Cross-Industry, Cross-Country Allocation

Recent empirical evidence has demonstrated that both global industry factors and country factors are important determinants of equity prices. In light of this evidence, we describe a cross-industry, cross-country allocation framework for making active global equity investment decisions. We present a forecasting approach to predicting the relative performance of industries in each of 22 developed country equity markets and demonstrate that a blend of style signals provides an effective way to predict the return performance of these assets. The out-of-sample portfolio performance of investment strategies based on these forecasts for the 1991–2001 period would have provided annual gross returns in excess of the world benchmark return of 400 bps a year with one-way turnover of 50 percent. Conventional global risk models cannot explain this outperformance. Thus, explaining this “anomaly” is a challenge for the investment and academic communities. The increasing globalization of business presents new challenges and new opportunities for asset managers. Traditionally, active international equity allocations were made in a two-step process that overlaid security selection within countries on top-down country selection. The effectiveness of this paradigm has been lessened, however, by the market recognizing that companies operate and compete on a global basis and pricing securities accordingly. Today, the risk–reward trade-offs of country factors and global industry factors need to be balanced in constructing global equity portfolios. In this article, we suggest that a cross-industry, cross-country allocation (CICCA) matrix provides the means to simultaneously account for industry and country factors in active equity allocation decisions. In this approach, managers make allocations among a grid of industries and countries.The CICCA approach is designed to balance the risk–reward trade-offs of investing in “local” industries (e.g., Italian media stocks); thus, it recognizes the interaction of country and industry factors in determining security prices. CICCA provides asset managers with an operational “middle ground” between traditional top-down equity allocation and pure bottom-up stock selection. In this framework, country allocations and global industry allocations result from local industry selection. Similarly, global style tilts result from local style tilts. The result is an alternative to emphasizing “global value” or “global growth” as the overriding top-down decision. The risks of the CICCA tilts can be monitored at the aggregate level and can be altered via local industry allocations. To obtain final security holdings, the manager can overlay security selection decisions on the local industry selection. Stock selection may thus override or reinforce CICCA decisions.CICCA can be used to construct local industry allocations aimed at outperforming global benchmarks. We present a forecasting framework to predict the relative performance of local industries in the global investment universe. A blend of style signals that includes measures of profitability, value, and price momentum provides an effective means of predicting asset price performance. The out-of-sample performance of risk-controlled investment strategies that used these forecasts over the 1990–2001 period suggests that CICCA could have been used to outperform global equity benchmarks by as much as 400 bps a year.We also examine alternative models—one that emphasizes country factors as the principal determinants of the relative attractiveness of a local industry and one that emphasizes global industry factors as the principal determinants. The predictions based on the relative attractiveness of securities within and across global industries dominate those based on the relative attractiveness of securities within and across countries. Our strategy backtests suggest that an industry-relative CICCA strategy could have been used to outperform the world index by 490 bps a year in the period studied.In addition, we studied the historical performance of CICCA strategies on a risk-adjusted basis. We used a four-factor model that included value, size, and momentum risks in addition to the market risk. Even after accounting for the risks of style tilts, CICCA strategies delivered an economically and statistically significant outperformance of market returns.The “anomaly” we document could be explained by a variety of factors. Possibly, because of home-biased investment decisions, large mispricings exist in the global investment universe that can be exploited by a fully integrated global investment approach. Alternatively, the CICCA approach may actually be carrying out style rotations within and across industries and thus providing returns that reflect risks that are not captured by conventional risk models or conventional definitions of style factors. This possibility suggests that analysis of risk factors in the new global equity landscape needs to be extended.