Crowd-sourcing hedge funds
The wisdom of the herd
A new sort of hedge fund bets on the expertise of amateurs
众包对冲基金
群众的智慧
一种新型对冲基金押注于业余人士的能力

“QUANT” hedge funds have long been seen as the nerdy vanguard of finance. Firms such as Renaissance Technologies, Two Sigma and Man AHL, each of which manages tens of billions of dollars, hire talented mathematicians and physicists to sit in their airy offices and develop trading algorithms. But what if such talent could be harnessed without the hassle of an expensive and time-consuming recruitment process? That is the proposition Quantopian, a hedge fund and online crowd-sourcing platform founded in 2011, is testing. Anyone can learn to build trading algorithms on its platform. The most successful are then picked to manage money. In April the firm announced it had made its first allocations of funds to 15 algorithms it had selected.
“量化”对冲基金长期以来都被视为金融界里的高智商前沿领域。复兴科技（Renaissance Technologies）、双西格玛（Two Sigma）和Man AHL等公司各自管理着数百亿美元的资产，聘请天才数学家和物理家坐在宽敞的办公室里开发交易算法。但假如无需耗资费时的招聘程序便可利用这类人才呢？这正是创立于2011年的对冲基金及网上众包平台Quantopian正在尝试的事。任何人都可以在它的平台上学习创建交易算法。公司而后选出最成功的算法来管理资金。4月，该公司宣布已把首批资金配置给选出的15种算法。
Quantopian would appear to have one striking advantage over its competitors: sheer weight of numbers. The difficulty of hiring and a desire for secrecy limit even big quant funds to a full-time research staff in the low hundreds (Man AHL, for instance, has 120). Quantopian boasts 120,000 members on its platform.
相比竞争对手，Quantopian似乎有一大显著优势：人多势众。招聘的难度，加上公司希望保密，即便是大型量化基金公司也只有一两百个全职研究人员（比如Man AH有120人）。而Quantopian的平台拥有12万会员。

These are amateurs, however, not full-time employees. John Fawcett, Quantopian’s CEO, says many sign up to learn how to apply algorithms to trading; they usually already have experience in coding and modelling in domains outside finance. Few will have their algorithms selected, an honour that comes with a licensing fee of 10% of net profits . The rest can at least use their algorithms to trade their own money.
但这些人都是业余人士，并非全职员工。Quantopian的首席执行官约翰·福西特（John Fawcett）表示，许多人注册是为了学习如何将算法应用于金融交易，他们通常在金融业以外的领域已经拥有编程及建模的经验。极少数人的算法会被看中，但如果有幸被选用，便可获得净利润的10%作为授权费。其余的人至少可以用自己的算法来交易自己的资金。
Mr Fawcett plans both to allocate funds to more algorithms, and to increase allocations to those already picked. There is no dearth of capital. Steve Cohen, a big-name investor who survived an insider-trading scandal at his previous hedge fund, provided some of Quantopian’s venture-capital funding and has pledged up to $250m to promising algorithms on the platform. The firm intends to launch a fund open to other investors this year.
福西特计划配置资金到更多的算法上，同时对已选用的算法追加配置。可投入的资本很充裕。著名投资人史蒂夫·科恩（Steve Cohen）挺过了自己上一只对冲基金的内幕交易丑闻，他为Quantopian提供了一部分风险投资，并承诺对平台上被看好的算法提供最高达2.5亿美元的投资。Quantopian打算今年推出一只对其他投资者开放的基金。
Quantopian-like models have the potential to bring the gig economy to high finance. Most people on its platform hold full-time jobs or are students, earning some income on the side. At least one quant hedge fund has already bet on the trend. WorldQuant’s WebSim platform, like Quantopian’s, offers access to financial data and a way to test ideas, though it is geared towards more basic research. The best performers on WebSim can become paid part-time research consultants, of whom there are now close to 500, nearly as many as WorldQuant’s full-time staff.
Quantopian这类模式有可能把零工经济拓展到涉及巨额资金的高端金融领域。其平台用户大多是在职人士或在校学生，只为兼职赚些外快。至少有一家量化对冲基金公司已经在这一趋势上押注。WorldQuant的WebSim平台跟Quantopian的类似，让人们得以访问金融数据及测试设想，不过该平台针对的是更为基础的研究。在WebSim上表现最佳的人可成为从该公司领取薪水的兼职研究顾问，目前已有近500名，几乎与WorldQuant的全职员工人数相当。

It is still early to judge Quantopian’s allocations (ranging from $100,000 to $3m per algorithm) by their financial return. As a pioneer, it has no obvious comparators. Some algorithms at Quantiacs, a competitor with only around 6,000 members on its platform, have generated up to 40% returns in the past year, but that is with small allocations of capital (Quantiacs has yet to manage outside assets). So the real test for the crowd-sourcers lies ahead: will a deeper talent pool mean better performance, even when serious money is involved?
要以财务回报来评价Quantopian的配置（每个算法管理10万美元到300万美元不等的资金），目前还为时尚早。作为行业先锋，Quantopian并无明显可比的对象。对手Quantiacs仅有约6000名用户，但该平台上的一些算法去年产生了高达40%的回报，不过配置的资金数额较小（Quantiacs尚未尝试管理外部资产）。因此，对众包平台而言，真正的考验仍在前方：当涉及巨额资金时，更大的人才库是否意味着更佳的表现？

【加油+1】