MAKING GREAT RETURNS
让伟大回归
Our returns in 2010 were the bestever—nearly 45 and 28 percent in our two Pure Alpha funds and close to 18percent in All Weather—almost exclusively because the systems we had programmedto take in information and process it were doing it superbly. These systemsworked far better than we could with just our brains. Without them, we wouldhave had to manage money the old and painful way: by trying to weigh in our headsall the markets and all the influences on them and then bring them togetherinto a portfolio of bets. We would have had to hire and supervise a bunch ofdifferent investment managers, and because we couldn’t have blind faith inthem, we’d have had to understand how each one made their decisions, whichwould mean watching what they were doing and why so we could know what toexpect from them, while dealing with all their different personality issues.Why would I want to do that? It seemed to me that that way of investing ormanaging an organization was obsolete, like reading a map instead of followinga GPS. Of course, building our system was hard work—it had taken us over thirtyyears to do it.
Having too much money to manage can hurt performance, since the costs of
getting in and out of positions can be high because being too big can push the
markets. Making over 40 percent in 2010 had put us in the position of having to
return a lot of money to clients who actually wanted to give us more to manage.
We were always careful to stay safely short of being too big, lest we kill the
goose that lays the golden eggs.
Our clients didn’t want theirmoney back—they wanted us to grow it. So we were presented with the puzzle ofhow to maximize our capacity without hurting our performance. We hadn’t lookedat that before, because we’d never had that much money. We quickly discoveredthat if we just tweaked what we did and created a new fund that managed moneythe same way as Pure Alpha but invested it solely in the most liquid markets,our expected returns would be the same and the expected risk (i.e., volatility)only slightly higher.
We programmed this new approachinto our computers, back-tested it to see how it worked in all countries andtime frames, and explained it to our clients in detail so they could thoroughlyunderstand the logic behind it. As much as I love and have benefited fromartificial intelligence, I believe that only people can discover such thingsand then program computers to do them. That’s why I believe that the rightpeople, working with each other and with computers, are the key to success.
Towardthe end of the year, we opened “Pure Alpha Major Markets” and clients invested$15 billion in it. Since then its returns have been as expected—that is, aboutthe same as Pure Alpha’s (actually better, but only slightly). Our clients weredelighted. In fact, this new option was so popular that by 2011 we had to closeit to new investment too.
翻译：
2010年我们以最佳状态回归—接近45%和28% 我们两只纯alpha 基金 份额，收官与18%全天候—差不多独占因为我们过去编制的系统吸收信息并运算的非常好。这些系统比我们只使用我们的脑力工作地好太多了。如果没有他，我们可能还要用古老的、痛苦的方式来管理钱，我想尝试看看在所有市场上我们的智力和所有在他之上的影响，接着把他们集合到一起形成一个债务投资组合。我们将不得不雇佣和监督一大帮不同的投资经理人，因为这些经理人对我们没有盲目的忠诚，我们被迫需要明白他们是怎么做决策的，这意味着监视他们在做什么和为什么这么做，以便于我们能知道能从他们那里期待什么，同时还要处理所有不同的个性化的文件。为什么我会这么做？似乎对我来说那种办法授予或管理一个机构是已经过时的，那样可能花费我们超过30年的时间。
超量的财富需要管理可能会伤害到我的表现，因为进入和离开都会有成本，成本可能很高因为体量太大能推动市场。2010年超过40%的占比迫使我们处于必须为客户带来大量回报的位置—我们的客户会把更多财富交给我们去打理。我们总是非常小心呆在安全地带避免过快的成长太大，免得我们会干出杀鹅取蛋的事情。
我们的客户并不想现在就拿回投资的钱—他们总是想经我们的手变的更多。所以我们总是将我们的能力最大化展示出来而不是破坏客户的印象。在此之前我们都不会看那些的，因为我们以前从未有那么多钱。很快我们就发现如果我们仅仅创建一支新的基金—跟纯alpha一样管理财富-但在易变的市场里赋予他独立的状态，我们期待的回报可能是一样的，而可能的风险（通常是易变的）仅仅高一点点。
我们把这个新应用纳入计算机中，回溯测试看看在任意国家和时间架构中工作的如何，然后详细的给我们的客户解释这一他们能全面理解她背后的逻辑。我从ai中得到的爱和收益已经够多了，我相信只有发现这些事情的人才能编程去做ai。那就是为什么我相信对的人，一起工作，计算机，是成功的关键。
这一年的末尾，我们公开了“纯alpha主要市场”项目，我们的客户大约投资了150亿美金。当然她的回报和预期一样-和纯alpha一样（事实上还要好，但只是一点点）。我们的客户都非常兴奋，实际上，这套新的选项在2011年是如此的流行，我们不得不对新投资关闭它。
读后感：
看到这里，我想你们和我一样大约要问，为什么桥水没有像巴菲特的基金那么出名，我猜是因为桥水大量依靠计算机和程序，也许桥水在西方的经济界并不受欢迎，因为他们显得有点另类，不受欢迎吧。
