IU-MCI measures the market conditions and is also a good leading indicator of economic growth in the country, as indicated by econometric exercises.

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1 Macro Vision Tuesday, September, 5 Itaú Unibanco Market Conditions Index We present the Itaú Unibanco Market Conditions Index IU-MCI for the Brazilian economy. IU-MCI measures the market conditions and also is a good leading indicator of economic growth in the country, as indicated by econometric exercises. The current market conditions measured by IU-MCI is compatible with a GDP contraction of.% in 5. ) Introduction Financial variables tend to summarize the state of the economy and influence the behavior of economic activity. Therefore, an index that is able to summarize relevant information for the economy contained in market prices can be a useful tool for assessing present and future growth. In this paper we present the Itaú Unibanco Market Conditions Index IU-MCI for the Brazilian economy. The indicator consists of two subcomponents: one comprising Brazilian financial variables interest rates, exchange rates, stock prices, country risk measure and other comprising commodity prices, given its importance to Brazil. IU-MCI measures the market conditions and is also a good leading indicator of economic growth in the country, as indicated by econometric exercises. ) Definitions Our goal is to create a daily index to monitor the Brazilian market conditions. To do so, we opt for building the index based on two subcomponents. The first one includes only domestic financial variables, while the second one includes only commodity prices. For the construction of the subcomponents, we used the principal component methodology..a) Variables included in our index Brazilian financial variables According to Hatzius et al. (), we should guide the choice of financial variables for this index based on the transmission channels of the effects of each variable on economic activity. We included shortand long-term interest rates, exchange rate, stock returns and a country risk measure in our index. Short- and long-term interest rates included in the index affect firms cost of financing, and also reflect financial intermediaries willingness to lend. In our index, we considered the Pre x DI swap rates with maturities of days and one year. Stock returns reflect firms costs to replenish capital, and, because of existence of information asymmetry in the credit market, also affect the value of firms collateral. The wealth of individuals is also affected by stock prices. In the index, we consider the Ibovespa as well as Petrobras and Vale s stock returns, given the importance of these two companies in the Brazilian economy. As uncertainty Another alternative would be to build an index without subcomponents, using domestic variables and commodity prices. However, we would lose information with this approach, as these series do not have much variation in common, which is relevant to principal components with the methodology used. Please refer to the last page of this report for important disclosures, analyst and additional information. Itaú Unibanco or its subsidiaries may do or seek to do business with companies covered in this research report. As a result, investors should be aware that the firm may have a conflict of interest that could affect the objectivity of this report. Investors should not consider this report as the single factor in making their investment decision.

2 about the collateral s value can also be an obstacle to obtaining credit, we have also included the volatility of the Ibovespa in our index. Last but not least, the exchange rate is another asset that influences economic agents decisions. In our index, we considered the real against the dollar. Finally, a country risk measure must also be considered. For this reason, we used the Brazilian five-year CDS. Commodity prices In addition to domestic variables, we understand that the market conditions in Brazil also depend on commodity prices, given the importance of these products in the economy. We base the Brazilian market conditions index on two subcomponents: the first one comprising the domestic financial variables described above, and the second one comprising commodity prices. To build the commodities subcomponent, we used the dollar prices of the following commodities: soybeans, corn, wheat, sugar, cotton, coffee, cocoa, aluminum, copper, nickel, zinc, lead, tin, iron ore (daily from ), natural gas, WTI oil, Brent oil, Dubai oil and gold..b) Methodology We used the principal components method to construct our market conditions index in Brazil. With this methodology, we were able to synthesize the information contained in financial variables into components that are independent of each other, organized by the proportion of variance of the data explained by each one. Thus, the first component explains the largest proportion of data variance; the second component explains the part of the variation that is not explained by the first one, and so on. We estimated the principal components based on quarterly data, considering the average of variables in each quarter. To make the variables stationary, we used the difference in the log of each series. Then, we subtracted from each one its own average and divided by its standard deviation, so that each variable has zero average and variance equal to one. To build the daily index, we used the weights of each variable in the components calculated from quarterly data, where we considered that each data is the difference between the logs of the average of 6 business days (one quarter) until the day considered and the 6 previous days. We also built an at-the-day index, which is composed of the difference of the log of each variable s value in a given day and the average of the previous 6 business days. The at-the-day index precedes what will occur in the average. In both cases (average and at-the-day), we also subtracted from each series its own average and divided by its standard deviation, so that each variable has zero average and variance equal to one. Finally, we normalized the index by its standard deviation. Thus, the interpretation of the market conditions index is the number of standard deviations, where positive values indicate expansionary market conditions and negative values indicate contractionary conditions. In the construction of the index, when we consider more than one principal component, we weight each component by the amount of its respective eigenvalue. As we wish to summarize the financial variables common information, it is best to use quarterly data, because there is much volatility in daily data. Page

3 ) Results.a) Subcomponent: Brazilian financial variables For the subcomponent comprising Brazilian financial variables, we used the first two principal components, which summarize 65% of the series variance. Chart shows this quarterly index and GDP growth. In Table, we show that the index Granger-causes the GDP growth rate, but the reverse does not occur. Chart : IU-MCI - Subcomponent: Brazilian financial variables % % % % % % -% Table : Granger Causality Test - Subcomp. Brazilian financial variables % PIB QoQ, sa (right) -5% Mar- Aug Jan Jun5 Sample: 999Q - 5Q Lags: 4 Null hypothesis Prob. Subcomp. Brazilian financial var. does not Granger cause GDP QoQ growth. GDP QoQ growth does not Granger cause Subcomp. Brazilian financial var..566 Chart shows the daily index (average and at-the-day). 4 - Chart : IC-MCI - Subcomponent: Brazilian financial variables (daily) -5 Subcomp. Brazilian financial variables Subcomp. Brazilian financial variables - at - theday Aug-99 Aug- Aug-7 Aug Aug5 Page

4 .b) Subcomponent: commodity prices In the case of the commodity index, we used four principal components, which correspond to 66% of the price variance of the commodities considered. Chart shows this quarterly index and GDP growth. In Table, we show that the index Granger-causes the quarterly GDP growth rate, and the opposite does not occur. - Table : Granger Causality Test Chart : IU-MCI - Subcomponent: commodities prices vs. GDP % % % % % % -% -5 Subcomp. commodities % PIB QoQ, sa (right) -5% Mar- Aug Jan Jun5 Sample: 999Q - 5Q Lags: 4 Null hypothesis Prob. Subcomp. commodities does not Granger cause GDP QoQ growth.5 GDP QoQ growth does not Granger cause Subcomp. commodities.675 Chart 4 shows the daily index (average and at-the-day). 4 Chart 4: IU-MCI - Subcomponent: commodities prices (daily) Subcomp. commodities Sucomp. commodities - at-the-day -8 Aug-99 Aug- Aug-7 Aug Aug5 Page 4

5 .c) IU-MCI To aggregate the complete index, we considered the correlation of each subcomponent with quarterly GDP growth. Weights are approximately / to the commodity prices subcomponent, and / to the Brazilian financial variables subcomponent. Chart 5 shows the full index at a daily frequency (average and at-the-day). 4 Chart 5: Itaú Unibanco Market Conditions Index IU-IMC IU-IMC - at - the - day -8 Aug-99 Aug- Aug-7 Aug Aug5 4) Using the market conditions index for forecasting GDP Growth Econometric exercises indicate that the IU-MCI is a good leading indicator of economic growth in the country. We estimated a model to forecast quarterly GDP growth in Brazil based on global GDP, the difference between real interest rates and their equilibrium value, real government spending and the components of IU-MCI (Table, Chart 6). 4 All variables have the expected sign and are statistically significant, and explain 74% of the variance of quarterly GDP growth for the period between the first quarter of and the second quarter of 5. Note that we considered the index subcomponents separately, as the effect of each one on GDP growth is different, as well as the lag. For example, the subcomponent with Brazilian variables has an effect with a lag of one quarter, while the commodity sub-component is contemporaneous. %, qoq sa Chart 6: GDP actual vs. fitted - Actual -5 Fitted Dec- Nov-5 Oct-7 Sep-9 Aug Jul Jun5 4 We also consider a dummy variable for the second quarter of 4. Page 5

6 Tabel : Model to forecast GDP growth considering IU-MCI Dependent variable: GDP growth, qoq as Sample: Q4-5Q Constant.6 *** Difference between real interest rates and their equilibrium value () -.8 *** DLog (Real government spending ).4 *** DLog (Global GDP).8 *** IU-MCI Subcomponent: Brazilian financial variables ().5 *** IU-MCI Subcomponent: Commodities.8 *** R.74 (***), (**), (*) significant at %, 5% and % Currently, the market conditions is deteriorating and in contractionary territory (Chart 5). To forecast activity, we maintained the value of financial variables at the same level as in the end of August. For the other variables, we followed our forecasts. With these assumptions, the model forecasts a.% GDP contraction in 5, in line with our scenario. 5 Laura Pitta Felipe Salles Caio Megale 5 See: More challenges, lower targets Page 6

7 Bibliography: Hatzius, Jan, Peter Hooper, Frederic S. Mishkin, Kermit L. Shoenholtz, Mark W. Watson,, Financial Conditions Indexes: A Fresh Look after the Financial Crisis, NBER Working Paper 65. Appendix Our market conditions indexes are available on Bloomberg: Itaú Unibanco Market Conditions: IUMCBR Index Subcomponent Brazilian financial variables: IUMCBRFV Index Subcomponent - Commodities: IUMCMDT Index Macro Research Itaú Ilan Goldfajn Chief Economist Click here to visit our digital research library. Relevant Information. This report has been prepared and issued by the Macro Research Department of Banco Itaú Unibanco S.A. ( Itaú Unibanco ). This report is not a product of the Equity Research Department of Itaú Unibanco or Itaú Corretora de Valores S.A. and should not be construed as a research report ( relatório de análise ) for the purposes of the article of the CVM Instruction NR. 48, dated July 6,.. 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