導覽亞洲的ESG數據

亞洲是一個多元化的市場,存在社會和文化差異,加上區內各國處於不同的發展階段,意味著我們將需要因應當地情況,調整原本為較先進國家而設的環境、社會及治理(ESG)數據框架。儘管第三方ESG評級可以提供具價值的分析資料,但我們認為傳統的信貸分析依然是無法替代-亞洲的數據挑戰可以為主動型投資經理人提供締造超額報酬的機會。

ESG投資的未來成長與數據息息相關,這已是不爭的事實。根據2019年的一份調查1顯示,受訪者把數據列為更廣泛融合ESG的主要障礙之一(見圖1)。

圖1:推動ESG融合面對什麼障礙?推動ESG融合面對什麼障礙?

對於投資人和基金經理人來說,ESG評級為投資框架提供具價值的分析資料,並可影響投資組合的組成。對於公司來說,ESG評級有助其了解是否已達到期望的ESG影響和成果。因此,近年來第三方ESG評級供應商的數量顯著增加,實在不足為奇。

反過來,這又衍生出其他對投資人來說更為重要的問題。

了解評級背後的含義

有別於財務比率(大多數屬標準化指標,並清楚顯示每個比率所量測的範疇),ESG數據尚未有一個全球通用的分類方法(儘管歐盟在2020年6月發佈了《永續發展金融分類法規例》)。因此,ESG評級供應商就同一個議題作出報告時,也可以透過多種不同的方式作出詮釋和比較。例如,單就多元化而言,重要指標不僅限於性別,還可延伸至包括種族、國籍、教育程度、年齡、殘疾、性取向及就業狀況。同時,不同國家和地區獨特的歷史、政治和文化環境亦會決定哪些多元化問題更為相關。舉例來說,種族問題可能是美國面對的一個主要多元化問題,但對於移民人口眾多的西歐國家來說,多元文化主義卻更為重要。另一邊,中國可能較為關注城鎮與農村之間的差距,而在印度,宗教和種姓制度可能是更重要的多元化指標2

ESG評級供應商如何定義同類組別,亦會影響ESG評級。大部份ESG評級供應商都沒有清晰展示如何定義同類組別,即使同類組別對公司的ESG評級具有重大影響。亞洲方面,許多綜合企業擁有多元化業務,而且業務遍佈多個國家,令情況更為複雜。

此外,ESG評級供應商採用不同的策略以填補數據缺口。舉例來說,某家供應商可能假設缺乏事件數據即代表並無安全問題紀錄。另一家供應商可能會對在受較嚴格監管的國家營運的公司給予較高評分,即使缺乏數據支持。例如,在缺乏數據的情況下,中國大型銀行在管理方面的評分往往低於新加坡的銀行。另一種方法是透過對其他可觀察數據及預測因素進行回歸分析,進而估算所欠缺的數據3

ESG評級對市值規模較小的公司亦可能存在偏頗,這些公司可能缺乏資源提供全面的ESG議題報告。同時,有別於財務數據,ESG數據未經審計的性質亦令人關注報告數據的可靠性和可用性。

這正好說明為何與信貸評級(以標準化的財務比率為基礎)相比,ESG評級(基於上述理由)的差異顯著較大。估計由穆迪與標準普爾作出的信貸評級,兩者之間存在0.9的正相關係數4。ESG評級的情況則不可同日而語。例如,Sustainalytics將印度公司Adani Ports and Special Economic Zone評為ESG風險較低,但MSCI對該公司的ESG評級卻評為CCC(最差級別)。另一方面,穆迪及惠譽則給予該公司BBB-信貸評級,與標準普爾的BB +級評分大致相若。

綜觀上述所有因素,加上ESG評級供應商目前對亞洲投資領域的覆蓋率僅為60%至70%,突顯亞洲面對不少ESG數據挑戰。

圖2:影響ESG評級的因素影響ESG評級的因素

引領亞洲數據之旅

ESG數據標準將繼續進行優化和協調。亞洲方面,亞洲證券業與金融市場協會(ASIFMA)正致力應對ESG數據不足的問題,並提出以下多項建議5

◇ 廣泛趨向以原則為本的全球(或至少區域)分類法

◇ 各司法管轄區與行業之間採取更高及較一致的公司披露標準提高分析標準,鼓勵採取更全面和穩健的策略以進行ESG量測和分析

◇ 為ESG評級供應商制定更高的標準和問責制,其中可能包括法規,以及明確和統一的產品披露規定

◇ 協調不同的ESG標準和框架(例如聯合國永續發展目標),以及在系統層面制定應對氣候變化和銀行監管的政策,包括氣候風險

◇ 公私營部門,以至公司和投資人等持股者維持夥伴合作關係,並就披露和報告標準進行交流對話

解決方案不一定是提供更多數據,而是協商一系列標準化的數據。值得注意的是,有研究顯示,提供較多ESG披露的公司在不同供應商之間的ESG評級差異往往較大6

在此情況下,主動型投資經理人自行建立ESG評估框架至關重要。Mercer是一家提供基金評級並協助資產擁有人挑選基金經理的公司,一直鼓勵基金經理人應自行制定公式,從而釐定ESG權重和評分。此外,Mercer主張把ESG視作投資決策流程的增值部份,毋須專設一支ESG團隊7。這與我們團隊的做法不謀而合。駐新加坡固定收益團隊擁有專有的ESG評估框架,這是我們信貸業務的自然延伸,並利用信貸研究團隊對投資領域內各發行人的深入了解。

非標準化的ESG數據激增,在某種程度上引發多宗「漂綠」(greenwashing)事件,這是一種企業行為,透過宣示關注永續發展的立場,以掩飾其可疑的環境紀錄。即使是奉行強大綠色、社會和永續發展(GSS)框架和原則的GSS標籤債券亦無法避免漂綠風險。正因如此,我們的團隊並無優先考慮把GSS標籤債券納入以ESG為焦點的債券策略,而是傾向採用我們專有的ESG評估框架。我們期望自行透過對ESG風險進行分析,以減低漂綠風險,因這項因素可能會影響企業的長期生存能力和償債能力。

締造超額報酬

儘管第三方ESG評級供應商為ESG投資流程提供重要的分析資料,但投資人需要了解影響這些評級的因素。

同時,ESG數據並非「一體適用」。基金經理可使用不同的策略,把ESG融合至投資流程,亦意味著需要不同類型的ESG數據8

儘管亞洲市場致力應對數據欠缺效率,並繼續提高數據標準,但傳統的信貸分析依然無可取替。畢竟,主動型投資經理人數十年來一直依賴財務數據的詮釋,以發掘獨特的投資機會。由此可見,現今亞洲的ESG數據挑戰可能為主動型債券經理提供締造超額報酬的空間。 

Sources:
1 EIU. Green Intelligence: Asia’s ESG investing, data Integrity and technology. (2019)
2 Cultureplusconsulting.com. “Meaningful metrics for diversity and inclusion”. 2018.
3 “Four things no one will tell you about ESG data”. Sakis Kotsantonis and George Serafeim.
4 “Investing in green ratings? It’s a grey area”. Ross Kerber.
5 Data Challenges and Opportunities for ESG and Sustainable Finance in Asia Pacific. ASIFMA & FOSDA. December 2020.
6 “Why is corporate virtue in the eye of the beholder? The case of ESG ratings”. Dane Christensen. George Serafeim Anywhere Sikochi.
7 ESG in manager selection – Mercer’s perspective. BofA Global Research. January 2021.
8 Solving the ESG data challenge. Factset.
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