Buyers can’t be fooled all the time: Lessons from a 50% fall in home sales in Delhi

India-Real-Estate-MarketVivek Kaul

If you are still in denial that all is well with the real estate sector, this should wake you up. The real estate consultant Knight Frank has released a research report in which it points out the depressing state of the real estate sector in Delhi and the National Capital Region.

As analyst Ankita Sood writing for Knight Frank points out: “The market registered a year on year dip of 50%, with 14,250 units sold.” Hence, home sales in the National Capital Region for the period January to June 2015 dropped by 50% in comparison to the same period last year.

At the same time the number of new launches also fell dramatically by 68% in January to June 2015 in comparison to the same period last year. The new project launches stood at 11,360 units.

There are a number of lessons that can be drawn from these numbers:

1) Investors do not have endless patience: The real estate market in and around Delhi has primarily been investor driven. This is primarily because of the massive amount of black money that the city manages to generate. Black money is money which has been earned but on which taxes have not been paid.
Falling home sales clearly indicate that investors are no longer interested in buying more new homes, given that they are still sitting on the ones they had bought over the last few years. And the returns on these apartments have been negative or next to nothing. Hence, investors are looking to sell out the homes they had bought.

As Sood writes: “The growth rate of the weighted average price has been witnessing a downward trend since 2013, and has slowed down considerably…Long-term investors who were with the developers over the 3–4 year construction period are now looking for an exit, owing to the depressed market sentiments. Stagnant prices and delayed project deliveries have contributed towards investors entering into a ‘distressed resale’ mode, as they are now offering to exit at a 15% to 20% discount than the primary market price.”

This “offer to exit” at 15 to 20% discount tells us very clearly that real estate prices do fall. And as more and more investors hit the market to sell what they have been sitting on, prices will fall further.

2) The total amount of black money coming into real estate has been coming down: As far as the metropolitan cities in India is concerned, the maximum amount of black money goes into real estate in Delhi. As analysts Saurabh Mukherjea and Sumit Shekhar of Ambit write in a recent research report titled Real Estate: The unwind and its side effects: “In Delhi, the ratio of unaccounted value of real estate transactions to the total value is as high as 78%. The same ratio is 50% in Kolkata and Bangalore. In smaller towns and semi urban centres, nearly 100% of property transactions are conducted in cash.” In Mumbai, they put the ratio of black money to total value at between 10-30%.

Hence, among the bigger cities, the maximum amount of black money goes into real estate in Delhi and the National Capital Region. And this has been coming down. How can we conclude that? The Delhi and the National Capital Region have approximately 189,678 unsold units, Knight Frank data suggests.
If black money were coming into real estate at the same pace as before, this number would have been much lower. A fall in new launches by 68% is another good indicator that black money coming into the sector has been coming down.

3) You can’t fool all the people all the time: The Delhi and the National Capital Region has had too many instances of builders disappearing as well as not delivering homes on time. As Santhosh Kumar, CEO – Operations & International Director, JLL India, wrote in a recent research note: “The National Capital Region (NCR) has some locations that buyers are best advised to avoid. Various issues like delays in delivery, oversupply, speculation and infrastructure deficit have been plaguing these markets, rendering them unsuitable for first-time home purchase.”

Kumar gives the example of the Greater Faridabad area. As he writes: “Many instances of fly-by-night operators (and even some established developers) reneging on their commitments to buyers have been evident in Greater Faridabad. There have even been cases of developers absconding altogether after selling as many flats as they could without finishing the projects.”

Obviously, such fraud cannot go on forever. Buyers have come to know about these things over a period of time and have decided to stay away from buying real estate. In fact, Kumar even warns people to stay away from under-construction property, such is the state of real estate in Delhi and National Capital Region.
As he writes: “Keep away from pre-launches. Instead, look for bargain buys when investors exit. At that point of time, construction will be closer to completion or completed, and Gurgaon is witnessing distress sales from investors.”

A real estate consultant asking people not to invest in pre-launches needs to be taken very seriously.

4) An end user market:  With investors staying away and the total amount of black money finding its way into real estate coming down, if things continue in this way, Delhi and the National Capital Region real estate market, will become a market which is driven by those people who are looking for a home to live in, rather than invest. In fact, Sood of Knight Frank suggests that is already the case: “NCR is now an end user-driven market – developers restrict new launches, while buyers carefully select clean projects.”

5) You can’t keep making a product which the consumer does not want: The main reason why the real estate sector is in a mess is because prices have gone way beyond what most people can afford. This is a fundamental reason that most people associated with real estate refuse to acknowledge. On being given this reason, they come up with reasons like there is corruption in the government, laws are complicated, so on and so forth.

These might be genuine reasons but that does not negate the point that real estate prices have gone way beyond what most people can afford. Even the “rich” that real estate companies were building for cannot afford real estate at current prices. A product cannot be endlessly priced above what people are willing to pay for it.

As Knight Frank points out: “Policy fallacies such as the opening up of new land for development, allotment of group housing licences in areas with no infrastructure, project delays due to litigations and the liquidity crunch, and stagnant incomes[emphasis is mine] have affected NCR’s real estate appetite adversely.”

It is nice to see a real estate consultant acknowledge stagnant incomes as one of the reasons for one of the mess in the real estate sector. What it means in simple English is that incomes haven’t been able to keep pace with real estate prices i.e. prices are now way beyond what people can afford. And this cannot go on forever.

The column first appeared on Firstpost on July 30, 2015

(Vivek Kaul is the author of the Easy Money trilogy. He tweets @kaul_vivek)

Why investors behave like football goalkeepers and how that hurts

goalkeeperVivek Kaul  
A very good friend of mine recently decided to take a sabbatical. But two weeks into it he started getting fidgety. The prospect of not doing anything was turning out to be too hot to handle for him. So, one morning he called up his boss and told him that this decision to go on a sabbatical was not the right one, and given this, he wanted to get back to work.
My friend’s boss, had taken a sabbatical last year, and understood the value of a big break away from work. Given this, he refused to let my friend get back to work so soon, and suggested that he continue with the sabbatical, now that he had decided to take one.
One more week into the sabbatical, my friend simply couldn’t handle it. One day he simply landed up at work, without consulting his boss. And thus ended his sabbatical.
The point in sharing this story is that it is difficult “do nothing”, even though at times it might be the most important thing to do.
In a recent interview to Wisden, the former Australian cricketer Dean Jones, pointed out that two thirds of Sachin Tendulkar’s game was based around forward defence, back-foot defence and leaving the ball, without trying to play it. As Amay Hattangadi and Swanand Kelkar write in a research eport titled The Value of Doing Nothing and dated February 2014 “As any coach would vouch, letting the ball go is possibly as important as hitting good shots in the career of a batsman.”
In fact, not doing anything is a very important part of successful investing. But the investment industry is not structured liked that. They have to ensure that their customers keep trading, even if it is detrimental for the them. As Arthur Levitt, a former Chairman of the Securities Exchange Commission, the stock market regulator in the United States, writes in 
Take on the Street – How to Fight for Your Financial Future “Brokers may seem like clever financial experts, but they are first and foremost salespeople. Many brokers are paid a commission, or a service fee, on every transaction in accounts they manage. They want you to buy stocks you don’t own and sell the ones you do., because that’s how they make money for themselves and their firms. They earn commissions even when you lose money.”
The brokers only make money when investors keep buying and selling through them. This is also true about insurance and mutual fund agents, who make bigger commissions at the time investors invest and then lower commissions as the investors stay invested.
As Adam Smith (not the famous economist) writes in 
The Money Game “They could put you in some stock that would go up ten times, but then they would starve to death. They only get commissions when you buy and sell. So they keep you moving.”
Levitt proves this point by taking the example of Warren Buffett to make his point. “Warren Buffett, the chairman and CEO of Berkshire Hathaway Inc and one of the smartest investors I’ve ever met, knows all about broker conflicts. He likes to point that any broker who recommended buying and holding Berkshire Hathaway stock from 1965 to now would have made his clients fabulously wealthy. A single share of Berkshire Hathaway purchased for $12 in 1965 would be worth $71,000 as of April 2002. But, any broker who did that would have starved to death.”
Hence, it is important for stock brokers, insurance and mutual fund agents to get their investors to keep moving from one investment to another.
But how do stock brokers manage to do this all the time? 
Andy Kessler has an excellent explanation for this in Wall Street Meat. As he writes “The market opens for trading five days a week… Companies report earnings once every quarter. But stocks trade about 250 days a year. Something has to make them move up or down the other 246 days [250 days – the four days on which companies declare quarterly results]. Analysts fill that role. They recommend stocks, change recommendations, change earnings estimates, pound the table—whatever it takes for a sales force to go out with a story so someone will trade with the firm and generate commissions.”
But why are these analysts taken seriously more often than not? As John Kenneth Galbraith writes in The Economics of Innocent Fraud “ And there is no easy denial of an expert’s foresight. Past accidental success and an ample display of charts, equations and self-confidence depth of perception. Thus the fraud. Correction awaits.”
This has led to a situation where investors are buying and selling all the time. As Hattangadi and Kelkar point out “In fact, the median holding period of the top 100 stocks by market capitalisation in the U.S. has shrunk to a third from about 600 days to 200 days over the last two decades.” Now contrast this data point with the fact that almost any and every stock market expert likes to tell us that stocks are for the long term.
This also happens because an inherent 
action bias is built into human beings. An interesting example of this phenomenon comes from football. “In an interesting research paper, Michael Bar-Eli2 et al analysed 286 penalty kicks in top soccer leagues and championships worldwide. In a penalty kick, the ball takes approximately 0.2 seconds to reach the goal leaving no time for the goalkeeper to clearly see the direction the ball is kicked. He has to decide whether to jump to one of the sides or to stay in the centre at about the same time as the kicker chooses where to direct the ball. About 80% of penalty kicks resulted in a goal being scored, which emphasises the importance a penalty kick has to determine the outcome of a game. Interestingly, the data revealed that the optimal strategy for the goalkeeper is to stay in the centre of the goal. However, almost always they jumped left or right,” write Hattangadi and Kelkar.
Albert Edwards of Societe Generale discusses this example in greater detail. As he writes “When a goalkeeper tries to save a penalty, he almost invariably dives either to the right or the left. He will stay in the centre only 6.3% of the time. However, the penalty taker is just as likely (28.7% of the time) to blast the ball straight in front of him as to hit it to the right or left. Thus goalkeepers, to play the percentages, should stay where they are about a third of the time. They would make more saves.”
But the goalkeeper doesn’t do that. And there is a good reason for it. As Hattangadi and Kelkar write “ The goalkeepers choose action (jumping to one of the sides) rather than inaction (staying in the centre). If the goalkeeper stays in the centre and a goal is scored, it looks as if he did not do anything to stop the ball. The goalkeeper clearly feels lesser regret, and risk to his career, if he jumps on either side, even though it may result in a goal being scored.”
Investors also behave like football goalkeepers and that hurts them.

The article originally appeared on on February 8, 2014
(Vivek Kaul is a writer. He tweets @kaul_vivek)  

People should listen to market experts for entertainment, not elucidation.

Michael J. Mauboussin is Chief Investment Strategist at Legg Mason Capital Management in the United States. He is also the author of bestselling books on investing like Think Twice: Harnessing the Power of Counterintuition and More Than You Know: Finding Financial Wisdom in Unconventional Places. His latest book The Success Equation: Untangling Skill and Luck in Business, Sports, and Investing is due later this year. In this interview he speaks to Vivek Kaul on the various aspects of luck, skill and randomness and the impact they have on business, life and investing.

How do you define luck?
The way I think about it, luck has three features. It happens to a person or organization; can be good or bad; and it is reasonable to believe that another outcome was possible. By this definition, if you win the lottery you are lucky, but if you are born to a wealthy family you are not lucky—because it is not reasonable to believe that any other outcome was possible—but rather fortunate.
How is randomness different from luck?
I like to distinguish, too, between randomness and luck. I like to think of randomness as something that works at a system level and luck on a lower level. So, for example, if you gather a large group of people and ask them to guess the results of five coin tosses, randomness tells you that some in the group will get them all correct. But if you get them all correct, you are lucky.
And what is skill?
For skill, the dictionary says the “ability to use one’s knowledge effectively and readily in execution or performance.” I think that’s a good definition. The key is that when there is little luck involved, skill can be honed through deliberate practice. When there’s an element of luck, skill is best considered as a process.
You have often spoken about the paradox of skill. What is that?
The paradox of skill says that as competitors in a field become more skillful, luck becomes more important in determining results. The key to this idea is what happens when skill improves in a field. There are two effects. First, the absolute level of ability rises. And second, the variance of ability declines.
Could you give us an example?
One famous example of this is batting average in the sport of baseball. Batting average is the ratio of hits to at-bats. It’s somewhat related to the same term in cricket. In 1941, a player named Ted Williams hit .406 for a season, a feat that no other player has been able to match in 70 years. The reason, it turns out, is not that no players today are as good as Williams was in his day—they are undoubtedly much better. The reason is that the variance in skill has gone down. Because the league draws from a deeper pool of talent, including great players from around the world, and because training techniques are vastly improved and more uniform, the difference between the best players and the average players within the pro ranks has narrowed. Even if you assume that luck hasn’t changed, the variance in batting averages should have come down. And that’s exactly what we see. The paradox of skill makes a very specific prediction. In realms where there is no luck, you should see absolute performance improve and relative performance shrink. That’s exactly what we see.
Any other example?
Take Olympic marathon times as an example. Men today run the race about 26 minutes faster than they did 80 years ago. But in 1932, the time difference between the man who won and the man who came in 20th was close to 40 minutes. Today that difference is well under 10 minutes.
What is the application to investing?
The application to investing is straightforward. As the market is filled with participants who are smart and have access to information and computing power, the variance of skill will decline. That means that stock price changes will be random—a random walk down Wall Street, as Burton Malkiel wrote—and those investors who beat the market can chalk up their success to luck. And the evidence shows that the variance in mutual fund returns has shrunk over the past 60 years, just as the paradox of skill would suggest. I want to be clear that I believe that differential skill in investing remains, and that I don’t believe that all results are from randomness. But there’s little doubt that markets are highly competitive and that the basic sketch of the paradox of skill applies.
How do you determine in the success of something be it a song, book or a business for that matter, how much of it is luck, how much of it is skill?
This is a fascinating question. In some fields, including sports and facets of business, we can answer that question reasonably well when the results are independent of one another. When the results depend on what happened before, the answer is much more complex because it’s very difficult to predict how events will unfold.
Could you explain through an example?
Let me try to give a concrete example with the popularity of music. A number of years ago, there was a wonderful experiment called MusicLab. The subjects thought the experiment was about musical taste, but it was really about understanding how hits happen. The subjects who came into the site saw 48 songs by unknown bands. They could listen to any song, rate it, and download it if they wanted to. Unbeknownst to the subjects, they were funneled into one of two conditions. Twenty percent went to the control condition, where they could listen, rate, and download but had no access to what anyone else did. This provided an objective measure of the quality of songs as social interaction was absent.
What about the other 80%?
The other 80 percent went into one of 8 social worlds. Initially, the conditions were the same as the control group, but in these cases the subjects could see what others before them had done. So social interaction was present, and by having eight social worlds the experiment effectively set up alternate universes. The results showed that social interaction had a huge influence on the outcomes. One song, for instance, was in the middle of the pack in the control condition, the #1 hit on one of the social worlds, and #40 in another social world. The researchers found that poorly rated songs in the control group rarely did well in the social worlds—failure was not hard to predict—but songs that were average or good had a wide range of outcomes. There was an inherent lack of predictability. I think I can make the statement ever more general: whenever you can assess a product or service across multiple dimensions, there is no objective way to say which is “best.”
What is the takeaway for investors?
The leap to investing is a small one. Investing, too, is an inherently social exercise. From time to time, investors get uniformly optimistic or pessimistic, pushing prices to extremes.
Was a book like Harry Potter inevitable as has often been suggested after the success of the book?
This is very related to our discussion before about hit songs. When what happens next depends on what happened before, which is often the case when social interaction is involved, predicting outcomes is inherently difficult. The MusicLab experiment, and even simpler simulations, indicate that Harry Potter’s success was not inevitable. This is very difficult to accept because now that we know that Harry Potter is wildly popular, we can conjure up many explanations for that success. But if you re-played the tape of the world, we would see a very different list of best sellers. The success of Harry Potter, or Star Wars, or the Mona Lisa, can best be explained as the result of a social process similar to any fad or fashion. In fact, one way to think about it is the process of disease spreading. Most diseases don’t spread widely because of a lack of interaction or virulence. But if the network is right and the interaction and virulence are sufficient, disease will propagate. The same is true for a product that is deemed successful through a social process.
And this applies to investing as well?
This applies to investing, too. Instead of considering how the popularity of Harry Potter, or an illness, spreads across a network you can think of investment ideas. Tops in markets are put in place when most investors are infected with bullishness, and bottoms are created by uniform bearishness. The common theme is the role of social process.
What about someone like Warren Buffett or for that matter Bill Miller were they just lucky, or was there a lot of skill as well?
Extreme success is, almost by definition, the combination of good skill and good luck. I think that applies to Buffett and Miller, and I think each man would concede as much. The important point is that neither skill nor luck, alone, is sufficient to launch anyone to the very top if it’s a field where luck helps shape outcomes. The problem is that our minds equate success with skill so we underestimate the role of randomness. This was one of Nassim Taleb’s points in Fooled by Randomness. All of that said, it is important to recognize that results in the short-term reflect a lot of randomness. Even skillful managers will slump, and unskillful managers will shine. But over the long haul, good process wins.
How do you explain the success of Facebook in lieu of the other social media sites like Orkut, Myspace, which did not survive?
Brian Arthur, an economist long affiliated with the Santa Fe Institute, likes to say, “of networks there shall be few.” His point is that there are battles for networks and standards, and predicting the winners from those battles is notoriously difficult. We saw a heated battle for search engines, including AltaVista, Yahoo, and Google. But the market tends to settle on one network, and the others drop to a very distant second. I’d say Facebook’s success is a combination of good skill, good timing, and good luck. I’d say the same for almost every successful company. The question is if we played the world over and over, would Facebook always be the obvious winner. I doubt that.
Would you say that when a CEO’s face is all over the newspapers and magazines like is the case with the CEO of Facebook , he has enjoyed good luck?
One of the most important business books ever written is The Halo Effect by Phil Rosenzweig. The idea is that when things are going well, we attribute that success to skill—there’s a halo effect. Conversely, when things are going poorly we attribute it to poor skill. This is often true for the same management of the same company over time. Rosenzweig offers Cisco as a specific example. So the answer is that great success, the kind that lands you on the covers of business magazines, almost always includes a very large dose of luck. And we’re not very good at parsing the sources of success.
You have also suggested that trying to understand the stock market by tuning into so called market experts is not the best way of understanding it. Why do you say that?
The best way to answer this is to argue that the stock market is a great example of a complex adaptive system. These systems have three features. First, they are made up of heterogeneous agents. In the stock market, these are investors with different information, analytical approaches, time horizons, etc. And these agents learn, which is why we call them adaptive. Second, the agents interact with one another, leading to a process called emergence. The interaction in the stock market is typically through an exchange. And, finally, we get a global system—the market itself.
So what’s the point you are trying to make?
Here’s a key point: There is no additivity in these systems. You can’t understand the whole simply by looking at the behaviors of the parts. Now this is in sharp contrast to other systems, where reductionism works. For example, an artisan could take apart my mechanical wristwatch and understand how each part contributes to the working of the watch. The same approach doesn’t work in complex adaptive systems.
Could you explain through an example?
Let me give you one of my favorite examples, that of an ant colony. If you study ants on the colony level, you’ll see that it’s robust, adaptive, follows a life cycle, etc. It’s arguably an organism on the colony level. But if you ask any individual ant what’s going on with the colony, they will have no clue. They operate solely with local information and local interaction. The behavior of the colony emerges from the interaction between the ants. Now it’s not hard to see that the stock market is similar. No individual has much of a clue of what’s going on at the market level. But this lack of understanding smacks right against our desire to have experts tell us what’s going on. The record of market forecasters has been studied, and the jury is in: they are very bad at it. So I recommend people listen to market experts for entertainment, not for elucidation.
How does the media influence investment decisions?
The media has a natural, and understandable, desire to find people who have views that are toward the extremes. Having someone on television explaining that this could happen, but then again it may be that, does not make for exciting viewing. Better is a market boomster, who says the market will skyrocket, or a market doomster, who sees the market plummeting.
Any example?
Phil Tetlock, a professor of psychology at the University of Pennsylvania, has done the best work I know of on expert prediction. He has found that experts are poor predictors in the realms of economic and political outcomes. But he makes two additional points worth mentioning. The first is that he found that hedgehogs, those people who tend to know one big thing, are worse predictors than foxes, those who know a little about a lot of things. So, strongly held views that are unyielding tend not to make for quality predictions in complex realms. Second, he found that the more media mentions a pundit had, the worse his or her predictions. This makes sense in the context of what the media are trying to achieve—interesting viewing. So the people you hear and see the most in the media are among the worst predictors.
Why do most people make poor investment decisions? I say that because most investors aren’t able to earn even the market rate of return?
People make poor investment decisions because they are human. We all come with mental software that tends to encourage us to buy after results have been good and to sell after results have been poor. So we are wired to buy high and sell low instead of buy low and sell high. We see this starkly in the analysis of time-weighted versus dollar-weighted returns for funds. The time-weighted return, which is what is typically reported, is simply the return for the fund over time. The dollar-weighted return calculates the return on each of the dollars invested. These two calculations can yield very different results for the same fund.
Could you explain that in some detail?
Say, for example, a fund starts with $100 and goes up 20% in year 1. The next year, it loses 10%. So the $100 invested at the beginning is worth $108 after two years and the time-weighted return is 3.9%. Now let’s say we start with the same $100 and first year results of 20%. Investors see this very good result, and pour an additional $200 into the fund. Now it is running $320—the original $120 plus the $200 invested. The fund then goes down 10%, causing $32 of losses. So the fund will still have the same time-weighted return, 3.9%. But now the fund will be worth $288, which means that in the aggregate investors put in $300—the original $100 plus $200 after year one—and lost $12. So the fund has positive time-weighted returns but negative dollar-weighted returns. The proclivity to buy high and sell low means that investors earn, on average, a dollar-weighted return that is only about 60% of the market’s return. Bad timing is very costly.
What is reversion to the mean?
Reversion to the mean occurs when an extreme outcome is followed by an outcome that has an expected value closer to the average. Let’s say you are a student whose true skill suggests you should score 80% on a test. If you are particularly lucky one day, you might score 90%. How are you expected to do for your next test? Closer to 80%. You are expected to revert to your mean, which means that your good luck is not expected to persist. This is a huge topic in investing, for precisely the reason we just discussed. Investors, rather than constantly considering reversion to the mean, tend to extrapolate. Good results are expected to lead to more good results. This is at the core of the dichotomy between time-weighted and dollar-weighted returns. I should add quickly that this phenomenon is not unique to individual investors. Institutional investors, people who are trained to think of such things, fall into the same trap.
In one of your papers you talk about a guy who manages his and his wife’s money. With his wife’s money he is very cautious and listens to what the experts have to say. With his own money his puts it in some investments and forgets about it. As you put it, threw it in the coffee can. And forgot about it. It so turned out that the coffee can approach did better. Can you take us through that example?
This was a case, told by Robert Kirby at Capital Guardian, from the 1950s. The husband managed his wife’s fund and followed closely the advice from the investment firm. The firm had a research department and did their best to preserve, and build, capital. It turns out that unbeknownst to anyone, the man used $5,000 of his own money to invest in the firm’s buy recommendations. He never sold anything and never traded, he just plopped the securities into a proverbial coffee can(those were the days of paper). The husband died suddenly and the wife then came back to the investment firm to combine their accounts. Everyone was surprised to see that the husband’s account was a good deal larger than his wife’s. The neglected portfolio fared much better than the tended one. It turns out that a large part of the portfolio’s success was attributable to an investment in Xerox.
So what was the lesson drawn?
Kirby drew a more basic lesson from the experience. Sometimes doing nothing is better than doing something. In most businesses, there is some relationship between activity and results. The more active you are, the better your results. Investing is one field where this isn’t true. Sometimes, doing nothing is the best thing. As Warren Buffett has said, “Inactivity strikes us as intelligent behavior.” As I mentioned before, there is lots of evidence that the decisions to buy and sell by individuals and institutions does as much, if not more, harm than good. I’m not saying you should buy and hold forever, but I am saying that buying cheap and holding for a long time tends to do better than guessing what asset class or manager is hot.
(The interview was originally published in the Daily News and Analysis(DNA) on June 4,2012.
(Interviewer Kaul is a writer and can be reached at [email protected])