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Most approaches in forecasting future correlation depend on the use of historical information as their basic information set. Recently, there have been some attempts to use the notion of "implied" correlation as a more accurate measure of future correlation. This study proposes an innovative methodology for backing-out implied correlation measures from index options. This new measure called implied correlation index reflects the market view of the future level of the diversification in the market portfolio represented by the index. The methodology is applied to the Dow JonesThe authors would like to thank Jeff Fleming, an anonymous referee, and their FRC colleagues, George Skiadopoulos, Spyros Xanthopoulos, and Raphael Markellos for helpful discussions and comments. Financial support from the Bank of Greece is also gratefully acknowledged. Any remaining errors are the responsibility of the authors. 172 Skintzi and RefenesIndustrial Average index, and the statistical properties and the dynamics of the proposed implied correlation measure are examined. The evidence of this study indicates that the implied correlation index fluctuates substantially over time and displays strong dynamic dependence. Moreover, there is a systematic tendency for the implied correlation index to increase when the market index returns decrease and/or the market volatility increases, indicating limited diversification when it is needed most. Finally, the forecast performance of the implied correlation index is assessed. Although the implied correlation index is a biased forecast of realized correlation, it has a high explanatory power, and it is orthogonal to the information set compared to a historical forecast.