kaisa has loads and loads of factors that we can evaluate proforma results on. we selected these for the following reasons. it's the most volatile asset. it's energy. it's currency. it's credit. it's equity. so we picked the big items. that's why you see, you know, some big left numbers here is because we're picking the most serious volatile assets. when they don't do well, what our results would be. >> these are the meaningful ones. we're talking about global equity going down 40% or just to put a perspective, barclays high yield going down 20%. if we assume an average of the spread duration is 4, that means this prep widened by 500 basis points. these are very strong tests. we would like to see, what does it mean for our portfolio. the next page has the results of the same analysis in dollar terms. >> can i ask a question about this? are we just looking at correlations of asset classes, and are we using average over a period of time? how are we coming to this. >> good question. go ahead. >> so we use -- we can configure that as well. the way we use it in kaisa

worked with blackstone asset management to get the aggregate to move to sector, geography, load it into kaisa, and then as susan mentioned, talked through what was the sensitivity or the price movement for those risk exposures that we saw in the absolute return. yes, the portfolio managers would have obviously changed this risk exposure over that year and a half or something. >> our current and -- >> current portfolio exposures. >> current portfolio -- risk exposures from our hedge fund managers. >> i need to add one variable to my comment. we would need to go back, because i was citing our fiscal year returns for those three-year periods. we would need to go back, and it's easy to do, to get our actual returns from march 2000 to october 2009 and compare that to here. i know the results of this are materially better than what we actually experienced during that period. i'll just get you those numbers. >> so that number we talked about, what we actually did during this downturn, during that peak period that is highlighted, that number, you said, is over? >> to be honest, i don't know what it i

i would like to turn it over to susan to introduce kaisa and talk about the example of how we put it together, the processes, the data review, and also thank the amazing responsive partners in this undertaking, and can i would like to acknowledge susan and david, our cofounders and ceo and president. kana is our representative. he's been answering my calls and e-mails over multiple weekends. megan is sitting there, i call her data queen. she knows every data point for multiple portfolios. i thank them for their partnership. >> thank you. nice to meet all of you. i was here a year and a half ago. my name is susan. i'm the president and cofounder joined by dave who is also a cofounder and ceo. for those of you unfamiliar, the platform is designed to aggregate exposures across multi-asset class portfolios, inclusive of hedge funds, private he can wet funds, direct investments, coinvestments, and typically complex portfolios. our entire client base is institutional allocators, like public pension plans, endowments and foundations. our relationship with sfers january in january of 2017. t