Books by the Greats: A Random Walk Down Wall Street

Hi friends,

Today, I will be talking about one of the more important books in investing – A Random Walk Down Wall Street by Burton G. Malkiel. Here are some of my comments about the book; The author has a strong command of the English language, hence, he used quite fanciful languages in the book. It was honestly a pain to read it as I would encounter an unfamiliar word quite frequently.

But it is because of his use of this language that the book did not feel like reading a textbook, but it felt like a novel. Without further ado, let me move on to the first chapter of the book (There are only 4 Chapters).

Chapter 1 (Stocks and their value)

1.1   Firm foundations and castles in the air

The author started off by saying the disadvantages faced by the common investors, a lack of time, a lack of a dedicated team of analyst and complex algorithm to do high-frequency trading. He painted a grim picture for the common investors (us) at the beginning but reversed this tone by writing that it is possible for us to perform better than the bigger players.

He then defined investing (a method of purchasing assets to gain profit in the form of predictable income and/or appreciation over the long term) and speculating (buying stocks for a short-term gain over next days or weeks)

After this, we are introduced to the 1^st of the 2 theories for asset valuations: Firm-foundation theory and Castle in the Air theory. Let’s take a closer look at them.

Firm-foundation theory (Fundamental Analysis):

This theory believes that every financial instrument has a value (the intrinsic value) which can be determined through analysis and prospects. Believers of this theory would buy a stock when they see that the market price is higher than the intrinsic price (undervalued). The author has also introduced us one of the ways to calculate the intrinsic values of an instrument – Dividend discount model (Research yourself or see my blog). The problems with this theory are that we cannot be certain about the discount rate, future dividends, etc.

Castle in the air theory (Technical Analysis):

This theory leans more to the psychology of investing rather than in financial evaluation. In this theory, a buyer will purchase a financial instrument if he believes that he can sell it to the “Next sucker” at a higher price.

1.2   Madness of Crowds

The author then talked about times in history when the Castle in the Air Theory was taken to an extreme – Times of financial bubbles. These are the incidents that the author has written about:

1.       Tulip Bulb Craze (1600s)

2.       South Sea Bubble (1700s)

3.       Great Depression (1920s)

The common theme that I found between these 3 incidents, was that people would be so fearful of missing out on the returns that they would be leverage/ borrowing money to invest, thinking that there will be one more sucker that will buy it off their hands at a higher price (not that they are not aware that they are buying something of little value like in the Tulip Bulb Craze). 

1.3   Speculative Bubbles from the 60s into the 90s

For this portion, the author talked about how even in the modern age, and with better financial supervising from institutions, we still make the same mistakes.

1.       Electronics Boom (1960s) – Bubble formed from companies issuing stocks with names associated with electronics

2.       Conglomerate Boom (1960s) – Conglomerates increase their EPS by merging

3.       Nifty Fifty (1970s) – People were too focused on blue-chip companies

4.       Roaring eighties (1980s) – Sort of led up to the dotcom boom from the new issues of companies associated with biotech or microelectronics

5.       Japan’s land and stock bubble (1990s)

These 5 bubbles tell a similar story to their predecessor

1.4   Explosive Bubbles of the 2000s

Yes, even in the 2000s, we are still facing all these bubbles by thinking that there is a bigger sucker out there to let us earn money.

1.       Internet Bubble (2000s) – Where companies with a .com domain would increase their share price dramatically even though the earnings did not change. At that point, people have argued that traditional valuation metrics are no longer relevant, they invented new ones like eyeballs (how many people looking at the site), mind share (how much market share the website hold in the sector they belong)

2.       U.S Housing Bubble or the GFC (2009) – Where mortgages are no longer held by banks and lending of money to the public was so prevalent that drove home prices up. People were rushing to increase their leverage to purchase more homes even though they may not have the means to pay back their loans.

3.       Cryptocurrency Bubble? The author has said that due to the speculative nature of cryptocurrency, it too can be considered as a bubble. This is as cryptocurrencies have not produced enough value that it can be labelled as not being a bubble. But he gave a fair opinion by saying that there are values that cryptocurrencies can bring if we are able to utilize it. Furthermore, as a large number of bitcoins are held in the hands of very little people, there is a possibility of currency manipulations by them.

Through all these crazy periods, the author is trying to tell us that history does repeat itself. But every time there was a bubble, the market would correct itself, which is important for all investors to know. Each financial instrument should not be judged based on how much returns it can bring us (which may lead to bad decision-making and taking on unnecessary risks), but based on the company’s true value.

Chapter 2 How the pros play the biggest game in town

2.1 Technical and fundamental analysis

The author has started off the chapter by introducing us the two approaches of investing by the professionals: Technical and fundamental analysis. Technical analysis correspond to the castle-in-the-air view of stock pricing and that trend history tends to repeat itself (done by looking at chart movements, that the market is 90% psychological and 10% logical. By looking at the charts, they hope to understand how the market would behave like in the future.). Fundamental analysis would correspond to the firm foundation approach to stock pricing to select individual stocks (By estimating the true value, checking through parameters like risk, assets, future growth rates).

Technical analysis:

Principle 1: All information about the company is automatically reflected in the company’s past market price

Principle 2: Prices tend to move in trends, a stock rising would tend to keep rising.

The author has talked about technical analysis in its most basic form and elaborated on certain chart patterns like the head and shoulders (sorry, the only head and shoulders I know is shampoo). He has also talked about the features of the charts, like channel, resistance, support. He has also written that many chartists admitted that they do not understand how charting work, that history has a habit of repeating.

He then tried rationalising some possible explanation for technical analysis. 1) Herd mentality makes trends perpetuate themselves. 2) Unequal access to fundamental information about a company. 3) Investors might under-react to new information. To read the elaboration in this part go find the information yourself.

Arguments against charting are 1) Buying and selling are done after price trends have been established and broken. This results in missing returns when a sharp reversal occurs. 2) As more and more people use it, the technique would not be useful.

Fundamental Analysis:

The fundament’s approach would be in opposition to the technical’s approach. It would be to look for the intrinsic value of the company. This is done by estimating the firm’s future stream of earnings and dividends. The author then listed the 4 basic determinants in estimating the value of a stock. 1) Expected Growth Rate 2) Expected Dividend Payout 3) Degree of Risk 4) Level of market interest. He then introduced 3 pitfalls to look out for: 1) The future cannot be proven in the present 2) Precise figures cannot be calculated from undetermined data 3) Growth companies may not be valued highly by the market.

The flaws in the fundamental analysis are: 1) Information or the analysis may be incorrect 2) Estimation of value may be faulty 3) Stock price simply doesn’t converge to the estimate

Combining technical and fundamental analysis (the author has developed this rule for himself):

1.       Buy only companies expected to have above-average earnings growth for >5 years

2.       Never pay more for a stock than its firm foundation value (PE, PEG ratio would be a good gauge)

3.       Look for stocks which appeal to investors that build castle in the air (like crypto company, weed companies, vape companies)

In the next portion, we will take a look at how the writer tears both technical and fundamental analysis apart.

2.2 Technical Analysis and the random-walk theory

For this portion, the author talked about how technical analysis historically performed against the stock market. He has commented that chartists (people who do technical analysis), when asked why they are unsuccessful, would blame it on himself for not believing his own charts. The author has taken a biased-stance against technical analysis and explained his stance with 2 reasons: 1) After costs and taxes, it does not do better than a buy-and-hold strategy 2) Easy to pick on (due to easy to check their progress)

His idea is that even though there are short-term momentum in the market (and a long-term upwards trend in stock prices), it would not be sufficient to ensure that you can beat the market consistently. This led to the weak form of the random-walk hypothesis.

“The history of stock price movement contains no useful information that will enable an investor consistently to outperform a buy-and-hold strategy in managing a portfolio”

The author has also done an interesting exercise in this portion, where he simulated chart patterns by using a coin flip (a random event). Head would mean 0.5 point move upwards and tails would mean 0.5 point downwards. This is one of the results of the charts:

He has also used more elaborate trading rules and applied scientific testing to them. The more elaborate rules are as follow:

1.       Filter System (buying stocks that moved up 5% from low, sell stocks that moved down 5% from high)

2.       Dow Theory (buying when market goes higher than last peak and selling when it goes lower than last valley)

3.       Relative Strength (buy and hold stocks outperforming index)

4.       Price – Volume Systems (buying stocks that have an excess demands in buying orders)

5.       Reading Chart Patterns (32 most popular patterns)

The results of these systems are that, after subjecting to taxes and transaction costs, they do not consistently outperform a buy and hold strategy. Effectively, performance of stocks now is not influenced by previous performance (the author mentioned something here, where we as human do not like to assign things to chance and would like to seek meaning when we encounter patterns like clusters or streaks, we refuse to believe that it is random)

Interesting indicators used throughout history:

1.       Hemline indicator (which is sexist and disgusting)

2.       Super bowl indicator (a case of correlation not causation)

3.       Odd lot (not useful)

4.       Dogs of the Dow (strategy became too popular and it failed)

5.       January effect (not dependable)

The author believes that there is no strategy that can consistently outperform the market (over a long period of time). Technical analysis would mean that investors would lose out on good returns days of the market: 95% of significant market gains over a 30-years period were on 90 out of the 7500 days. $1 invested in the Dow in 1900 would be $290 in 2013. But if you missed the best 5 days of returns in the year, the invested $1 would be less than $0.01 in 2013.

In the next chapter, the author targets fundamental analysis.

2.3 How good is fundamental analysis? The Efficient Market Hypothesis

In this chapter, the author turned his focus on the flaws of fundamental analysis, where fundamental analysis would focus on getting the intrinsic value of the stock through expected returns. He then summarised 5 reasons for the difficulties in predicting the future:

1.       Influence of random events (Natural disasters, death of CEOs, price wars)

2.       Production of dubious reported earnings through “Creative Accounting” (Enron, Xerox, Motorola)

3.       Errors made by Analysts (Analysts prefer to copy the forecast of other analysts or to swallow the guidance of company managements)

4.       Loss of best analysts to portfolio management or hedge funds (Yup, I would too)

5.       Conflicts of interest between research and investment banking department (Firms are incentivised to give a buy signal as they are fearful of potential loss of customers)

He used some interesting facts to illustrate the point: Buy recommendations underperformed the market by 3% each month. Sell recommendations outperformed the market by 3.8% each month. Furthermore, researches at Dartmouth and Cornell found that stock recommendations of Wall street firms without investment banking relationships perform better than brokerage firms involved in investment banking relationships.

Then, the author looked at the epitome of fundamental analysis, people that have cashflow analysis, and future dividends prospect for breakfast – Mutual funds. Hence, he looked at their performance (publicly available) and compare them to the market.

#what he discovered is what I have been saying on my blog. So, I shall not write any more on that, he does mention that Benjamin Graham, Peter Lynch and Warren Buffett have admitted that most investors would be better off with an index funds. #

Important things to note for the efficient market hypothesis:

1.       No one knows for sure if stock prices are too high or too low (not that stock prices are always correct)

2.       Efficient market would mean that prices move so quickly when information arise (through a random process, that no one can predict) that no one can buy/sell fast enough to benefit

Chapter 3 The New Investment Technology

3.1   A new walking shoe: Modern portfolio theory

After tearing apart both fundamental and technical analysis, the author talked about a valuation theory that is created by academia – Modern portfolio theory. Essentially, what allows us to achieve better returns is by taking on more risk – hence high-risk high returns. Risk in this case is defined by the standard deviation of return. He then used a picture to show the distribution of monthly returns based on the past performance of the S&P 500 from 1970 -2018. It is a normal distribution. He then showed the distribution of returns of other financial instruments as well.

In modern portfolio theory, the magical number is 50 equal-sized, well-diversified stocks (the total risk is reduced by 60% compared to owning just one stock). This is as stocks would not have a perfect positive correlation with each other. By pairing these stocks together, you can achieve diversification (However, with globalisation, stocks are now more positively correlated than more. But it doesn’t mean that diversification cannot occur).

3.2   Reaping reward by increasing risk

In this theory, the author talked about the concept of measuring risks quantitatively – Beta (a measurement of systematic risk). Effectively, risk can be classified into 2 portions, specific risk (can be diversified away) and systematic risk (cannot be diversified away and it’s the risk that we get paid for holding on to a financial instrument)

Capital-Asset-Pricing Model (CAPM) – Returns = Risk-Free Rate + Beta*(Returns from market – Risk-free rate)

The risk-free rate is the 3-6 months treasury bond and market rate is The average market returns. Beta is then a measurement of how volatile the asset is compared to the stock market. Hence, there is now a way for investors to know how their investment will do, the higher the portion of stocks which are volatile, the higher the expected return!

NOPE, the author was fair and pointed out studies that showed otherwise:

There is no relationship between beta and returns.

The author has reasoned that this may be due to the instability and sensitivity of beta to markets. So even academia has failed to devise a sure-win strategy. Next, he wrote about a theory where investors are not rational creatures and hence, the efficient-market-hypothesis may not be valid at times.

3.3   Behavioural finance

Efficient market hypothesis assumes that all players are rational, hence, the efficiency would prevent people to profit consistently from the market for a long period of time. In 1990s, there was a new economic discipline that examine this assumption. They argue that people deviate from rationality, which leads to imprecise market prices. There are four factors that create irrational market behavior:

·         Overconfidence

The author wrote – As humans, we have this tendency to be overconfident about our abilities (we often attribute success to our skills rather than the fact that we are lucky) and be optimistic about the future. The author has used some experiments done in the past to illustrate the examples. He said that this applies to investors especially well; We tend to exaggerate our skills, deny the role of chance, overestimate our knowledge, and underestimate the risks that we are taking. He introduced a nice gauge; If we are 99% sure, we are most likely 80% to be correct.

#Important thing that I cannot find a way to add it; The more we trade, the worse we do, and women are better investors than men

·         Biased Judgments

In this case, it means that even though the stock market’s movement is random, with an upward trend, we want to give meaning to the random movement of the stock market. Because of this, we would think that our decisions can “influence” the market, leading to excess-extrapolation from recent data and chasing hot funds (even though the returns may be random).

·         Herd Mentality

The author has used an experiment where a participant is in a group with a bunch of actors. When given 2 pictures with one line longer than the other, the participant tends to choose the obviously shorter line when asked to point out the long line picture if everyone else is pointing to the wrong answer. This would show that our decisions can be easily influenced (our perception would be affected by others) if everyone is doing it (from social pressure).

In investing, it was found out that mutual fund managers are more likely to hold similar stocks if other managers in the same city are holding a similar portfolio. Hence, we should avoid being influenced by this to avoid the bubbles that happened in history from happening to us.

·         Loss Aversion

Essentially – Losses to us are more significant compared to gains. Losing $1 would cause us a pain that is more significant than gaining $1.

The author then concluded on how to control these 4 pitfalls. 1) Avoid herd behavior (have a more diverse group of friends) 2) Avoid Overtrading (The more you trade, the worse you perform) 3) When we trade, sell losers and not winners (selling the winners would incur tax, selling the losers can help in your tax claim) 4) Beware of hot investors’ trick (things like new issues – IPO tend to do badly, hot tips, foolproof schemes)

3.4   New methods of portfolio construction: Smart-Beta and Risk Parity

Smart-beta would mean to combine different passive investment instruments to have more returns than an all-stock index fund and have lower volatility as well. This is measure in terms of the Sharpe ratio – Returns/Risk. A higher ratio would mean that you get a high return per unit risk that you are taking on. This is something that you want, hence, factor-based investing would see that you tilt a portfolio towards a certain style to increase take on more risks and more returns.

The factors:

1.       Value – Value is based on current realities than future projections. In a study, there is a negative correlation between PE ratio and returns

2.       Capitalization Size – Small-cap stocks do better than large-cap stocks even with the same beta level

3.       Some momentum exist in the stock market – From 1927 to 2017, a momentum strategy involving longing the best performing stocks and shorting the worst performers had a Sharpe ratio of 0.58

4.       Low-Beta stocks return as much as high-beta stocks – Leverage can be used to amplify the returns of a low beta financial instrument while having lesser volatility.

But however, the author has explained that using a single factor is not enough to outperform the market. But a multi-factor approach shows some promise of an increase in Sharpe Ratio, not taking into account the fees.

For the risk parity method, the author has recommended the all-weather (leveraged) if they are low cost. #Do refer to my all-weather post for that#

Chapter 4 A practical guide for random walkers and other investors

4.1   A fitness manual for random walkers

For this portion, the author gave specific advise on how to plan for your own financial future. He has followed the same tier-based approach that I have written as well. Namely:

1.       Saving money to invest is the most important step

2.       Emergency cash (Invested in liquid instruments like CD, money market funds, t-bills, high-interests bank account)

3.       Insurance against pitfalls

4.       Investing in accordance with your risk appetite (low cost of investing would allow for better returns

4.2   Handicapping the financial race

The author gave a very general view on the difference in performance between different financial assets:

He then reiterated that the P/E ratio is a good gauge to determine future returns. (the lower the PE ratio, the higher the potential for returns)

4.3   Life-cycle guide to investing

Alright, the last portion of this book. It has been a long book, with a lot of chapters, but I hope that you have learnt a lot from it. I certainly did. For this last chapter, the author gave 5 asset-allocation principles:

1.       Risk and returns are related

2.       Risk in stocks and bonds depends on the time horizon, the longer the time horizon, the lower the variations of asset’s returns

3.       DCA is a helpful technique to reduce risk (not in an upmarket, but certainly useful in a sideways situations)

4.       Rebalancing can reduce risk, and maybe increase investment returns

5.       Attitude to risk is not equal to capacity for risk (that is dependable on our financial situations, and we should not attach our portfolio to our main source of income,  do not invest too much in the company that you are working for)

After setting the principles, he gave 3 guidelines to tailor an investment plan:

1.       Specific needs require dedicated financial instrument (money for down payment should be in a safe place like an endowment or a CD instead of in the stock market)

2.       Recognise our tolerance for risk (are we able to sleep knowing that our investment can lose 80% of its value)

3.       Persistent saving in regular amount

He then gave specific portfolio allocations for investors at different age ranges (all the way from 20s to 60s)

The reason for an increase in cash is for emergency cases as compared to when we are younger.

4.4   Three Giant Steps Down Wall Street

For this LAST (I promise), for those of us that want to invest ourselves and not rely on etfs or mutual funds to invest for, the author has provided a set of strategies that can help us achieve better returns than the market. But first, he needs us to be avid readers of financial news from New York Times, Wal Street Journal, Barron’s, Bloomberg Businessweek, Fortune, Forbes. After this is done, then we can look at some strategies that he has:

1.       Companies should be able to sustain above-average earnings growth for at least 5 years

2.       Never pay more for a stock that can reasonably be justified by a firm foundation of value

3.       Buy stocks with growth that appeals to investors to build castles on the air

4.       Trade as little as possible

5.       Sell the losers, hold the winner

Closing comments by Dionysius:

This book has started off shooting technical and fundamental supporters, effectively claiming that in an efficient market, both would not allow for consistent profits. However, he was an objective writer, even shooting down the valuation theory developed by academia – where he belongs. He then talked about some of the more recent developments like behavioral finance, factor-based investing, risk parity, and how they stack up in achieving higher returns for lesser risk. Lastly, the author gave specific recommendations in financial planning, which instruments to invest in, and how each financial instrument will behave in different economic periods and the allocation for the age that we are in. Even for those of us that wants to invest ourselves, he gave guidelines and principles to follow.