Insightful investor podcast interviewed Greg Bond, CIO of Man Group 20260609

 

Insightful investor podcast interviewed Greg Bond, CIO of Man Group 20260609
洞見投資人播客專訪英仕曼集團資訊長格雷格·邦德 20260609
 

说话人  說話人
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说话人1  說話人 1
00:00:01
Welcome to the insightful investor podcast，a weekly series that seeks to share industry investment and market insights。Learn more about our show at insightful investor dot org。Today we're joined by Greg Bond，cio at man group，one of the world's largest hedge fund firms with 220 billion dollars in assets under management as of the end of March。The firm was founded way back in seventeen eighty three and now operates across fourteen countries of more than seventeen hundred employees.
歡迎收聽《洞察先機的投資者》Podcast，這是一個每週更新的系列節目，致力於分享產業投資與市場洞見。想了解更多關於我們節目的資訊，請造訪 insightful investor dot org。今天我們邀請到 Greg Bond，他是英仕曼集團的投資長，該集團是全球最大的避險基金公司之一，截至三月底，其管理的資產規模達到 2,200 億美元。這家公司創立於遙遠的 1783 年，目前在 14 個國家營運，擁有超過 1,700 名員工。
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说话人1  說話人 1
00:00:34
In this conversation, we'll briefly explore man groups history, the evolution of systematic and discretionary investing, and Greg's perspectives on alpha technology and the future of active management. We're so pleased to have you join us, Greg. Thanks Alex, really happy to be here.
在這次的對話中，我們將簡要探討英仕曼集團的歷史、系統性與主觀判斷投資的演變，以及 Greg 對於超額報酬、科技和主動管理未來的看法。我們非常高興能邀請你來，Greg。謝謝 Alex，真的很開心能來到這裡。
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说话人1  說話人 1
00:00:49
I'd like to first ask a few quick questions about your firm. So obviously, Man Group's history stretches back more than two centuries. How does leading a firm with. Of history shape the way you think about legacy stewardship innovation and the appropriate time horizon for decision making.
我想先快速請教幾個關於貴公司的問題。很明顯，Man Group 的歷史可以追溯到兩個多世紀以前。領導一家擁有如此悠久歷史的公司，如何影響您對傳承、管理責任、創新以及決策時應有的時間視野的看法？
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说话人2  說話人 2
00:01:08
Yeah, we're very proud of that history having that history particularly you know going through the last several market inflection points. I think that gives us confidence that we can navigate through those things. Building hopefully robust infrastructure and importantly the culture, right? I think having you know different strategies work at different times and having some of that internal diversification, I think helps some of that where you're not just stuck in sort of one mode of investing. And that legacy is important to us going back through time, and then particularly over the last 2030 years where we've got you know a few businesses that have been running for that long and in sort of certain areas and really looking forward to the next phase and hopefully being well positioned to manage whatever happens next because there always seems to be something next of course.
是的，我們對這段歷史感到非常自豪，特別是經歷了過去幾次市場轉折點。我認為這給了我們信心，讓我們能夠應對這些情況。我們致力於建立穩健的基礎設施，更重要的是，建立正確的文化，對吧？我認為，擁有能在不同時期發揮作用的不同策略，以及一些內部多元化，有助於避免你只被困在一種投資模式中。這段歷史傳承對我們來說很重要，可以追溯到很久以前，尤其是在過去二、三十年裡，我們有一些業務已經運行了這麼長時間，並在某些領域深耕。我們非常期待下一個階段，並希望能做好充分準備，以應對接下來發生的任何事情，因為當然，接下來似乎總會發生些什麼。
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说话人1  說話人 1
00:01:52
Yeah, that's always the case. So when you zoom out over man groups evolution, what do you see as the pivotal moments or. Key decisions that most clearly defined what the firm is today.
沒錯，情況總是如此。所以當你回顧曼氏集團的演變時，你認為哪些關鍵時刻或重大決策，最清楚地定義了這家公司今日的樣貌？
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说话人2  說話人 2
00:02:03
Well, I think if I think about the firm and I grew up on the quant side of firm called Numeric, which we were acquired by Man Group back in 2014. And if I look in sort of the decades before that, before Numeric joined, I think it was really an evolution of just broader investment capabilities, whether it was sort of AHL on the trend side. What was GLG on the discretionary side, and then ultimately Newbery joining?
嗯，我想，當我思考這家公司的時候，我是在公司裡量化部門 Numeric 成長起來的，我們在 2014 年被 Man Group 收購。而如果我回顧在那之前的幾十年，在 Numeric 加入之前，我認為那真的是一個更廣泛投資能力的演進過程，無論是 AHL 在趨勢策略方面，還是 GLG 在主動選股方面，以及最終 Newbery 的加入？
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说话人2  說話人 2
00:02:28
So I think the first phase, if you will, of that recent phase is really about building out the investment capabilities, leveraging you know a strong central tech platform, you know centralized operations, centralized sales. So I think from that side, it's a bit about kind of a business diversification piece. But what's really... I think evolved over the decade or so, you know, plus that we've been that I've been at the firm.
所以我認為，近期發展的第一階段，可以這麼說，重點確實在於建立投資能力，利用強大的中央技術平台、集中化的營運和集中化的銷售。所以從這個角度來看，這有點像是業務多元化的一部分。但真正……我認為在這十多年間，也就是我在這家公司任職的期間，所演變出來的東西。
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说话人2  說話人 2
00:02:51
That's also evolved from a kind of a pure business diversification into more of a solution space focus for clients. Can we put those things together that we've built? Up a really good track record into solutions, into one strategy or a few strategies that they that will fit their needs, and so that much more I'd say cross collaboration across those engines. So think about it as man group rather than a GLG numeric or AHL. I think that one of the evolutions of the firm is people have thought about man group historically as sort of tier three different businesses, and the mindsets now shifted to this is man group and this is what we could do.
這也從一種純粹的業務多元化，演變為更聚焦於為客戶提供解決方案的空間。我們能否將我們已經建立起來、擁有優異實戰紀錄的這些能力，整合成解決方案，整合成一個或少數幾個能滿足他們需求的策略？因此，我認為這更像是跨引擎的協同合作。所以，請將其視為整個曼氏集團，而不僅僅是 GLG、Numeric 或 AHL。我認為公司的演變之一，就是人們過去習慣將曼氏集團視為三種不同的業務，而現在的心態已經轉變為：這就是曼氏集團，這就是我們能做的事。
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说话人1  說話人 1
00:03:28
So for listeners who may be. Less familiar with main group. How would you describe its core identity? A little bit beyond.
那麼，對於可能不太熟悉 Man Group 的聽眾，您會如何描述它的核心定位？稍微深入一點談談。
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说话人2  說話人 2
00:03:35
what you just described. I lean towards alpha at scale. So it's important that we generate alpha. We aim for hopefully top quartile and everything that we do. But also do it in a way that actually helps investors at you know at scale, so that it's sort of the alpha times the assets, not just the alpha, not just the AUM, but really that focus on dollars of excess return, which is what which is what I call it, um, and maybe. People call it, and that way you can think about that solves real problems and different ways and different strategy sets work at different times.
就如你剛才所描述的，我傾向於追求具規模效應的超額報酬。因此，產生超額報酬對我們來說至關重要。我們致力於在所有業務中達到頂尖四分位的表現。但同時，也要以一種能真正幫助投資人的方式來實現規模化，也就是說，重點在於超額報酬乘以資產規模，不僅僅是超額報酬本身，也不僅僅是資產管理規模，而是真正聚焦於超額報酬的絕對金額，這是我對它的稱呼，嗯，或許別人也這麼稱呼。這樣一來，你可以思考這種方式如何解決實際問題，以及不同的策略組合在不同時期如何發揮作用。
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说话人2  說話人 2
00:04:08
But it's truly that alpha scale, and if your alpha scale that has downstream repercussions on how you think about technology, how you think about who you hire in the organization, how you organize compliance and legal. So I think one of the nice things about that strategy is it then dictates how you want to position. The rest of your firm and all the different activities that it does.
但這確實就是具規模效應的超額報酬，而如果你的超額報酬具有規模效應，這會對你如何思考技術、如何思考組織內該聘用什麼樣的人才、如何組織法遵與法務部門，產生下游的連鎖影響。所以我認為這個策略的優點之一，就是它會決定你如何定位公司的其他部分，以及它所進行的所有不同活動。
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说话人2  說話人 2
00:04:28
I think it's consistency in that messaging that's really, really powerful. And so that message has gone from a few different kinds of strategies. Now we've done a bit more work on in the private market side and just kind of leveraging that concept out into the outer world. And I think also just having that right culture and a very collaborative culture really to deliver that, you need to have that broad based kind of collaboration and creativity.
我認為，正是這種訊息傳遞的一致性，力量才非常、非常強大。而這個訊息已經從幾種不同類型的策略中傳遞出來。現在我們在私募市場方面做了更多研究，並將這個概念向外推展到更廣闊的世界。而且我認為，要真正實現這一點，還需要有正確的文化和一個非常協作的環境，你需要那種廣泛基礎的合作與創造力。
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说话人1  說話人 1
00:04:52
Alpha at scale sounds like a very reasonable objective, but in my experience, a lot of times those two compete. With one another, those two interests, because as you get larger and you scale, it's harder to generate alpha. So I think it is, even though it sounds very simple in terms of alpha at scale, in practice, it can be very challenging.
大規模創造超額報酬聽起來是個非常合理的目標，但根據我的經驗，這兩者往往會相互競爭。這兩個目標之間存在衝突，因為當你的規模變大、不斷擴張時，要創造超額報酬就會變得更加困難。所以我認為，雖然「大規模創造超額報酬」這個概念聽起來很簡單，但在實務上，這可能極具挑戰性。
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说话人2
00:05:13
Well, yeah, I mean, my dorky answer to that is you could think about an objective function where there's kind of an optimal amount, right? You have one pressure, as you say, of. Of increased assets hurting the kind of your raw alpha, but at the same time your AUM is growing.
嗯，對，我的意思是，我比較書呆子的回答是，你可以把它想像成一個目標函數，其中存在某種最適量，對吧？正如你所說，一方面有資產規模增加，會損害你原始的阿爾法（alpha）的壓力，但同時你的資產管理規模（AUM）也在成長。
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说话人2  說話人 2
00:05:27
So there is conceptually at least a kind of an optimal point right where that's the right size of your firm depending how fast your alpha decays as you raise assets. And so that's important. That's things that that's things we look at.
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说话人2  說話人 2
00:05:39
It's a measurement. It has a lot of uncertainty around it. And if anything, maybe we lean a little bit towards the left side of that AUM curve, maybe running a little bit less AUM, it makes sure that we are delivering that alpha.
這是一種衡量標準，其中存在許多不確定性。如果真要說的話，或許我們稍微傾向於資產管理規模曲線的左側，也就是管理規模稍微小一點，這樣能確保我們能夠創造出超額報酬。
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说话人2
00:05:50
And so that's important. I think there's a few caveats to that broader statement. I think for sure individual strategies should decay at some rate with assets, but there are. places where economies of scale can't start to play into the equation that if you have more assets you can do more things on the technology side maybe you could hire additional diversifying capabilities so there is a little bit of the corporate question on that side as well particularly you put strategies together but i definitely agree at the individual strategy level that principle just definitely holds.
因此這點很重要。我認為這個廣泛的論述有幾個需要留意的地方。我確信個別策略的績效在某種程度上會隨著資產規模擴大而衰減，但確實存在一些領域，規模經濟可以開始發揮作用，也就是當你擁有更多資產時，你可以在技術方面做更多事情，或許可以增聘人手來增加多元化的能力，所以這其中也帶有一點企業層面的考量，特別是在你整合不同策略的時候。但我絕對同意，在個別策略的層面上，這個原則絕對是成立的。
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说话人1  說話人 1
00:06:19
yes certainly you need assets to generate revenues so you can hire the best people. incorporate the best technology. So there's probably some sweet spot in there, as you described. And I guess you can also think of it in terms of alpha in percentage terms or alpha in dollar terms.
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说话人2  說話人 2
00:06:37
Correct. And I think, you know, I get the theoretical answers. You want to think about it in dollar terms, but clearly people in their own portfolios see those percentages and that and that's very critical.
沒錯。我認為，理論上的答案我懂，你應該用美元金額來思考，但顯然人們在自己的投資組合中看到的是那些百分比，而這點非常關鍵。
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说话人2  說話人 2
00:06:45
So you need that's why ultimately my, you know, a simple answer about maximizing dollars of excess return is too simple. You need to again, lean back a little bit on what. What is the alpha? I mean, if we were generating one basis point on a trillion dollars of assets, that would be great, but I'm not sure.
所以你需要——這就是為什麼最終我認為，單純追求超額報酬最大化這個答案太過簡化了。你需要再稍微退一步思考，究竟什麼是阿爾法？我的意思是，如果我們能在數兆美元的資產上創造出一個基點的超額報酬，那當然很棒，但我不太確定這是否就是答案。
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说话人2  說話人 2
00:07:00
On one basis, you know, it is sort of the extreme with a could be interesting outcome. So that's I think most importantly, well, it's a hard problem to crack and you're going to come out with something that's got some uncertainty around it. I think culturally, it's important that you think about it.
從某個角度來看，這可以說是一種極端情況，但可能帶來有趣的結果。所以我認為最重要的是，這是一個難以解決的問題，而你最終得出的結論必然會帶有一些不確定性。我認為，在文化層面上，思考這個問題是很重要的。
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说话人2  說話人 2
00:07:13
So I think that capacity question. Because it's very hard, you know, to go to an investor and sort of sell them one thing, and then ultimately it massively changes over time with the success of that strategy. So I think being very clear and articulate about how you think about capacity upfront.
因此，我認為這個容量問題很重要。因為這非常困難，你知道，去向投資人推銷某個策略，然後最終隨著該策略的成功，它卻隨著時間大幅改變。所以我認為，一開始就非常清楚、明確地闡述你對容量的看法，是很重要的。
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说话人2  說話人 2
00:07:30
And then the other thing that has been very beneficial for folks, and I think as we talk to clients, is that one of the questions around scale also amounts to how much volatility or tracking error does one want in a portfolio. So let's take a classic long-only portfolio: you want to hire manager to attack the MSCI World or S&P 500. And so you can have a very, very active strategy, you know, five percent kind of tracking error relative to that, or you can have.
另外一件對大家非常有益的事情，而且我認為在我們與客戶交流時也是如此，就是關於規模的問題，其中一部分也取決於投資組合中希望承擔多少波動性或追蹤誤差。舉一個典型的純多頭投資組合為例：你想聘請經理人來擊敗 MSCI 世界指數或標普 500 指數。因此，你可以採取一個非常非常積極的策略，比如說相對於基準指數有百分之五左右的追蹤誤差，或者你也可以選擇——
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说话人2  說話人 2
00:08:00
A less active strategy, maybe running one or 2% tracking error, and those are fine. Fine, it's sort of that dial, but I think what's important is that the client's getting the same series of, let's say, alpha models or portfolio manager attention on the discretionary side, and then some of that downstream tracking everything could just be done through portfolio construction. So I think what we find very useful with investors as we sit down is to say here's the menu of alpha sources, alpha ideas.
一種較不積極的策略，或許只承擔 1% 或 2% 的追蹤誤差，那些策略也都不錯。這有點像是一個調節鈕，但我認為重要的是，客戶獲得的是同一系列的，比如說，超額報酬模型，或是來自主動選股方的投資組合經理關注，然後一些下游的追蹤工作，全都可以透過投資組合構建來完成。所以我認為，我們坐下來與投資人交流時，覺得非常有效的一點是，向他們展示這份超額報酬來源、超額報酬想法的菜單。
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说话人2  說話人 2
00:08:27
Here's the kinds of volatilities that one could run or levered or less levered, let's say in the traditional hedge fund side. And let's just have an open conversation about what works. And then that also maps back to fees and other things. So having that dialogue, I think is really, really important.
這是在傳統避險基金領域中，可以操作或運用不同程度槓桿的波動率類型。讓我們就哪些策略有效進行開放式討論，而這也會回過頭來對應到費用結構和其他事項。因此，我認為進行這樣的對話確實至關重要。
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说话人1  說話人 1
00:08:41
So you mentioned AHL and AHL was founded long before systematic investing became mainstream. What would you tell us about AHL and the original insight that made this approach so powerful at the time?
你提到了 AHL，而 AHL 在系統化投資成為主流之前就已經成立了。你能跟我們談談 AHL，以及當時讓這種方法如此強大的最初洞見是什麼嗎？
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说话人2  說話人 2
00:08:53
It's kind of interesting, I think both AHL and then also numeric at about the same time sort of came up AHL very much on the trend. Following taking the you know taking advantage of the behavior of various commodity markets to trend behavioral reasons maybe there's some other sort of economic rationale and hedging behavior things that happen versus active and versus and hedging participants in those markets and so I think a lot of that is the is the insight hey see this behavior that's one thing and then also how do you actually monetize that and how do you build strategies that that are robust and obviously in the early days of some of these insights.
這其實挺有意思的，我認為 AHL 和差不多同時期的 Numeric，在某種程度上都源於趨勢追蹤。就是利用各種大宗商品市場的行為來追蹤趨勢，這背後可能有行為面的原因，或許還有其他某種經濟理據和避險行為，這些現象發生在投機者與避險者參與的市場中。所以我認為，很大一部分的洞見在於，嘿，觀察到這種行為是一回事，然後你該如何真正從中獲利，以及如何建立穩健的策略，尤其是在這些洞見剛萌芽的早期階段。
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说话人2  說話人 2
00:09:26
It's really the insight that drives everything, and then over time competition comes in, and you really have to think about really on execution: do I want to add more and more markets? So I think the key is the evolution not only of identifying what happened but the anomaly, but then also to add more capabilities, extend it across geographies, and I think even on the bottom-up equity side at numeric, it was really ah an insight around animals behavior around earnings announcements and. You know, typically analysts would would upgrade their estimates, but not all the way to where they think it should go.
這正是洞察力驅動一切，隨著時間推移，競爭對手會加入，你就必須認真思考執行層面：我是否要增加更多市場？所以我認為關鍵不僅在於辨識發生了什麼以及異常現象的演進，更在於增加更多能力、將其擴展到不同地理區域，而且我認為即使在由下而上的股票量化方面，最初也是源自於對盈餘公告前後市場行為的洞察。你知道，分析師通常會上調他們的預估，但不會一次調到他們認為應該達到的目標價位。
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说话人2  說話人 2
00:09:56
They're waiting for other other analysts in the market. Change or maybe back in the old days waiting for that whisper number from the company, those kinds of things. And so you had an anomaly there. So that was essentially kind of a trend or momentum following but on analyst earnings analyst revisions that numerick was founded on.
他們在等待市場上其他分析師改變看法，或者像過去那樣，等待公司釋出所謂的耳語數字，諸如此類的情況。因此，你看到了一個異常現象。所以，這基本上是一種趨勢或動能追蹤，但追蹤的是分析師的盈餘修正，而 Numerick 正是建立在此基礎上。
2
说话人2  說話人 2
00:10:12
So I think the stories there are quite similar in the sense there was an anomaly took advantage of it, but then to stay ahead of the game, it really means you have to morph and become stay innovative because I think there are a lot of trend followers that aren't around anymore. There's a lot of bottom up equity quant. That aren't around anymore, and it's really how do you evolve into the into the coming decades?
所以我認為這些故事相當類似，都是發現了異常現象並加以利用，但若要保持領先，就必須轉型並持續創新，因為我認為有許多趨勢追蹤者如今已不復存在。也有許多由下而上的量化股票投資者已不復存在，真正的關鍵在於如何進化，以在未來數十年中生存下來？
1
说话人1  說話人 1
00:10:34
And do you think they're not around anymore because they try to stay true to what originally works, even though that ultimately did not work over time?
你認為他們之所以不再存在，是因為他們試圖堅持原本有效的方法，即使那些方法最終隨著時間推移不再奏效？
2
说话人2  說話人 2
00:10:44
Well, there's a pressure, right? It's important that you have a strong culture, a strong idea of what you want to be as an organization. So it's not, hey, I'm doing trend and all of a sudden I'm going to.
嗯，這確實有壓力，對吧？重要的是，你要有強大的文化，清楚知道自己作為一個組織想成為什麼樣子。所以不是說，嘿，我在做趨勢交易，然後突然之間我就要轉向。
2
说话人2  說話人 2
00:10:54
COMPLETELY CHANGE INTO ANOTHER PRIVATE EQUITY OR SOMETHING, JUST BECAUSE IT SEEMS TO BE DIFFERENT, YOU KNOW. Given my philosophy, given where I want to play, what is the next thing in innovation? What makes sense? So maybe it's instead of looking at just analyst revision activity, I look at other stock fundamentals.
徹底轉向私募股權或其他領域，只因為它看似不同，你知道的。基於我的理念，考量我想投入的領域，下一步的創新是什麼？什麼才是合理的？所以，也許不只是看分析師的修正活動，我還會關注其他股票基本面。
2
说话人2  說話人 2
00:11:13
I start to bring another alternative data set. So it's all linked, and I think that that's important, and particularly in this day of AI. I find it's really important not to change everything.
我開始引入另一套另類數據集。所以這一切都是相互關聯的，我認為這點很重要，特別是在當今這個人工智慧時代。我發現，不徹底改變一切，這一點真的非常重要。
2
说话人2  說話人 2
00:11:25
Because of AI, but really how does AI fit your philosophy? And so as a manager of businesses, as you try to build capabilities, it's really that trade-off of how what is actually innovative in your current lane versus something that's unrelated and you don't have a lot of opportunity to add value. So it's a trade-off.
因為人工智慧，但實際上人工智慧如何融入你的理念呢？所以作為企業管理者，當你試圖建立能力時，這其實是在權衡：什麼是真正在你現有領域中具有創新性的，相較於那些與你無關、且你沒有太多機會增加價值的事物。所以這是一種取捨。
2
说话人2  說話人 2
00:11:41
It's something you work on every day. Maybe sometimes you go a little too far in the diversification front. Or often what can happen in these strategies is that you talk to clients and your clients may not want change in their portfolios.
這是你每天都在努力的事情。有時候，你可能在分散投資方面做得有點過頭了。或者在這些策略中，經常發生的情況是，你與客戶溝通，而你的客戶可能不希望他們的投資組合有所變動。
2
说话人2  說話人 2
00:11:52
Maybe they hired you to be the trend manager or they hired you to be the value momentum quality kind of quant manager or a discretion. Style that's brought on, and so often you can get stuck not wanting to upset your clients either. So that's one of the pros of being in this business as long as we have is you've gone through multiple market environments. But that's also one of the downsides is maybe you have a lot of anchoring, and so that's really the hard part: what is the right amount of change? And we spend a lot of time thinking about.
也許他們聘用你是為了讓你擔任趨勢經理，或是讓你成為價值、動能、品質這類量化經理，又或者是一種被引入的自主性風格。因此，你常常會陷入不想讓客戶失望的困境。這也是我們在這個行業待久了的好處之一，就是你經歷過多種市場環境。但這同時也是缺點之一，也許你有很多定錨效應，所以真正的難題在於：什麼才是恰當的改變幅度？而我們花了很多時間思考這個問題。

1
说话人1  
00:12:18
Do you think trend following and systematic strategies have proven durable across decades and very different market regimes?
您認為趨勢追蹤和系統性策略是否已證明在數十年間及截然不同的市場體制下具有持久性？
2
说话人2  說話人 2
00:12:27
I think we've seen very good differential performance over different regimes. It's not that we get every regime correct. I mean, I think clearly, you know, around trend and some of the strategies there, we haven't really had a sustained equity drawdown since twenty twenty two.
我認為我們在不同體制下看到了非常好的差異化表現。並非我們在每個體制下都判斷正確。我的意思是，很明顯，圍繞趨勢和一些相關策略，自 2022 年以來，我們其實還沒有經歷過持續的股票回撤。
2
说话人2  說話人 2
00:12:40
So it's not a lot of what we've seen and about a lot of these V shaped recoveries have not necessarily been kind to trend, but barely starting. Q3 Q4 of last year, and then into this year we're seeing that kind of more normal behavior. I guess is what you you would expect from trend.
所以我們所見的並不多，而且很多這類 V 型復甦未必對趨勢策略有利，但才剛開始。從去年第三季、第四季，一直到今年，我們開始看到那種更正常的行為。我想這就是你會對趨勢策略所預期的表現。
2
说话人2  說話人 2
00:12:54
If you go back 2018, 19 and 20, what we would call the value winter on the on the system. Somatic equity side, right? There was some adjustments and things that needed to happen in the quant side, but it was also just a tough time for value based investing. So there's these different regimes.
如果你回顧 2018、19 和 20 年，我們稱之為系統性股票端的價值股寒冬，對吧？在量化方面，確實需要做一些調整和改變，但那段時間對價值型投資來說，本來也就很艱難。所以存在著這些不同的市場狀態。
2
说话人2  說話人 2
00:13:10
I think one of the hard parts as a manager and a CIO of the firm is to differentiate, okay, is this strategy underperforming because there's just competitive decay, right? There's just a lot of people doing it, or is there just some cyclical event that's happening that makes it tough for these strategies? And so I think.
我認為，作為一名經理人和公司的資訊長，其中一個困難之處在於要區分，這項策略表現不佳，是因為單純的競爭衰退，對吧？就是有太多人在做這件事，還是說，只是發生了一些週期性事件，讓這些策略變得難以執行？所以我認為。
2
说话人2  說話人 2
00:13:27
The cyclicality can often overwhelm that secular decay, and so it's just spending time thinking about environments: what can we do to be better? Undoubtedly there is kind of general decay. I think people get that in kind of the baseline signals and strategies, and you know our earnings revisions model that I talked about.
這種週期性往往會壓過長期的衰退趨勢，所以就是花時間去思考各種環境：我們能做些什麼來做得更好？無疑地，確實存在一種普遍的衰退。我想人們在那些基礎的訊號和策略中都能體會到這點，還有我之前提到過的我們那個盈餘修正模型。
2
说话人2  說話人 2
00:13:44
You trade it over months; you could wait for your analyst book to come in and type it in by hand. And now some of those things last two to three days, so. You just need to adapt. But in all of those tough periods of a certain strategy, you need to have strong reflection and see if they think you could do better. And maybe improve it and make it more robust the next time around.
你交易它的週期是以月來計算；以前你甚至可以等分析師報告送來，再手動輸入。而現在，有些東西的有效期只剩兩三天，所以你就是需要去適應。但在任何策略面臨艱困時期的時候，你都必須深刻反思，看看他們是否認為你能做得更好。或許可以加以改良，讓它在下一輪變得更穩健。
1
说话人1  說話人 1
00:14:03
It is a really interesting challenge because you start with the assumption that your insight should decay over time as it becomes more widely understood and implemented. But then you have cycles within that natural decay. And so you have to assess at every low point of that cycle whether the underperformance is temporary or if it's more permanent. And so that can be challenging to underwrite.
這確實是個很有意思的挑戰，因為你一開始的假設是，你的洞見會隨著時間推移，被越來越多人理解和採用而逐漸失效。但在這個自然衰退的過程中，又會出現週期性的循環。所以你必須在每個週期的低點，去評估表現不佳究竟是暫時的，還是更為長久的現象。因此，要為這種情況提供保證，確實相當有挑戰性。
2
说话人2  說話人 2
00:14:28
Well the funny part, and again, I make fun of our industry, because when when we're in a period of down, like sort of the downward side for a certain strategy, it's oh, well there been outflows in the space and you know there's just downward pressure because people are selling out of the strategy, but we never come to you and say hey, when all the inflflows are coming in, look at that, the tailwind that's from there. So some of that.
說來有趣，我再開個我們這行的玩笑。當我們處於某個策略表現低迷的階段時，就會說，喔，這是因為這個領域資金外流，你知道的，大家正在拋售這個策略，所以造成了下行壓力。但我們從來不會在你面前說，嘿，當資金大量流入的時候，你看，那才是順風的助力來源。所以，大概就是這麼一回事。
2
说话人2  說話人 2
00:14:46
You need to be reflective on both sides when you're doing well and when you're doing poorly, and be honest about, you know, maybe you can estimate some of those effects of flows both on the good and the bad side. So I think one of the the keys. For us is how do we communicate from it in a transparent way to clients what we think the drivers of that performance are right? And I think that that's that can become more difficult with new technologies, other things that are coming across.
無論表現好壞，你都必須對兩方面進行反思，並誠實面對，你知道，或許你可以估算資金流動在好與壞兩方面所帶來的一些影響。所以我認為對我們來說，其中一個關鍵是，我們如何以透明的方式向客戶傳達我們認為這些績效的驅動因素是什麼，對吧？而我認為，隨著新技術和其他事物的出現，這可能會變得更加困難。
2
说话人2  說話人 2
00:15:13
But I think we spend as much time building the technologies as we do sort of building the tools to explain what's going on. I can't come to you now and say well the AI model told me to do it. That's why we lost a bunch of money that.
但我認為，我們在建構技術上所花費的時間，與我們開發用來解釋狀況的工具所花的時間一樣多。我現在不能跑來跟你說，是 AI 模型叫我這麼做的，這就是我們虧了一大筆錢的原因。
2
说话人2  說話人 2
00:15:26
Doesn't work with people, obviously for obvious reasons. So you need... And I think that's why you kind of tie him back to that strong philosophy. You can always anchor back to your philosophy: 'Here's what happened' and let's be very transparent.
這對人來說行不通，原因很明顯。所以你需要……我認為這就是為什麼你要把他拉回到那個強大的哲學理念上。你總是可以回歸到你的哲學理念作為定錨點：『這就是發生的事情』，然後讓我們保持高度透明。
2
说话人2  說話人 2
00:15:38
I think that's whether that's a long-only strategy, a hedge fund strategy, or strategies of strategies — a lot of the multi-strategy work that we do to make sure that you can be transparent. You know, and that's also. Discretionary, it can be often a little bit easier because you can talk about individual stocks and bonds and other things that have been bought, but also making sure we can do.
1
说话人1  說話人 1
00:15:57
At a high level, how does. Systematic discipline potentially improve investment outcomes. Not obviously, we know about mitigating behavioral biases and human emotion, but it can also enable scale, breadth, and more complex decision making. What would you talk about that?
從宏觀角度來看，系統化的紀律如何可能改善投資成果？顯而易見，我們知道這能減輕行為偏誤和人類情緒的影響，但它也能實現規模化、廣度以及更複雜的決策。您對此有什麼看法？
2
说话人2
00:16:14
Well, I think again there's two camps in the world, and I think they are converging this kind of discretionary versus systematic. They're both, they both have pros and cons. They seem to work a bit differently at different times, which is good, which is naturally diversifying. So.
我認為世界上再次出現兩個陣營，而且我看到他們正在趨同，就是這種主觀判斷與系統化交易的區別。兩者各有優缺點，在不同時期表現也略有差異，這其實是好事，自然形成了分散投資的效果。所以。
2
说话人2  說話人 2
00:16:28
Obviously，some of the benefits of systematic is that these are rules we can show you the rules，it has，it's well tested over various regimes and other things，but you know，it's not changing necessarily on a day to day basis or reacting in the short run。Immediately to serve macro shocks, whereas discretionary can do that. This is a bit more flexible.
2
说话人2  說話人 2
00:16:48
And so that's the trade off between the two sides. You do get, you know, the back testability, other things that comes on the systematic side, but the trade off is somewhat on the short term decision making. And so you go through cycles.
因此，這就是兩邊之間的權衡取捨。你確實會得到，像是可回測性，以及其他系統化這一面所具備的優點，但代價就是在短期決策上會有些影響。所以你也會經歷各種循環週期。
2
说话人2
00:17:00
I remember coming out of 2008, everybody hated systematic and everybody loved discretionary, and then you kind of move into the recent world where systematic's done quite well. We've also seen discretionary for strong performance as well. So these things run in cycles.
我記得 2008 年之後，所有人都討厭系統性策略，偏愛主觀判斷型策略，然後到了近期，系統性策略表現相當出色。我們也看到主觀判斷型策略同樣有強勁表現。所以這些事情都是週期性循環的。
2
说话人2  說話人 2
00:17:14
It's why I'm not in either camp on that side. I think there's a nice blend that can be had. I do worry bringing a bunch of discretionary into a systematic strategy or a bunch of systematic stuff into a discretionary strategy can be a little tricky.
這就是為什麼我不屬於這兩個陣營中的任何一邊。我認為可以有一個很好的融合方式。我確實擔心，把一堆主觀判斷的東西帶入系統化策略，或是把一堆系統化的東西帶入主觀判斷策略，可能會有點棘手。
2
说话人2  說話人 2
00:17:27
Maybe eighty twenty twenty eighty, but never fifty fifty. And I think you'd rather as an investor sitting there to allocate, maybe you allocate. Discretionary systematic on your own rather than forcing you know this concept of quantamental and other things which can be a tricky phrase.
或許是八二分或二八分，但絕不會是五五分。而且我認為，你作為一個坐下來進行配置的投資人，或許你自己去配置主觀和系統化的部分會更好，而不是強行套用你知道的「量化基本面」或其他概念，這些詞彙可能很棘手。
1
说话人1  說話人 1
00:17:42
So you just mentioned this but man group has deliberately built both systematic and discretionary capabilities. Would you talk us through why you feel it's important to not choose just one of those philosophies?
你剛才提到這一點，但 Man Group 刻意同時建立了系統化和主觀判斷的能力。能否談談為什麼你認為不該只選擇其中一種理念？
2
说话人2  說話人 2
00:17:54
What the original impetus I think was to have again back to a very strong technology platform Salesforce operation. All of that to be able to diversify across discretionary and systematic. I think that was sort of the general idea and over time adding more capabilities.
我認為最初的動力，還是要回歸到建立一個非常強大的技術平台 Salesforce 營運體系。這一切都是為了能在主觀判斷和系統化交易之間實現分散投資。我想這大概就是整體構想，隨著時間推移再逐步增加更多能力。
2
说话人2  說話人 2
00:18:11
And I think where we're headed today is a world given the advancements of AI that you can start to see a bit of a convergence between the two approaches where. Discretionary managers can do a bit more back testing, a bit more deliberation on what and make it a bit more repeatable, incorporating new data concepts, all of that. I think you see this on the systematic side that you can build more intelligent models that can be a bit more reactive to the macro regime.
我認為，隨著 AI 技術的進步，我們現在正走向一個可以開始看到兩種方法逐漸融合的世界。主觀型基金經理人可以進行更多回測，對投資標的進行更深入的思考，讓決策過程更具可重複性，並納入新的數據概念等等。我認為在系統化投資方面，你可以建立更智能的模型，使其對宏觀環境的反應更加靈敏。
2
说话人2  說話人 2
00:18:39
So I think we're in a fortunate position. That we've got both, and given the influx of these new technologies could be in a world and sort of going back against what I said earlier about fifty-fifty that you can't really distinguish between discretionary and systematic down the road. I mean this is sort of five to ten years because AI sits in the middle AI.
所以我認為我們處於一個很幸運的位置。我們兩者兼具，而且鑑於這些新技術的湧入，我們可能會進入一個——這有點推翻我之前說的五五波——在未來，你將無法真正區分主觀和系統化投資。我的意思是，這大概需要五到十年的時間，因為 AI 就位居其中。
2
说话人2  說話人 2
00:19:00
Sits in the middle, you start to move away. You know, one of the reasons systematic how people come up on the systematic side is they're typically generally more technical, and so they come out from that band. So discretionary is a bit more fundamental by nature, and think of it as sort of MBA PhD, you know kind of thing.
2
说话人2
00:19:16
I'm an MBA, so I've grown up on the quant side, but I appreciate more fundamental analysis. And now, given that you've removed a bit of that basic, you know, you don't need that extreme technical background now. That you start to focus on people that are the most creative, and you know, obviously the best clients I see today are the ones that are the most creative, the ones that ask the right questions.
我是 MBA 出身，在量化領域成長，但我更欣賞基本面分析。如今，既然已經不需要那麼極端的技術背景，你開始專注於最有創造力的人才，而我見過最優秀的客戶，就是那些最具創造力、能提出正確問題的人。
2
说话人2
00:19:35
And that's exactly the same case on the discretionary side. So it's just now the toolkit has opened up on both sides. And that's important, I think. And that also kind of dictates how you think about hiring now and emphasizing a bit more that creativity, and which is always the hardest for me when I do interviews for folks, whether it's discretionary or systematic. If they've got a good resume in the. Of undergrad, you can see that they would be technically competent.
2
说话人2  說話人 2
00:20:02
They would be good diligent builders of spreadsheets and analyzers of earnings reports, or they'd be good technologists or writing attacking new data sets those kinds of things. But it really takes two three four years to figure out if that person's going to actually be creative. And I'm wondering now if you can sort of emphasize a bit more on the probability of being creative rather than the sort of the floor ceiling effect where maybe in hiring that you want to get a good high floor for somebody so you really lean into their technical capabilities. Now maybe you kind of shoot a little bit more for the moon on the creative side and so you look for more ceiling. So these are really interesting strategic questions for folks on the hiring front and what happens ultimately with some of the AI technologies, large language models in particular.
他們會是優秀勤奮的試算表建構者、財報分析師，或是出色的技術專家，善於處理新的數據集之類的工作。但真的要花上兩、三年甚至四年，才能判斷這個人是否真的具備創造力。我現在在想，你是否可以稍微更強調具備創造力的機率，而不是那種地板天花板效應——也許在招聘時，你想要為某人設定一個較高的地板，所以你會非常倚重他們的技術能力。現在，也許你在創造力方面要稍微更敢於追求突破，所以你會尋找更高的天花板。所以這些對招聘方來說是非常有趣的策略性問題，而最終某些人工智慧技術，特別是大語言模型，會帶來什麼樣的結果。
1
说话人1
00:20:45
Yeah, and it's interesting when you think about it from that perspective where you have the you have the kind of the fundamental analysis side and you add AI to that, and then you have the quantitative systematic side and you add AI to that, and how you could see how it. Could potentially benefit both sides.
是啊，從那個角度來思考確實很有趣，你擁有基本面分析的那一面，然後你把人工智慧加進去；接著你又有量化系統性的那一面，你也把人工智慧加進去。你可以看出這如何可能同時讓兩方面都受益。
2
说话人2  說話人 2
00:21:02
Yeah, it's exciting. And so the key right now for organizations is to get those technologies in the hands of both sets. Don't limit it to just your quants, for example.
2
说话人2  說話人 2
00:21:11
And let people experiment. And I think that's been our approach is let's make it easily accessible, whether it's more through a web based interface or a more technical interface. Ironically, I thought in terms of adoption, we've seen a lot more people do both.
並且讓人們去實驗。我認為我們的做法一直是讓它易於使用，無論是透過更偏向網頁的介面，還是更技術性的介面。諷刺的是，就採用情況而言，我看到有更多人兩種都在使用。
2
说话人2  說話人 2
00:21:27
I thought there'd be groups that would kind of just run to the more straightforward web based interface versus the hard code technical stuff. But a lot of people, because now it's easy to do, easier to do, people kind of lean to actually on both. They lean on both sides. And they also think it's important organization that you don't have vendor lock in on these models. I think every few months one firm is going to you know run to the lead with a different capability, and so you want to have an organization that can scale and change quickly as these new technologies come about and new evolutions of the models.
我原本以為會有一些團隊，會直接奔向更直覺的網頁介面，而不是硬核的技術性操作。但很多人，因為現在做起來很簡單、更容易上手，人們其實傾向於兩者都倚賴。他們兩邊都倚賴。而且他們也認為，組織很重要的一點是，你在這些模型上不能有供應商鎖定的問題。我覺得每隔幾個月，就會有一家公司以某種不同的能力領先群雄，所以你會希望擁有一個能夠隨著這些新技術和模型的新演進，而快速擴展和變革的組織。
1
说话人1  說話人 1
00:21:58
And do you think about. Two different sides helping train those models so they can benefit the entire firm.
你有沒有想過，從兩個不同的面向來協助訓練這些模型，讓它們能夠造福整個公司。
2
说话人2  說話人 2
00:22:04
So there's a couple of ways that that could happen. I think right now where we sit at these technologies, a lot of the IP is in the skill files, right? What you know, sort of the harness if you... They can they call them harnesses. The technology is the horse, but you need a harness on how to move and direct that horse, right? And these harnesses I call them skill files, other things market whatever the phrase is.
所以這種情況可能會以幾種方式發生。我認為，以我們目前所處的這些技術階段來看，很多智慧財產權都存在於技能檔案中，對吧？你所知道的，有點像是那套駕馭方法，如果你……他們稱之為駕馭工具。科技是那匹馬，但你需要一套駕馭工具來知道如何驅動和引導那匹馬，對吧？而這些駕馭工具，我稱之為技能檔案，市場上可能有其他稱呼，不管用什麼詞彙。
2
说话人2  說話人 2
00:22:28
Where you go in that skill, how you want to think about a problem, how does man group want to think about the problem, how does a really good discretionary portfolio manager want to think about a problem so that when somebody is interacting or tackling a new problem, they already immediately as they sit down and interact with the large language model, there's all of this great IP from across the firm that the large language model already knows about. It knows that it. It understands in and out of sample testing, it understands being fooled by different regimes.
當你深入那項技能，你該如何思考一個問題，Man Group 想要如何思考這個問題，一位真正優秀的主觀投資組合經理會想要如何思考這個問題，這樣一來，當有人在互動或處理一個新問題時，他們一坐下來與大型語言模型互動，模型就已經掌握了來自公司內部所有這些寶貴的智慧財產權。它知道這些。它理解樣本內與樣本外的測試，它理解被不同市場體制所愚弄的情況。
2
说话人2  說話人 2
00:22:58
So I think that that. It's kind of boring in one way because it's not as cool as the actual technology, but just how do you go about researching different things and building things is hugely valuable. So I think that's where we've gone.
所以我認為，從某個角度來看這有點無聊，因為它不像實際技術那麼酷炫，但如何研究不同事物並建構東西的方法，其實非常有價值。所以我認為這就是我們發展的方向。
2
说话人2  說話人 2
00:23:11
I technologies have gotten a lot better in the last six to nine months, a lot of excitement, a lot of what I called dashboard building, helping people automate their day to day lives and putting together manager performance, other things. But now it's in that next phase. And can we actually bring it to bear on actual problems, but in a way that you don't have to continually relearn? So I, for example, been working, you know, when I write something.
科技在過去六到九個月進步非常多，有很多令人興奮的地方，也有很多我所謂的儀表板建構，幫助人們自動化他們的日常生活，以及整合經理人績效之類的東西。但現在它進入了下一個階段。我們能否真正將其應用在實際問題上，但以一種你不需要不斷重新學習的方式？所以，舉例來說，當我寫東西的時候。
2
说话人2
00:23:37
Or work or review a research proposal by somebody I've created my own, I guess Craig Bond like person in this large language model that will attack it with things that I would always ask. And then you can also augment it with things like: Hey, I want the best mathematician in the world to review this. I want a high-level multi-strat PM to review.
2
说话人2  說話人 2
00:23:58
So you can create these. Personas, I guess nine or ten personas of things that you like and just have them review your work. And this is very basic stuff and I think anybody could do it, but once you've built that skill, I can then send that out to other people, you know, and I think that's very helpful organizationally that you have this concept across because anybody can sit down and build a dashboard.
2
说话人2
00:24:21
Right, that's great. It's fun, but we don't need a hundred thousand dashboards that all do about the same thing. We actually need to bring it to bear on real problems.
對，這很棒。這很有趣，但我們不需要十萬個功能都差不多的儀表板。我們實際上需要將它應用在真正的問題上。
1
说话人1  說話人 1
00:24:27
As CIO, how do you personally think about diversification of ideas, not just diversification of assets or strategies?
2
说话人2  說話人 2
00:24:35
One of the fears I have in our industry, there's a little bit of. I guess I call it FOMO, right? If you're missing out on various strategies, products, what might be out there, or you see a very successful firm and you want to copy that firm or go in that direction.
我對我們這個產業有個擔憂，有一點⋯⋯我想我稱之為 FOMO（錯失恐懼症），對吧？如果你錯過了各種策略、產品，或是市場上可能出現的東西，或者你看到一家非常成功的公司，就想複製那家公司或朝那個方向發展。
2
说话人2
00:24:52
I think that's very hard to do. You can never quite observe the entire organization you're sitting externally. You can talk to people inside, outside, whatever it might be, but it.
我認為這非常難做到。你永遠無法完全觀察整個組織，因為你是從外部觀察的。你可以與內部、外部的人交談，無論是什麼方式，但就是這樣。
2
说话人2  說話人 2
00:25:00
That's really not the way to set a strategy. It's more about where do you want to be in the marketplace. I like our alpha at scale positioning, and if you take that, that makes some decisions internally very clear.
那真的不是制定策略的方式。更重要的是你想在市場中佔據什麼位置。我喜歡我們「大規模創造超額報酬」的定位，如果你採納這個定位，它會讓一些內部決策變得非常明確。
2
说话人2  說話人 2
00:25:11
I also know over my career, some people work differently. Some people are very good in meetings and you know could be a twenty-person meeting and they are willing to pound the table and make their voice heard. Other people don't necessarily like to do interact that way.
我也知道在我的職涯中，有些人工作的方式不同。有些人在會議中表現非常出色，你知道，就算是一場二十個人的會議，他們也願意拍桌表達自己的意見。而其他人則不一定喜歡用這種方式互動。
2
说话人2  說話人 2
00:25:25
Clearly, when the CIO is in the room or our CEO or whoever it might be, they can also dominate the conversation unknowingly, or maybe they feel like they have to dominate it because they're in the position that they are. So what we try to do in certain places is really make it much more collaborative, allow multiple ways for people to have their opinions heard, systematic engine bottom upside at numeric, for example, we use something called the expert panel. Where people will vote on an idea in an anonymous fashion, everybody sees the comments of what everybody's written, but they don't know who who wrote them, and then you can use that particularly.
很明顯地，當資訊長在場，或是我們的執行長，或任何高層在場時，他們也可能在不知不覺中主導了對話，或者他們可能覺得自己必須主導，因為他們身處在那個位置。所以我們在某些地方試著做的是，讓它變得更具協作性，提供多種途徑讓人們的意見能被聽見，例如系統性的、由下而上、以數據為基礎的方式，我們會使用一種叫做專家小組的方法。在這個小組中，人們會以匿名方式對某個想法進行投票，每個人都能看到所有人寫下的評論，但他們不知道這些評論是誰寫的，然後你就可以特別運用這一點。
2
说话人2  說話人 2
00:26:00
Questions that are sort of 5545 in the voting to try to drive that to 9010 or 1090 right, and try to build some understanding seeing of the people's comments but not with the bias that can come across if somebody walks into the room. You know, if I said hey we got to go do this, those are some subtle things that you can do. A lot of it comes back to collaboration.
在投票中大約是 5545 的問題，試著把它推向 9010 或 1090，對吧，並試著建立對人們意見的理解，但不要帶有那種如果有人走進房間可能會出現的偏見。你知道，如果我說嘿我們得去做這件事，這些都是你可以做的一些微妙的事情。很多都歸結為協作。
2
说话人2  說話人 2
00:26:19
And the other thing I think philosophically for folks to have them work in different parts of the organization, right? So I think that also helps decision making. Because once you've seen the discretionary side, or the systematic side, or even within systematic the research versus the PM side, the analyst side of discretionary, that you start to get an appreciation for where other people are coming from in some of these discussions.
我認為從理念上來說，讓同仁們在組織的不同部門歷練，也是很重要的一點，對吧？所以我覺得這也有助於決策。因為一旦你見識過主觀判斷的領域，或是系統化運作的那一面，甚至在系統化投資裡，研究端與投資組合經理人角色的差異，以及主觀判斷領域的分析師角色，你就會開始理解在這些討論中，其他人是從什麼角度出發的。
2
说话人2  說話人 2
00:26:41
So I think flexibility, movement, collaborations, a lot of just talent development, growth focus, where they can they go in the organization. Sometimes again, as going back to my. When you hire people in an organization, it might take three or four years to figure out what the best fit is.
所以我認為彈性、流動、協作，以及大量的才能培育、聚焦於成長，讓他們在組織內有發展的空間。有時候，這又回到我之前的觀點。當你在一間公司招募人才時，可能需要三、四年的時間才能摸索出最適合他們的位置。
2
说话人2  說話人 2
00:26:56
So maybe you move into a different part of the organization. So that's really. talents hr all of those things are as important as anything else because the people whether it's discretionary or a quant side of the business are super important.
1
说话人1
00:27:09
And I guess increasingly AI may have a voice at the table as well.
而且我猜想，人工智慧在會議桌上可能也會越來越有發言權。
2
说话人2
00:27:14
That's interesting, is AI another employee? Right? You can think of it that way, or you know, some of these these large language models. I think what's important, I think there is a reinforcing effect because of the new technologies and sort of the older ways of doing things, because it might bring in insights that you just didn't observe. It can help push back, but I think when you again going back to design. Sort of the digital version of your organization, it needs to have a consistent culture with what you're doing on the organic side.
2
说话人2  說話人 2
00:27:47
So I think of this where one of the short-term applications and near-term applications is just on the research side, where historically organic researchers kind of digging away on ideas, but could you augment them with kind of their digital counterparts? The digital counterparts. Parts have been trained by the organic parts, right? And you can get the scaling effect whether that's systematic or discretionary.
所以我認為，其中一個短期應用和近期應用是在研究方面，歷史上，有機研究人員一直在埋頭鑽研想法，但你能用他們的數位對應物來增強他們嗎？數位對應物。這些部分是由有機部分訓練出來的，對吧？而且你可以獲得規模效應，無論是系統性的還是自由裁量的。
2
说话人2
00:28:06
And so that's one way that organizations can scale. That's why I'm not... I don't think we can debate this five to ten years from now, but I don't think people are looking to do necessarily job reductions. It's more giving more power to people that are in the organization and getting uplift there because ultimately the scaling benefits. I think could be there if it's done correctly.
因此，這是組織可以實現規模化的一種方式。這就是為什麼我不……我認為我們在未來五到十年內無法辯論這個問題，但我不認為人們必然是在尋求精簡人力。這更像是賦予組織內人員更多權力，並讓他們獲得提升，因為最終的規模化效益，如果做得正確，我認為是可以實現的。
1
说话人1  說話人 1
00:28:29
Would you share some insight about how? Or what effective collaboration may look like when you're also trying to preserve independent thinking and low correlation across viewpoints.
2
说话人2  說話人 2
00:28:41
Yeah, this is a really interesting debate, right? And I think they're different and they're different models. There's some people are highly siloed. That's been very successful. I think people that have been on the very end of the very sharp end of collaboration have also been successful. So I'm not sure there's.
是啊，這確實是個很有意思的辯論，對吧？我認為存在著不同的模式。有些人高度專業分工，這種模式也非常成功。我認為那些極度傾向於協作的人，也同樣取得了成功。所以我不太確定是否有絕對的...
2
说话人2  說話人 2
00:28:55
One right answer depends on what your organizational philosophy is. I think it's important. And that if you're going to be in a siloed world, don't hire a bunch of collaborative people.
一個正確答案取決於你的組織理念是什麼。我認為這很重要。而且，如果你要處於一個各自為政的世界，那就不要雇用一群善於協作的人。
2
说话人2  說話人 2
00:29:04
And if you're in a collaborative world, not to hire people that are really into their into their PNL and you know, more on the kind of called mercenary side, whatever you want to describe it. Again, all reasonable models, all reasonable human behavior, everything, you know, is shown a lot of success. I think we've leaned more on the on the collaboration side.
而如果你處於一個協作的世界，就不要雇用那些非常在意自己損益表的人，你知道，就是比較偏向所謂傭兵心態的人，不管你想怎麼形容。再說一次，這些都是合理的模式、合理的人類行為，所有的一切，你知道，都展現了許多成功案例。我認為我們比較傾向於協作那一邊。
2
说话人2  說話人 2
00:29:20
I think part of that is just. THE EVOLUTION OF THE FIRM. I, I do go back and forth with myself if, if I have one idea I want to explore as a firm. Is it better to have two teams work on it, and they may come up with a better answer sort of individually that you then bring back together? But the opportunity cost is we could have looked at two ideas.
我認為這部分只是公司的演進過程。我確實會反覆思考，如果我有一個想在公司探索的想法，讓兩個團隊同時進行，他們各自可能會得出更好的答案，然後你再把成果整合起來，這樣會比較好嗎？但機會成本是，我們本來可以研究兩個不同的想法。
2
说话人2  說話人 2
00:29:40
And is that better to have one team per idea, and then you can do two ideas, or do you have two teams on one idea, which means one idea, and sort of this. concept of scale. So that's a question.
那麼，是每個點子由一個團隊負責，這樣你就可以做兩個點子比較好，還是讓兩個團隊做同一個點子，這意味著只做一個點子，以及這種規模化的概念。這是一個問題。
1
说话人1  說話人 1
00:29:53
So you talked about this earlier, but multi strategy investing, it's become one of the dominant models in hedge funds. From your perspective, what problem does a multi strategy platform solve that perhaps singles strategy funds may struggle with?
所以你之前談到過這個，但多重策略投資，它已成為避險基金中的主流模式之一。從你的角度來看，多重策略平台解決了什麼單一策略基金可能難以應付的問題？
2
说话人2  說話人 2
00:30:08
It's an interesting thing because you said multi strategy platform, and I think that's very much how people think about multi strats today, kind of capital M capital S. I bring together several hundred portfolio managers, whatever it might be, and I think that is one model, and that's been a very successful model, but I think it's not the only way.
這很有趣，因為你提到了多重策略平台，我認為這正是現今人們對多重策略基金的主要看法，也就是那種大型的、集合數百位投資組合經理人的模式。我認為這是一種模式，而且一直以來都非常成功，但我覺得這並非唯一的方式。
2
说话人2
00:30:26
To think about multi strategies, like move into little M little S, having multiple strategies in one vehicle, one fund, what have you, has some advantages that investors and allocators can't necessarily do on their own. Okay? So forget what's inside the multi-strat for a second because I think that's you know there's differentiation there, but just the structure.
2
说话人2  說話人 2
00:30:45
So one as an individual allocator maybe you could allocate to five to ten hedge funds. On your own, right? And that's people have done that in the past.
2
说话人2
00:30:55
You know, fund to funds have come in to help manage some of that. But what are the downsides? Well, you have. To get to know five to ten portfolio managers and firms very well, it's a little bit hard maybe to move capital across those five to ten strategies. Maybe there's lockups. It's also just everybody has investment committees.
你知道，組合基金已經介入協助管理其中一些事務。但缺點是什麼呢？嗯，你必須深入了解五到十位投資組合經理人及其公司，要在這五到十種策略之間調度資金可能有點困難。或許還會有閉鎖期的限制。而且，每個人都有自己的投資委員會。
2
说话人2  說話人 2
00:31:12
It's also hard that hopefully these five to ten hedge funds that you're hiring have low correlation with each other. That's great, but if I put them together, maybe I don't have enough volatility to make it worth my while, or at least whatever dollars I'm putting in, maybe not getting as much efficiency. And what you'd maybe like to do is leverage that, but that can be hard if you've got five to ten separate.
2
说话人2  說話人 2
00:31:32
A fund investments. And so the theoretical benefits of multi strat little and little S is that okay, well you can hire a firm to go out and internally build those capabilities internally find. YOU KNOW, A SOURCE ADDITIONAL UNCORRELATED CONCEPTS AND THAT COULD BE DISCRETIONARY, IT COULD BE SYSTEMATIC, IT COULD BE ALL KINDS OF.
一種基金投資方式。因此，多重策略（multi strat）理論上的好處在於，你可以聘請一家公司，由他們去外部或內部建立那些能力，尋找更多不相關的投資概念，這可以是主觀判斷型的、系統化的，或是各種類型都有。
2
说话人2
00:31:54
different ideas，and so the pros are that you can bring that together，that the manager of that fund. Can then allocate quite quickly across new managers, different risk regimes, other things. They can see the whole risk of the portfolio in one fell swoop, rather than sort of relying on monthly reports and then trying to aggregate.
不同的想法，所以優點是你可以把它們整合起來，讓那個基金的經理人能夠相當快速地在新的經理人、不同的風險機制和其他事物之間進行配置。他們可以一次性地看到整個投資組合的風險，而不是依賴每月報告然後再嘗試彙整。
2
说话人2  說話人 2
00:32:12
So you've got a lot of hyper detail and what's in the portfolio, you can be quite nimble. And then importantly, if it is uncorrelated, you can also that manager can manage the leverage of that fund so that you get your. Volatility back up to what you may have had on a single fund before, maybe five or six percent, whatever that might be.
所以，你對投資組合中的細節瞭若指掌，可以相當靈活地操作。而且重要的是，如果這些策略彼此不相關，那麼該經理人也可以管理基金的槓桿，讓你的波動率回到你之前投資單一基金時的水準，也許是 5%或 6%，諸如此類。
2
说话人2  說話人 2
00:32:28
In certain cases, maybe you want even more volatility and sort of moving that would depend on some of the content. Hey, maybe you want to take that multi-strat and put it on top of the S&P 500 and like a portable alpha type. So there's a lot of flexibility.
在某些情況下，或許你希望追求更高的波動性，而這種調整會取決於部分內容。嘿，也許你想把多重策略疊加在標普 500 指數之上，形成一種可攜式阿爾法的配置。所以這裡有很大的彈性空間。
2
说话人2  說話人 2
00:32:41
So the downside obviously relying on this manager to put this together in a very efficient way. It also you lose some maybe some transparency, or what if you're buying into a multi-strat what's actually in there? And then there's this other part around you know cost and what is the the cost of of supporting that that infrastructure.
所以缺點顯然是依賴這位經理人以非常有效率的方式來整合這一切。你也可能會失去一些透明度，或者當你買進多重策略時，裡面究竟包含了什麼？然後還有另一個層面，就是成本問題，以及支撐那套基礎架構的費用究竟是多少。
2
说话人2  說話人 2
00:33:00
So there's a lot of pros. There can be cons, but I think the important part is there's not just one way to do multi strat. And I think what you're seeing in the place today in the spectrum is differentiation of what's there.
所以有很多優點。也可能有缺點，但我認為重點在於，做多重策略基金不只有一種方法。而且我想你現在在這個領域看到的情況，正是各種做法的差異化所在。
2
说话人2  說話人 2
00:33:13
Some are a bit more quant, maybe some are more discretionary, some are more liquid, some are less liquid. So that profile has changed and augmented. And I think the people that. might be getting in trouble or have had difficulty in the space is really going back to that fomo side of just trying to find a firm that they want to emulate and go out and copy that exactly. I think if they have some self-reflection about where you want to fit in that spectrum.
有些基金可能更偏向量化，有些或許更偏向主觀判斷，有些流動性較高，有些流動性則較低。所以這種組合樣貌已經改變且擴增了。而我認為，那些可能在這個領域陷入困境或遭遇困難的人，其實問題都回歸到那種害怕錯失（FOMO）的心態，只是一味地想找到一家他們想要仿效的公司，然後出去完全照抄。我認為，如果他們能自我反思，想想自己想在這個光譜的哪個位置立足，情況就會不同。
1
说话人1  說話人 1
00:33:35
I know technology has always been a part of man group's dna. How do you think about technology as a strategic advantage rather than just a tool?
我知道科技向來是曼氏集團基因的一部分。你如何看待科技作為一種策略優勢，而不僅僅是一個工具？
2
说话人2  說話人 2
00:33:44
So going back to my early days of my career, I wrote cases and did work with Michael Porter at Harvard Business School around strategies in the competition and strategy group at Harvard Business School and. And one of his big points was there's a difference between operational effectiveness. Strategy, you know, operational effectiveness is doing things better and better.
2
说话人2
00:34:04
Strategy is actually making choices, you know, which products and services, how do you want to think about the market pricing volume? All of those kinds of things because it's hard to do everything. And so if you... The technology in and of itself is not necessarily a competitive advantage, right? Everybody's going to continually invest there, get better and better, right? I think if you go way back to the.
策略其實就是做選擇，你知道的，要提供哪些產品和服務，你如何看待市場的定價與數量？所有這些事情，因為你很難什麼都做。所以如果你……技術本身不一定就是競爭優勢，對吧？每個人都會持續在那方面投資，不斷進步，對吧？我想如果你回顧很久以前的。
2
说话人2
00:34:25
The Japanese auto manufacturers in the eighties, right? They were very, very good at operational effectiveness. That was that operational effectiveness was quickly copied around the world, right? So it's hard to maintain that.
2
说话人2  說話人 2
00:34:35
So the key is how does the technology fit into the strategy? And therefore, you make choices on your tech platform, right? If it's a single strategy fund, the firm has one fund. Right, if they have multiple PMs, but it's basically one fund that leads to one level of complexity, right? Sort of a narrower complexity in terms of what the product that you're supporting.
所以關鍵在於，科技如何融入策略之中？因此，你會根據策略來選擇你的技術平台，對吧？如果是單一策略基金，公司就只有一支基金。對，即使他們有多位投資組合經理人，但基本上就是一支基金，這會導致一種層級的複雜度，對吧？就你所支援的產品而言，這屬於一種範圍較窄的複雜度。
2
说话人2
00:35:00
But maybe you need to have broader capabilities for all the PMs on your platform, if you're offering many different kinds of strategies, different asset classes, and you're doing a lot of bespoke work for clients that has a different impact and concept on your tech platform. So it's really important that you align those, and particularly now with the development of AI. That you need perfect alignment and that allows you then to have AI and large language models digested more efficiently through the organization.
但如果你在平台上提供多種不同策略、不同資產類別，並為客戶進行大量客製化工作，那麼你的平台可能需要為所有產品經理提供更廣泛的能力，這對你的技術平台會產生不同的影響和概念。因此，讓這些保持一致非常重要，尤其是在人工智慧發展的當下。你需要完美的協調一致，這樣才能讓人工智慧和大型語言模型在組織內更有效地被消化吸收。
2
说话人2  說話人 2
00:35:27
So just be on the lookout for people radically changing their their tech stack somehow because of AI. No, no, it's only the tech stack should evolve with the strategy and not the other way around. And I think that's important.
2
说话人2  說話人 2
00:35:41
I think concepts around being flexible with your technology, and let's not forget, even with all of the great AI technology that have been developed, this goes back to your data management. That's the most important thing, and I think eventually you'll see a lot of AI models that will be open sourced other things. So it really sits back on how your your data is stated.
我認為，在技術上保持彈性的概念很重要，而且別忘了，即使現在開發出這麼多優秀的 AI 技術，最終還是要回歸到你的數據管理。那才是最重要的，而且我認為，你終究會看到許多 AI 模型走向開源或其他形式。所以，關鍵真的在於你的數據狀態如何。
2
说话人2  說話人 2
00:36:00
Managed and protected. And that moat, I think, that kind of competitive advantage will sit there for firms that are very, very good with their data. So let's not forget about that kind of very old school block and tackling thing is how do I manage all of the data I have organizationally?
妥善管理並受到保護。而我認為，那道護城河，那種競爭優勢，將會存在於那些極其擅長處理數據的公司身上。所以，我們別忘了那個非常老派的基本功：我該如何管理組織內所有的數據？
1
说话人1  說話人 1
00:36:13
I guess one way to think about the potential impact of AI is on one hand, it may help you do what you're already doing, producing the same thing more efficiently. And on the other, maybe it helps you create new things to produce and new alpha to generate.
我想，思考人工智慧潛在影響的一種方式是，一方面，它或許能幫助你更有效率地完成你已在做的事情，產出相同的成果。另一方面，它或許能幫助你創造出新的產品，產生新的超額報酬。
2
说话人2  說話人 2
00:36:29
And I think that's where we're, you know, in terms of some of the training and as we go through in the broader company, how people think about AI not as exactly that productivity piece, but also kind of a partner in the journey along researcher creative endeavors. So can you create goes back to my persona concept, right? And that sort of research partner learning how I mean the prompt engineering is really, really critical.
我認為這就是我們在進行一些培訓時，以及在整個公司範圍內推展時，人們如何看待人工智慧，不僅僅是將其視為提升生產力的工具，更是研究創意過程中的一種夥伴。所以，能否創造，這又回到了我的人格概念，對吧？那種研究夥伴的學習方式，我的意思是，提示工程真的非常非常關鍵。
2
说话人2  說話人 2
00:36:51
How you interact, you can't just say make me make me more alpha right? That doesn't really work very well. It's like a thought partner right? That has.
你如何與之互動，你不能只是說「讓我創造更多超額報酬」，對吧？那樣效果其實不太好。它更像是一個思想夥伴，對吧？它具備……
2
说话人2  說話人 2
00:37:01
That's a great way to describe it, and I think that takes some thinking in how to do that and which task, which model you want to use for a given task. There's all of that kind of interesting stuff, but even the models that are now whatever one or two generations old are still really, really good. So yeah, I think we just need to be better users of those technologies, I think.
這是個很棒的描述方式，而我認為這需要一些思考，去琢磨該怎麼做，以及針對特定任務，你該選用哪一種模型。這其中有很多有趣的地方，但即使是那些現在已經是一、兩個世代前的模型，依然非常、非常好用。所以，是的，我認為我們只需要成為這些技術更好的使用者，我是這麼想的。
1
说话人1  說話人 1
00:37:22
Yeah, it is interesting. Like the way you frame the question, I think is perfect, which is if you just go to an AI and say, 'Create help me figure out how to create more alpha,' and you go to a person and you say, 'Help me create more alpha,' but you put the two together and you say, 'Let's solve this problem together,' and they go back and forth with idea sharing and challenging one another. You could see why adding the two together could be more beneficial.
對，這很有趣。我覺得你提問的方式非常完美，也就是說，如果你只是去找一個 AI 說：「幫我想辦法創造更多超額報酬」，然後你去找一個人說：「幫我創造更多超額報酬」，但你把兩者結合起來，說：「我們一起解決這個問題吧」，然後他們一來一往地分享想法、互相挑戰。你就能理解為什麼把兩者加在一起會更有益處。
2
说话人2
00:37:47
And what's really, really important I find when I do this is let the technology know as much about you as possible. Load up as many documents, things you've written, how your firm approaches whatever the topics are, because that context. is very very important，and I think even in certain cases，you know，some of the newer models，you can actually talk into the large language model，so talking，you get more context than maybe you're just sitting there and typing，so，but more information you give it。THE MORE LIKELY YOU'RE GOING TO GET AN ANSWER THAT'S PRODUCTIVE.
1
说话人1  說話人 1
00:38:15
AND SO WHEN YOU THINK ABOUT AI AND LARGE LANGUAGE MODELS, WHAT EXCITES YOU THE MOST AT A CONCEPTUAL LEVEL?
2
说话人2
00:38:21
WELL AGAIN, WHEN IT FIRST CAME OUT. you know i was particularly on the systematic side maybe less excited only in the sense that you we already do a lot of reviews of of analyst report it's been using ai for many many years in some ways it's letting the competition catch up correct and then i'd say over the last eighteen months. This kind of partner or thought partner part.
話說回來，當它剛問世時，你知道，我特別是在系統性方面，可能沒那麼興奮，只是因為我們早已大量運用 AI 分析研究報告，這方面我們已經做了很多年了。某種程度上，這只是讓競爭對手迎頭趕上。然後，我會說在過去十八個月裡，出現了這種夥伴或思考夥伴的角色。
2
说话人2  說話人 2
00:38:42
It's really, really improved partly because the technology has also the way we use it has improved and interacting with it. So that's I think very exciting. The ability to use it to help you think and go through problems and also try things you may not have been able to do in the past because it would have taken too much time.
2
说话人2  說話人 2
00:38:57
So just one of the things I like to do. Approach problems is like this concept of ensemble thinking, which is you bring different ways of doing it together and sort of average across them rather than picking one way or another to do it. That could be a portfolio allocation question.
這就是我喜歡做的一件事。處理問題的方式，就像這個「集成思維」的概念，也就是你把不同的做事方法匯集在一起，然後在某種程度上取其平均值，而不是只選擇某一種方法。這可能是一個投資組合配置的問題。
2
说话人2
00:39:11
It could be a model question. It could be how do we want to allocate, you know, across discretionary manager, whatever it might be. And so. It allows you to kind of open up.
這可能是個模型問題。也可能是我們該如何在全權委託經理人之間進行配置之類的問題。所以，這讓你得以拓展視野。
2
说话人2  說話人 2
00:39:21
Your mind a bit on how to approach it, and I also find it's very good as you go through recording your thoughts in that research process of kind of creating a live document or living document as you attack these things, because then you can go back and look at it: How did I get to this point? That's exciting for folks. And I think the.
你對於如何處理這個問題有一些想法，而且我也發現在研究過程中記錄你的想法，建立一份動態文件或活文件，在你處理這些事情時非常有用，因為這樣你就可以回過頭去看：我是如何走到這一步的？這對大家來說很令人興奮。而我認為那...
2
说话人2  說話人 2
00:39:41
The question, and as we get the models get better and better, at what point do you switch to the outsource? You take an open source model, bring it in-house, and then start to train your own things. I think the smaller models trained over your own work is actually might be a very productive thing going forward.
問題在於，隨著模型愈來愈進步，我們何時該轉向自行開發？採用一個開源模型，帶回公司內部，然後開始訓練自己的東西。我認為，針對自身業務訓練的小型模型，未來可能極具生產力。
2
说话人2  說話人 2
00:40:00
Which you could see in the next couple of years, rather than off the shelf. And I know a lot of the providers out there building very specific agents, you know finance agents, other things. But you could imagine a world where you don't necessarily need that. You can the models that are open source are powerful enough that you can actually build something for your own own use.
你可能在未來幾年內看到，與其使用現成的方案，不如自行打造。我知道很多供應商正在開發非常特定的代理，像是金融代理或其他領域的代理。但你可以想像一個世界，在那裡你未必需要那些東西。開源模型已經夠強大，你實際上可以為自己的用途打造專屬工具。
1
说话人1  說話人 1
00:40:20
Yeah, if you can incorporate some of your proprietary insights into the model that others don't have access to, you could see how that could create an edge.
沒錯，如果你能將一些他人無法取得的專有洞察融入模型中，你就能看出這如何能創造出優勢。
2
说话人2  說話人 2
00:40:30
Absolutely. I think we've got a lot of history doing that. I mean, I think a lot of the firms that do. Traditional kind of machine learning and other things, they often start with the standard open source package or whatever, and then you put your own IP around it.
當然。我認為我們在這方面有很長的歷史。我的意思是，我認為很多公司都是這樣做的。傳統的機器學習和其他技術，它們通常從標準的開源套件或類似的東西開始，然後你再圍繞它建立自己的智慧財產權。
2
说话人2  說話人 2
00:40:45
And I think the other nice thing is you do bring in somebody's models on discretionary side in particular, right? You can start to train that a bit more with your human data, right? And I think that's to be very reinforcing for a portfolio manager on discretionary side.
我認為另一個好處是，你確實引入了某人的模型，特別是在主觀判斷方面，對吧？你可以開始用你的人類數據對其進行更多訓練，對吧？我認為這對主觀判斷方面的投資組合經理來說會非常有強化作用。
1
说话人1  說話人 1
00:40:58
Man, if you think about AI feeds. UM DATA AND IF WHAT IS PUBLICLY AVAILABLE ALL OF A SUDDEN IS EASILY ACCESSIBLE BY EVERYONE, THEN IT'S THE DIFFERENTIATED DATA THAT COULD BE THE SOURCE OF FUTURE ALPHA.
2
说话人2
00:41:11
DIFFERENTIATED DATA. UM ONE OF THE QUESTIONS I WE TALK ABOUT QUITE A BIT IS WILL AI LET PEOPLE MAKE BETTER OR WORSE DECISIONS? Right on the one hand, you should make better decisions, but then you can have more people trying to make decisions in the space because it is so democratized.
差異化數據。我們經常討論的一個問題是，AI 究竟會讓人們做出更好還是更差的決策？一方面，你理應能做出更好的決策，但另一方面，由於 AI 如此普及，可能會有更多人試圖在這個領域做出決策。
2
说话人2
00:41:29
And I don't know how it's going to affect ultimately policy making decisions as well, which ultimately have a huge impact on the market. So it's not clear to me that we'll make better or worse decisions. It might create more alpha opportunities because of that. So that's one way to think about it because I do get questions around is everybody just going to think the same way. And I think well your point having more data, different data that's going to help. But also, the way you deploy the technology is just a lot of different ways to do it that will create some dispersion, and there will be bad uses of the technology in terms of bad decision making that could come up come out of it. So it's going to be a very interesting, you know, next decade.
1
说话人1  說話人 1
00:42:04
I think the interesting part about what you just described is, I think it's important to keep in mind that better and worse decisions are relative metrics, and you know, you can you can argue better decisions are made today than 50 years ago, but it's relative to the higher level of expectations. So so maybe AI allows us to in. In absolute terms make better decisions, but you have to think of it relative and is it better relative to others? Is it worse relative to.
關於你剛才描述的，我認為有趣的部分在於，我認為重要的是要記住，更好和更差的決策是相對的衡量標準，你可以說，現在的決策比 50 年前更好，但這是相對於更高的期望水準而言。所以，也許 AI 讓我們能夠在絕對意義上做出更好的決策，但你必須從相對的角度來思考，相對於他人，這是更好還是更差？
2
说话人2
00:42:34
others with a higher bar? The society benefits from better decision making in general, but the dispersion, you know, the sort of it makes it harder and harder for the people to add value above and beyond that. Exactly. And that's the nature of what we do, which is why it makes it fun.
其他人門檻更高？整體而言，社會會因更好的決策而受益，但這種分散性，你知道，會讓人們越來越難創造出超越平均的附加價值。正是如此。而這就是我們工作的本質，也是它有趣的原因。
1
说话人1  說話人 1
00:42:49
So the other thing that I think is interesting is we obviously live in a period of great uncertainty, and oftentimes investors feel very uncomfortable in periods like that. Do you think that can actually. Be healthy for active management.
2
说话人2  說話人 2
00:43:02
I think we're in a really good environment for active management. I think you could argue that, you know, coming out of the GSC and the lower interest rate environment, you know, there wasn't a lot of dispersion in different things, different classes, you know, cash was zero and it was really, hey, I should just maybe buy equities and it'll be fine. And what we've seen as we've gone into a different rate regime.
我認為我們正處於一個對主動管理非常有利的環境。我認為你可以這樣說，你知道，在走出全球金融危機和低利率環境後，你知道，不同事物、不同資產類別之間沒有太多差異，你知道，現金是零，而且真的是，嘿，我或許應該只買股票，這樣就沒事了。而我們看到的是，當我們進入一個不同的利率體制時。
2
说话人2  說話人 2
00:43:24
We've seen better opportunities for alpha. So I think that that also manifests in better risk management hopefully, right? So I think one of the reasons you see some of the data maybe on some of the multi strats have done quite well is that ability maybe to do both the alpha and the risk management a bit more effectively in the market.
我們看到了更好的超額報酬機會。所以我認為，這也希望能在更好的風險管理中體現出來，對吧？我想，大家看到某些多策略基金的數據表現相當出色，其中一個原因可能就是它們在市場中更有效地同時掌握超額報酬和風險管理的能力。
2
说话人2  說話人 2
00:43:42
Of course, that's brought in a lot of extra capital into the space as well. So you have that competitive dynamic, but. Generally across many sets of strategies, alpha has been pretty good the last several years. That can change year to year, but I would say the opportunity for active management is very good today.
當然，這也為這個領域帶來了大量額外資本。所以存在那種競爭動態，但是。總體而言，在過去幾年裡，許多策略類別的超額報酬都相當不錯。這可能會逐年變化，但我會說，如今主動管理的機會非常好。
1
说话人1  說話人 1
00:44:00
So if you look at today's macro environment, what characteristics tend to create the richest opportunity set for alpha?
那麼，若審視當今的宏觀環境，什麼樣的特徵往往能創造出最豐富的超額報酬機會呢？
2
说话人2  說話人 2
00:44:06
I think it's always the opportunity, but also the danger in some of this. I think the kind of continual shorter term shifts from risk on to risk off, right? That's dominated, you know, the last several years, obviously.
我認為這始終是機會，但其中也潛藏著危險。我指的是那種持續不斷的短期轉變，從風險偏好轉向風險趨避，對吧？很明顯，這主導了過去幾年的走勢。
2
说话人2  說話人 2
00:44:20
You go back 24, 25 about inflation as well, which I think you're ending up in around periods where if your portfolio, if you're up at night worried about the next. Earnings print from a large cap S&P 500 company or the CPI print or a Federal Reserve decision, then your portfolio is probably not as well diversified as you'd like it. So I kind of use that as my backdrop to make sure that going into these events and other things that you may lose some in some parts of your portfolio, maybe win in others.
回溯到 24、25 年，關於通膨也是如此，我認為你最終會處於這樣的時期：如果你的投資組合讓你夜不能寐，擔心著下一份大型標普 500 成分股的財報數據、消費者物價指數的公布，或是聯準會的決策，那麼你的投資組合可能沒有你想像的那麼分散。所以，我大概會以此為背景，確保在面對這些事件和其他情況時，你可能在投資組合的某些部分蒙受損失，但也可能在另一些部分獲利。
2
说话人2  說話人 2
00:44:51
It's not going to be a. Kind of what we call a left tail disaster. All of a sudden, you have a very, very tough, you know, day or two of performance. And so that's. Guiding principles is about just risk balance, less about trying to pick individual strategies that will be the best in this particular environment. It's more about being being a bit more balanced, so that does create opportunities because there is so much information flow in the market on a day-to-day basis.
這不會是我們所謂的左尾災難。突然之間，你會遇到非常、非常艱難的一兩天表現。所以指導原則就是風險平衡，而不是試圖挑選在特定環境下表現最佳的個別策略。這更多是關於保持更平衡的狀態，這樣確實會創造機會，因為市場上每天都有大量的資訊流動。
2
说话人2
00:45:17
You've got the rise of of a lot of retail investing coming into the space. There's just a lot of interesting pieces that are different today than there were 10 years ago. I do worry that people. A lot of investors today were not around in 2008. But you sort of what's going on back then when credit could sell off and there's distress and you know the markets are yeah so I think just remembering or at least if you didn't live through that then when you're thinking about asset allocation or risk at least have some of that history in mind and what's what can happen because. That's those are hard lessons, and I think people generationally maybe that they forget that like every ten to fifteen years you need, you need a reminder of some of that.
1
说话人1  說話人 1
00:46:02
Yeah, it is interesting how living through it is so different from just reading about it because you have to, it has to hit you hard for those lessons to stick, and it kind of enforces a certain risk discipline that unless you've been through that or if it happened too long ago, those memories fade.
2
说话人2
00:46:21
exactly exactly.  沒錯，正是如此。
1
说话人1  說話人 1
00:46:23
So one observation that I've had is talent competition in the industry is pretty intense beyond compensation. What did the best investors really want from a platform or firm?
2
说话人2  說話人 2
00:46:34
Again, I think it comes up to what does the portfolio manager sort of their style, what do they want to go towards. And so I think you've got a group that have been very successful clearly on the portage based silo based approach. Other people are looking for a more collaborative type setup, so I think that's interesting.
我認為這又回到投資組合經理人的風格，以及他們想朝哪個方向發展。所以我覺得有一群人顯然在以套利交易為基礎的獨立操作模式上非常成功。其他人則在尋求更具協作性的設置，所以我認為這很有意思。
2
说话人2
00:46:51
Now again, if you're aiming for collaborative, it's hard to have 10 portfolio managers on the platform doing the same thing, right? That's sort of. is against.
再強調一次，如果你的目標是協作，那麼平台上很難有 10 位投資組合經理做著同樣的事情，對吧？這有點互相矛盾。
2
说话人2  說話人 2
00:47:00
It's the opposite of the thesis. So maybe if you're more collaborative, maybe if one or two PMs in each of the buckets, not ten to fifteen. So that sets up your model goes back to strategy, organizational design, how you want to think about it.
這與原先的論點相反。所以也許如果你更具協作性，也許每個類別只有一兩位投資組合經理人，而不是十到十五位。這樣的設定會讓你的模型回歸到策略、組織設計，以及你如何思考這些問題。
2
说话人2  說話人 2
00:47:12
I think stability of the platform, I think the use of technology, are they getting access to the great. Bating capabilities, what what are our firms' prime broker relationships like, so they get good, you know, margin? So all of that package that as they sit from the O outside and looking in, and I don't think it's always about compensation or expected compensation.
我認為平台的穩定性、技術的運用，他們是否能獲得強大的交易能力，我們公司的主經紀商關係如何，讓他們能拿到不錯的保證金條件？所以這一整套配套，都是他們從外部觀察時會考量的，而我認為這並不總是關乎薪酬或預期薪酬。
2
说话人2  說話人 2
00:47:31
I think, particularly as the multirap models evolved over time, people are seasoneded with it. people may start to value some of the other stability points, collaborative points a bit differently than the pure pod base. But again, people have different preferences and.
我認為，特別是在多重經理人模式隨著時間演進後，人們對它已經相當熟悉了。相較於純粹的獨立交易團隊模式，人們可能會開始對其他穩定性因素、協作因素有不同的重視程度。但話說回來，每個人都有不同的偏好。
2
说话人2  說話人 2
00:47:45
And you can do that, I think it's just. You not only do you need a strategy when you go out to your clients about being differentiated, I think you need to have a similar strategy when try to recruit talent. What do you stand for as an organization? And that can be tricky, you know, uh... But you try to. Have every you need everything aligned.
而且你可以做到這一點，我認為這正是關鍵。當你面對客戶時，不僅需要一套差異化策略，我認為在招募人才時，也應該要有類似的策略。你的組織代表什麼價值？這可能很棘手，你知道的，嗯...但你得盡力讓一切保持一致。
1
说话人1  說話人 1
00:48:02
yeah? And ultimately it comes down to alpha. So if you're join, if you join a firm that gives you the best opportunity they generate alpha, ultimately that leads your compensation as well.
是啊？最終還是要回歸到超額報酬。所以如果你加入一家能給你最佳機會創造超額報酬的公司，最終這也會反映在你的薪酬上。
2
说话人2  說話人 2
00:48:12
Correct? No alpha, no business right?
正確嗎？沒有超額報酬就沒有生意，對吧？
1
说话人1  說話人 1
00:48:15
So that's right.
2
说话人2
00:48:16
which is the way it should be right because the.
這本來就該是這樣，對吧，因為...
1
说话人1
00:48:18
clients are paying the fees they should earn alpha over time and and that that feeds the is the net alpha that matters. Yes.
2
说话人2  說話人 2
00:48:25
that's right.  沒錯。
1
说话人1
00:48:26
For younger listeners considering a career in finance, why do you believe creativity is becoming as important as technical skill? You touched on this a little bit earlier.
對於正在考慮從事金融職業的年輕聽眾，為什麼您認為創造力正變得和技術能力一樣重要？您稍早稍微提到了這一點。
2
说话人2  說話人 2
00:48:35
The technical barriers have dropped significantly. I don't think that still means you need some, you know, some technology background in terms of some basic data science work. And I think you're seeing that whether it's in the more traditional technical fields or even humanities, social sciences, they all have a little bit of a quant track, I'll call it, again, sort of rudimentary programming.
2
说话人2  說話人 2
00:48:56
Using data to answer questions，so I participate whatever your field is，and I'm. Big fan of multidisciplinary, doesn't have to be finance, doesn't have to be economics. It can be a lot of different fields, but even whatever fields you choose, having there is a little bit of a in all of those fields a track that's a bit more quantitative.
用數據來回答問題，所以無論你的領域是什麼，我都會參與，而且我是跨領域的忠實擁護者，不一定要是金融，也不一定要是經濟學。可以是很多不同的領域，但即使你選擇任何領域，在這些領域中，都有一條稍微更偏向量化分析的路徑。
2
说话人2  說話人 2
00:49:14
I think exploring that world is quite helpful. It gives you some skills that allows you to at least when you're working in this new environment of large language models that you're. ABLE TO KIND OF UNDERSTAND WHAT THE CODE IS DOING AND NOT DOING, SO YOU KIND OF PUSH BACK ON IT.
我認為探索那個世界相當有幫助。它會帶給你一些技能，至少當你在這個大型語言模型的新環境中工作時，你能夠大致理解程式碼在做什麼、沒做什麼，這樣你就能對它提出一些質疑。
2
说话人2  說話人 2
00:49:29
I THINK THAT'S IMPORTANT, BUT I ALSO THINK BROAD EXPERIENCE IS REALLY, REALLY HELPFUL. SO AGAIN, MULTIDISCIPLINARY, MULTIPLE MAJORS, MULTIPLE MINORS, ALL OF THOSE KINDS OF THINGS ARE REALLY, REALLY GOOD FOR F. And if you tie that in with a little bit of technical, then it really opens up what you can do.
我認為那很重要，但我也覺得廣泛的經驗真的非常非常有幫助。所以再次強調，跨學科、多主修、多輔修，所有這類的事情對金融領域來說都非常非常好。如果你再結合一點技術能力，那它真的會為你能做的事情打開大門。
2
说话人2  說話人 2
00:49:47
And again, that's where you're going to go in the discretionary world or the systematic world, right? I think even on the discretionary side, there are you still have to run a spreadsheet or however you want to run it, model companies. It's just very specific. It's very narrow in terms of the company. Your following versus the broader set on quant side, but I think that's really helpful for folks on both whatever career path they pick.
這同樣也是你在主觀投資領域或系統化投資領域中會遇到的情況，對吧？我認為即使在主觀投資這一邊，你仍然需要操作試算表，或者用你偏好的任何方式來建立公司模型。只是它非常特定，就你追蹤的公司而言範圍非常狹窄，相較於量化投資領域更廣泛的集合。但我認為這對於選擇任何職涯道路的人來說，都確實很有幫助。
1
说话人1  說話人 1
00:50:06
So when you reflect on your own career path, what non-obvious experiences ended up shaping how you think as an investor and leader?
那麼，回顧你自己的職涯歷程，有哪些非顯而易見的經歷，最終塑造了你作為投資人和領導者的思維方式？
2
说话人2  說話人 2
00:50:14
When I came out of college, I wasn't exactly sure. What I wanted to do, but I did know that I wanted to do different things and just and see. So part of the career path went from investment banking.
當我大學畢業時，我不太確定。我想做什麼，但我確實知道自己想嘗試不同的事情，邊做邊看。所以職涯的一部分是從投資銀行業開始的。
2
说话人2  說話人 2
00:50:26
I worked at Walt Disney in the Strat Planning Group. I worked for Michael Porter in the Competition and Strategy Group. I start, I joined right out of business school, I start up quant shop, which I was doing everything from coding to trading to talking to clients, and then ultimately joining numeric back all the way back in 2003.
我在華特迪士尼的策略規劃小組工作過，也在競爭與策略小組為麥可·波特效力。我從商學院畢業後就直接加入，創立了量化交易部門，從寫程式、做交易到與客戶溝通，什麼都做，最後在 2003 年回到 Numeric。
2
说话人2
00:50:47
So I think having different experiences is really useful, different contexts. I took a two or three month break from numeric and did some work with the Boston Red Sox for a little bit. And my. Here is evolved.
2
说话人2  說話人 2
00:51:01
I was a researcher on the quant side, then ran the hedge funds, was the director of research, did a lot more on the discretionary side as part of our development of cross firm capabilities, and then moving into the broader man group CIO role last summer. So part of it is getting different experiences of different parts of the organization is really helpful because that allows you to. Two more things, but at the same time, it's okay to be an expert in one particular area.
2
说话人2
00:51:27
So there's a couple of different models for folks. If they love being a portfolio manager covering US financial stocks and they really get it, that's great. If you want to be more on the managerial side, organizational design, all that, there's other paths. So I think kind of find what you like to do. If you can, and if in when in doubt, then try different things.
所以對大家來說，有幾種不同的模式。如果你熱愛當個涵蓋美國金融股的投資組合經理，而且你真的搞懂了，那很棒。如果你想走更偏向管理、組織設計那方面，也有其他的路徑。所以我覺得，就是去找到你喜歡做的事。如果可以的話，當你不確定時，就去嘗試不同的事情。
1
说话人1  說話人 1
00:51:45
Are you able to share your experience with the Red Sox? I think that would be interesting.
2
说话人2  說話人 2
00:51:49
Oh yeah, I know. I was there's a on the elementary base that kind of like had quant there at the time. This is ah... this is quite a while ago, so I think it's okay to talk about. I was brought in to work a bit. Strategy，so you know baseball，you have uh amateur draft every year，and and sort of looking at that，so I spent a few weeks，I was an intern，I was punching taking my card and punching in every day，um，so it was a lot of fun。
喔，對，我知道。我當時在那裡，那是一個初階的基礎部門，那時候有點像是有量化團隊在那裡。這是啊……這已經是很久以前的事了，所以我覺得現在談談應該沒關係。我被帶進去參與一些策略工作，所以你知道棒球，每年都有業餘選秀，就有點像是在研究那個，所以我待了幾個星期，我是實習生，每天都打卡上班，嗯，所以那非常有趣。
2
说话人2
00:52:13
you do realize you know in well sports is fun sports analytics is fun there's only about there's only thirty baseball teams right and there's one per city it's a very rewarding career but you're also very the alpha there is definitely if you're not winning you might you know not be there as much so i think that was fun for me because i was a bit of an outsider doing it and having fun whereas if you're living it day to day it could be it's just like running running money in the real world right same thing and it's probably more popular today than it was back then. Yeah, I mean quite frankly, if there had been more moneyball type stuff, maybe that's what I would have ended up doing coming out of college. Who knows? It's very interesting.
你確實明白，你知道嗎，運動很有趣，運動數據分析也很有趣，大概就只有三十支棒球隊，對吧？而且每個城市一支。這是一份非常有回報的職業，但你也非常……那個領先地位，如果你沒有贏球，你可能，你知道，就沒辦法待那麼久。所以我覺得那對我來說很有趣，因為我有點像個局外人在做這件事，並且樂在其中，但如果你是日復一日地身處其中，那可能就會像在現實世界中操盤資金一樣，同一回事。而且它現在可能比當時更受歡迎。是啊，老實說，如果當時有更多像《魔球》那類的東西，也許我大學畢業後就會去做那個了。誰知道呢？這真的很有意思。
2
说话人2  說話人 2
00:52:47
Maybe we've gone too far that way though. I think again, I'm back to discretionary and systematic, and I think maybe the systematic parts dominate a little too much. We need to go back to good old fundamental scouting, but that.
不過，我們可能在那個方向走得太遠了。我想，我又回到了主觀判斷與系統化交易的討論，而我認為系統化的部分可能主導得有點過頭了。我們需要回歸到那種優良傳統的基本面探勘，但就是那樣。
2
说话人2  說話人 2
00:53:00
What do I know? The pendulum swings back and forth. Yeah, so I think maybe it's gone way too because it did the other way. So hopefully bring it back a little bit.
我懂什麼呢？鐘擺本來就會來回擺盪。是啊，所以我認為它可能走得太過了，因為之前是偏向另一邊。所以希望能把它拉回來一點。
1
说话人1  說話人 1
00:53:07
Hello Greg, this has been a fun conversation. A lot of great insights. I appreciate you joining us. Thank you so much. Oh yeah, thanks Alex. It was a lot of fun. Thank you.
哈囉，葛瑞格，這次對談真的很有趣，收穫了許多精闢見解。很感謝你加入我們，非常謝你。喔，沒錯，謝謝艾力克斯。這真的很好玩，謝謝。