探索投資新高度

The big question we have been hearing from clients is, ‘How can AI help us invest?’

Hi, I’m Rui Zhao, a portfolio manager within BlackRock’s Systematic Active Equity team.

With so many stocks in the global market, it’s extremely difficult for human investors to analyze all the information available from a multitude of sources on their own, and then extract useful insights of all the companies such as the company’s products, profitability, and growth prospects. That is where the benefit of AI come in, and why we have been using it across our systematic platform.

We began using AI back in 2008 - building infrastructure that accumulate all the big data, and train machines to analyze the data.

We assess a universe of five thousand securities every day, constantly advancing our machine learning technique and evolving the signals that we use to generate alpha more effectively.

These signals can help us identify trending products among consumers, such as products recommended by online influencers, and assess investor sentiment from social media posts across different platforms and languages. We can also spot early red flags in company documents exchanged with regulators, which may indicate a potential negative impact on shareholder value.

So by using AI in our investment process, we can strive to better forecast returns and generate consistent income for our clients.

Over the years we’ve seen the investment landscape evolve dramatically. The industry has tied itself in knots trying to make something which, at its heart should be quite straightforward, into something of astonishing complexity.

They’re trying to solve for multiple competing issues, attempting to deliver consistent alpha while also ensuring acceptable performance volatility relative to a benchmark on a quarterly or annual basis. In order to do this, investors then have to trade frequently to time economic cycles, changes in bond yields, and so on - all within statistical risk parameters. The chances of a misstep whilst trying to juggle these competing factors is astonishingly high. The greatest threat to any portfolio is the risk of being repeatedly whipsawed, and it’s precisely this that leads to so many investors buying high and selling low.

How about we simply redefine our opportunity set and just invest all our capital in the world’s best companies and then leave it there for years, and years, and years. And that’s what the global unconstrained equity fund is. We invest all the assets into those few extraordinary companies that are both great now, and which we believe are highly likely to still be great in 10 years time.

So, if long-term capital growth is the primary objective, then we should just focus on that, and ignore all the noise. We start by completely ignoring the benchmark and then - build a portfolio which adheres to the following objectives:
 - Identify the rare companies that we believe have a very high likelihood of sustaining high returns for a decade and longer.
 - Select a small number of them in a concentrated portfolio to maximise their impact.
 - Hold them for a long time and allow them to compound for years and years.

This is what we mean by unconstrained investing. It’s a deeply fundamental, extremely simple approach designed for optimists who believe that the extraordinary opportunity set offered by equity markets could offer something better than benchmark returns. We therefore aim to invest in the winners. 

亞洲客戶提出的關鍵問題是 , 我們在科技行業看到強大增長 , 若它已經結束或只是噱頭 , 那麼科技行業是否會持續增長 ?

我是貝萊德科技產業投資團隊的負責人 Tony Kim 。

我認為我們才剛剛起步 , 而且這投資主題將會主導這十年餘下時間 。 針對人工智能及其對科技行業所帶來的影響 , 我們在智能發展方面仍處於初期階段 。 我們全方位檢視人工智能 , 當中我們分解人工智能的所有元素 , 從能源到計算 、 軟件 、 模型 、 數據到應用程式 。 然後我們觀察這些類別和子類別 , 並沿著整個系統進行投資 。
我們相信這趨勢將持續整個十年 , 因此科技行業增長絕對不會就此結束 , 事實上 , 這行業趨勢才剛剛開始 。