What is *Better Than Alpha* by Christopher Schelling about?

*Better Than Alpha* challenges traditional investing strategies focused on beating markets ("alpha") and advocates for a three-step framework prioritizing **smart behavior, disciplined processes, and effective governance** to achieve superior returns. It emphasizes behavioral finance insights, critiques market myths, and offers actionable steps for institutional investors to align decisions with long-term objectives.

Who should read *Better Than Alpha*?

This book is ideal for **institutional investors, fund managers, and finance professionals** overseeing pensions, endowments, or insurance portfolios. Individual investors seeking to refine their strategies with behavioral finance principles and structured decision-making will also find value, though the content leans toward institutional applications.

Is *Better Than Alpha* worth reading?

Yes—it provides a **fresh, evidence-based perspective** on investing, debunking alpha-chasing myths while offering practical frameworks for improving outcomes. Its blend of technical analysis, real-world examples, and behavioral insights makes it a standout resource for professionals navigating complex markets.

What are the three steps outlined in *Better Than Alpha*?

Schelling’s framework focuses on: * **Behavior**: Mitigating cognitive biases like overconfidence and herd mentality. * **Process**: Implementing systematic habits for asset allocation and risk management. * **Organization**: Establishing governance structures to reduce conflicts of interest and ensure accountability.

How does Christopher Schelling critique the pursuit of alpha?

Schelling argues that chasing alpha is **statistically futile** for most investors due to market efficiency and fees. Instead, he advocates focusing on **value creation** through disciplined processes and behavioral adjustments, which offer more reliable paths to excess returns.

What role does behavioral finance play in *Better Than Alpha*?

The book highlights how biases like loss aversion and recency bias sabotage decision-making. Schelling provides tools to **identify and counter these tendencies**, such as precommitment strategies and checklist-driven processes, to improve investment discipline.

Is *Better Than Alpha* relevant for individual investors?

While geared toward institutions, individual investors can apply its **hierarchy of alpha** concept—prioritizing tax efficiency, cost control, and asset allocation over stock-picking. The behavioral frameworks also help avoid common pitfalls like emotional trading.

How does *Better Than Alpha* compare to other investing books?

Unlike populist guides (e.g., *The Intelligent Investor*), it targets **professional money managers** with advanced strategies for governance and institutional psychology. It complements academic texts by linking theory to practical, real-world execution.

超越阿尔法

捕捉变革世界中超额收益的三个步骤

克里斯托弗·谢林

3.83(18 Reviews)

《超越阿尔法》概述

《超越阿尔法》（Better Than Alpha）彻底革新了超越市场回报的投资理念。克里斯托弗·谢林（Christopher Schelling）提出的三步走框架——行为阿尔法、流程阿尔法和组织阿尔法——已经改变了机构投资策略。该书获得了 CFA 协会的认可，揭示了在当今金融格局中，明智的思维为何比追逐市场更为重要。

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第 1 章

Beyond the Numbers: Redefining Investment Success

In a world where financial jargon often serves as a smokescreen rather than illumination, Christopher Schelling's "Better Than Alpha" cuts through the confusion with surgical precision. This isn't just another investment book-it's a paradigm-shifting examination of what truly matters in portfolio management. Schelling, a Harvard-educated investment veteran who has allocated billions across alternative investments, challenges the very foundation of how we measure success in the financial world. The book has garnered praise from institutional investors and wealth managers alike, with The Wall Street Journal calling it "essential reading for anyone serious about understanding modern portfolio theory." Even Ray Dalio of Bridgewater Associates noted it "fundamentally reframes how we should think about investment returns." What makes this work particularly timely is its relevance amid the retail investor revolution, as regulatory changes increasingly expose everyday investors to alternative investments previously reserved for institutions.

第 2 章

The Alpha Mirage: Understanding What We're Really Chasing

Alpha-that magical excess return above market performance-has become the holy grail of investing. Yet most investors don't truly understand what they're pursuing. At its core, alpha is a quantitative metric measuring excess returns versus market performance, represented mathematically as the intercept in Jensen's alpha equation: a manager's returns equal their beta (correlation with market) multiplied by market excess returns, plus the risk-free rate, plus alpha. This pursuit of alpha has driven the explosive growth of active management, with trillions of dollars allocated to strategies promising market-beating returns. This seemingly simple concept becomes deceptively complex in practice. Two managers with identical 10% returns could have dramatically different alpha-one with a beta of 0.6 would generate 4% alpha (taking less risk for the same return), while another with a beta of 1.4 would produce -4% alpha (taking more risk without proportional returns). Consider a real-world example: during the 2008 financial crisis, many hedge funds boasted strong returns but achieved them through excessive leverage, masking negative alpha beneath superficially impressive numbers. Benchmark selection further complicates matters. An effective benchmark must satisfy five critical criteria: it must be specified in advance, relevant to the strategy, measurable and transparent, investable through passive vehicles, and provide comprehensive market coverage. For instance, a small-cap manager comparing returns against the S&P 500 rather than the Russell 2000 might appear to generate alpha simply through size exposure. Similarly, emerging market managers often claim outperformance by selecting convenient local indices that exclude important market segments. The mathematical reality of alpha is sobering-it's zero-sum across markets. For every investor generating positive alpha, another must underperform. This fundamental truth explains why sustainable alpha requires consistently extracting returns from less sophisticated market participants. Even with proper benchmarks, managers can manipulate calculations through subtle portfolio adjustments like adding higher-risk bonds or small-cap stocks to large-cap portfolios. Common tactics include style drift, where managers gradually shift their strategy to capture trending sectors, or risk-shifting, where they increase leverage during favorable conditions. The challenge of identifying genuine alpha extends beyond mathematics to behavioral factors. Research shows that even professional investors often mistake beta-driven returns for skill-based alpha. This confusion is compounded by the industry's tendency to highlight successful periods while downplaying underperformance, creating an illusion of persistent alpha generation. Studies of mutual fund performance over multiple decades reveal that true, sustainable alpha is exceptionally rare, with fewer than 1% of funds consistently generating significant risk-adjusted outperformance after fees.

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第 3 章

The Evolution of Public Markets: From Stock Picking to Factor Investing

The story of alpha in public markets begins with pioneers like Jonathan Bell Lovelace, a mathematical prodigy who founded Capital Group after correctly predicting the 1929 crash. His flagship Investment Company of America fund delivered impressive returns-$1 invested in 1934 grew to $16,550 by 2019 versus just $7,602 for the S&P 500. This 12% annualized return versus the index's 10.9% represented true alpha of 1.4% annually, with particularly strong outperformance during market downturns. But the landscape transformed dramatically with John "Jack" Bogle's creation of Vanguard and the world's first index fund in 1976. Despite industry ridicule-critics called it "unmanaged," "socialist" and "un-American"-Bogle's vision revolutionized investing. By 2019, passive equity funds ($4.27 trillion) had overtaken active management ($4.24 trillion), a remarkable shift from 1987 when active managers controlled 612 times more assets than indexers. This transition wasn't arbitrary-it reflected active management's consistent failure to deliver on its promises. By 2018, 65% of large-cap mutual funds trailed their benchmarks, marking the ninth consecutive year of underperformance. Even more damning, 85% of active managers failed to beat their index over 10 years, and more than 90% underperformed over 15 years. Market efficiency explains this phenomenon. As Charles Ellis noted, the investment profession has transformed from just 5,000 professionals engaged in price discovery to over 1 million today. The paradox is inescapable: the more investors seek to exploit inefficiencies, the more efficient markets become. This evolution gave rise to factor investing-strategies that split the difference between indexing and concentrated active management by using computers to analyze thousands of stocks based on specific characteristics like price-to-book, earnings quality, and momentum. Research published in the Journal of Portfolio Management confirmed that pure factor exposure generated consistent excess returns over forty years: small caps delivered nearly 5% annually over large caps, while value stocks outperformed growth by 11.6% annually. Most critically, subsequent research revealed that after controlling for factor exposures, no mutual fund managers have ever generated persistent alpha-all predictable excess returns came from these fundamental characteristics.

第 4 章

The Hedge Fund Story: From Extraordinary to Ordinary

Hedge funds began in 1949 when Alfred Winslow Jones created an investment partnership that generated remarkable returns. His success attracted legendary investors like Warren Buffett, Michael Steinhardt, and Julian Robertson, who collectively averaged nearly 22% returns over three decades. The second generation of hedge fund managers in the late 1980s and early 1990s still averaged 20% returns over 20-year periods-double market returns. These early hedge funds primarily employed arbitrage or relative value strategies-buying one security while shorting a related one. Examples include pairs trading, merger arbitrage, capital structure arbitrage, and fixed-income arbitrage. These strategies exploited price relationships between economically linked securities, with risk determined by how closely related the assets were. However, the industry's performance has deteriorated dramatically. While hedge funds historically outperformed equities (9.5% vs 9.2% since 1990), from 1990-2004, they dominated with 14.4% annual returns versus the market's 9.9%. But since 2005, they've averaged just 4.5% annually compared to the market's 8.5%-trailing by nearly 50%. This collapse coincided with institutional investors replacing funds of funds as the dominant investor group. By 2012, institutions controlled nearly half of industry assets, helping fuel explosive growth from 1,250 funds managing $25 billion in the early 1990s to almost 10,000 funds with $3 trillion by 2018. Despite research consistently showing smaller, younger funds outperform by approximately 3.65% annually, institutional capital flowed disproportionately to the largest managers, with 11% of firms controlling 92% of industry assets by 2014. Expectations also shifted dramatically. Early institutional investors sought return enhancement, receiving double-digit returns with low volatility (6.9%) and moderate correlation to equities (0.7). But as more institutions entered, they demanded "equitylike returns with bondlike risk"-roughly 9% returns with 6% volatility. Unfortunately, from 2005-2019, hedge fund correlation to stocks jumped to 0.83, forcing managers to reduce volatility below 6% while returns plummeted to 4.5%. The future of hedge funds likely lies in quantitative strategies, which have generated 12.9% annual returns since January 2010 versus just 5.1% for the broader hedge fund index. True quant alpha comes from constantly researching new signals, implementing robust statistical processes, and disciplined killing of signals that no longer work.

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第 5 章

Private Equity: The Last Frontier of Alpha?

Private equity traces its institutional roots to the 1940s with the founding of American Research and Development Corporation (ARDC) and JH Whitney and Company. ARDC's investment in Digital Equipment Corporation reportedly returned 500 times their initial investment with an IRR exceeding 1,000%, spawning industry stalwarts like Draper and Johnson, Kleiner Perkins, and Sequoia. The industry has experienced four distinct waves: the 1980s LBO boom fueled by Michael Milken's junk bonds, the 1990s internet bubble and subsequent dot-com bust, the mid-2000s credit-fueled LBO boom that ended with the Global Financial Crisis, and the current post-crisis expansion that has seen private equity assets grow from under $1 trillion to nearly $4.5 trillion. Despite its cyclicality, private equity has historically delivered strong returns, averaging around 13% IRR according to Cambridge Associates data. Using the public market equivalent (PME) calculation for proper comparison shows that private equity has outperformed public markets by 2.5-4.0% over 20 years. A Cliffwater study examining public pension returns from 2000-2017 found private equity returned 9.3% versus 6.8% for public stocks. However, in more recent periods, this outperformance has diminished significantly. Over 1-, 5-, and 10-year periods, the average excess return drops to roughly 1%, with virtually no outperformance versus large-cap stocks in the most recent timeframes. Analyzing 25 major PE firms from 1976-2010 reveals a dramatic drop in returns-IRRs fell from an impressive 33% in the first wave to under 15% in recent periods, while the multiple of invested capital (MOIC) plummeted from 4.7x to just under 2.0x. To understand what truly drives private equity returns, consider the hypothetical acquisition of "Super Amazing Private Company"-a growing business purchased for $200M (8x earnings), using 50% equity and 50% debt. Four years later, it's sold for $520M (9.5x expanded EBITDA), yielding a 2.5x return on the original $100M investment. This outcome resulted from several factors: revenue growth, expanded profit margins, multiple expansion, and increased leverage-the same factors that drive returns in public equities. Unlike public equity managers, private equity exhibits tremendous return dispersion. While top-quartile public equity managers outperform bottom-quartile ones by just 2.6% annually (10.3% vs 7.7%), in private equity this gap explodes to nearly 20% (22.5% vs 2.7%). More importantly, private equity demonstrates stronger performance persistence than almost any other asset class, with top performers consistently outperforming in subsequent funds.

第 6 章

The Hierarchy of Alpha: Understanding Different Return Sources

After examining various investment strategies, a clear hierarchy of alpha emerges, from the rarest and most valuable forms to the most common and accessible: 1. True Alpha: The rarest form of investment skill-generating returns with no observable correlations to known return streams. Renaissance Technologies' Medallion fund stands as perhaps the only example, achieving 39% net returns for nearly 30 years with almost no down months. So valuable is this true alpha that Renaissance no longer offers Medallion to external clients, reserving it exclusively for employees. 2. Manufactured Alpha: Created by actively implementing structural changes or operational improvements to assets. Examples include private equity strategies that grow revenue or expand profit margins, value-add real estate investments where managers renovate underutilized properties, and shareholder activism pushing for corporate changes. The operationally intensive nature of these strategies leads to stronger performance persistence. 3. Transitional Alpha: Emerges from temporal market inefficiencies where natural buyers temporarily exit a market. Research shows buying equity spin-offs after initial shareholders liquidate can generate significant outperformance-0.5% to 1.0% per month for almost two years. Other examples include post-reorganization equities and downgraded high-yield bonds that institutional investors must divest due to rating restrictions. 4. Inaccessible Risk Premium: Represents quasi-permanent structural barriers preventing many investors from accessing certain markets, including accreditation requirements, minimum investment thresholds, and regulatory prohibitions. These barriers create uneven playing fields with clear pricing differentials-privately originated corporate loans might yield 6-8% while similar broadly syndicated loans yield only 4-6%. 5. Alternative Beta: Former alpha strategies that have become more accessible through liquid, registered products like mutual funds and ETFs. Examples include catastrophe bonds, merger arbitrage funds, commodities, and systematic trend-following products. Assets in these vehicles have exploded from $14 billion in 2003 to nearly $300 billion by 2019. 6. Pure Beta: Basic, long-established asset class exposures with decades of price history and extensive research, available through thousands of competing low-fee products-essentially commoditized return streams like S&P 500 index funds or broad market investment-grade bond portfolios. 7. Factors: The fundamental building blocks underlying all investment return streams. Market beta itself is merely a rule for accessing factors, as are all forms of investment skill.

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第 7 章

Behavioral Biases: The Enemy Within

If alpha is increasingly elusive, why do investors persist in futile attempts to beat efficient markets? The answer lies in behavioral finance, which explains the gap between optimal decision-making and actual market behavior. This field has revolutionized our understanding of why even sophisticated investors often make suboptimal choices. Daniel Kahneman and Amos Tversky's groundbreaking "Prospect Theory" revealed that people make predictably irrational decisions based on how choices are presented rather than optimal outcomes. Kahneman describes two thinking systems: fast, intuitive System 1 that favors efficiency but makes errors, and deliberate, logical System 2 that requires more effort. In investment contexts, System 1 often leads to snap judgments about market movements, while System 2 is needed for careful portfolio analysis and risk assessment. Several cognitive biases consistently undermine investment decisions: 1. Inherence Heuristic: Our tendency to attribute patterns to inherent, immutable characteristics rather than conducting deeper analysis. In investing, this manifests when concepts like the equity risk premium are viewed as natural features rather than complex phenomena driven by dividend yield, earnings growth, and multiple expansion. For example, investors often assume tech stocks "naturally" outperform without examining underlying business fundamentals or changing market conditions. 2. Confirmation Bias: Our tendency to overweight information supporting existing views while dismissing contradictory evidence. Unlike scientific discovery, which advances through falsification, humans naturally seek validation rather than disconfirmation. A value investor might focus exclusively on traditional metrics like P/E ratios while ignoring crucial technological disruption factors that could invalidate their thesis. 3. Illusory Pattern Perception: Our tendency to see meaningful patterns in random data. Research shows people perceiving nonexistent patterns correlates with feeling lack of control. Financial markets create perfect conditions for this bias: decision-making about an unknowable future using imperfect data with compensation tied to outcomes. Technical analysts often fall prey to this by seeing predictive patterns in random market movements. 4. Familiarity Bias: Our tendency to favor what we know over the unknown, conflating familiarity with safety. In investing, this manifests as home country bias, with American investors allocating 82% of equity exposure to domestic stocks despite the US representing only 44% of global market capitalization. Similarly, employees often overweight their own company's stock in retirement accounts, creating dangerous concentration risk. 5. Loss Aversion: Our tendency to feel losses more acutely than equivalent gains-roughly twice as painfully according to Kahneman's research. In investing, this manifests as the "sunken-cost fallacy" where investors hold losing investments too long, hoping for recovery rather than accepting the pain of selling at a loss. This behavior often leads to larger eventual losses and missed opportunities for better investments. These biases are particularly dangerous because they operate largely unconsciously and can affect even experienced investors. Professional money managers, despite their training and expertise, show systematic biases in their trading patterns. Research indicates that up to 50% of active management underperformance can be attributed to behavioral biases rather than lack of skill or information. To combat these biases, successful investors often implement systematic decision-making processes, including pre-commitment strategies, regular portfolio rebalancing schedules, and quantitative screening tools. Some firms now use artificial intelligence to help identify and correct for human behavioral biases in investment decisions.

第 8 章

Beyond Alpha: A New Investment Paradigm

The traditional pursuit of alpha relative to benchmarks has proven largely futile for most investors, with decades of evidence showing that few consistently outperform their benchmarks after fees. While benchmarks serve a valuable purpose in evaluating historical performance, their utility as forward-looking investment tools has been severely limited. The fundamental problem is that beating a benchmark is ultimately meaningless to real-world investors - they don't "eat" alpha, they require absolute returns to fund their goals. Retirement checks, college tuition payments, and charitable distributions aren't paid from relative outperformance alone. A more sophisticated and practical approach focuses on three alternative sources of investment advantage that have demonstrated more reliable results: 1. Behavioral Alpha: This represents the excess return earned by systematically overcoming human cognitive and emotional biases rather than trying to outsmart the market. Implementation requires robust frameworks like a detailed Investment Policy Statement (IPS) that clearly specifies investment goals, risk tolerances, decision-making roles, and systematic review procedures. It demands replacing wishful thinking with evidence-based return expectations - for equities, this means understanding that returns can only come from three sources: dividend yield, earnings growth, and changes in valuation multiples. Research shows that investors who maintain systematic rebalancing processes typically outperform those making tactical shifts based on market views by 1-2% annually. 2. Process Alpha: This encompasses the improved returns achieved through implementing disciplined, systematic approaches to investment decisions. Beyond the Fundify research showing dramatic differences in angel investment outcomes based on due diligence effort (5 hours = 69% loss rate; 40+ hours = 7.1x average return), additional studies demonstrate similar patterns across asset classes. For example, institutional investors conducting thorough qualitative hedge fund due diligence achieve 1.5% annual outperformance, while systematic value investors following strict investment criteria outperform discretionary approaches by approximately 2% per year. Documentation, checklists, and consistent evaluation frameworks are crucial elements. 3. Organizational Alpha: The institutional equivalent of behavioral alpha focuses on optimizing organizational structure and decision-making processes. Multiple studies demonstrate that empowering qualified investment professionals with clear accountability generates superior returns compared to committee-based or non-professional decision making. CEM Benchmarking's comprehensive study of 900+ US institutional investors revealed corporate pensions outperforming public ones by 67 basis points annually, with the gap expanding to over 100 basis points in complex markets like private equity and real estate. Key factors include clear governance structures, competitive compensation, and operational independence. The State of Wisconsin Investment Board (SWIB) provides a compelling case study in successfully implementing these modern alpha strategies. Operating as an independent agency focused exclusively on investment management, SWIB maintains strict separation between board oversight and professional investment staff execution. Their governance structure emphasizes clear accountability, competitive compensation to attract talent, and operational flexibility. The results validate this approach: SWIB has consistently outperformed both its policy benchmark and required return rate over multiple market cycles, achieving a funded ratio of approximately 102% - ranking as the best-funded public pension system in the United States. Their success demonstrates how proper implementation of behavioral, process, and organizational alpha can generate superior long-term results without relying on traditional market-beating strategies.

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第 9 章

The Future of Investment Success

In the new paradigm of alpha, improving the odds of investment success isn't a zero-sum game. Excess returns must come from predictable drivers of income and capital appreciation-it's always been about intelligently accessing factors to hit return targets. Outperforming your underwriting provides a margin of safety; that's the true alpha. This principle becomes especially important in an era where traditional alpha generation through stock picking has become increasingly challenging. While public markets have become increasingly efficient, private markets still offer both return dispersion and persistence-the intersection where alpha potential remains. Unlike public markets where most secrets have been uncovered, private markets retain significant information asymmetry. Finding alpha here requires exploring overlooked areas, accepting illiquidity, and working with smaller, newer managers. For example, emerging managers in private equity often outperform established firms by 200-300 basis points, primarily due to their ability to focus on smaller deals and maintain operational improvements in their portfolio companies. The evolution of investment success requires a more nuanced understanding of risk assessment. True risk is 100% minus the probability of success-it's more intuitive to compare portfolios with different probabilities of meeting objectives than comparing volatility percentages. This framework helps investors better understand the real implications of their investment decisions. For instance, a portfolio with 80% probability of meeting its return target might be preferable to one with higher expected returns but only a 60% probability of success. Success in this new paradigm demands multiple complementary approaches. First, maintain an open mind toward new investment opportunities and strategies. Second, apply a scientific approach that couples fundamental theories with empirical research, testing hypotheses rigorously before deployment. Third, acknowledge that investing is inherently probabilistic - even the best strategies will fail some percentage of the time. The role of technology and data analytics has become increasingly crucial in this evolution. Machine learning algorithms can now process vast amounts of alternative data to identify patterns and opportunities that human analysts might miss. However, this technological advantage must be balanced with human judgment and experience. Perfect isn't attainable, but better always is. Perhaps real alpha isn't alpha at all, but something better - a comprehensive approach that combines behavioral discipline, systematic processes, and organizational excellence to maximize the probability of meeting your unique investment objectives. This might include implementing robust risk management systems, developing clear investment processes, and building strong organizational cultures that support long-term thinking and continuous improvement. The future of investment success lies in the ability to adapt to changing market conditions while maintaining disciplined processes. This includes understanding the limitations of traditional investment approaches, embracing new technologies and data sources, and maintaining a clear focus on probability-weighted outcomes rather than just potential returns.

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《超越阿尔法》核心主题

alpha generation
portfolio construction
active management failure
factor investing
benchmark selection

《超越阿尔法》经典语录

Alpha-that magical excess return above market performance-has become the holy grail of investing.
The mathematical reality of alpha is sobering-it's zero-sum across markets.
Critics called it "unmanaged," "socialist" and "un-American"-Bogle's vision revolutionized investing.
The more investors seek to exploit inefficiencies, the more efficient markets become.

《超越阿尔法》主要人物

Christopher SchellingAuthor and investment veteran
Jonathan Bell LovelaceFounder of Capital Group and investment pioneer
John "Jack" BogleFounder of Vanguard and creator of index funds
Charles EllisInvestment professional and market commentator

关于作者

Christopher M. Schelling 是 《Better Than Alphα: Three Steps to Capturing Excess Returns in a Changing World》 一书的作者，也是一位专注于私募市场和另类投资的资深机构投资者。凭借二十多年的从业经验，他目前在 Caprock 担任私募投资董事总经理，该公司是一家为超高净值客户管理着 88 亿美元资产的财富管理机构。

Schelling 的专业见解源于他在对冲基金、私募股权和实物资产领域近 70 亿美元的资产配置经验，期间他评估了超过 4,000 家投资机构，这使他在不断演变的市场中捕捉超额收益（alpha）方面拥有独特的洞察力。

作为 《机构投资者》（Institutional Investor） 的专栏作家，Schelling 将严谨的学术理论与实战策略相结合。他拥有伊利诺伊大学芝加哥分校的工商管理硕士（MBA）学位和伊利诺伊理工学院的金融市场硕士学位。他的 CAIA®（特许另类投资分析师）身份进一步彰显了他在另类投资领域的权威地位。本书凝聚了他经受过市场考验的框架，旨在识别表现优异的基金管理人并应对复杂的市场周期，反映了他职业生涯中长期致力于将投资者目标与可操作方法论相结合的重点。

《Better Than Alphα》 将 Schelling 的机构投资背景与易于理解的指导相结合，提供了一份他在德克萨斯州市政退休系统（Texas Municipal Retirement System）和肯塔基州退休系统（Kentucky Retirement Systems）任职期间不断完善的路线图。他的工作影响了家族办公室和养老基金，巩固了他作为现代投资组合策略领域值得信赖的权威声誉。

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Think like Nassim taleb

In an increasingly volatile world, traditional linear thinking often leads to catastrophic failure. This plan is essential for decision-makers, investors, and strategists who want to move beyond mere resilience and learn to profit from uncertainty.

5 h 30 m•4 章节

由哥伦比亚大学校友在旧金山创建

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@OojasSalunke

"The themed book list podcasts help me connect ideas across authors—like a guided audio journey."

@Leo, Law Student, UPenn

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@Cashflowbubu

查看更多网络上关于 BeFreed 的讨论

由哥伦比亚大学校友在旧金山创建

LOVED BY

1,000,000+ curious minds.

4.7

avg rating

1M+ learners

"Instead of endless scrolling, I just hit play on BeFreed. It saves me so much time."

@Moemenn

"I never knew where to start with nonfiction—BeFreed’s book lists turned into podcasts gave me a clear path."

@Chloe, Solo founder, LA

117

"Perfect balance between learning and entertainment. Finished ‘Thinking, Fast and Slow’ on my commute this week."

@Raaaaaachelw

"Crazy how much I learned while walking the dog. BeFreed = small habits → big gains."

@Matt, YC alum

108

"Reading used to feel like a chore. Now it’s just part of my lifestyle."

@Erin, Investment Banking Associate , NYC

254

"Feels effortless compared to reading. I’ve finished 6 books this month already."

@djmikemoore

"BeFreed turned my guilty doomscrolling into something that feels productive and inspiring."

@Pitiful

4.5K

"BeFreed turned my commute into learning time. 20-min podcasts are perfect for finishing books I never had time for."

@SofiaP

"BeFreed replaced my podcast queue. Imagine Spotify for books — that’s it. 🙌"

@Jaded_Falcon

201

"It is great for me to learn something from the book without reading it."

@OojasSalunke

"The themed book list podcasts help me connect ideas across authors—like a guided audio journey."

@Leo, Law Student, UPenn

483

"Makes me feel smarter every time before going to work"

@Cashflowbubu

"Instead of endless scrolling, I just hit play on BeFreed. It saves me so much time."

@Moemenn

"I never knew where to start with nonfiction—BeFreed’s book lists turned into podcasts gave me a clear path."

@Chloe, Solo founder, LA

117

"Perfect balance between learning and entertainment. Finished ‘Thinking, Fast and Slow’ on my commute this week."

@Raaaaaachelw

"Crazy how much I learned while walking the dog. BeFreed = small habits → big gains."

@Matt, YC alum

108

"Reading used to feel like a chore. Now it’s just part of my lifestyle."

@Erin, Investment Banking Associate , NYC

254

"Feels effortless compared to reading. I’ve finished 6 books this month already."

@djmikemoore

"BeFreed turned my guilty doomscrolling into something that feels productive and inspiring."

@Pitiful

4.5K

"BeFreed turned my commute into learning time. 20-min podcasts are perfect for finishing books I never had time for."

@SofiaP

"BeFreed replaced my podcast queue. Imagine Spotify for books — that’s it. 🙌"

@Jaded_Falcon

201

"It is great for me to learn something from the book without reading it."

@OojasSalunke

"The themed book list podcasts help me connect ideas across authors—like a guided audio journey."

@Leo, Law Student, UPenn

483

"Makes me feel smarter every time before going to work"

@Cashflowbubu

"Instead of endless scrolling, I just hit play on BeFreed. It saves me so much time."

@Moemenn

"I never knew where to start with nonfiction—BeFreed’s book lists turned into podcasts gave me a clear path."

@Chloe, Solo founder, LA

117

"Perfect balance between learning and entertainment. Finished ‘Thinking, Fast and Slow’ on my commute this week."

@Raaaaaachelw

"Crazy how much I learned while walking the dog. BeFreed = small habits → big gains."

@Matt, YC alum

108

"Reading used to feel like a chore. Now it’s just part of my lifestyle."

@Erin, Investment Banking Associate , NYC

254

"Feels effortless compared to reading. I’ve finished 6 books this month already."

@djmikemoore

"BeFreed turned my guilty doomscrolling into something that feels productive and inspiring."

@Pitiful

4.5K

"BeFreed turned my commute into learning time. 20-min podcasts are perfect for finishing books I never had time for."

@SofiaP

"BeFreed replaced my podcast queue. Imagine Spotify for books — that’s it. 🙌"

@Jaded_Falcon

201

"It is great for me to learn something from the book without reading it."

@OojasSalunke

"The themed book list podcasts help me connect ideas across authors—like a guided audio journey."

@Leo, Law Student, UPenn

483

"Makes me feel smarter every time before going to work"

@Cashflowbubu

查看更多网络上关于 BeFreed 的讨论

开启你的学习之旅，就是现在

第 8 章

超越阿尔法

概述《超越阿尔法》概述

一本书，多种聆听方式。

Beyond the Numbers: Redefining Investment Success

The Alpha Mirage: Understanding What We're Really Chasing

边听边看，每个词都清晰呈现

The Evolution of Public Markets: From Stock Picking to Factor Investing

The Hedge Fund Story: From Extraordinary to Ordinary

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Private Equity: The Last Frontier of Alpha?

The Hierarchy of Alpha: Understanding Different Return Sources

边听边看，每个词都清晰呈现

Behavioral Biases: The Enemy Within

Beyond Alpha: A New Investment Paradigm

从 《超越阿尔法》中收获更多

The Future of Investment Success

你已读完 《超越阿尔法》

《超越阿尔法》核心主题

《超越阿尔法》经典语录

《超越阿尔法》主要人物

关于作者

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What are the three steps outlined in Better Than Alpha?

发现更多

1,000,000+ curious minds.

1,000,000+ curious minds.

一本书，多种聆听方式。

Beyond the Numbers: Redefining Investment Success

The Alpha Mirage: Understanding What We're Really Chasing

边听边看，每个词都清晰呈现

The Evolution of Public Markets: From Stock Picking to Factor Investing

The Hedge Fund Story: From Extraordinary to Ordinary

从 《超越阿尔法》中收获更多

Private Equity: The Last Frontier of Alpha?

The Hierarchy of Alpha: Understanding Different Return Sources

边听边看，每个词都清晰呈现

Behavioral Biases: The Enemy Within

Beyond Alpha: A New Investment Paradigm

从 《超越阿尔法》中收获更多

The Future of Investment Success

你已读完 《超越阿尔法》

用户还喜欢

发现更多

《超越阿尔法》概述

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从《超越阿尔法》中收获更多

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