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sd-10-EFTA01384459Dept. of JusticeOther

EFTA Document EFTA01384459

18 September 2017 Long-Term Asset Return Study: The Next Financial Crisis It's almost impossible to have a one size fits all definition of a financial crisis, especially as there is no set definition. Our analysis might pick up severe market turbulence rather than a well defined textbook crisis but the reality is that as long as it's consistent over time the results through history should be comparable and give us a quantifiable indicator of periods of notably unstable (and negative) fina

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18 September 2017 Long-Term Asset Return Study: The Next Financial Crisis It's almost impossible to have a one size fits all definition of a financial crisis, especially as there is no set definition. Our analysis might pick up severe market turbulence rather than a well defined textbook crisis but the reality is that as long as it's consistent over time the results through history should be comparable and give us a quantifiable indicator of periods of notably unstable (and negative) fina

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18 September 2017 Long-Term Asset Return Study: The Next Financial Crisis It's almost impossible to have a one size fits all definition of a financial crisis, especially as there is no set definition. Our analysis might pick up severe market turbulence rather than a well defined textbook crisis but the reality is that as long as it's consistent over time the results through history should be comparable and give us a quantifiable indicator of periods of notably unstable (and negative) financial markets. We will call our analysis financial shocks to avoid confusion. Our 'financial shock' index is calculated based on the proportion of countries experiencing one of the above conditions in any rolling 12-month period. Given this definition, our indicator for each country is a binary variable that takes on a value of 1 if the country experiences a financial shock and 0 otherwise. Thereafter we aggregate this measure in 2 ways. Our Ira ~SUM is an equally, weighted measure that counts the number of countries suffering from a financial shock in a given month and divides it by the number of countries for which we have data available in that same month (hence each country has an equal weight in the aggregate measure), to get the percentage of countries (for which we have data) which are suffering. Our second measure is a GDP weighted measure that uses the sum of each country's indicator (0 or 1) weighted by the ratio of the country's GDP to the total GDP for which we have data available in a given month. Note that both measures are adjusted for data availability so that our aggregate measures are robust to changes in cross-sectional sample size as new countries enter our sample (as data becomes available). In Figure 12 we show the results for the global economy. We show this both ways with the GDP weighted measure placing a greater emphasis on crises in the larger countries. Figure 13 and Figure 14 then breaks this down by DM and EM economies. [Figure 12: Percentage of Countries facing a Financial Shock .- Equally weighted (Id 1 and GDP eicjilteci (Ugh' 100% 0% Shocks 100% 90% 90% - 80% 80% - 70% 70% - 60% 60% - 50% 50% 40% 40% - 30% 30% - 20% 20% 10% 10% • 0% 0% 0000000000000000000000 8c7, 8gM683S8ScrolVignES8G CN 04 San@ MOW Bs* atoll lino:Si Dett Atlel calculator'. 0%Shock) §i7A ig§g§g§Mailgg§E 0.101 Deutsche Bank AG/London Page 11 CONFIDENTIAL - PURSUANT TO FED. R. CRIM. P. 6(e) DB-SDNY-0084660 CONFIDENTIAL SDNY_GM_00230844 EFTA01384459

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