創業公司怎樣才能“打倒”彭博終端？
|
????（2）它是很多小眾產品的集合。對于金融數據界來說，每個資產類別（包括其亞種）都有相當的特殊性，人們可以針對每個資產類別做出一個基本上完全不同的產品。這不僅需要深厚的專業知識，也需要大量精力和財力，才能滿足每一個規模相對較小的用戶群（有時搞某一種資產類別的人全球加起來也只有幾萬人）。彭博一開始做的是固定收入數據，這么多年走過來，一路憑借雄厚的財力逐漸攻克了其它資產類別（而且直到今天，彭博的這種努力還在繼續）。所以要挑戰彭博的地位，并不是研制一個“萬金油”式產品那么簡單，而是要投入海量的風險資金，在所有這些小眾領域都打造一個直接的競爭對手。 ????（3）不光是技術之爭。要想大范圍地提供金融數據，并不只是一個純粹的技術問題，所以不是光靠研究出更好的收集和展示數據的技術就能解決問題。至少在現階段，彭博終端背后已經有一張龐大的人力網絡、關系網絡和數據提供商的合同網絡支持它很多年了。 ????（4）它是一個用于執行極為重要的任務的產品。這是很關鍵的一點。在金融界，人們靠數據來做大賭局，所以絕對的精確性和可靠性必不可少。因此人們在試用新產品的時候難免心里會七上八下，尤其當它還是一家創業公司的產品。 ????就像《機構投資人》的那篇文章中所講的一樣，彭博終端業務由于宏觀因素而受到了一些打擊（比如華爾街相關工作崗位的減少，以及全球范圍內由傳統電腦數據向數據饋送轉變）。但是綜上所述，我認為彭博終端短期內不可能被任何創業公司完全“打倒”。而且我認為對于創業公司來說，就算他們能拿到大量風投資金，要想直接與彭博終端的任何核心功能競爭（松綁）都是非常困難的事情。并不是說完全不可能實現，我只是覺得如果創業公司把自己定位得離彭博遠一點，或許有機會摘到一些更容易摘到的果子。 ????金融數據的商機在哪里？ ????雖然我認為創業公司研發出能取代彭博終端的產品的可能性很小【研發出能取代湯森路透（Thomson Reuters）或Factset的產品的可能性也很渺茫】，但我認為在彭博終端的“周邊”和“下方”依然存在可以作為的空間——也就是說去開拓彭博不太可能想去涉足的領域。 ????尤其是我認為如果能把某些精華的互聯網理念和流程（比如網絡、眾包等）以及新技術（大數據）帶到金融數據界，還是有機會的，比如： ????（1）金融網絡/社區。就像彭博終端所做的一樣，如果能把金融數據、分析工具和社區糅合在一起，也許會產生一些商機。資本市場歷來不太有分享的文化（其中有很多微妙之處，我懂的），這有一部分原因是因為金融投資的天性。但是至少在某些領域，隨著數碼一代在機構內部得到晉升，這種文化也會發展變化。這個領域除了早期試水者Stocktwits和Covestor之外（他們主要瞄準非專業群體），現在面向專業人士的社區還包括一開始主要面向買方分析師、但現在已經發展得更廣的SumZero。另外還有稍晚時候一些面世的Quantopian，它是一個算法交易社區，很多科學背景的人和搞數量分析的人都在這里分享算法和策略。早期創業公司ThinkNum認為金融模型應該被分享，而且它想建設一個像“Github”一樣的金融模型庫。大家可以想想，除此之外還有什么可以分享的？ |
????2. It is an aggregation of niche products. In the world of financial data, there is enough specificity to each asset class (and subsegment thereof) that you need to build a substantially different product for each, which requires deep expertise -- as well as a huge amount of effort and money -- to address a comparatively small user base (sometimes just a few tens of thousands of people around the world). Bloomberg started with fixed income data and, over many years, used its considerable cash flow to gradually conquer other classes (still a work in progress, to this day). So disrupting the Bloomberg is not as "easy" as coming up with a great one-size-fits-all product. It would take immense amounts of venture capital money to build a direct competitor across all those niches. ????3. It's not just a technology play. Providing financial data at scale is not a pure technology play, so it is not a matter of coming up with radically better technology to aggregate and display data, either. At this stage at least, there is a whole web of human processes, relationships and contracts with underlying data providers that has been put on place over many years. ????4. It's a mission critical product. This is a key point. In the financial world, data is used to make gigantic bets, so total accuracy and reliability is an absolute must – which makes people cautious when experimenting with new products, particularly built by a startup. ????The Bloomberg terminal business may face macro headwinds, as described in the Institutional Investor piece (dwindling of the number of relevant jobs on Wall Street and a global shift from desktop data to data feeds). However, as a result of the above, I don't see the Bloomberg terminal being entirely "toppled" by any one given startup anytime soon, and I think even competing directly with any of its key functionalities (unbundling) is a tall order for startups, even with access to large amount of VC money. Not that it can't be done – I just think there are lower hanging fruits out there and some real benefit to position away from the Bloomberg. ????Where are the opportunities in financial data? ????While I don't see much opportunity for startups to build a Bloomberg terminal replacement (or a replacement to Thomson Reuters or Factset, either), I think there are fertile grounds "around" and "below" the terminal – meaning in areas where the company is unlikely to want to go. ????Specifically, I believe there are going to be ongoing opportunities to apply some of the quintessential internet concepts and processes (networks, crowdsourcing, etc) as well as new-ish technology (Big Data) to the world of financial data, including: ????1. Finance networks/communities. Like the Bloomberg terminal did, some of the more interesting "adjacent" plays opportunities will marry data, tools and community. Historically, capital markets haven't seen much of a sharing culture (lots of nuances here, I know), which is in part due to the nature of finance investing itself. However, it's going to be interesting to see how, at least in certain areas, that culture will evolve as digital natives rise in the ranks of their organizations. Beyond early entrants Stocktwits and Covestor (which generally target a more casual audience), examples of such professional communities include SumZero, initially for buy-side analysts but now wider, and more recently Quantopian, an algorithmic trading community where scientifically educated people and other quant types share strategies and algorithms. Early stage startup ThinkNum thinks financial models should be shared and wants to the "Github" for financial models. What else can be shared? |
最新文章