雙語閱讀｜智慧型貝塔投資基金是否有效？

IN THE world of investing, everyone is always looking for a better mousetrap—a way to beat the market. One approach that is increasingly popular is to select shares based on specific 「factors」—for example, the size of companies or their dividend yield. The trend has been given the ugly name of 「smart beta」.

在投資領域，世人皆想找到更好的投資策略——想藉此跑過市場。這其中有一種投資策略日益盛行。該策略基於某些特殊「因子」，譬如根據企業規模或其股息收益率選擇股票進行投資組合。人們給這種投資策略起了一個很難聽的名稱，即「智慧型貝塔」（smart beta）。

A recent survey of institutional investors showed three-quarters were either using or evaluating the approach. By the end of January some $534bn was invested in smart-beta exchange-traded funds, according to ETFGI, a research firm. Compound annual growth in assets under management in the sector has been 30% over the past five years.

最近有一項針對機構投資人的調查表明，這些投資人中有四分之三的人使用了智慧型貝塔投資策略或對其進行評估。行業研究公司ETFGI的研究數據顯示，截止今年1月，共有5340億美金用於智慧型貝塔交易所買賣基金。過去五年中，該投資策略板塊下的管理資產年復增長率達到30%。

The best argument for smart-beta funds is that they simply replicate, at lower cost, what fund managers are doing already. For example, many fund managers follow the 「value」 approach, seeking out shares that look cheap. A computer program can pick these stocks more methodically than an erratic human. A smart-beta fund does what it says on the tin.

智慧型貝塔投資策略的精髓在於其可替代基金管理者的工作，且價格低廉。比如，許多基金投資者採用」價值「投資法，尋求看起來廉價的股票組合。這些股票只需一個電腦程序就能挑選出來，比單純的人力更加有效。智慧型貝塔投資策略不負眾望，與宣傳盡皆吻合。

But does it work? The danger here is 「data mining」. Carry out enough statistical tests, and you will always find some strategy that worked in the past. It may be that stocks beginning with the letter 「M」 have outperformed other letters of the alphabet; that does not mean they will do so in future. According to Elroy Dimson of Cambridge University and Paul Marsh and Mike Staunton of the London Business School, researchers have found 316 different factors that might form the basis for a successful investment strategy.

但是，這個策略奏效嗎？它的危險在於「數據挖掘」上面。只要進行足夠的數據統計測試，你就會找到一些過去行之有效的投資策略。可能此前M開頭的股票的業績比其他字母開頭的股票更好，但那不意味著之後也如此。劍橋大學的埃爾羅伊迪姆森（Elroy Dimson）及倫敦商學院的保羅馬什(Paul Marsh)和麥克斯丹頓(Mike Staunton) 指出，研究人員找到了投資策略成功的316種不同因子。

The best-known fall into four groups—size, value (including dividend yield), momentum (buying stocks that have risen in the recent past) and volatility (buying less-risky shares). Research by Messrs Dimson, Marsh and Staunton shows that the size, value and momentum effects have worked across a wide range of markets over many decades. The low-volatility effect (for which fewer data are available) has worked in America and Britain over an extended period.

最為人所知的因子分為四組，分別為規模、價值（含股息率）、動量（即購買近期上漲股票）以及波動（即購買風險更低的股票）。迪姆森、馬什和斯丹頓的研究表明，規模、價值和動量因素幾十年來在各個市場都產生作用。在很長一段時期，低波動值在美國和英國具備影響力。

In the case of momentum, the effect is very large. In a theoretical exercise , an investor identifies the best-performing stocks over the previous six months, buys the winners and sells short the losers (ie, bets that their prices will fall). The exercise assumes it takes a month to implement the strategy each time. In some countries, the return is more than 1% a month; globally, it is 0.79% a month, or nearly 10% a year. That is more than sufficient to make up for any transaction costs.

動量因素的影響則十分明顯。在一次理論演示中，假設實踐該策略每次歷時一個月，一位投資人在過去六個月中持續辨別出運勢最佳股票，買贏賣輸賣空（即賣出股價看跌的股票）。在有些國家，每個月的投資回報率大於1%；而就全球來說，月投資回報率為0.79%，或年投資回報率為近10%。這一投資回報率用於補償任何交易成本都綽綽有餘。

This is a bit of a mystery. Even if markets are not completely efficient, it seems hard to understand how outsize returns can be achieved by looking at something as simple as recent price movements, without clever traders taking advantage until the anomaly vanishes. One explanation may be that the effect can go sharply into reverse; in 2009 a broad-based momentum approach would have lost 46% in the British stockmarket and 53% in America. Any hedge fund that used borrowed money to exploit the momentum effect would have been wiped out.

這一投資有些許微妙之處。即使市場不是完全有效，也很難解釋為什麼交易者無需動用聰明的頭腦利用異常現象，僅靠觀察近期價格變動就能獲得超常回報。其中一個解釋就是該策略可以扭轉影響方向，如2009年時一次廣泛動量方法可以在英國股市跌落46%，在美國股市跌落53%。任何企圖消除動量因素的對沖基金最終都可能血本無歸。

Similarly, smaller companies and value stocks have beaten the market over the long run. Nevertheless, there have been times when such shares have been out of favour for years. The returns from such strategies have been much lower than from momentum (2-4% a year): not enough, perhaps, to induce a patient buy-and-hold strategy among those willing to ride out the bad times.

同理，小公司和價值股從長遠來看搶佔了市場。但是，這一類股票多次出現長期不受青睞的情況。這種戰略的收益遠遠低於動量每年2%-4%的收益率，因此，這一購入觀望的耐心策略可能還不足以吸引那群準備好坦然面對失敗的股民們。

The obvious answer is to select the right factors at the right moment. The obvious question is how to do so. Relying on past performance is risky. A study* by Research Affiliates, a fund-management group, found that a factor』s most recent five-year performance was negatively correlated with its subsequent return. This is probably a case of reversion to the mean. Stocks that perform well over five years are probably overvalued by the end of that period; those that perform badly for the same period are probably cheap.

顯而易見的答案是，在適當的時候選擇正確的因子。明顯的問題是如何做到這一點。依靠過去的表現是有風險的。銳聯資產管理有限公司(Research Affiliates, LLC) 基金管理組的研究發現，一個影響因子最近五年的發展趨勢與其之後的回報率呈負相關。這可能是回歸均值的一個例子。五年來一直看好的股票可能只是該階段高估了；而同時不看好的股票也可能真的很廉價。

Indeed, the publicity given to smart beta, and the money flowing into these funds, will lead to upward pressure on shares exposed to the most popular factors. (Add an extra layer of irony when this applies to momentum stocks.) Investors who believe in the beta mousetrap may find that the rodents have already escaped with the cheese.

事實上，智能型貝塔投資策略所得到的推廣及流向這些基金的錢都可能給最受歡迎因子影響的股票施加上行壓力（這一說法應用於動量因素時又另當別論）。信任貝塔投資策略的投資者有一天可能會發現收益已經悄然歸零，利潤突然消失，正如捕鼠器上的老鼠已經叼著乳酪跑了。

編譯：張美珍

審核：屈揚銘

編輯：翻吧君

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