第 404 集：改变一切的那份金融论文

但如果你只盯着股息，就会无意中暴露在其他因子下，而你本可以直接瞄准真正驱动收益的因子，构建一个更分散、更灵活的投资组合。

But when you focus on dividends, you sort of get naive exposure to the other factors when you could be focusing on the factors that are actually driving returns and get a more diversified, more customizable portfolio.

还有一点值得提一下，就像法玛和弗伦奇在论文里说的，他们把那些因子当作系统性风险因子来建模，这一点至今仍有争议。

One thing that is worth mentioning is it's still debatable, like Fama and French, the language they use in this paper is that we're modeling these as systematic risk factors.

这确实还存疑。

That's still debatable.

我们其实还不清楚，这些因子到底是风险带来的，还是定价错误造成的。

We don't really know if they're risk factors or if they're artifact of mispricing.

这也是个特别特别难彻底验证的问题。

And that's another one of those things that's really really hard to test definitively.

我们从数据里看到的这些系统性因子，究竟是因为定价错误才存在，还是因为风险才存在？

Do these systematic factors that we can see in the data, do they exist because of mispricing or do they exist because of risk?

我甚至不确定这到底有没有关系。

I don't even know if it matters.

但如果你觉得定价错误迟早会被套利消除——确实有人这么认为——那这就很重要了。

I think it matters if you believe that mispricing would be arbitraged away, which some people do believe.

我们请过一些嘉宾，他们谈过自己对这个问题的看法。

We've had some guests talk about how they think that has happened.

如果你相信套利有局限，系统性的定价偏差会因此持续存在，那其实不用纠结我们是在看风险还是定价偏差——只要相信这些现象会继续下去，这才是真正关键的问题。

If you believe that there are limits to arbitrage and that systematic mispricings won't go away for that reason, I don't think it's really relevant whether we're looking at risk or mispricing as long as we believe these things are going to persist, which is really the big question from a practical perspective.

因为如果我们能观察到这些因子，发现它们确实能解释不同投资组合之间的收益差异，那就挺好的。

Because if we can look at these factors and say, they exist and hey, cool, they explain differences in returns across diversified portfolios.

但我们无法确定。

We can't know.

但如果认为这些因子未来的溢价不会为正，那我们可能就不想主动配置它们。

But if we don't think that the premiums for these factors are going to be positive going forward, we may not want to tilt toward them.

甚至如果知道溢价会是负的，我们可能还会主动避开它们。

I mean, may even want to tilt away from them if you knew that the premiums were going to be negative.

这两者其实是分开的：一个模型可以很好地解释收益差异，但溢价未必必须为正。

They're kind of separate I guess, where you can have a model that does a good job explaining differences in returns, but the premiums don't have to be positive.

但如果你打算配置它们，自然还是希望它们的溢价能是正的。

But if you're to tilt toward them, you kind of hope they're going to be positive.

法玛和弗伦奇最重要的发现是，规模效应和价值效应并不一定是异常现象。

The big thing Fama and French showed is that size and value don't need to be anomalies.

我们没必要非得用资本资产定价模型的视角来看世界，觉得这些东西说不通。

We don't have to look at the world from a CAPM perspective and say, hey, these things don't make sense.

法玛和弗伦奇认为，这些因素可能是系统性的风险因子，我们在分析投资组合、评估不同股票时，必须把它们考虑进去。

What Fama and French said is maybe these things are systematic factors risk or otherwise that we need to account for when we're looking at portfolios and assessing different types of stocks.

当他们把这些因素纳入模型后，几乎能完全解释这些广泛多元化投资组合之间的收益差异。

And when they include those in their model, they are able to almost fully explain return differences across this broad range of diversified portfolios.

这彻底改变了我们对市场的看法。

That really changed how we viewed markets.

我们从资本资产定价模型下大约60%的解释力，提升到了三因子模型超过90%的解释力。

We went from in a CAPM world, that's sort of whatever you want to call it 60% explanatory power to with a three factor model, 90% plus explanatory power.

这个提升非常显著。

It's a very powerful increase.

这种影响还体现在其他方面，不只是简单地说‘哦，挺有意思’。

Other area that this has an impact is not just it's like, okay, cool.

我们能够解释收益之间的差异。

We can explain differences in returns.

这挺有意思的。

That's neat.

这些现象不一定都是异常情况。

These things don't all have to be anomalies.

明白了。

Okay.

但当我们问为什么有些主动管理者表现更好时，事情就变得更有趣了。

But it gets really interesting again when we say, why have some active managers outperformed?

如果他们表现好是因为能力出众，那我们或许该多给他们投点钱。

If they've outperformed because they're skilled, then maybe we should be giving them more money to invest.

但如果他们只是押注了价值股或小盘股，那这就不那么特别了，也不该为此收取高额费用。

If they've outperformed because they tilted toward value or size, maybe that's not as interesting and maybe they shouldn't command a high fee for that service.

说白了，如果你知道一个经理只是在押注价值股，他却要收你1.5%到2%的管理费。

It's basically like if you know a manager is just tilting toward value stocks, they're going to charge you one and a half or 2% to do that.

你直接买个价值指数基金，费用可能就二十个基点而已。

You could just buy a value index for whatever 20 basis points.

法玛和弗伦奇后来用三因子模型研究过这个问题。

Fama and French did look at that in later research using the three factor model.

那就是他们那篇关于主动基金中运气与能力的著名论文。

That's their famous paper on luck versus skill in active fund management.

确实让人好奇，在这些道理还没被搞清楚之前，就已经有基金经理跑赢市场了。

One does wonder, before this was really understood, there were managers who outperformed.

回头看的时候，难免带点事后诸葛亮的视角，我们会说：你赢是因为你更偏向小盘股或者价值股。

Looking back with hindsight bias, we can say, well, you outperformed because you tilted more to small stocks or value stocks.

但那些基金经理在学术研究证实这些因子有溢价之前，就已经发现了这些机会。

But those managers identified those opportunities presumably before the academic research showed that they had premiums.

所以他们可能是运气好，但也可能是直觉特别准。

So they might have been lucky, but they might have just had very good intuition.

一旦这些因子被广泛知晓，由于市场整体效率很高，它们的超额收益可能会逐渐缩小。

Once the factors get publicized, there is some potential for them to shrink because the market is mostly efficient.

如果这些确实是定价错误或对风险的误解，随着人们逐渐理解，它们未来应该会逐渐缩小。

If some of these things were indeed mispricings, misunderstandings of risk, that would presumably get smaller in the future as people understood that.

但要从实际的基金和经理表现中把这些问题分辨清楚，实在太难了。

But this is all very difficult to tease out from real world fund and manager performance.

是的，没错。

Oh, yeah.

确实如此。

Very much so.

确实，论文发表后，这些因子的收益趋势上确实在变小。

That is true that post publication factor premiums have tended to get smaller.

但我认为它们还没完全消失。

I don't think they've gone to zero.

我们有个叫安德鲁·陈的人，他认为它们已经消失了。

We've had one guess Andrew Chen who thinks that they have.

他研究了美国市场，觉得可能就是因为这个原因，这些溢价已经归零了。

He's looked at The US and said that maybe they've gone to zero for exactly that reason.

你看美国以外的地方，因子溢价依然相当可观，甚至在安德鲁的美国样本之后，价值溢价在那段特定时期内仍然是正的。

You look outside The US and The fact premiums have still been quite positive and even post Andrew's sample in The US, the value premium for example has been positive over that specific period.

这些东西里头的噪音实在太多了。

So much noise in this stuff.

很难说什么是真的。

It's hard to say what is true.

我觉得我们有的只是不同程度的似真性，而不是真正的真相。

I think we have degrees of truthiness rather than truth.

是的。

Yeah.

我们能确信的东西实在太少了。

There's so little that we can be confident and certain about.

你只能根据现有证据做合理判断，别对任何理论赋予太多预测能力。

You just try to do what makes sense based on the evidence without putting too much predictive power on any theory.

总的来说，这篇论文的发现既挑战了单因子CAPM资产定价模型，又在此基础上构建了一个更全面的框架，帮助投资者系统性地思考如何构建和评估投资组合。

Altogether, the findings of this paper, they challenged, but they also built on single factor CAPM asset pricing to create a much more comprehensive framework for how investors should think about building and evaluating portfolios systematically.

这篇论文发表后，我前面提到的那个术语——实证资产定价——突然就火了起来。

And then after this paper came out, it kind of caused this explosion in the term that I mentioned earlier, which is called empirical asset pricing.

其实就是看收益数据，琢磨到底是什么因素在推动这些收益。

It's really like looking at returns and figuring out what factors might be driving them.

这个研究领域一下子爆发了。

So that field of study really exploded.

研究人员都想找出最有效的那些因素。

Researchers wanted to find the best factors.

他们还试图构建更优的资产定价模型。

They wanted to create better asset pricing models.

这事儿后来可能有点过头了。

It kind of became a bit of a problem maybe.

约翰·科克伦在2011年美国金融协会的主席演讲中，把那些层出不穷的因素称为一个动物园。

John Cochran in his twenty eleven presidential address at the American Finance Association, he described the proliferation of factors as a zoo.

所以‘因子动物园’这个说法就这么出名了。

So it's kind of become this famous term, the factor zoo.

你甚至可以管它叫‘因子杂烩’。

You could maybe even call it factor slop.

我不确定要不要借用我最近那个关于ETF杂烩视频里的说法。

I don't know to use the language from my recent video on ETF slop.

这么说可能对那些发现这些因子的研究人员不太公平。

That's probably not very nice to some of the researchers who have discovered some of the any factors.

我也说不准。

I don't know.

不过2016年有一篇由卡姆·哈维、刘和朱合著的论文。

But there was a 2016 paper from Cam Harvey Liu and Zhu.

他们当时发现——也就是十年前了——学术期刊上已经发表了360个不同的因子。

And they found at that time, this is ten years ago now, they found that there were three sixteen distinct factors that had been published in academic journals at the time.

后来的研究似乎表明，虽然当时发表了360个因子，但其实它们大都属于少数几类。

I think later research has kind of suggested that maybe there were three sixteen published factors, but they really all fall into a relatively small number of categories.

所以表面上看有三百六十种花样，但归根结底，真正核心的也就那么几个。

So we found like three sixteen different flavors, but there's when you really boil it down, there's only a handful still.

无论如何，这催生了一整套新的学术方法，用来筛选因子。

In any case, it did create this whole new set of academic techniques for choosing factors.

你怎么判断哪些因子该放进模型里？

How do you evaluate which factors belong in a model?

还有各种比较资产定价模型的技术。

Different techniques for comparing asset pricing models.

现在这方面的论文已经多得不得了。

So there's like a whole bunch of papers on this now.

面对这堆乱七八糟的因子，你怎么叫它都行。

In the face of the zoo or the slop, whatever you want to call it.

法玛和弗伦奇后来确实更新了他们1993年的论文。

Fama and French did go on to update their 1993 paper.

我不确定那算不算更新，反正他们重新搞了个模型。

I don't know if they call an update, guess.

2015年他们推出了新模型，加了两个新因子：盈利能力和投资。

They created a new model in 2015 and they introduced two new factors with that update and those are profitability and investment.

盈利能力用RMW表示，也就是高盈利减去低盈利。

So profitability is expressed as RMW or robust minus week.

指的是高盈利公司相对于低盈利公司的超额收益，或者说稳健盈利对薄弱盈利的回报差。

And that's the excess return from companies with high profitability over those with weak profitability or robust profitability over weak profitability.

投资行为则用CMA表示，即保守型减去激进型。

And then investment is expressed as CMA conservative minus aggressive.

那些资产账面价值增长缓慢的公司属于保守型，通常表现更好，而那些大举投入资金追求快速资产扩张的公司则被称为激进型。

And that's companies that grow the book value of their assets slowly, which is conservative, tend to outperform those that pour cash into rapid asset growth, which are called aggressive.

五因子模型确实解决了三因子模型没能解释的一些问题。

And the five factor model did help to solve some of the problems that the three factor model was not able to.

我们之前提到过低波动率异常现象。

We talked about the low volatility anomaly.

三因子模型还有几个其他无法解释的现象，不过法玛和弗伦奇写过另一篇论文专门讨论这个。

There were a couple of other ones that were still unexplained by the three factor model, but Fama and French have a separate paper.

我记不清具体标题了，但大概是关于用五因子模型剖析异象，他们挑了一堆资产定价异象，指出这些现在基本都能被五因子模型解释了。

I can't remember what exactly what the title is, but it's something about dissecting anomalies with the five factor model where they go and take a bunch of asset pricing anomalies and say, well, these are largely explained by the five factor model now.

正如我之前提到的，根据我们讨论的不同投资组合分类，解释力提升到了接近95%。

And as I mentioned earlier, it did move the explanatory power up closer to 95 depending on which portfolio sort we were talking about.

在不同多元化投资组合的收益差异中，它能解释高达94%的部分。

Was sort of up to 94% of the differences in returns across diversified portfolios.

如今，五因子模型可以说已经成为业界的标准工具。

And the five factor model is really now today, I would call it the sort of workhorse.

它现在是学术金融领域最主流的资产定价模型。

It's like the benchmark asset pricing model in academic finance.

你觉得我们花点时间聊聊盈利能力怎么样？

You think it's worth a quick chat about profitability?

对我来说，投资因子一直最难直观理解，但盈利能力也有同样的问题。

I mean, investment to me has always been the most difficult one to understand intuitively, but profitability has that issue as well.

我觉得这其实又回到了低波动率异象这个点上。

I think it does come back to this idea of the low volatility anomaly.

换句话说，我们都直觉上明白，小盘股的预期收益通常高于大盘股，主要是因为它们风险更高。

Like in other words, I think we all understand intuitively, small stocks have higher expected returns than large companies, it's usually because they're riskier.

对于价值股，也许是因为风险。

For value, maybe it's risk.

行为因素我觉得也解释了很多。

The behavioral component, I think explains a lot too.

人们通常不喜欢那些便宜又无聊的公司，反而偏爱大而贵的公司。

People generally don't like cheap boring companies and they like big expensive companies.

他们愿意为这些公司多付钱。

They will pay more for them.

盈利能力就更难理解了，为什么投资者不愿意投资那些明显盈利的公司呢？

Profitability is a lot harder to understand because why would investors not want to invest in companies that are clearly profitable?

如果他们真的青睐这些所谓的优质公司，那价格早该被推高，直到这种现象消失——就像老话说的，你不能单凭公司好坏来判断一只股票。

If they were attracted to those quote unquote good companies, would they not drive up the price until the point where this is kind of the old idea of you can't tell a good stock by identifying a good company.

因为价格才是关键。

Because price means everything.

有没有什么合理的解释，说明为什么投资者反而不青睐盈利好的公司，从而让这些公司获得更高的预期回报？

Is there some explanatory reason why investors would not prefer profitable companies and therefore impart some kind of higher expected return on them?

我一直以来都是从多因子的角度来思考这个问题的。

I've always had to think about it from a multi factor perspective.

这其实是一种其他条件都相同的情况。

It's really like an all else equal perspective.

如果我们拿两家在所有特征上都完全一样的公司，只是其中一家盈利能力更强，但它们的价值特征和其他方面都一样。

If we take two companies that are otherwise identical on all characteristics, but one has higher profitability, but they've got the same value characteristics and all that stuff.

为了让这两家公司的估值相同，盈利能力更强的那家，其未来现金流必须被赋予更高的折现率。

The higher profitability company must have a higher discount rate applied to its future cash flows in order for their valuations to be the same for these two companies.

所以当我们考虑该买哪只股票时，如果发现一只更盈利的股票，却和另一只股票的相对价格一样。

So if we're looking at which stock should I buy and we find one that's more profitable, but it's trading at the same relative price as some other stock.

那么市场为体现这些特征而隐含的折现率，一定更高。

The inferred discount rate or implied discount rate that the market must be pricing it for those characteristics to be the way that they are, must be higher.

我觉得这也是法玛和弗伦奇在他们的五因子模型论文里所讲的逻辑。

And I think that's the story that Fama and French talk about in their five factor paper as well.

而当你从单一因子的角度来看时，我觉得价值因子其实也差不多。

And then when you think about it from a single factor perspective, I think it's kind of similar for value actually.

如果我们从整体来看价值股，就像你说的，它们的预期回报更高，因为这些公司都挺枯燥的。

If we think about just value stocks in aggregate, they have higher expected returns like you said because they're boring companies.

人们觉得它们的风险没那么高。

People aren't had maybe riskier.

人们对这些公司兴趣不大。

People aren't as interested in them.

所以它们的价格比较低。

So they've got lower prices.

但我们也得问一个问题：它们价格低，是因为公司本身很差吗？

But we've also got that question of do they have lower prices because they're crappy companies?

如果是这样，那它们就不是好的投资标的；还是说，它们虽然公司不错，但市场给的折现率更高？

In which case they're not good investment opportunities or is it because they have higher discount rates but are pretty good companies.

单靠价值因子来筛选的时候，这里面的干扰因素太多了。

There's a lot of noise in that when you just look at the single factor value sort.

但一旦引入盈利能力这个维度，就能更容易找出哪些公司的预期回报更高了。

When you introduce profitability, it's a lot easier to find which companies have high expected returns.

它们盈利高、价格低，这正是我们想要的组合。

They've got high profitability and low prices, which is the combination that you want.

单靠低价，即使不考虑盈利能力，也能让投资组合获得更高的预期回报。

Low prices without sorting on profitability are enough on their own to have higher expected returns as a single factor portfolio.

我觉得盈利能力也是类似的情况——真正理想的是那些盈利高又价格低的公司，这才是多因子的筛选方式。

I suspect it's something similar going on with profitability where you really want the high profitability companies with low prices and that's a multifactor sort.

如果你只看整体的盈利能力投资组合，可能还是能捕捉到足够多的这种效应，从而获得溢价。

If you just take the aggregate profitability portfolio, you're probably still picking up enough of that for there to be a premium.

我一直都是这么理解的。

That's the way I've always thought about it.

也许还有更好的方式来看待这个问题。

Maybe there are better ways to think about it.

我同意，这个说法确实没那么直观，尤其是如果你只从单一因子的角度去想的话。

I agree it is a less intuitive story, especially if you try and think about it from a single factor perspective.

一旦你叠加多个因子，因为很多公司可能在多个维度上都会呈现高低不同的分布。

And once you layer on the factors, because again, maybe most companies will sort high or low across multiple factors.

很多价值股的盈利能力其实也很强。

A lot of value stocks are probably high profitability as well.

正因如此，它们才被称为价值股，而不仅仅是便宜。

That's what makes them value as opposed to simply cheap.

价值股不只是价格低，而是价格相对于公司的盈利、资产等正面指标来说偏低。

A value stock is not just one with a low price, it's a low price relative to some positive characteristics in the company earnings, assets, whatever it is.

所以这些因素在很多情况下是重叠的。

So a lot of these are going to overlap.

因此，预期回报最高的公司，很可能在三个或更多这些因素上都表现突出。

So I mean, companies with the highest expected returns may score high on three or more of these factors.

在很多情况下，这些因素之间其实是负相关的。

In a lot of cases, they're going to be negatively correlated.

如果我们只看价值股组合，它的盈利能力通常会低于整个市场。

If we just take the portfolio value stocks, it's going to tend to be less profitable than the market as a whole.

公司规模也是如此，这就是为什么从多因子角度来分析如此重要。

Similar things can happen with company size, which is why taking that multi factor perspective ends up being so important.

因为如果你只看价值股，最终持有的投资组合会偏向低盈利性，而这种偏向的预期回报是负的。

Because if we just take value stocks, you end up with a basically low profitability tilt, which has a negative expected premium.

如果你能在价值投资的基础上，再通过盈利性筛选提升整体盈利水平，预期回报就会明显提高。

If you can take that value portfolio and bring the profitability characteristics up by also doing a profitability sort, then your expected return just goes up.

正因如此，当这些研究结果陆续出炉后，像Dimensional和Avantis这样的公司才特别重视把这些发现融入他们的策略中——稍后我们会更详细地讲到。

This is why as this research has come out, it's been so important for firms like Dimensional and Avantis who will talk more about in a second to incorporate that research.

你不想只是买一些便宜的股票，却根本不清楚它们为什么便宜。

Because you don't want to just own cheap stocks when you don't really know why they're cheap.

因为那些股票可能是质量很差的公司，你根本没必要持有它们。

Because maybe they're crappy companies and you don't actually want to own them.

如果你只靠单一因子做筛选，确实很容易碰到这种情况。

And I think you do get a lot of that if you just do the single factor sort.

但一旦你加入第二个因子，尤其是现在Dimensional已经调整了因子权重的计算方式，他们的Vector投资组合——在加拿大上市，同时提供加拿大和美国的基金——就明显更积极地偏向规模和价值因子。

But once you add in the second factor, you see that in especially now that they've changed the way that they're doing their weighting of the factors, dimensional in the vector portfolios, which are Canadian listed, well, have a Canadian and US funds that are pretty aggressively tilted towards size and value.

他们过去确实非常侧重规模和价值，后来才把盈利性因素也加了进去。

They used to be pretty aggressively tilted towards size and value and then took profitability into account.

但他们最近调整了方法，让规模、价值和盈利能力这三个因素的权重更加均衡。

But they fairly recently changed their methodology to have a much more sort of equal emphasis on size value and profitability.

如果看他们整体的投资特征，以前的向量组合比市场便宜很多，但盈利能力要么略低，要么和市场差不多，这本身已经很了不起了。

And when you look at their aggregate characteristics, it used to be that the vector portfolio would be way cheaper than the market, but also have a little bit lower profitability or similar profitability to the market, which was in itself pretty impressive.

因为如果你只按价值选股，最终得到的公司盈利能力会差很多。

Because if you just did the value sort, you'd end up with a much worse profitability characteristic.

而现在由于权重更均衡了，整体表现也更加平衡了。

And then now with more equal emphasis, it's even more balanced.

你必须主动决定如何权衡这些因素，因为如果简单地叠加越多因子，尤其是当它们彼此负相关时，最终很可能就变成了市场组合。

You need to make some kind of active decision about how you want to weight all of these factors because in a naive way, like the more factors you layer on, especially if they're negatively correlated, at some point you just end up with the market.

除非你打算大幅集中持仓，否则最终得到的投资组合和普通的市值加权指数不会有太大差别。

Unless you plan on concentrating the portfolio quite aggressively, you just end up with a portfolio that's not dramatically different from just a boring market cap weighted one.

所以你会看到它和普通指数高度相关，超额收益的机会变小了，但跑输市场的风险也相应收窄了。

So you're gonna see a lot of correlation with just a plain vanilla index and any opportunity for outperformance, but also risk of underperformance maybe gets narrowed.

除非你真有一套非常有力的组合方法，能把这些因子恰到好处地结合起来。

Unless you've got a really compelling formula for how to combine these in the right way.

这时候就看出本事了。

That's where the skill comes into.

你有研究数据。

You've got the research.

好的，这就是原材料。

Okay, that's the raw material.

那接下来该怎么用呢？

Now what do we do with it?

我觉得确实需要技巧。

I think there's skill.

同时也要保持谦逊。

There's also an element of humility.

Dimensional 和我觉得 Avantis 的做法很像，都是高度分散，但依然以市场因子为主。

The way that Dimensional and I think Avantis is similar, the way that they do this is very diversified and it is still dominated by the market factor.

由于这种极度分散的策略，它们对市场的跟踪误差也比较低。

And it's going to have relatively low tracking error to the market because they are taking that super broad diversification.

市场上有一些产品集中度高得多。

There are products out there on the market that are much more concentrated.

它们更偏向主动投资组合构建，通过建立集中但依然基于量化分析的组合。

They tilt much more toward the active portfolio construction by building concentrated portfolios that are still quantitatively informed.

你仍然可以把它们称为因子投资组合。

Like you could still call them factor portfolios.

我觉得很多产品名称确实自称为因子组合，但它们的集中度要高得多。

I think a lot of the product names actually do call themselves factor portfolios, but they're much more concentrated.

在这种情况下，你就像你提到的那样，对因子溢价下了更大的注。

In that case, you're making a much bigger bet on the premiums to your point Dan.

同时，你的跟踪误差会大得多，如果因子表现不如预期，跑输市场的风险也会更高。

You're also going have much more tracking error and you've also got much more risk of underperforming the market if the factors don't work out as expected.

像Dimensional这样的产品，我们还没怎么聊过，但听众们可能已经很熟悉了，它的表现和市场非常相似。

With something like Dimensional, which we haven't really talked about yet, although listeners are probably already familiar, you do look a whole lot like the market.

从我们的角度看，这反而是好事。

And from our perspective, that's a good thing.

对于那些追求极高信心、希望大幅跑赢市场的人来说，

From someone's perspective who wants you know, really high conviction or wants to really outperform the market.

他们可能觉得这并不是什么好事。

They might consider that not such a good thing.

我们对这些因子并没有那么强的信心，所以不会去构建只含25只股票、高度集中的多因子组合。

We don't have so much conviction in these factors that we want to build 25 stock portfolios that are as concentrated as possible in the multifactor sort.

我觉得说得对。

I think that's right.

到了某个阶段，你的组合确实会很像市场，因为你已经广泛分散了。

That at a certain point you do look a lot like the market because you're broadly diversified.

从我们的角度看，这其实是好事，但不是每个人都会这么想。

I think that's kind of a good thing from our perspective, but not everybody would necessarily agree with that.

对。

Yeah.

我觉得‘倾斜’这个词用得挺贴切的，因为它确实很微妙。

Think that's why the term tilt is apt because it's subtle.

这并没有从根本上偏离广泛分散的投资组合。

It's not an enormous fundamental move away from a broadly diversified portfolio.

我们其实是从一个前提出发的：分散投资本来就很棒，现在只是在边缘做一些微调。

It's sort of starting from the premise that a diversified portfolio is very good, and now we're just trying to tweak it around the edges.

这就像法玛那句著名的话：你得说服自己放弃市场组合。

It's like Fama's famous line that you've got to talk yourself out of the market portfolio.

这最终还是取决于你对这些细微调整到底有多大的信心。

That really comes back to how much conviction do you have in these kind of tilts.

值得一提的是，学术界和实务界至今仍在激烈争论：哪些因子真正有效，以及我们该采用哪种资产定价模型。

It is also worth mentioning that there's still tons of ongoing debate both in academia and in practice about which factors make sense and which asset pricing model we should be using.

Dimensional 和 Avantis 都在广泛使用法玛-弗伦奇五因子模型，以及这种整体思路。

Dimensional and Avantis as well are broadly using the Fama and French five factor model and that general approach and type of thinking.

但市场上还有大量其他竞争性的因子模型。

But there are tons of competing factor models.

各种竞争性的投资产品也多得数不清。

There are tons of competing products.

有些公司会开发自己独有的因子。

There are companies that have their own factors.

这远没有定论。

That's not like a settled debate by any means.

我觉得可以比较有把握地说，当考虑到交易成本时——这一点在学术界比较不同资产定价模型的文献中已经有人做过分析——

I'm pretty comfortable saying that when transaction costs are accounted for, which is something that has been done in academic literature that compares asset pricing models.

有一篇论文指出，一旦把交易成本算进去，法玛和弗伦奇的五因子模型表现得非常非常出色。

That there's one paper that shows that when you account for transaction costs, Fama and French's five factor model is really, really strong.

它为构建投资组合和评估组合表现提供了一个非常好的基础。

It's a very good foundation for thinking about portfolio construction and evaluating portfolio performance.

交易成本这个问题很重要，因为还有一个因子叫动量，实证上非常强势，而法玛和弗伦奇在他们的论文里对这个因子的态度一直挺有意思的。

That transaction cost things is important because another factor is momentum, which is very empirically strong and Fama and French have always kind of it's interesting reading their papers.

他们一直对它感到纠结。

They've always kind of struggled with it.

他们在一篇论文里提到，曾经在测试的资产定价模型中加入了动量因子，但明确说这是勉强加入的。

They say in one paper that they included momentum in an asset pricing model that they were testing, but they say that they include it reluctantly.

他们非常担心数据挖掘，担心仅仅因为某些因素看起来有效就随意添加，却没有理论依据。

They're very concerned about data mining and about adding factors just because without any sort of possible theoretical story.

有一篇论文比较了不同的资产定价模型，发现如果忽略交易成本，动量因子的表现会非常出色。

So there's one paper that compares different asset pricing models and shows that momentum can look really good when you ignore transaction costs.

但一旦考虑交易成本，不包含动量因子的法玛-弗伦奇模型反而显得更有优势。

But when you account for transaction costs, the Fama and French model without momentum starts to look a lot better.

是的。

Yeah.

动量一直是大家特别关注的话题。

Momentum is one of these things that's always famous.

它在理论上说得通。

It makes theoretical sense.

有很多数据表明，就像你说的，如果忽略交易成本，它的效果确实很吸引人，但问题是交易成本根本没法忽略。

There's a lot of data showing, like you said, if you ignore transaction costs, it's compelling, except you can't ignore transaction costs.

和其他那些偏向型投资组合不同，它们并不适合长期持有，而是需要定期调整。

And unlike these other tilted portfolios, which are pretty buy and hold, they will need reconstitution from time to time.

但动量因子通常涉及一到三个月的交易周期，到底谁在实际操作呢？

But the momentum factors are typically like one to three months trading cycles and they're like, who's implementing that?

如果你在操作，光是税务影响就够头疼的了。

And if you are, I mean, just the tax impact.

经纪佣金倒还好说，但频繁交易带来的税务负担，很可能把原本的收益都吃光了。

Brokerage fees are kind of not a thing, but certainly just the churning and the tax implications of that are likely gonna eat up any premium that was there.

所以动量策略在执行上比其他一些因子要难得多。

So hard to implement in a way that some of these other factors are not terribly difficult to implement.

相对而言，其他因子的换手率更低。

Relatively speaking, they're lower turnover.

它们也不算特别复杂。

They're not super complicated.

所有指标都挺直接的，但就连动量因子也有好几种衡量方式。

Like all the metrics are fairly straightforward, but even momentum like there are bunch of different ways you can measure it.

你根本不知道哪种衡量方法才是最好的。

You don't know which measure is the best one.

价值和盈利能力也是一样。

We can say the same thing for value and profitability too though.

这一领域的每个细节都还在激烈争论中。

There's still every layer of this is still hotly debated.

你随便找五个学者，他们各自都发表过论文，证明自己的价值或盈利能力衡量方法比别人更优。

You could go and find five different academics who have published papers on why their measure of value or their measure of profitability is better than everybody else's.

他们每个人都能拿出扎实的论据和充分的证据。

They would all have great cases and great evidence.

我特别喜欢一句话：每个博士背后，总能找到一个立场完全相反的博士。

One line that I love in this type of stuff is that for every PhD, there's an equal and opposite PhD.

你总能找到人跟你讲，他们的资产定价模型、因子或者产品才是最好的。

You can find me someone to tell me why their asset pricing model or their factor or their product is the best.

但我也能找到同样聪明、同样有资质的人来反驳他们。

And I can find somebody just as smart, just as qualified to disagree with them.

这行里挺有意思的一点。

One of the funny things about our space.

没人知道谁对谁错，得等三十年后才能看清。

And nobody will know if they're right until thirty years from now.

到时候我们回头一看，哦，原来那个人是对的。

And then we'll look back and say, oh yeah, well that guy was right.

但即便如此，我们还是不知道他们接下来三十年会不会继续对。

But then we won't know if they're going be right for the next thirty years.

确实如此。

That's so true.

我们这行挺有意思的。

We work in a funny space.

金融圈里的人随便说什么都行。

People in finance can just say stuff.

人们愿意相信他们，只是因为他们的说法听起来有道理。

People can choose to believe them because they have a good story.

但真正验证他们说的对不对，得等很多年以后。

But we won't know if what they're saying is right or true until many years in the future.

到那时候，大家 probably 早就忘了这场争论，转而去追下一个热门趋势了。

And everyone will have probably forgotten about the whole debate by then anyway and chased whatever new hot trend is out there.

没错。

That's right.

我想把话题拉回到实际应用上来。

I do want to bring this back to practical relevance.

我们刚才在讨论这些资产定价因子。

So we're talking about these asset pricing factors.

意思是说，这些因子可能带来更高的预期收益，投资者如果相信的话，可以适当偏向它们，从而提升股票组合的预期回报。

We're talking about the idea that they may have higher expected returns and that investors could potentially tilt toward them to increase the expected returns of their equity portfolio.

持有市值加权的市场组合，本质上就是让你暴露在市场风险溢价之下。

So owning the market capitalization weighted market is giving you exposure to the market risk premium.

但正如你所说，丹，如果你相信这些模型的判断，你也可以主动偏向其他因子，来提升预期收益。

But as you said, Dan, you can tilt toward other factors to potentially increase your expected returns, at least if you believe what these models suggest.

那么，具体该怎么做呢？

Now how do you do that?

个人想要通过选股来实现这一点，恐怕会很麻烦，也很困难，不值得这么做。

For an individual to do it by selecting individual stocks be probably kind of arduous and tricky and probably not worth it.

不过，有些基金公司正在利用这些研究成果，构建多元化的投资组合。

But there are fund companies that are using this research to build diversified portfolios.

它们有点像低成本的指数基金，但能让你获得超越市场风险的回报敞口。

They're kind of like low cost index funds that deliver exposure to more than just market risk.

严格来说，它们不算指数基金，因为并不跟踪某个指数。

They're usually not technically index funds because they don't track an index.

但从实际效果看，它们非常相似——分散度高、换手率低、费用低廉，等等。

But functionally, they're very similar, broadly diversified, low turnover, low cost, all that stuff.

Dimensional基金顾问公司在因子投资研究方面有着悠久的实践历史。

Dimensional fund advisors have a long history of implementing factor investing research.

他们在这些研究成果发表之前，就已经开始设计相关产品了。

They started building products before any of this research came out.

我记得他们第一个产品推出的时间，差不多就是那篇揭示规模异象的论文问世的时候。

I think their first product launched around the same time that the paper documenting the size anomaly came out.

Dimensional刚推出时，因子投资还不存在。

Factor investing wasn't a thing when Dimensional launched.

他们当时只是想做一个小盘股指数，虽然严格来说那根本不是指数。

They were just trying to build a small cap index basically, although it wasn't actually an index.

他们想打造一款小盘股产品，让机构投资者能用它来平衡自己通常偏向大盘股的投资组合。

They're trying to build a small cap product that institutions could use to complement their often large cap tilted portfolios.

后来学术研究陆续出来，而他们早就和学术圈建立了联系。

And then this academic research starts coming out and they already had the connections to the academic community.

随着新研究的发表，他们持续把这些成果应用到产品中。

They continued to implement the academic research as it came out.

他们最早是从规模因子开始的。

So they started with a size portfolio.

等到价值因子的研究出来后，他们也加入了价值策略，之后还持续纳入了盈利能力等其他因子。

They eventually started using value once that research started to come out, and they've continued to implement things like profitability.

他们确实有一套实现动量因子的方法，而且 turnover 并不高。

They do have a way of implementing momentum actually that's not super high turnover.

他们把这一点融入了自己的交易流程中。

They use it as part of their trading process.

他们一直紧密联系着这个理念的学术根源。

They're very connected to the academic roots of this idea.

尤金·法玛——我们提到的那篇论文的合著者之一——是公司的创始董事，至今仍在董事会任职。

Eugene Fama, one of the paper that we're talking about co authors, was a founding director and remains on the board today.

肯特·弗伦奇，另一位合著者，也与Dimensional有着长期的合作关系。

Kent French, other co author, has long standing connections to Dimensional.

从长期来看，Dimensional的投资业绩一直相当不错。

Dimensional's track record in the long run has been pretty good.

最近几年，他们在美國的表现有些吃力，因为那里的大盘成长股表现太强势了，而Dimensional恰恰避开了这类股票。

They struggled a bit recently in The US in particular because large cap growth has just done so well there and Dimensional tilts away from that.

但在国际市场，甚至在加拿大，他们的表现都很出色。

But in international markets and even in Canada, they've done pretty well.

不过有个限制是，很多年来，Dimensional的产品只通过理财顾问提供。

One catch is that Dimensional used to be only available through financial advisors for many, many years.

现在在美国市场，它们已经以ETF的形式推出了，不过加拿大还没有。

They're now available as ETFs in The US market, not in Canada though.

但最近发生的事是，Avantis这家公司的创始人，原本是Dimensional的老员工，他们离开后创办了这家竞争对手。

But what happened more recently is that Avantis investors, is a Dimensional competitor basically, who's some folks who had previously been at Dimensional for many years left and started this competitor called Avantis.

他们推出了类似的产品。

They launched similar products.

他们在Dimensional之前就率先在美国推出了ETF。

They launched ETFs in The US before Dimensional did.

就在几周前，他们和加拿大帝国商业银行合作，正式在加拿大推出了ETF。

And they have now just launched a few weeks ago when this episode comes out ETFs in Canada in partnership with CIBC.

我们今年三月曾邀请Avantis的首席投资官爱德华多·雷佩托来做客，他详细又生动地聊过这些加拿大产品。

And we did have the CIO of Avantis, Eduardo Repetto on this podcast back in March talking in lots of entertaining detail about those Canadian products.

我觉得以后我们可能会专门做一期，深入聊聊他们的加拿大产品。

I think we probably will do an episode at some point doing a deeper dive on their Canadian products.

我得顺便提一下，我们确实大量使用了Dimensional的基金。

I do want to mention real quick PWL, we do use Dimensional funds pretty extensively.

我们没有从Dimensional或Avantis那里拿过任何报酬。

We're not paid by Dimensional or Avantis.

在这期节目中提到它们，我们也没有收任何费用。

We're not being paid to mention them in this episode.

我们从来不搞这种操作。

We don't do that kind of thing.

那这对作为投资者的你来说意味着什么？

So what does this all mean for you the investor?

证据表明，长期的预期收益主要来自某些系统性的风险因子。

Evidence suggests that long term expected returns are driven by specific systematic exposures.

这些因子我们今天已经很清楚了，得益于几十年的学术研究，表明投资者可以通过偏向某些类型的股票来获得更高的预期回报。

Exposures that we know about today due to decades of academic research implying that investors may achieve higher expected returns by tilting toward certain types of stocks.

至于具体是哪些股票，以及如何高效、低成本地实现这一点，那就是另一回事了。

Which stocks and knowing how to do it effectively and efficiently at a low cost is a whole other kettle of fish.

但像Dimensional基金顾问和Avantis投资者这样的公司，正是在做这件事。

But there are fund companies like Dimensional Fund Advisors and Avantis investors that do that.

他们打造低成本、广泛分散的投资组合，专门用来实践我们刚才讨论的学术理论——多因子资产定价，并将其应用到实际投资中。

They create low cost broadly diversified investment portfolios that are specifically built to take the academic theory that we've been talking about, multi factor asset pricing and apply it to investment portfolios.

就像我开头说的，法玛和弗伦奇的这篇开创性论文，构成了我投资思维的重要基础。

So like I said at the beginning of this episode, this seminal paper from Fama and French really forms the foundation for a big part of how I think about investing.

正如我之前提到的，这也是我最终加入PWL的原因之一。

As I mentioned earlier, it's part of how I arrived at PWL.

同样，PWL资本自2003年帮Dimensional进入加拿大以来，一直使用他们的产品，这也是原因之一。

And it's also part of the reason that PWL Capital has been using Dimensional since we helped bring them to Canada back in 2003.

那又是另一个故事了。

That's a whole other story.

当年卡梅伦和几位同事读到拉里·斯威德罗关于这方面的文章，觉得挺有意思，后来就和Dimensional搭上了线。据说中间还有个挺有意思的事儿，大卫·布思当年特地来加拿大见PWL的人。

That was like Cameron and a few other folks came across Larry Swedroe's writing on this stuff and thought that was pretty cool and ended up getting connected with Dimensional and ended up I think there's a funny story in there somewhere about David Booth came to Canada to talk to PWL.

他们差点儿把我们给拒了，因为我们有个研究部门。

And I think they almost shut us down because we had a research department.

他们以为我们搞的是个股研究，但其实不是，完全不是。

And then they assumed that that meant that it was like individual security research and like, no, no, no.

我们并不想跟你们合作。

We don't want to partner with you guys.

但他们后来发现，我们用的是指数基金，不是那种个股研究。

But then they kind of figured out that we were using index funds, and it wasn't that kind of research that we were doing.

那时候，PWL还没那么大。

Back then, I mean, PWL was not that big.

今天，要是有家大型基金公司说‘好吧’，我一点都不意外。

Today, it wouldn't surprise me if a big fund company said, okay.

他们会认真听你的意见，如果是一家美国大公司，说不定还会把产品引入加拿大。

You know, we're gonna listen to what you have to say, and maybe if this is a big US company, maybe bring the product to Canada.

但在2003年，PWL还是一家很小的公司。

But in 2003, it was a pretty small company.

在那之前，PWL就已经从选股转向了传统的指数基金投资。

PWL sort of transitioned from being stock pickers to traditional index fund investing before that.

但即便在2003年，加拿大市场上也几乎没有适合想做基础指数基金投资的人的产品。

But even in 2003, there wasn't a whole heck of a lot of product out there for people who wanted to do even the most basic index fund investing in Canada.

那时候还处于非常早期的阶段。

So that was really early days.

要是能亲耳听听那些讨论，肯定特别有意思。

It would have been fun to have been in those rooms and heard those discussions.

我敢打赌，肯定有不少精彩的故事。

Oh, I'm sure there are some cool stories.

我以前还真没怎么深入细讲过这些事。

That's something I've never really tried to camera in too much detail about.

我知道大概的来龙去脉，但确实，里面肯定藏着不少有意思的事。

I know the kind of the broad strokes of the story, but yeah, I'm sure there's some neat stories in there.

你说得对。

You're right.

我没见过他们当年用的那些模型，但我知道他们用了一些在美国上市的小盘价值型ETF来获取因子敞口。

I haven't seen the models that they were using back then, but I know they were using some US listed small cap value ETFs to get some factor exposure.

他们用的应该是些指数基金，我猜多半是指数型共同基金。

They're using some index funds, probably some index mutual funds, I would imagine.

我觉得那时候这些产品更常见一些。

I think those were a little bit more common.

那时候是iShares吗？

Was it iShares at that point?

我想应该是Jeez。

I guess it was Jeez.

对。

Yeah.

巴克莱。

Barclays.

那是最初的加拿大所有者。

That was the original Canadian owner.

所以九十年代末，加拿大确实已经有ETF了，但选择非常少。

And so, like, in the late nineties, yeah, there was some ETF availability in Canada, but the pickings were pretty slim.

当时你能买到的产品种类很有限。

You didn't have a whole lot of flexibility with what you were buying.

如果听众想了解我们如何把这种思路应用到PWL客户的投资组合中，我们做过一期节目，专门聊了我和丹在这方面的一些不同看法。

So if listeners want to learn more about how we apply this thinking to our clients portfolios at PWL or not, We did an episode on discussing how Dan and I think about that a little bit differently.

你可以在节目简介里找到链接，预约和PWL的同事聊一聊。

You can use the link in the episode description to book a time to chat with one of our folks here at PWL.

好了。

All right.

关于那篇改变一切的金融论文，我们的讨论就到这里。

That concludes our discussion on the finance paper that changed everything.

接下来进入节目后半段。

Let's go to the after show.

今天咱们只有一条听众留言。

I think we just have one review in there today.

不过挺长的。

It's a long one though.

Dan，你来念一下吧？

Do you want to read it, Dan?

我今天话可真不少。

I did a lot of talking today.

好的。

Alright.

我们先念一下免责声明吗？

Do we need to read this disclaimer first?

对，对，说得对。

Oh, true, true, true.

我来念免责声明。

I'll do the disclaimer.

你来念评论吧。

You can do the review.

这个安排不错。

That sounds good.

我们收到一条来自苹果播客的评论，需要在SEC规定下朗读。

We have a review from Apple Podcast to read under SEC regulations.

根据证交会的规定，我们必须披露这条评论是否由客户留下，是否支付了直接或间接的报酬，以及是否存在与该评论相关的利益冲突。

We are required to disclose whether a review, which may be interpreted as a testimonial was left by a client, whether any direct or indirect compensation was paid for the review or whether there are any conflict of interest related to the review.

通常评论都是匿名的，包括这一条。

As reviews are generally anonymous including this one.

是的。

Yep.

来自澳大利亚的戴夫。

Dave Down Under.

这确实是个匿名名字。

That is anonymous indeed.

也可能是他的真名。

Could be his real name.

有可能。

It could be.

我们无法判断评论者是否为客户，也无法披露任何相关的利益冲突。

We are unable to identify if the reviewer is a client or disclose any such conflicts of interest.

他们也在澳大利亚？我表示怀疑。

They're also in Australia, I highly doubt.

要是的话，我们早该知道了。

I think we would know.

不太可能是我们的客户。

Unlikely to be our clients.

对。

Yes.

那好吧。

So, all right.

这是那条评价。

Here's the review.

上面说，投资问题已经解决了。

It says, investing has been solved.

这个播客改变了我对金钱的看法。

How this podcast changed my money mindset.

这个播客彻底改变了我对投资、金钱以及许多其他事情的看法。

This podcast has completely changed how I think about investing, money, and many other things.

从小就被灌输投资就是赌博，但这个播客用扎实、理性又有趣的内容让我明白，事实根本不是这样。

Having been told that investing is always gambling growing up, this podcast has shown me that this does not need to be the case by providing evidence based level headed and entertaining content.

虽然有些集数更侧重加拿大市场，但其中的原则对全球任何个人投资者都适用。

While some episodes are more Canada focused than others, the principles can be applied by any retail investor around the world.

我特别喜欢本和他的搭档、嘉宾们一再强调：投资本质上早就有了标准答案，大多数人只是问错了问题。

I especially like when Ben, his co hosts and guests show over and over again that investing has basically been solved and most people simply ask the wrong questions.

我确实持有一个全球分散、按市值加权的指数基金组合，还稍微做了一些因子倾斜，但更重要的是，我为自己制定了一套财务计划——虽然说起来挺简单的。

I do hold a globally diversified market cap weighted index fund portfolio with a slight factor tilt, but more importantly, I've created my own financial plan, admittedly a pretty straightforward situation.

从明确目标开始，到建立一套能长期坚持的投资理念，再到模拟各种可能的结果，算出我需要存多少钱、能承受和愿意承担哪些风险，才能实现未来的支出目标，这一切让我对自己的决策充满信心。

Starting with defining goals over creating an investment philosophy that I can stick with to eventually modeling outcomes to figure out the required savings rate, the risks I'm able, willing and need to take along the way to meet my future spending goals has made me very confident in my decision making.

我有软件工程的背景，作为租房族，自从四年前半开始投资以来，我从未错过一次定投，反而一直稳步提高投入金额，没让生活成本的膨胀拖后腿。我也特别喜欢那些讨论租房和买房的节目。

Software engineering background helps As a renter who has not missed a single DCA contribution since I started investing four and a half years ago, and in fact has managed to increase contributions consistently instead of letting lifestyle creep win, I also love the episodes about the rent versus buy decision.

虽然没能让我的朋友们相信我买房不是傻瓜行为，但话说回来，也不可能人人都认同啊。

Not that it has convinced any of my friends that I'm not a complete idiot by buying a property, but Hey, you can't win them all.

感谢你付出的所有努力，来自澳大利亚的戴夫·唐·安德森在 iTunes 上向你们致以最美好的祝福。

Thank you for all your work and all best wishes from the land down under from Dave Down Understand from Australia on iTunes.

这评论真不错。

Very nice review.

看来戴夫确实认真听了。

It seems like Dave has been paying attention.

他可能是那种在几周内把全部四百集都回听了一遍的人。

It sounds like he's maybe one of these people have gone back and listened to all 400 episodes over the course of a few weeks.

我们之前也听说过有几个人这么做过。

We've been talking or hearing about a few people who have done that.

这可真是一场漫长的旅程。

That is quite a marathon.

是啊，确实如此。

Yeah, it is.

太惊人了。

It is wild.

我们这次没提那篇论文的名字。

We never said the name of the paper that we talked about in this episode.

我们会把它放在缩略图里之类的，讲的是股票和债券的共同风险因素。

We'll put it in the thumbnail or something, but it's common risk factors and the returns on stocks and bonds.

这篇论文改变了世界，现在你知道它叫什么了。

It changed the world and now you know what it's called.

这就对了。

There we go.

好了。

Alright.

还有别的吗，丹？

Anything else, Dan?

没有。

No.

没问题了。

We're good.

好的。

Alright.

感谢大家收听。

Thanks everyone for listening.

下次见。

See you next time.

大家好。

Hey, everyone.

我是制作人马特。

It's producer Matt.

非常感谢您收听本期节目。

Thank you so much for tuning in to this week's episode.

在结束之前，来听听大家期待的免责声明。

Before we sign off, here's the disclaimer you've been waiting for.

在加拿大，投资组合管理与经纪服务仅由PWL Capital提供，该公司受加拿大投资监管组织监管，并是加拿大投资者保护基金的成员。

Portfolio management and brokerage services in Canada are offered exclusively by PWL Capital, which is regulated by the Canadian Investment Regulatory Organization and is a member of the Canadian Investor Protection Fund.

在美国，投资咨询服务仅由One Digital Investment Advisors LLC提供。

Investment advisory services in The United States Of America are offered exclusively by One Digital Investment Advisors LLC.

One Digital和PWL Capital是关联公司，两家合作得相当默契。

One Digital and PWL Capital are affiliated entities, and they mostly get on really well with each other.

但每家公司只对其自身的金融产品和服务承担财务责任。

However, each company has financial responsibility for only its own products and services.

本内容不构成任何证券买卖的要约或邀请。

Nothing herein constitutes an offer or solicitation to buy or sell any security.

我们偶尔会提醒大家别买那些烂投资，但这不等于建议你去抛售它们。

Occasionally, we tell you not to buy crappy investments in the first place, but that's not the same thing as telling you to sell them.

本沟通材料仅用于信息参考目的。

This communication is distributed for informational purposes only.

文中信息来源于我们认为可靠的渠道，但未必完全准确。

The information contained herein has been derived from sources believed to be truthy, but not necessarily accurate.

我们确实很认真地在做，但无法提供任何保证。

We really do try, but we can't make any guarantees.

即使我们说的都没什么原则性错误，也可能只是部分真相。

Even if nothing we say is fundamentally wrong, it might not be the whole story.

此外，本内容不应被视为投资、税务或法律建议。

Furthermore, nothing herein should be construed as investment, tax, or legal advice.

虽然我们称这个播客是帮你每周认清理性投资和财务决策的现实，但你做实际决定时别真靠我们，只适合拿来假设性地参考。

Even though we call the podcast your weekly reality check on sensible investing and financial decision making, you shouldn't rely on us when making actual decisions, only hypothetical ones.

不同类型的投资和策略风险程度不同，并不是每个人都适合。

Different types of investments and investment strategies have varying degrees of risk and are not suitable for all investors.

你应该咨询专业顾问，看看这些信息如何适用于你个人的情况。

You should consult with a professional adviser to see how the information contained herein may apply to your individual circumstances.

也有可能完全不适用。

It might not apply at all.

说实话，大部分内容你其实可以当没看见。

Honestly, you can probably ignore most of it.

所有提到的市场指数都不含管理费，也无法间接投资，这挺遗憾的，因为要是能投的话简直太棒了。

All market indices discussed are unmanaged, do not incur management fees, and cannot be invested indirectly, which is a shame because it would be awesome if you could.

所有投资都伴随着风险，可能赔钱、睡不着觉、掉头发，甚至丢面子。

All investing involves risk of loss, including loss of money, loss of sleep, loss of hair, and loss of reputation.

本内容绝不构成任何特定收益或回报的保证。

Nothing herein should be construed as a guarantee of any specific outcome or profit.

过去的表现并不能代表或保证未来的成果。

Past performance is not indicative of or a guarantee of future results.

要是能的话，多伦多枫叶队的球迷日子可就轻松多了。

If it were, it would be much easier to be a Leafs fan.

本节目中所有陈述和观点均属主持人或嘉宾个人意见，仅基于本节目首次发布时的情况。

All statements and opinions presented herein are those of the individual hosts and or guests and are current only as of this communication's original publication date.

如果这些观点后来都被推翻了，也不用觉得意外。

No one should be surprised if they have all since recanted.

One Digital 和 PWL Capital 都没有义务在情况变化后更新这些陈述或观点。

Neither One Digital nor PWL Capital has any obligation to provide revised statements and or opinions in the event of changed circumstances.

我们下次再见。

See you next time.