#读书笔记 #2 Asset Management

Author: Andrew Ang, Professor at Columbia Business School.


主要观点：

• Investment is about BAD TIMES. （非常同意）
• RE-BALANCE, re-balance, re-balance. （保留看法） 
• The future of asset management: CHEAP exposure to DYNAMIC factors. 

PART 1 - THE ASSET OWNER

Chapter 1 Asset Owners

以贫困的Timor-Leste（东帝汶民主共和国）为例子，引出asset management的重要性。进而分类探讨几类asset owner：主权财富基金(sovereign wealth fund)，养老基金(pension fund)，捐赠受托基金(foundations and endowments)，个人与家庭。

东帝汶的例子很有趣。这是个很穷的国家，人均GDP仅有1000美元左右，但其主权基金却有高达120亿美元的资产！这些钱主要来自东帝汶的石油产业。一个穷得叮当响国家，为什么把卖油赚的钱了存起来，而没有“花在刀刃上”呢？一个重要的考虑是预防荷兰病(Dutch disease)：中小国家发现自然资源后大力开采，容易导致其他产业相继衰落，并且货币升值、国际竞争力下降。一旦所依赖的大宗商品价格下跌，对经济的影响将是致命的。历史上，挪威就曾经吃过大亏：80年代油价下跌，依赖石油出口的挪威马上被打入了一段漫长的零增长。如果在大宗商品繁荣时期对外汇有所储备，困难时期就可以拿出来实施经济政策和扶植其他产业。有趣的是，东帝汶的主权基金正是在挪威人的建议下创建的，而挪威自己时至今日仍然拥有着世界上最大的主权基金。


Chapter 2 Preferences

Mean-variance utility有许多不足。比如，它并不要求return服从正态分布；而当return不是正态分布时，仅仅依赖first 2 moments是不够的。又如方差不区分涨和跌，而投资者对涨和跌是不对称的。


Chapter 3 Mean-Variance Investing

讨论diversification benefits和mean-variance optimization。作者比较了几种不同的portfolio construction（用4 broad asset classes）的Sharpe ratio：

• risk parity > equal weights / MinVol >> mean-variance

为什么unconstrained mean-variance表现差？需要估计的东西太多，而对first moments的估计非常noisy。事实上，Sharpe ratio高的几种策略本质上就是CONSTRAINED mean-variance portfolio，三者都避开了对expected return的估计：

• MinVol假设所有资产的mean return一样
• Risk parity假设所有资产的mean return一样且correlation = 0
• Equal weight假设所有资产一模一样

此外，仅依靠历史数据来算各资产的mean和variance是危险的，尤其当sample比较短的时候（pro-cyclicality）：最近return高，意味着现在价格高，E(r)应该更低才对。


Chapter 4 Investing for the Long Run

Re-balance是一种short volatility的投资策略，有negative convexity（lower/higher exposure when price is high/low），和selling put option类似。和所有short volatility strategy一样，re-balancing earns risk premium。

Rebalance有premium可以赚的另一个原因是liquidity provision。股价下跌，是因为有人想要卖掉该股票，而此时去买它就是提供了liquidity。

本章案例讲的是金融危机后的private wealth management。有趣的是，在重大损失之后，人们往往会改变投资策略，但其中的原因很少是因为risk aversion变化，而是因为expectation的变化。



PART 2 - FACTOR RISK PREMIUMS

Chapter 6 Factor Theory

作者以CAPM为切入点，讨论了它的不足和启示。值得注意的是，虽然这一模型有很多问题，但75%的CFO在capital budgeting的时候会使用它：What the market uses to price asset is the correct asset pricing model?

市场不是有效的，risk factors有risk premium，而它们有risk premium的原因又分两类：

• Rational: high return compensate for losses during bad times。因此，如果投资者对某些bad time不那么敏感，就可以获得超额回报。
• Behavioral + barrier of entry: 一个超级无敌理性的投资者和一个能绕过投资壁垒的投资者均可以获得超额回报。

Chapter 7 Factors

本章依次介绍了几个常见Factor。

首先介绍了Macro Factor：经济增长、通货膨胀、Volatility等。这些因素之所以成为factor因为他们和average投资者的“BAD TIME”息息相关：低增长/高通胀是坏消息。一般而言宏观factor的变化，尤其是非预期的变化（shock），比水平（level）更重要。需要注意的是，资产回报对这些factor的反应是contemporaneous的。

作者尤其强调了volatility as a risk factor。历史上，volatility和stock return呈负相关，这一相关性的渠道有二：其一是leverage effect，当股票下跌时，公司的D/E变大，使得其股票风险更大、volatility更高；其二是time-varying risk premium，volatility变高时，discount rate变高，进而导致股票下跌。Volatility的price of risk是负的；collect risk premium的方式是short volatility。

接下来介绍了dynamic factors。和Macro factor最根本的不同：macro factor都是long-only portfolio，dynamic factor是long-short，且确实tradable。

• Size：略讲。SmL premium自1985年以来并不明显。
• Value：背后的bad time和market risk类似，但不完全相同，更侧重LONG-TERM investment / consumption growth。理论解释：Firm investment risk，value firm有更多的unproductive capital（体现为高book-to-price），当bad time时不够flexible，high and asymmetric adjustment cost。行为解释：over-extrapolation/overreaction，投资者认为过去的growth可以继续，使得growth stock被高估。
• Momentum：回报远远高于size和value。很多声称自己是growth investing的基金其实是momentum investing（毕竟growth其实是negative risk premium）。和value不同，momentum有positive feedback，越涨越买，越买越涨，这种destabilizing的投资策略往往会有大crash。Momentum至今没有好的理论解释，大多数解释都是行为方面的：delayed over-reaction和initial under-reaction。

Chapter 8 Equities

一直以来有equity premium puzzle：股票为什么有如此高的超额回报（相比债券）？SP500自1947年以来的mean nominal return是10.4%。这样的超额回报不能完全用宏观factor如consumption解释。有几大主流的理论：

• Time-varying risk aversion：基于habit utility，当原来生活富裕的人的消费水品降低时，marginal utility会变得极高，导致非常高的local risk aversion。股票价格急剧下降，未来的return变高。
• Disaster risk：reward to compensate for rare catastrophes。此外，衡量equity premium本身有survivor-ship bias，历史上出现过若干次国家的stock market整个消失的情况。
• Long-run risk：如果model中fundamental consumption factor是一个changing process且有time-varying volatility，equity premium可被解释。(Bansal and Yaron, 2004)
• Heterogeneous investors: 重要的不是average investor，而是marginal investor。Asset price depends on the XSec distribution of agents.

股票不是好的inflation hedge。可能的理论原因：高通胀减低了real production，或升高了discount rate。行为方面，人们有money illusion，用nominal discount rate来discount real dividend。

要预测equity premium很难。在诸多变量里，唯一有一些预测能力的是10-yr Shiller earnings yield和5-yr dividend yield；而且predictability也随时间变化，市场好的时候难预测，坏的时候好预测（Henkel, Martin, Nardari, 2011）。需要注意的是，以上两个被证明略有预测力的变量都是negative feedback的，当股市涨的时候，E/Y和D/Y都会变低，对未来的equity premium期望减低，应该减持。这一特性使得rebalance是好的。

Chapter 10 Alpha

本章主要讲active management。

关于Alpha的几点零散notes：

• 如果定义alpha = r(portfolio) - r(bmrk)，所隐含的假设是产品对该benchmark的beta为一，但很多情况下并非如此。
• Alpha，尤其是CAPM alpha，是在linear framework下定义的。如果所持资产有non-linear payoff，则不能使用alpha。
• “Alpha是否真的存在？”是一个joint hypothesis问题，取决于benchmark。只有当benchmark对该投资者确实tradable/accessible时，alpha才有意义。

本章的例子是low volatility和low beta anomaly：

• realized volatility和未来回报负相关。事实上，它和contemporaneous回报也是负相关。
• realized beta和未来sharpe ratio负相关（主要因为高volatility）。与CAPM相符的是，它和contemporaneous return是正相关。由此推论，beta有一定的mean-reversion。

可能的原因有data mining, leverage constraints, agency problem, lottery preference. 

Agency Problem: Focus on TE
"Do not invest in A because it introduces large TE"

Chapter 14 Factor Investing

Factor的定义：investment styles that deliver high returns over the LONG RUN，而他们有higher return的原因是因为他们可能underperform in the SHORT RUN. 后者即所谓的"bad times"。

因此，投资决策中最重要的问题应该是：How different am I from average？我比一般人更能/更不能接受哪些bad times？一个完全average的人应该hold market。不同hedging needs的人则应该有选择性的take on risk factors。发散一点说，这帮资产管理从业者回答了一个更基本的、道德层面的问题：active management不是"loser's game"。表面上看市场是零和游戏，winner背后必有loser，但如果看risk-return profile，everybody might be better-off.

如果和mean-variance investing做比较的话，factor investing对risk的定义是bad time，而不是volatility。更重要的是，expected return根本没有进入讨论的框架内。根据Ch.3的讨论我们知道mean-variance在实际使用中很糟糕的主要原因就是无法准确对expected return进行估计；factor investing显然避开了这一问题。

作者最后特别探讨了safe assets，即各种sovereign bonds。和一般的股票和债券不同，government bond是zero net supply，只体现了cross-generation liability borrowing/lending，不能代表任何real wealth。因此，不能用其market weights作为portfolio weights。



PART 3 - DELEGATED PORTFOLIO MANAGEMENT

Chapter 15 Delegated Investing 

从principle-agent问题出发，探讨了资产管理产业的一些结构性问题。作者提出了几点建议：

• 单纯使用linear contracts/fees是很糟糕的（Irrelevance results理论认为这样的contract对delegated portfolio management没有任何作用）。Linear contract：根据manager beat static benchmark的多少按比例提成。
• Incentive payment不应该成为这个行业的主流。根据理论，当agent需要multitask时，incentive payment和fixed payment没什么区别，因为agent会选择性完成任务。
• 改进：
• dynamic/factor-based benchmark，而不是static
• Non-linear/option-like compensation
• 加入constraints
• 更多的transparancy
• 按收费方式，尽量减少AUM-based fee。Retail investor应该付flat fees by the hours.

资产管理收费的历史：早年，大多数资产管理公司赚的都是commission-based fee，即客户交易所产生的佣金。直到1960年，Morgan Bank才开始率先收取AUM-based fee；当时人们都预测它会丢掉很多客户，但最终只有一个客户离开了Morgan。有趣的是，虽然这个行当竞争日益激烈，但AUM-based收费标准反而越来越高：60年仅有25bps，而现在大概在1%（散户）、50bps（机构）左右。

Agency issue对市场本身有影响，比如造成Herding。造成herding的原因可能有：大家的benchmark一样，或者仅仅因为manager的career concern。研究还表明：

• Stocks widely held by institutions have lower returns
• Institutional flow has predictive power of stock returns
• Delegated portflio management can give rise to momentum and long-term reversal in large and liquid asset class (but not OTC). 例子：一支股票因为基本面消息下跌，所以持有该股票的基金表现差，投资者认为这些基金经理不行而撤资，导致这些基金不得不抛售所持有的股票，进一步造成了股票价格下跌，而撤资的过程比较缓慢，所以股票价格在这段时间内出现了下跌的momentum。

Chapter 16 Mutual Funds and Other 40-Act Funds

作者认为部分基金经理是有资产管理才能的，但这一才能不能为投资者带来回报，只能时基金经理本身获益。

这是因为investor chase past return，好的基金经理会得到inflow。（此外，投资mutual fund的钱还相当sticky，当表现不好时的outflow比表现好时的inflow慢。）。根据decreasing return to scale，好的基金最终会成长到一定大小，使得return和market return相当。因此，投资者并不能持续的从这些基金中获得超额回报。

但是这个过程中，这些有才能的基金经理将从AUM-based fee中获得可观收益。事实上，基金公司本身的收益非常可观，operating margin能达到30%左右。


Chapter 17 Hedge Funds

作者认为hedge fund不过是repackaged risk factors，其中又以equity factor + volatility factor为主。考虑到他们高昂的费用，作者把他们称为expensive betas。

相应的，作者认为资产管理的未来在cheap alternative betas，用new generation of factor (index) funds to gain access to dynamic factor risk premiums.



几点思考：

• 市面上已经开始出现alternative beta的产品了。它们会取代active managed product吗？根据作者的观点，它们只会raise the bar for active management，而不会取代之。
• 怎么知道active management的alpha究竟是alpha，还是仅仅是beta timing？
• 从投资角度而言，自由市场无益于社会平等；社会福利必须进行再分配。穷人面对更多的bad times，避险需求更高，所能获得的投资回报非常有限。相反，富人能承担更多风险，因此也就能收获更高的投资回报。这将加剧社会的不平等。

#读书笔记 #1 A Random Walk Down Wall Street (Chapter 5)

Chapter 5: Technical and Fundamental Analysis

"A picture is worth ten thousand words" - Old Chinese proverb

1. Technical v.s. Fundamental Analysis

Most opt for one of two methods: technical or fundamental analysis. Technical is essentially the making and interpreting of stock charts. Fundamental analysts believe the market is usually logical. Caring little about the particular pattern of past price movement, fundamentalists seek to determine a stock's proper value.

2. What can chart tell you? The rationale for the charting method

The fist principle of technical analysis: all information about earnings, dividends, and the future performance of a company is reflected in the company's past market price.

The second principle: prices tend to move in trends. "Prices move in trends, and trends tend to continue until something happens to change the supply-demands balance." - Magee, Technical Analysis of Stock Trends

Three "most plausible" explanations of why charting is supposed to work: First, it has been argued that the crowd instinct of mass psychology makes trends perpetuate themselves. Second, there may be unequal access to fundamental information about a company. Third, investors often underreact initially to new information.

Why might charting fail to work? Market may well be a most efficient mechanism.

3. The technique of fundamental analysis

In estimating the firm-foundation value of a stock, the fundamentalist's most important job is to estimate the firm's future stream of earnings and dividends.

Because the general prospects of a company are strongly influenced by the economic position of its industry, the obvious starting point for the security analyst is a study of industry prospects.

Four basic determinants to help estimate the proper value for any stock:

(1) The expected growth rate

Hazardous as projections may be, share prices must reflect differences in growth prospects if any sense is to be made of market valuation. Also, the probable length of the growth phase is very important. ("the rule of 72": number of years to double your money ~= 72 divided by the interest rate you earn)

Rule 1: A rational investor should be willing to pay a higher price for a share the larger the growth rate of dividends and earnings or the longer an extraordinary growth rate is expected to last.

It is the P/E multiple, not the price, that really tells you how a stock is valued in the market. High P/E ratios are associated with high expected growth rates.

(2) The expected dividend payout

Many companies tends to buy back their shares rather than increasing their dividends, If expected growth rates are the same, you are better off with the one whose dividend payout is higher.

Rule 2: A rational investor should be willing to pay a higher price for a share, other things being equal, the larger the proportion of a company's earnings that is paid out in cash dividends.

(3) The degree of risk

Rule 3: A rational and risk-averse investor should be willing to pay a higher price for a share, other things being equal, the less risky the company's stock.

A "relative volatility" measure may not fully capture the relevant risk of a company (see Chapter 9).

(4) The level of market interest rates

To attract investors from high-yielding bonds, stock must offer bargain-basement prices. In the early 1980s, when yields on prime-quality corporate bonds soared to close to 15%, the expected returns of stocks had trouble matching these bond rates. Again in 1987, interest rates rose substantially, preceding the stock market crash of October 19. However, the relationship between interest rates and stock prices is somewhat more complicated than this discussion may suggest.

Rule 4: A rational and risk-averse investor should be willing to pay a higher price for a share, other things being equal, the lower the interest rates.

4. Three important caveats of fundamental analysis

The mathematical precision of fundamental-value formula is based on treacherous ground: forecasting the future.

Caveat 1: Expectation about the future cannot be proven in the present.

Caveat 2: Precise figures cannot be calculated from undetermined data.

Caveat 3: What's growth for the goose is not always growth for the gander.

It would be very dangerous to use any one year's valuation relationship as an indication of market norms.

5. Why might fundamental analysis fail?

(1) incorrect information and analysis

(2) estimate of "value" might be faulty

(3) the stock price may not converge to its value estimate

Example: the market may revalue its estimate of what growth stocks are worth. Not only can the average multiple change rapidly for stocks in general, but so can the premium assigned to growth.

6. Using fundamental and technical analysis together

Rule 1: Buy only companies that are expected to have above-average earnings growth for five or more years.

Rule 2: Never pay for a stock than its firm foundation of value.

There are important advantages to buying growth stocks at reasonable earnings multiple - "double bonus". Peter Lynch's strategy: PEG (P/E-to-growth) ratio!

Rule 3: Look for stocks whose stories of anticipated growth are of the kind on which investors can build castle in the air.

Ask yourself whether the story about your stock is one that is likely to catch the fancy of the crowd.

#读书笔记 #1 A Random Walk Down Wall Street (Chapter 4)

Chapter 4: The Explosive Bubbles of the Early 2000s

1. The Internet Bubble

Most bubbles have been associated with some new technology (as in the tronics and biotech booms) or with some new business opportunity (as when the opening of profitable new trade opportunities spawned the South Sea Bubble). The Internet was associated with both: it represented a new technology, and it offered new business opportunities that promised to revolutionize the way we obtain information and purchase goods/service. 

Bubbles are "positive feedback loops" - Robert Shiller (Irrational Exuberance).

In the first quarter of 2000, 916 venture capital firms invested $15.7 billion in 1,009 startup Internet companies. An astonishing 159 IPOs had been completed in the previous quarter. As happened during the South Sea Bubble, many companies that received financing were absurd. IN earlier times, one needed actual revenues and profits to come to market with an IPO. Some Internet companies had neither. We learned that investors would throw money at businesses that only five years before would not have passed normal due diligence hurdles.

Security Analyst $peak Up

Security analysts always find reasons to be bullish. They seldom utter the "sell" word, because they do not want to endanger current or future investment banking relationship or to offend corporate chief financial officers. Traditionally, ten stocks were rated "buys" for each one rated "sell". But during the bubble, the ratio was almost 100:1. 

New Valuation Metrics

Somehow, in the new Internet world, sale, revenues, and profits were irrelevant. In order to value Internet companies, analyst looked instead at "eyeballs" - the number of people viewing a Web page or "visiting" a Web site. Particularly important were numbers of "engaged shoppers" - those who spent at least 3 minutes on a website. "Mind share" was another popular non-financial metric.

Special metrics were established for telecom companies. Security analysts clambered into tunnels to count the miles of fiber-optic cable in the ground rather than examining the tiny fraction that was actually lit up with traffic.

The Writes of the Media

The bubble was aided and abetted by the media, which turned us into a nation of traders. Like the stock market, journalism is subject to the laws of supply and demand.

The Internet itself became the media. The Internet had democratized the investment process, and it played an important enabling role in perpetuating the bubble. Online brokers were also a critical factor in fueling the Internet boom. Trading was cheap, at least in terms of the small dollar amount of commissions charged.

Cable networks such as CNBC and Bloomberg became cultural phenomena. Across the world, health clubs, airports and bars were permanently tuned into CNBC.

Fraud Slithers In and Strangles the Market

Speculative manias , such as the Internet bubble, bring out the worst aspects of our system. Many businesses were managed not for the creation of long-run vale but for the immediate gratification of speculators - "obliged" high short-term earnings, "creative accounting, etc.

Enron was only one of a number of accounting frauds. Various telecom companies overstated revenues through swaps of fiber-optic capacity at inflated prices.

Should We Have Known the Dangers?

Fraud aside, we should have known better. We should have known that investments in transforming technologies have often proved unrewarding for investors. In the 1850s, the railroad was widely expected to greatly increase the efficiency of communications and commerce. It certainly did so, but it did not justify the prices (collapses in August 1857). History tells us that eventually all excessively exuberant markets succumb to the laws of gravity.

Many villains: fee-obsessed underwriters; research analysts that could be pushed by commission-hungry brokers; corporate executives using "creative accounting" to inflate their profits. It was the infectious greed of individual investors and their susceptibility to get-rich-quick schemes that allowed the bubble to expand.

2. The US Housing Bubble and Crash of the Early 2000s

This bubble was undoubtedly the biggest US real estate bubble of all time. Moreover, the boom and later collapse in house prices had far greater significance for the average Americans than any gyrations in the stock market.

In order to understand how this bubble was financed and why it created such far-reaching collateral damage, we need to understand the fundamental changes in the banking and financial systems.

The New System of Banking

Old system is "originate and hold" system. Banks would make mortgage loans and hold those loans as assets until they were repaid. In such an environment, bankers were very careful about the loans they made. This system fundamentally changed in the early 2000s. New system is the "originate and distribute" model of banking - e.g. mortgage-backed securities, CDS (second-order derivatives), etc.

Looser Lending Standards

The financiers created structured investment vehicles, or SIVs, that kept derivative securities off their books, in places where the banking regulators couldn't see them. In the new system loans were made with no equity down in the hopes that housing prices would rise forever. NINJA loans were common - loans to people with no income, no job , and no asset.

The government itself played an active role in inflating the housing bubble. Under pressure by Congress to make mortgage loans easily available, the FHA was directed to guarantee the mortgages of low-income borrowers. Indeed, almost 2/3 of the bad mortgages on the financial system as of the start of 2010 were bought by government agencies or required by government regulations. No accurate history of the housing bubble can fail to recognize that it was not simply "predatory lenders" but the government itself that caused many mortgage loans to be made to people who cannot afford them.

3. Bubble and Economic Activity

The bursting of bubbles has invariably been followed by severe disruptions in real economic activity. The fallout from asset-price bubbles has not been confined to speculators. Bubble are particularly dangerous when they are associated with a credit boom and widespread increases in leverage both for consumers and for financial institutions. Credit boom bubbles are the ones that pose the greatest danger to real economic activity.

Are the markets inefficient?

"The stock market is not a voting mechanism but a weighing mechanism." - Benjamin Graham (Security Analysis). Valuation metrics have not changed. Eventually, every stock can only be worth the present value of the cash flow.

Market prices must always be wrong to some extent. But at any particular time, it's not obvious to anyone whether they are too high or too low. Markets are not always or even usually correct. But no one person or institution consistently knows more than the market. (???)

#读书笔记 #1 A Random Walk Down Wall Street (Chapter 3)

Chapter 3: Speculative Bubbles from the Sixties into the Nineties

By the 1990s, institutions accounted for more than 90% of the trading volume on the NYSE.

1. The Soaring Sixties

1.1 The Growth-Stock/New-Issue Craze

In the 1959-1962 period, "Growth" was the magic word. Growth companies such as IBM and TI sold at more than 80 multiples of P/E (A year later they sold at multiples in the 20s and 30s). It was called "tronics boom", because the stock offerings often include some garbled version of "electronics" in their title. The tronics boom came back to earth in 1962. Yesterday's hot issue became today's cold turkey.

1.2 Synergy Generates Energy: The Conglomerate Boom

Part of the genius of the financial market is that if a product is demanded, it is produced. The product that all investors desired was expected growth in earnings per share. By the mid-1960s, creative entrepreneurs suggested that growth could be created by synergism.

In fact, the major impetus for the conglomerate wave of the 1960s was that the acquisition process itself could be made to produce growth in earnings per share - manipulation of P/E multiples. The trick that makes the game work is the ability of the electronics company to swap its high-multiple stock for the stock of another company with a lower multiple.

The aftermath of this speculative phase revealed two disturbing factors. First, conglomerates could not always control their far-flung empires. Second, the government and the accounting profession expressed concern about the pace of mergers and about possible abuses.

An interesting footnote is that during the 1990s and early 2000s, de-conglomeration came into fashion. Many of these sales were financed through a popular innovation, the leveraged buyout (LBO).

1.3 Performance Comes to the Market: The Bubble in Concept Stocks

"Performance" fund concentrated the portfolio in dynamic stocks, which had a good story to tell, and at the first sign of an even better story, they would quickly switch. Performance investing took hold of Wall Street in the late 1960s. "Since we hear story early, we can figure enough people will be hearing it in the next few days to give the stock a bounce. even if the story doesn't prove out."

Why did these stocks perform so badly later on? One general answer: their price-earnings multiples were inflated beyond reason. These companies were run by executives who were primarily promoters. not sharp-penciled operating managers.

2. The Nifty Fifty

In the 1970s, Wall Street's pros vowed to return to "sound principles". Concepts were out and blue-chip companies were in. "Big capitalization" stocks (Nifty Fifty) meant that an institution could buy a good-size position without disturbing the market. Hard as it is to believe, institutions started to speculate in blue chips. They once again proved the maxim that stupidity well packaged can sound like wisdom. The craze ended like all other speculative manias.

3. The Roaring Eighties

The high-tech, new-issue boom of the first half of 1983 was an almost perfect replica of the 1960s episodes, with the names altered slightly to include the new fields of biotechnology and microelectronics. During the late 1980s, most biotechnology stocks lost three-quarters of their market value. Even real technology revolutions do not guarantee benefits for investors.

4. What Does It All Mean?

Styles and fashions in investors' evaluations of securities can and often do play a critical role in the pricing of securities. The stock market at times conforms well to the castle-in-the-air theory. For this reason, the game of investing can be extremely dangerous.

5. An International Example: The Japanese Yen for Land and Stocks

One of the largest booms and bursts of the late 20th century involved the Japanese real estate and stock markets. From 1955 to 1990, the value of Jap. real estate increased more than 75 times. By 1990,  tot. value of Jap. real estate was estimated at ~20 trillion - equal to >20% of the entire world's wealth, or about double the tot. value of the world's stock market, or five times as much as all American property. The high value of Jap. land was "explained" by both the density of Jap. population and the various regulation and tax laws restricting the use of habitable land.

Jap. stocks sold at >60 times earnings, almost 5 times book value, and >200 times dividends. In contrast, US stocks 15 P/E; UK stocks 12 P/E. Supporters of the stock market had answers to all the logical objections that could be raised. One being that the book values did not reflect the dramatic appreciation of the land owned by Jap. companies. (Sam: "what is the relationship between real estate and stock ?")

Weakness of Jap. economy at that time:

1) Even when earnings were adjusted, the multiples were still far higher than in other countries and extraordinarily inflated relative to Japan's own history;

2) Jap. profitability had been declining, and the the strong yen was bound to make it more difficult for Japan to export;

3) although land was scarce in Japan, its manufacturers  (e.g. auto makers) were finding abundant land for new plants at attractive prices in foreign lands;

4) Rental income had been rising for more slowly than land values, indicating a falling rate of return on real estate;

5) The low interest rates that had been underpinning the market had already begun to rise in 1989.

The BOJ saw the ugly specter of a general inflation stirring amid the borrowing frenzy and the liquidity boom underwriting the rise in land and stock prices. And so the central bank restricted credit and engineered a rise in interest rates. The hope was that further rises in property prices would be choked off and the stock market might be eased downward. INSTEAD, it collapsed. The fall was almost as extreme as the US stock crash from the end of 1929 to mid-1932.

The rise in stock prices during the mid- and late 1980s represented a change in valuation relationships. The fall  in stock prices from 1990 on simply reflected a return to the price-to-book-value relationships that were typical in the early 1980s. The air also rushed out of the real estate balloon during the early 1990s.

#读书笔记 #1 A Random Walk down Wall Street (Chapter 1-2)

副博主近期决定投身到全职炒股票的事业中去，为了显示副博主的敬业精神+B格，今天隆重推出#读书笔记#系列。

A Random Walk down Wall Street (10th Edition)

By Burton G. Malkiel

About the author

Burton Malkiel is Emeritus Professor in Department of Economic at Princeton University. He is a leading proponent of the efficient-market hypothesis and in general supports buying and holding index funds as the most effective portfolio-management strategy. He also spent 28 years as a director of the Vanguard Group.

Chapter 1: Firm Foundations and Castle in the Air

Inflation

In US and most of the developed world, inflation fell to 2% in the early 2000s, and some believe that relative price stability will continue indefinitely. (True? What affect inflation?) What is the possibility that inflation will accelerate again at some time in the future? Productivity growth accelerated in the 1990s and 2000s, but history tells us the pace of improvement has always been uneven. Moreover, productivity improvement is hard to come by in some service-oriented activities (like musicians, surgeon, etc).

Firm-foundation Theory

It relies on some tricky forecasts of the extent and duration of future growth (dividend, cash distribution, etc.). An influential book is Security Analysis (by B. Graham and D. Dodd).

Castle-in-the-air Theory

The castle-in-the-air theory concentrates on psychic values ("greater fool" theory).

Every investor should remember: Res tantum valet quantum vendi potest (A thing is worth only what someone else will pay for it).

Chapter 2: The Madness of Crowds

GREED RUN AMOK

has been an essential feature of every spectacular boom in history. Remember the movie Margin Call ? "I am here for one reason and one reason alone. I am here to guess what the music might do a week, a month, a year from now. That's it. Nothing more..." Unsustainable prices may persist for years, but eventually they reverse themselves.

Tulip-bulb Craze and South Sea Bubble

Part of the genius of financial markets is that when there is a real demand for a method to enhance speculative opportunities, the market will surely provide it.

Options provide one way to leverage one's investment to increase the potential rewards as well as the risks. Such devices helped to ensure broad participation in the market. The same is true today.

As happens in all speculative crazes, prices eventually got so high that some people decide they would be prudent and sell their bulbs.

Big losers in the South Sea Bubble included Isaac Newton, who exclaimed, "I can calculate the motions of heavenly bodies, but not the madness of people."

Wall Street lays an egg (1929)

Calvin Coolidge - "The business of America is business." Stock market speculation was central to the culture.

Specialist could be so valuable to the pool manager. The book gave information about the extent of existing orders to buy and sell at prices below and above the current market. Wash sales created the impression that something big was afoot.

Monday, October 21, 1929: The stage was set for a classic stock market break. The declines in stock price had led to calls for more collateral from margin buyers. Unable or unwilling to meet the calls, these customers were forced to sell their holdings. This depressed prices and led to more margin calls and finally to a self-sustaining selling wave.

The crash in the stock market was followed by the most devastating depression in history. History teaches us that very sharp increases in stock prices are seldom followed by a gradual return to relative price stability. Even if prosperity had continued into the 1930s, stock prices could never has sustained their advance of the late 1920s. In addition, the anomalous behavior of close-end investment company shares provides clinching evidence of wide-scale stock market irrationality during the 1920s. From January to August 1929, the typical closed-end fund sold at a premium of 50%.

An afterword

It is not hard to make money in the market. What is hard to avoid is the alluring temptation to throw your money away on short, get-rich-quick speculative binges. It is an obvious lesson, but one frequently ignored.