analysis of past stock performance, will not consistently produce excess returns because future price movements are only determined by current share prices and information not contained in historical price data. Under this hypothesis, share prices demonstrate no serial dependencies (recognizable patterns) that can be exploited by investors. However, most financial analysts whose job it is to make recommendations about whether to buy, hold, or sell stocks point to research showing that some markets demonstrate trends, such as cycles, over time and moreover, that the longer the period of study, the higher the degree of trending.
Semi-strong EMH posits that prices adjust proportionally and near-instantaneously to reflect the most current public information. To disprove this hypothesis, analysts have looked for repeated or substantial changes immediately after an initial price change; these changes would indicate that there is some market reaction to the initial change leading to an adjustment period during which the market price of a stock and its true value are not perfectly matched. If it were found, this adjustment period could theoretically be capitalized upon through fundamental analysis—the assessment of market information—and strategic timing. Investors and computer scientists who recognize this possibility have constructed complex algorithms to discover opportunities for arbitrage, the practice of capitalizing on price differences between markets that may occur only for milliseconds.
Strong EMH claims that the market is perfectly efficient in terms of all private and public information. Investors who have consistently gained excess returns are often used as examples to disprove Strong EMH (and to prove that strategy can yield excess returns), though a solid refutation generally follows from proponents of Strong EMH: among thousands of investors, some will succeed based on pure chance, rather than expert stock selection, purchase timing, or discrepancies between the true and market values of stocks. Thus, proponents of Strong EMH claim, the fact that investors sometimes see high returns does not, in and of itself, disprove even the Strong EMH hypothesis.
According to the passage, someone who believes in the Weak Efficient Market Hypothesis would agree with all of the following statements EXCEPT
[A] One can only obtain higher returns by assuming more risk.
[B] Knowledge of historical price data will not significantly enhance an investor’s capacity to achieve excess returns consistently.
[C] Historical price data does not contain information that would determine future price movements.
[D] Technical analysis is not a productive strategy for gaining excess returns consistently.
[E] New market information concerning an important take-over would be immediately reflected in the current price of a share.
It can be inferred from the passage that those who believe in the validity of Semi-Strong EMH would agree with which of the following statements?
(A) Investors who have not consistently gained excess returns should improve their stock selection and timing.
(B) Analysis of historical price data and new market information is the best strategy for consistently gaining excess returns.
(C) In the absence of new information released to the public, stock prices will not adjust substantially immediately following an initial change.
(D) Algorithms that calculate arbitrage opportunities could be effective because the market value of a stock tends toward the intrinsic value of that stock.
(E) Fundamental analysis is likely to yield excess returns on a consistent basis.
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