이 논문은 과거의 산업 포트폴리오 수익률이 어떻게 확률추세(stochastic trend)로부터 전체 주식시장과 두 가지 거시경제 변수(경기동행지수와 산업생산)들을 예측할 수 있는 지를 알아보는 데에 초점을 두고 있다. 먼저, 산업들의 포트폴리오 수익률과 전체 주식시장 수익률이 VAR모형을 토대로 볼 경우 Granger 인과관계를 갖고 있는지를 살펴보았다. 이 분석의 결과에서 건설, 금속, 무역, 반도체, 보험, 비금속광물, 서비스, 섬유, 식료, 운수/창고, 유통, 의류, 자동차부풀, 전기전자, 정유, 조선, 종이/목재, 증권, 컴퓨터, 통신, 화학 등 21개 업종은 각 산업별 포트폴리오 수익률이 전체 주식시장 수익률을 수준에서 통계적으로 유의한 영향을 주고 있음을 알 수 있었다. 이들 21개의 산업별 포트폴리오 수익률은 경제적으로도 중요한 의미를 지니고 있다. 즉, 당월(t)의 비금속광물과 정유, 금속 포트폴리오 수익률 등은 다음 월(t+1)의 전체 주식시장 수익률과 음(-)의 상관관계를 갖고 있는 것을 알 수 있었다. 이는 역사적인 데이터를 살펴볼 때, 이들 산업 제품의 가격의 상승은 향후 경제에 악영향을 주기 때문인 것이다. 반면에, 의류 및 무역 등의 경우에는 반대로 이들 산업들의 포트폴리오 수익률이 전체 주식시장 수익률과 양의 상관관계를 나타내 이들 산업들에 있어서 높은 수익률은 향후 경제가 상승국면이 예상됨을 나타내어 주고 있다. 이와 같은 산업별 포트폴리오 수익률과 거시경제변수 간의 높은 상관관계를 토대로 하여 전체 주식시장 수익률 예측을 가능하게 하는 업종 정보(sector information)의 점진적 확산(slow diffusion) 현상이 발생하게 되는 것이다.

I test the hypothesis that the gradual diffusion of information across asset markets leads to cross-asset return predictability in Korea. Using thirty-six industry portfolios and the broad market index as our test assets, I establish several key results. First, a number of industries such as semiconductor, electronics, metal, and petroleum lead the stock market by up to one month. In contrast, the market, which is widely followed, only leads a few industries. Importantly, an industry's ability to lead the market is correlated with its propensity to forecast various indicators of economic activity such as industrial production growth. Consistent with our hypothesis, these findings indicate that the market reacts with a delay to information in industry returns about its fundamentals because information diffuses only gradually across asset markets. Traditional theories of asset pricing assume that investors have unlimited information-processing capacity. However, this assumption does not hold for many traders, even the most sophisticated ones. Many economists recognize that investors are better characterized as being only boundedly rational(see Shiller(2000), Sims(2201)). Even from casual observation, few traders can pay attention to all sources of information much less understand their impact on the prices of assets that they trade. Indeed, a large literature in psychology documents the extent to which even attention is a precious cognitive resource(see, eg., Kahneman(1973), Nisbett and Ross(1980), Fiske and Taylor(1991)). A number of papers have explored the implications of limited information- processing capacity for asset prices. I will review this literature in Section II. For instance, Merton(1987) develops a static model of multiple stocks in which investors only have information about a limited number of stocks and only trade those that they have information about. Related models of limited market participation include brennan(1975) and Allen and Gale(1994). As a result, stocks that are less recognized by investors have a smaller investor base(neglected stocks) and trade at a greater discount because of limited risk sharing. More recently, Hong and Stein(1999) develop a dynamic model of a single asset in which information gradually diffuses across the investment public and investors are unable to perform the rational expectations trick of extracting information from prices. Hong and Stein(1999). My hypothesis is that the gradual diffusion of information across asset markets leads to cross-asset return predictability. This hypothesis relies on two key assumptions. The first is that valuable information that originates in one asset reaches investors in other markets only with a lag, i.e. news travels slowly across markets. The second assumption is that because of limited information-processing capacity, many (though not necessarily all) investors may not pay attention or be able to extract the information from the asset prices of markets that they do not participate in. These two assumptions taken together leads to cross-asset return predictability. My hypothesis would appear to be a very plausible one for a few reasons. To begin with, as pointed out by Merton(1987) and the subsequent literature on segmented markets and limited market participation, few investors trade all assets. Put another way, limited participation is a pervasive feature of financial markets. Indeed, even among equity money managers, there is specialization along industries such as sector or market timing funds. Some reasons for this limited market participation include tax, regulatory or liquidity constraints. More plausibly, investors have to specialize because they have their hands full trying to understand the markets that they do participate in.

요약
 Abstract
 1. 서론
 2. 문헌조사
 3. 모형
  3.1 모형설정
  3.2 시계열과 교차상관계수
  3.3 자산간 수익률 예측가능성 검증
 4. 자료설명
 5. 실증분석
  5.1 전체 주식시장 및 산업 포트폴리오 수익률을 포함하는 자산간 수익률 예측 가능성 (cross-predictability) 분석
  5.2 산업별 포트폴리오 수익률과 거시경제변수
  5.3 충격반응분석
 6. 요약 및 결론
 참고문헌

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