掌握因子投资全攻略：Swedroe权威指南

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《Your Complete Guide to Factor-Based Investing》是一本全面介绍因子投资的权威指南，专为金融领域的投资者特别是量化投资爱好者设计。本书由Larry E. Swedroe和Andrew L. Berkin共同撰写，他们在书中深入浅出地总结了学术界和实践者在因子投资领域的研究成果。作为一本被誉为因子投资界的“米其林指南”，它不仅适合初入投资门径的新手，也对经验丰富的投资者有着重要的参考价值。因子投资是一种策略，它强调通过识别和利用资产定价中的特定因素（如规模、价值、动量、低波动性等）来构建投资组合，以期超越市场平均水平的回报。与传统的被动指数投资，如基于市值加权的指数基金相比，因子投资更侧重于主动管理，旨在捕捉到那些被市场忽视但能带来超额收益的机会。书中详细探讨了因子投资的关键概念，包括如何识别有效的因子、如何衡量因子的表现、以及如何在实际操作中结合这些因子进行投资决策。此外，作者还对因子投资的税务影响和潜在争议进行了分析，比如关于是否因子投资在扣除税收后仍优于广泛使用的低成本指数投资的问题，这可能会引发深入的讨论和思考。 Swedroe本人以其在量化领域的长期贡献和持续的学术分享而闻名，他的博客成为了许多投资者获取最新研究成果的重要平台。《Your Complete Guide to Factor-Based Investing》的出版，无疑为读者提供了一个系统化的学习资源，帮助他们理解因子投资的理论基础和实战技巧，以便在不断变化的金融市场环境中做出明智的投资决策。这本书是每一个想要深入了解因子投资并提升投资技能的读者不可或缺的参考资料，无论是寻求超额收益的投资者，还是希望保持投资策略多样性与效率的资产管理者，都能从中受益匪浅。通过阅读这本书，投资者不仅能掌握现代投资理论，还能了解到如何将这些理论应用于实际投资实践中，以实现更稳健且有策略的财富增值。

applies to sports betting, you would expect it to work there, too. Finding it does is a

wonderful confidence-builder, even if you never watch sports, let alone bet on

them. That is, after seeing similar intuition hold up for sports betting, you should

have somewhat more confidence in that intuition leading to real, not random,

returns for stocks.

Vitally, Larry and Andrew always stress that no investing plan, diversifying

across good factors included, survives too much impatience. Although they strive to

show us factors that work more often than they don’t, and work better and more

consistently in combination, Larry and Andrew don’t go down the cheap, easy, and

false path of promising an easy road. Rather, they stress that belief in the factors

you choose is vital not just to make sure they are real, and not just data mining, but

because without well-formed, strongly held beliefs (perhaps stemming from

persistence, pervasiveness, robustness, intuition, and investability!), nobody will

stick with their investing process through the inevitable tough times. Good and wise

advice. It’s not hard to give back more than all the positives of a good investment

process by falling down on this last vital hurdle.

Finally, I’d contrast their work with the legion of investing books telling you

how to actively pick stocks just like Warren Buffett (actually, Larry and Andrew do

this, too, but I’ll let them tell you about it). Those books are, in my view, far easier

to write than this one. There are always great stories when it comes to individual

companies: fascinating tales of greatness and woe that end wonderfully for the sage

stock picker who is the hero of this tale. In contrast, Larry and Andrew have taken

on the task of describing an inherently quantitative affair. Factors don’t have made-

for-TV endings. Success is measured by less thrilling statements like, “and then the

factor had a +1 standard deviation decade,” versus discretionary stock-picking

stories that end with “and then the company I invested in invented the iPod!” Of

course, while the stories are better in the world of discretionary stock picking, it

has one small problem (just a small one, mind you): It generally doesn’t work! This

is not the place to dive into such a contentious issue (so I’ll just assert it), but both

economic logic and a large body of research has shown that discretionary stock

picking is, in broad generality (with obvious exceptions like Mr. Buffett), not the

path to riches. So they could’ve gone with the better and easier stories, and written

an easier (for them and the reader) and maybe more entertaining book. Instead, they

What you will learn is that while Buffett is considered by many to be a peerless

stock picker, we now know that his success has not been due to such skill. Instead,

it is attributable to his identification of certain key characteristics, or factors, that

would deliver above-market returns. In other words, if you knew what

characteristics to look for, you could replicate his record of successful equity

selection by investing in funds that own the stocks with those key traits. It is

important to understand that in no way does this detract from what Buffett, or his

mentors (legendary value investors Benjamin Graham and David L. Dodd)

accomplished. After all, they discovered these characteristics decades before the

academics. In fact, it is often the case that academics uncover important stock

characteristics by studying the performance of investors who have outperformed the

market. Their goal, then, is to determine if these investors’ successes were the

result of exposure to a common factor or factors, or instead a result of stock-

picking and/or market-timing skill. With that said, once the secret sauce of great

investors has been discovered, there is no longer any need for investors to perform

any fundamental research on individual stocks. You can now achieve the results of

these legends of finance by investing in low-cost, passively managed (meaning

there is no individual stock picking or market timing) exchange-traded funds

(ETFs) or mutual funds that provide exposure to these factors.

Our journey will take you through the land of academic research with an

extensive review, citing more than 100 academic papers, of the more than 50-year

quest to uncover the secret of successful investing. Our objective is not to convince

you to adopt any one viewpoint or our specific interpretation of the research on

factor investing, but rather to provide you with the information and data you need to

make your own informed investment decisions. Along the way, you will come

across some technical terms — we have included a glossary to provide an

explanation of these terms, while allowing for ease of reading.

Given the great rewards available to those who could identify these factors, it

should not be a surprise that there has been a great amount of effort expended in this

pursuit. In their 2014 paper, “Long-Term Capital Budgeting,” authors Yaron Levi

and Ivo Welch examined 600 factors from both the academic and practitioner

literature. And authors Campbell R. Harvey (past editor of The Journal of Finance),

Yan Liu, and Heqing Zhu in their 2015 paper “…and the Cross-Section of Expected

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