CHAPTER 25
CHAPTER 25 The First Bubble Model EVERY TIME WE HAVE A major collapse in stocks, real estate, commodities or even tulips, experts declare the crash a Black Swan event – rare and unpredictable. “Oh, that was more than three standard deviations from the norm,” they’ll say… or something equally ridiculous. In layman’s terms that means they simply don’t have a clue about what’s going on! You don’t get a major bubble burst without a Yes, major crashes are rare, but they’re anything but unpredictable. That “black swan” psychology simply shows an incredible lack of understanding of the most fundamental law of life, as Newton expressed in his third law of physics: for every action, there is an equal and opposite reaction. It’s like that TV commercial for TD Ameritrade, where this lady is talking about how most things are predictable… From Jerry getting dumped every third Tuesday… To the UPS guy coming around 3 p.m. every day for pick-ups. “No way to predict that!” Ha! Maybe, but the simple truth is that 1
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everything occurs in cycles – in equal and opposite reactions. If something seems unpredictable, it’s because it’s following one of a zillion cycles that you don’t know about or understand. Of course, no one can know about and understand every single cycle in existence. It’s beyond the human brain’s capacity. And even if we could grasp it all, it would overwhelm us rather than help us. That’s why, as I discussed earlier, I focus on the few key cycles that matter for any key dynamic, like the economy or climate. With the information these cycles give me, bubble bursts are absolutely predictable. And I’ve made doing so even easier with this first-ever Bubble Model. Before I detail this model for you, I will say that, while inflating and deflating bubbles are easy to predict, nailing down that precise day and time the fish will fall off the wall is impossible. Think of it like this… If you keep dropping one grain of sand at a time on the floor, a mound will build. It will get steeper and steeper until it looks like a Hershey’s Kiss (a clear sign of a bubble in its late stage). That’s when you know that an avalanche or crash is coming. That’s easy to predict. But there will literally be just one, single grain of sand that will suddenly cause the mound to dissolve. Predicting that one, single grain of sand is just NOT possible. When it comes to bubbles, especially in stocks, it’s easier to see the downside risks and roughly how long it will take a bubble to unwind once it has built exponentially and is in the orgasmic final bubble stage. And really, this is what we want to know about because it’s how we avoid the chaos and financial injuries that are inevitable when the wheels come off. I’ve said this dozens of times throughout this book, but I’ll say it again: bubbles don’t correct. They crash and burn. If you try to time the peak, you’ll lose, because the first rapid crash can see 50% of the total disappear in just a matter of months.
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Even the few people who see bubbles rarely see the extent of the downside risks. They think that such bubbles in financial asset values can plane out for a while or correct 20% to 50%, like what you see during normal longer-term bull markets. That NEVER happens! So, to create the first ever Bubble Model, I identified five key principles… Key Principle #1: Bubbles begin when stocks or any financial asset start growing faster than the linear or fundamental trends, most often well after the bottom of the last major correction or crash. As this trend builds, investors increasingly buy just because a market is going up faster than usual, for a long enough period of time to give them confidence in their decision. Greed and speculation start to take hold. Fundamentals fly the coup. I call this point the Bubble Origin. Key Principle #2: Bubbles then build exponentially for several years – typically five to six years in stocks and longer in real estate. Key Principle #3: The greater the bubble, the greater the burst. Bubbles vary in intensity, which determines both their height and the how big their crash. I calculate the Bubble Intensity by taking the “Times Gain” – how much it increased in value expressed as a ratio (instead of a percentage) – and dividing that by the length of time from origin to peak. So, for example, if a bubble took five years from bottom to top to triple (a 3-times gain), the Bubble Intensity is 0.60. This allows me to compare bubbles in different asset sectors to historical ones, especially if their durations differ. Key Principle #4: Bubbles then burst at least twice as fast as they build, more-so with stocks than commodities or real estate.
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The typical stock bubble is about five to six years in length, with a 2.5 to three-year crash after the peak. This was the case with the stock bubbles in the late Roaring ’20s in the U.S., the Japan Nikkei bubble in the ’80s, and the ’90s in tech stocks. The typical real estate bubble is about eight to 10 years, taking about as long to unwind because they’re far less liquid than stocks. Key Principle #5: Most important, bubbles tend to go back to where they started, at what I call the Bubble Origin. Sometimes they’ll not make it all the way down. Other times they’ll drop lower. That’s why it’s so important to identify where a bubble started. Knowing that, along with several other factors, gives us a good idea of where the crash will end. At this point, I need to take you on a quick, and important, detour…
How Simple Linear Trends Always Go Exponential My first principle of bubbles is that all long-term growth is exponential, not linear. Then I say that when we get an exponential trend from the fundamental linear trend, that’s the Bubble Origin. Sounds a little contradictory, I’ll admit. But it’s not. The best and easiest way to think about this is with the principal of compound interest or growth… If you take a constant 3% growth rate, which is apparently linear, and compound that growth – which means that 1% becomes 1.03% and then 1.06% and so on – that seemingly linear trend becomes exponential over time. That 3% trend is building on an increasingly larger base, like that mound of sand being built one grain at a time. Your experience in investing is linear if you just watch your annual gains or withdraw your gains every year and spend them. If you reinvest them, they ultimately become exponential.
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Figure 21-1 : Simple vs. Compound Growth Rates
Compound Annual Rate of 3%
Simple Annual 3% Rate
$190,000 $170,000 $150,000 $130,000 $110,000 $90,000 $70,000 $50,000 $30,000 $10,000
0
5
10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 Years
Source: Dent Research
That’s why systematic saving is so important to building wealth longer term. That’s why you can achieve unbelievable wealth if you just invest consistently from a young age, and then reinvest those gains and dividends. Knowledge and evolution is also exponential in the long-term. They build on themselves and compound naturally. The more knowledge grows the more it builds on itself. Ultimately, it comes down to perspective. If you look at the horizon when both your feet are planted firmly on the ground, the Earth looks flat. Go up just a hundred miles and immediately you can see Earth’s curve. Look at a trend close up and it’ll look linear. Step away and take a longer-term view, and you’ll see that it’s actually exponential (and cyclical). When bubbles pop up in the late stages of a long-term growth trend, they’re simply reflecting the late and most extreme stages of such compounded growth. This always comes in the fall (peak)
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economic season of any four-stage cycle… like the colors of leaves morphing to their greatest beauty before they die in winter. So, when the seemingly linear trend of 7% real stock growth shifts gears and races to 15% or 20%-plus, you know it’s nearing the end. I’ll repeat this chart here because it makes this point so clearly… Figure 21-2 : Stock Prices Since 1700
Great Resets Throughout History 100,000 Annual Average Prices, Semi Log Scale 10,000
1,000 British Stock Prices
100
U.S. Stock Prices
!
10
Great Resets
1
1700
1730
1760
1790
1820
1850
1880
1910
1940
1970
2000
2030
In this logarithmic chart, we see three clear bubbles and crashes (or resets). We also see we’re clearly in the fourth one. Source: Conquer the Crash by Robert Prechter, pg. 33, Dent Research
Bubbles always burst. And the greater the bubble, the greater the burst. With all that said, let’s return to the point of this chapter: my Bubble Model.
Creating the Base Lines My model starts with the male orgasm chart from Masters and Johnson, which I introduced to you in Chapter 4. To it, I add several
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key average parameters. Note that this model is specifically for stocks. It’s slightly different for real estate and commodities. Figure 21-3 : Bubble Model for Stocks
Masters and Johnson Sexual Response Cycle: Male Times Gain From Origin
Orgasm
Excitement & Plateau (Arousal)
Crash Percent Bubble Intensity = Times Gain / Duration
Desire (Appetitive) Bubble Origin
Bubble Duration (Years)
Crash Duration = 50% Bubble Crashes Back to Origin
a bubble has begun to form, I draw a trend line through Source: After Dent Research the linear fundamental trend going back to the last bottom. Where the markets diverge above those trends – and keep diverging exponentially – is the Bubble Origin, as you can see in Figure 21-3. The bubble accelerates into the last blow-off and that’s when we know the peak is getting close (we saw this clearly in late 1998 to early 2000, in the dramatic tech bubble). As that top approaches, I can calculate the intensity of the bubble and compare it to other current or past bubbles. Well before the actual top, I know the downside potential because the sector should return at least near the Bubble Origin. Once the bubble starts to burst – and it typically does so violently, with 30% to 50% of the total decline occurring in the first
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sharp crash – I can estimate about how long the overall crash will take by calculating how long it took to rise from the Bubble Origin to the peak and taking 50% of that. Again, this calculation is for stocks only (it’s different for commodities and real estate, which I’ll get to in a few minutes). That’s why calculating the Bubble Origin is more important than just looking at the last long-term low before the bull market began. There you have it. As my model shows (and as I’ll demonstrate in the next few pages), bubbles aren’t so complicated and unpredictable. The hardest thing is predicting the peak because everything involved in the bubble gets so irrational at the top. This has clearly been the case since late 2008, when governments began moving to extreme lengths to prevent the bubbles from bursting. Since then, bad news has become good news because governments have convinced people that they will only stimulate harder and drive more free money into the financial markets, driving speculation and mutating the bubble ad-infinitum. What no one seems to realize is that it all eventually collapses in on itself because bubbles always defeat themselves from their very extremes, no matter what’s actually driving it.
The Model in Action The Japanese stock market enjoyed the first major baby boom bubble from late 1984 through late 1989. Then it crashed dramatically into late 1992, just as the rest of the world was living large through the greatest boom in modern history. I alone predicted that bubble crash back in 1988-1989 in my presentations and my book, Our Power to Predict. Here’s that Nikkei Bubble chart again, but this time with my Bubble Model applied…
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Figure 21-4 : Japan Nikkei Bubble and Burst: Late 1984 - Mid 1992
4.4 Times Gain
40,000
35,000 Bubble Instensity = 0.80 4.4 Times Gain / 5.5 Duration 30,000
25,000
20,000 Actual Crash -64%
15,000 (50%) 2.75 Years
5.5 Years
10,000
Forecast Crash: -77%
Bubble Origin
5,000 1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
Source: Bloomberg, Dent Research
I went back several years and drew that fundamental trend line. This showed me that the Nikkei started going exponential from around late 1984, when the index was around 8,000. That was the Bubble Origin. It then exploded into the very end of 1989, reaching 39,000. That gives it a gain of 4.4-times. The bubble lasted 5.5 years and had an intensity rating of 0.8, a bit higher than average for stocks. My model forecast that the crash would have lasted 2.75 years, with a 77% decline. The actual crash saw a loss of 64%, but very close to the bottom time estimate in late 1992. The reason the crash was a bit less than expected was because the rest of the world was in the greatest stock boom in history – as I also predicted back in 1988/89. The first, very sharp crash saw a 31% decline in less than three months, declaring that a top had finally occurred. After a brief bounce the market went down 49% in just the first eight months.
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Again, that’s why you get out a bit early! The crash lasted 2.75 years, in this case exactly 50% of the 5.5year rise, and first bottomed 64% down in July 1992, just above the Bubble Origin. The ultimate low (thus far) – down 80% at just 7,600 – came in early 2003, when Japan’s demographic trends were at their worst. Eventually this bubble did erase all of its gains and go back to the Bubble Origin. Looking at the most prominent stock bubbles in modern history in the table below, you can see we get similar dynamics and parameters to the Nikkei bubble. Stock crashes are both more rapid and predictable because investors can panic much faster than they can with real estate, which is far less liquid. Figure 21-5 : Table of Stock Bubbles Past and Present
Bubble
Start
Bubble Duration
Times Gain
Bubble Intensity
Crash Duration
Crash Severity
Nikkei, 1989
1984
5.5 Years
4.4
0.80
2.75 Years
-64%
Dow, 1929
1924
4.9 Years
3.8
0.78
2.5 Years
-89%
Nasdaq, 2000
1995
5.3 Years
6.8
1.3
2.6 Years
-78%
Shanghai, 2007
1996
1.75 Years
5.2
3.0
0.9 Years
-72%
Biotech, 2015
2011
3.75 Years
4.2
1.12
1.9 Years
S&P 500, 2016
2009
7.3 Years
3.2
0.44
3.7 Years
-75% (Est.)* -69% (Est.)*
*Est. = Estimated by Model
The major bubble preceding the Nikkei collapse was the infamous Roaring ’20s stock bubble that peaked in September 1929, a moment in history we are all too familiar with as the beginning of the Great Depression. Its Bubble Origin date was very late 1924 and it peaked in late 1929. It saw a 3.8-times gain in just five years, with a Bubble Intensity of 0.78 (similar to Japan’s bubble). My model projected that the crash would last 2.5 years and see losses as much as 74%, but the actual crash was worse! By July of 1932, the Dow had lost 89%.
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The Nasdaq bubble of 2000 had its Bubble Origin in very late 1994. It peaked in early March of 2000, building over 5.2 years. The gain was a whopping 6.8-times, so it had a Bubble Intensity of 1.31 – the highest major developed country stock bubble in modern history. The bubble took exactly half the time to unwind, losing 78% (my model projected an 85% loss). Over in China, the Shanghai Composite saw the most dramatic short-term bubble from very late 2005 into October 2007. It had a 5.2-times gain and a Bubble Intensity off the charts at 3.0. That’s the highest I’ve ever seen! The crash bottomed in early November of 2008 at 72%, only a bit above my forecast target of 81% down. That is still very close for a forecast of such a volatile event. Then came the second bubble in the Nasdaq: biotech. Its Bubble Origin was in early 2012, with a 4.2-times gain into mid-2015. It’s Bubble Intensity was 1.12, nearly as high as the first Nasdaq bubble. Its initial crash saw losses of 40% in the first 2.5 months – the classic sign of a bubble beginning to burst, and yet more evidence of why you should get out a bit early rather than later. My model projects that this bubble burst will likely end into late 2017, with losses extending to as much as 75%. (As a leading-edge sector, this biotech bubble burst strongly suggests that the broader tech sector will soon follow suit.) The last sector to peak in the U.S. – the best house in a bad neighborhood – is the S&P 500 in late 2016. Most stocks around the world peaked sometime in 2015 and have little or no chance of seeing new highs. But the prime large-cap stock indicator in the U.S. made slight new highs in July 2016, with the Dow and Nasdaq following. This index saw its third and final bubble origin in early March 2009, enjoying a 3.2-times gain into August 2016. Its bubble
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intensity is at a lower and more typical 0.44. The first bubble was the most dynamic. Every one since then has been less intense, given slower demographic and technological trends, not to mention steadily worsening geopolitical trends. The current bubble is the worst because it’s totally artificial, driven by 0% interest rates and endless QE. My model here projects a 69% crash into early 2020. Since my demographic cycle doesn’t turn up again until early 2023, I think the markets could continue to be volatile and move sideways or lower into mid- to late-2022… and ultimately be down as much as 80% to get back to the origin of the first bubble, at 450 on the S&P 500 and 3,800 on the Dow by late 2022.
Real Estate Bubbles: A Different Beast When applying my new Bubble Model to real estate, I had to make some adjustments because it’s a different beast to the stock market. Stocks fit the orgasm model the best because they’re highly liquid (mostly). Real estate, on the other hand, is highly illiquid so when bubbles burst in this sector, they take much longer to unwind. Also, when real estate crashes, it has a greater impact on the economy and banking system because it’s such a highly leveraged asset through mortgages. Perhaps the three biggest differences in the real estate bubble model are: 1. The crashes are more symmetrical and tend to last about as long as the bubble build. Remember, stock bubbles deflate in half the time it took them to build. 2. Real estate bubbles vary more because of larger differences in regional supply and demand.
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3. Thanks to limited supply in most coastal areas, crashes tends to go back only about 85% to the Origin Point, not 100% like they do for stocks. Let’s look at the largest and the first real estate bubble to illustrate. Figure 21-6 : Japan Residential Real Estate Bubble of 1991
4.9 Times Gain Bubble Intensity = 0.38 4.9 Times Gain / 13 Duration
200
-68% Forecast
Index 100=200
150
100 -70% 13 Years
13 Years
50 Bubble Origin
0
1964
1969
1974
1979
1984
1989
1994
1999
2004
2009
2014
Source: Land Institute of Japan, 6-City Real Estate Index, Dent Research
This one was a doozy! Japan’s residential real estate went up 4.9-times from its Origin in 1978. That took 13 years. Then it crashed 70% into 2004, taking as long to unwind as it did to build. My model forecast that the crash should have been 68%, very close to the actual. The country’s commercial real estate bubble was worse. It gained 6.2-times and crashed 87%. Why did I start out with this extreme example? To counter the ultimate baby boom generation delusion. Most members of this
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generation believe that real estate can never go down because they ain’t making any more of it. That’s just plain wrong. History proves their belief to be untrue. For centuries in Europe, real estate went up and down almost as violently as stocks. We have lived in a rare period where the first middle-class generation after WWII bought homes en-masse. They were followed by the largest generation in history, who bought even more property. Except for rare minor bubbles in regional areas like California, Texas or Florida, real estate enjoyed a long period of appreciation since its major bottom in 1933! But as I showed you earlier in this book, those two trends are over. Demographics tells us that there will be more sellers than buyers into 2039, hence net demand for houses will continue to slow and real estate “will never be the same.” Here’s a comparison of other residential bubbles around the developed world, as seen through my model. The downside projections would startle most people, even when I allow for only an 85% decline back towards the Origin Point. While typically only stocks go all the way back to that starting point, a 100% decline in real estate is possible… but it’s just the worst case scenario. Figure 21-7 : Real Estate Bubbles in Developed Countries
Bubble
Start
Bubble Duration
Times Gain
Bubble Intensity
Crash Duration
Crash Severity
Japan, 1991
1978
13 Years
4.9
0.38
13 Years
-70%
London, 2016
1999
17.25 Years
4.0
0.23
Vancouver, 2016
2002
14.2 Years
2.9
0.21
Sydney, 2016
2000
14.75 Years
2.8
0.19
Shanghai, 2016
2001
15.5 Years
8.0
0.52
Mumbai, 2016
2009
6.25 Years
2.1
0.33
*Est. = Estimated by Model
17.25 Years -64% (Est.)* 14.2 Years -55% (Est.) 14.75 Years -55% (Est.) 15.5 Years -77% (Est.) 6.25 Years -44% (Est.)
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Japan’s housing bubble roared to life way back in mid-1978, as its baby boom peak in 1949 came 12 years before it did in North America and 15 years before Europe. It rose an astounding 4.9-times in 13 years, with a bubble intensity of 0.38. That’s high for real estate, which typically doesn’t climb as fast as stocks do. Then it collapsed, right on schedule, into mid-2004… and it has never recovered. Nor will it, considering the country faces more dyers than buyers into 2033. Again, the actual crash was 70% while my model forecast losses of about 68%! As for London, the richest people there are convinced that property in that city could never go down… because it’s a “special place.” It may have some unique attributes and definitely limited space, but history shows that those “special places” always bubble the most and then crash the worst. London’s bubble started around early 1999, just ahead of the U.S. It went up 4-times but over 17.25 years. That’s the longest I’ve seen. The more typical real estate bubble grows anywhere between six and 10 years. Because of how long it’s taken the London property bubble to build, it’s intensity is 0.23, much less than Japan’s. According to my model, the projected crash would be 64%, taking prices back to within 15% of the Origin. And that decline could last well into 2033, although I think we may see the bottom sooner than that. Remember that Europe overall has declining demographics and London may not continue to be the clear major financial center after Brexit and the ultimate dissipation and restructuring of the Eurozone and euro. Since Vancouver is “so special,” it has bubbled big time. The typical, crappy little home now goes for $1.2 million! Vancouver’s Bubble Origin was around late 2002. It’s seen a 2.9-times gain into 2016 and a bubble intensity of 0.21. That doesn’t
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sound so high, but consider that the home prices in the city were already very expensive before the bubble began to inflate. As I predicted they would, Vancouver copied Singapore and slapped a major tax on foreign buyers in August 2016. This move will destroy their bubble and it was down 24% just in the first five months. My model projects a collapse of as much as 55% into mid2031, if not sooner. Then there’s my favorite city in the developed world: Sydney. You don’t know how unpopular I am to many there given my forecasts. No one thinks Australian real estate can ever go down because it’s a large desert with a few wonderful cities and great weather. People there are always telling me: “Harry, you don’t understand Australian real estate.” My reply is always: “I lived in California for 22 years. I saw THAT bubble build and burst… and Australia is exactly like California… except with better long-term demographics.” Sydney’s real estate boom started around early 2000 and lasted 14.75 years. It’s had an intensity of only 0.21. But like California, Vancouver and Tokyo, it was already expensive before the bubble began. At this point, it’s downright unaffordable except to foreign buyers (who are largely laundering their money out of China). My model projects a loss of 55% in Sydney by 2033. Demographics may soften that decline a little. As I said earlier in this book, if I had to own real estate in a first-class city and sit out the greatest financial crisis since the early 1930s, it would be in Sydney. The bubble in Melbourne is even greater, and the bubbles in Brisbane, Perth and Adelaide are a little less so. But all of Australia is in for a rough ride, despite its better demographic trends. Its government debt may be the lowest in the developed world, but its
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banks’ and households’ exposure to high real estate costs are among the highest. Before moving on to look at the double property bubble in the U.S., let’s consider the two more prominent emerging-world cities, starting with Shanghai... Its Bubble Origin was around early 2001, and it has seen a whopping 8.0-times gain in 15.5 years. A long bubble with a high intensity at 0.52, it’s greater than Japan’s bubble. My model projects a crash of 77% into late 2021. And finally, India. The Asian Tiger has some of the most favorable demographic trends into 2060-plus, and has much urbanization to exploit for decades. But, it too faces a real estate bubble burst. Mumbai’s property bubble only started around early 2010 and has advanced 2.1-times over the last 6.25 years. The intensity is a bit less than China’s, but it’s still a decent 0.33. Here, my model projects a crash of 44% into mid-2023. After that, India is an ideal place to invest in because it faces the boom of the century ahead (more about this in Chapter 24)!
Double Trouble in the U.S. Just as stocks saw an unprecedented three major bubbles before peaking between 2015 and 2016, real estate from the U.S. to Spain, to Ireland to Singapore, to the United Arab Emirates have seen two bubbles. That makes the analysis a bit different. I took three cities from around the world and broke them into Bubble #1 and Bubble #2. The range of downsides is more varied because there are two scenarios here. The first one is that the second and final bubble burst takes them back to the bottom of the first bubble. The second one is that these cities go to within 15% of the first Bubble Origin.
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I use a chart of the twin San Francisco bubbles to illustrate… Figure 21-8 : Double Bubble in San Francisco
Bubble #1
230
3.0 Times Gain
Bubble #2
1.8 Times Gain Bubble Intensity = 0.42 1.8 Times Gain / 4.25 Duration
210 190
Bubble Intenstiy= 0.34 3.0 Times Gain / 8.75
100=2000
170 150 130 110
-47% Best Case
-45% Actual -57% Forecast
-58% Forecast
90 70
5.75 Years
4.25 Years
4.25 Years
1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
50
8.75 Years Bubble Origin
Source: St. Louis Federal Reserve, S&P/Case-Shiller, Dent Research
Just like in Vancouver, you don’t want to have to buy a condo in downtown San Francisco at 2016 prices! The city’s first Bubble Origin was in mid-1997. It saw a bubble into early 2006 that lasted 8.75 years with a 3-times gain for an intensity of 0.35. The crash was faster than usual, losing 45% in just 5.75 years compared to my model’s projected losses of 56%. The second bubble started in early 2009 and went up 1.8-times into early 2016 – reaching substantial new highs. That lasted 4.25 years, with an intensity a bit higher at 0.42. The best-case projection here is that this latest bubble sheds 47% by around late 2020. The more likely scenario is that it will lose as much as 58%, going within 15% of its 1997 Bubble Origin. I show two other double bubbles to compare to San Francisco in the table below.
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Figure 21-9 : Table of Stock Bubbles Past and Present
Bubble
Start
Bubble Duration
Times Gain
Bubble Intensity
Crash Duration
Crash Severity
San Francisco, Bubble #1, 2006 San Francisco, Bubble #2, 2016 Singapore, Bubble #1, 1996 Singapore, Bubble #2, 2013 Dubai, Bubble #1, 2008 Dubai, Bubble #2, 2014
1997
8.75 Years
3.0
0.34
5.75 Years
-45%
2012
4.25 Years
1.8
0.42
4.25 Years
-47% to -58% (Est.)*
2.7
0.70
2.5 Years
-48%
1992
3.75 Years
2009
4.25 Years
1.9
0.40
4.25 Years
-47% to -50% (Est.)*
2008
2.25 Years
2.1
0.94
2.75 Years
-35%
2014
3.75 Years
1.7
0.46
3.75 Years
-42% to -49% (Est.)*
*Est. = Estimated by Model
Singapore has one of the highest per-capita incomes in the developed world and is unique in that the country is just one large city. It has no rural areas. It’s 100% urban! Its government was the first to slap a heavy surcharge of 26% on foreign buyers, with an additional 12% to 16% if they flip in one to two years. Ouch! Not surprisingly, since then, prices have fallen 22% from their highs. Singapore’s first real estate bubble started way back in late 1992 and saw a 2.7-times gain with a high intensity of 0.70 over a brief 3.75 years. The crash lost 48% in just 2.5 years. That is exactly as my model forecast. Bubble #2 then went up 1.8-times into late 2013. My crash forecast is that, at best, Singapore property prices will lose 47% into late 2017 or so. More likely, though, is loses closer to 50% (bringing it within 15% of the original 1997 starting point). The worst-case scenario is that Singapore real estate could go down 59% to its first bubble low. Then there’s Dubai, which I was fortunate to visit right near its peak in late 2007. No one in the large and global audience there could see real estate going down. Except me. It’s first bubble was really brief, from early 2006 into early 2008 (just 2.25 years) at a strong intensity of 0.94. The fall was -35% into
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early 2011. My model projected losses as high as 45%. The second bubble went up 1.7-times into late 2014, over 3.75 years, with a lower intensity of 0.46. The best-case projection here is that Dubai real estate will see losses up to 42% by mid-2018… it may go even lower, to 49% to reach 15% from the first Bubble Origin. Strong demographics in Dubai and Singapore should cushion their downside risk. But oil is the wild card for Dubai. It has already seen the bulk of its potential decline, but given that we could see oil going at low as $10 to $20 a barrel, Dubai real estate could go back down 59% to its first Bubble Origin.
Commodity Bubbles: The Drama Queens Commodities have more extreme bubbles and crashes. They collapse faster during the initial burst. They are more likely to bottom at the Origin Point or lower. And there is more variation between different sectors, making an apples-to-apples comparison essential. Because of this, commodity bubbles are perhaps hardest to predict – that’s why the best traders are commodity traders! Look at the broader commodity bubble in the chart below.
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Figure 21-10 : Global Commodities Bubble, CRB Index
500
3.1 Times Gain
450 Bubble Intensity = 0.48 3.1 Times Gain / 6.4 Duration
400
350
300
250
200
First Crash 58%
6.4 Years
150
100 1994
7.6 Years -67% Back to Origin
Bubble Origin
1996
1998
2000
2002
2004
2006
2008
2010
2012
2014
or 74%
2016
2018
Source: Bloomberg, Dent Research
CRB is the most basic commodities index. Just look at the bubble from around late 2003 into early 2008! Over 6.4 years, it went up 3.1-times with an intensity of 0.48. And look at that first dramatic burst! The index lost 58% and in just eight months, from March 2008 to November 2008. That’s just 12% of the time it took the bubble to build! The low thus far has already been -67%, and should be lower still into at least early 2018. I’m talking down a total of 74% or more. Commodities were among the first to crash in this global bubble environment, and they’ll likely be the first to bottom as well. Oil’s bubble and crash was the most extreme of the lot, going from $32 in late 2014 to $147 in mid-2008 (just 3.6 years) and then crashing back down to $32 in just 4.5 months. I have never seen a bubble crash that hard and fast! Oil advanced 5.4-times in a short period, so its Bubble Intensity was 1.13 – very high. Then it crashed 79% in just 4.5 months. That’s the fastest and greatest bubble burst I have ever seen!
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Oil is likely to bottom somewhere between $8 and $20 by late 2017 (maybe a little later). That will mean as much as a 95% decline from its peak in mid-2008. However, typical commodity bubbles are more like real estate bubbles and tend to take about the same time to reach their ultimate bottom as it took the bubble to build. I summarize some of the other key bubbles in the table below. Figure 21-11 : Commodity Bubbles: Past and Present
Bubble
Start
Bubble Duration
CRB, 2008
2002
6.4 Years
Copper, 2011
2003
Oil, 2008
2003
Gold, 2011 Iron Ore, 2011 Corn, 2012
Times Gain
Bubble Intensity
Crash Duration
Crash Severity
3.1
0.48
7.6 Years
-67% Actual or -74% (Est.)*
7.75 Years
4.6
0.59
7.75 Years
-84% (Est.)
4.8 Years
5.4
1.13
7.6 Years
-82% Actual or -88% (Est.)
2005
6.25 Years
3.5
0.56
6.25 Years
-78% (Est.)
2007
3.25 Years
4.1
1.26
4.5 Years or 7.9 Years
-76% Actual or -88% (Est.)
2006
6 Years
3.3
0.55
6 Years
-70% (Est.)
*Est. = Estimated by Model
Copper is the more typical industrial metal that follows the economy because it goes into so many different products. Its Bubble Origin was in mid-2003 and it peaked in early 2011, with a 4.6-times gain and an intensity of 0.59 over 7.75 years. Its My model projects copper’s crash will continue into around late 2019/early 2020, ultimately losing as much as 84% from its peak. It has seen a loss of 43% recently, so it has a lot farther to go before this one’s over… more than many other industrial or energy-related commodities. Then we come to one of the areas of greatest interest: gold. Firstly, gold is, at its core, a commodity. The greatest consumers are the two countries with the largest population, China and India!
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Secondly, gold has been in a bubble like all other commodities. The last time gold bubbled was into 1980, along with the broader commodity sector. Thirdly, gold correlates most with inflation, as commodities in general do. It is NOT a safe place to be during deflationary times, which we face ahead (as I’ve already explained). Gold’s latest bubble started around mid-2005, when the yellow metal was close to $400 (its ultimate low was at $250 back in 2001). From 2005 though, it went up 3.5-times over 6.25 years into late 2011, giving it a Bubble Intensity of 0.56. (From the 2001 low, it went up 7.7-times.) Either way folks, that’s a bubble! Gold has already been down 46% in early 2016, despite the greatest money-printing spree in history. The most likely bottom target, according to my model – taking the metal back to its Origin – would be $400 by early 2018. That would represent a 79% crash from its September 2011 high. The commodity bubble with the most extreme Bubble Intensity and most persistent crash is iron ore. That bubble started in late 2007 and exploded into early 2011, with a higher intensity than oil at a whopping 1.26. That was a 3.25-times gain in just 4.5 years, So, of course there would be a big crash. It’s already lost as much as 76% by early 2016. It could lose as much as 88% by early 2018 or so, when all is said and done. And finally, corn. I keep hearing people say that the one thing people can’t stop doing in a downturn is eating, so there’s little downside in agricultural commodities. Well, tell that to corn prices! In six years, corn bubbled up 3.3-times into late 2012 and has crashed 63% already. It’s likely headed lower, down a total of 70%plus in the years ahead, especially with sunspot cycles suggesting a bout of cooling into late 2019/early 2020.
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And that’s a big reason that farmland in Iowa has started to crack, although not as much as you would think given such a sharp fall in corn prices. I get a lot of questions about whether farmland is in a bubble or not. The answer unfortunately is that it is! I chose to illustrate this point using Iowa farmland instead of other states like Illinois or Indiana, or Ohio, because Iowa is more rural. It has fewer large, sprawling cities. Farmland prices are still edging up in those other states due to suburban sprawl. But farmland in Iowa peaked in late 2012/early 2013, more in-line with their largest crop, which is corn. Figure 21-12 : Iowa Farmland Bubble, 2013
$10,000 3.8 Times Gain
Bubble Intensity = 0.38 3.8 Times Gain / 10 Duration
$9,000 $8,000
-63%
Price per Acre
$7,000 $6,000 $5,000 $4,000 $3,000 10 Years
$2,000
85% Back to Origin
10 Years
Bubble Origin
2023
2022
2021
2020
2019
2018
2017
2016
2015
2014
2013
2011
2012
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
$1,000
Source: Farmland Value Survey Lowa State University, Dent Research
Between early 2003 and early 2013, the state’s farmland went up 3.8-times, giving the bubble an intensity of 0.38 (not an extreme bubble). But my model projects that it could deflate 63% by early 2023… right when I see the next global boom emerging and commodity prices rising sharply again on my 30-Year Commodity Cycle. This means other Midwestern states and farm areas have even
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more downside since their prices are still going up due to suburban sprawl that is not as prevalent.
And So… I hope at this point I’ve shown you that major stock bubbles tend to come every 60 to 80 years, in-line with the average human lifetime. Commodity bubbles rise into the high point of the 29- to 30-Year Commodity Cycle. And real estate bubbles come on the 80year generation and economic cycle, but real estate also has its own 18-year cycle. We are in the twilight of the greatest and most pervasive bubble in modern history. Commodities burst first, and then real estate in selective areas follow suit. This third major bubble in stocks globally is last, and it’s set to burst by early 2017 at the latest with a global real estate crash this time around led by China. This is the time to understand bubbles – how they build, how they crash – because there’s no time in your life when they’ll affect you more… and if you’re ready, you can make a fortune in a matter of years by buying financial assets at the lowest prices you will see in your lifetime. So let's move on to that...
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everything occurs in cycles – in equal and opposite reactions. If something seems unpredictable, it’s because it’s following one of a zillion cycles that you don’t know about or understand. Of course, no one can know about and understand every single cycle in existence. It’s beyond the human brain’s capacity. And even if we could grasp it all, it would overwhelm us rather than help us. That’s why, as I discussed earlier, I focus on the few key cycles that matter for any key dynamic, like the economy or climate. With the information these cycles give me, bubble bursts are absolutely predictable. And I’ve made doing so even easier with this first-ever Bubble Model. Before I detail this model for you, I will say that, while inflating and deflating bubbles are easy to predict, nailing down that precise day and time the fish will fall off the wall is impossible. Think of it like this… If you keep dropping one grain of sand at a time on the floor, a mound will build. It will get steeper and steeper until it looks like a Hershey’s Kiss (a clear sign of a bubble in its late stage). That’s when you know that an avalanche or crash is coming. That’s easy to predict. But there will literally be just one, single grain of sand that will suddenly cause the mound to dissolve. Predicting that one, single grain of sand is just NOT possible. When it comes to bubbles, especially in stocks, it’s easier to see the downside risks and roughly how long it will take a bubble to unwind once it has built exponentially and is in the orgasmic final bubble stage. And really, this is what we want to know about because it’s how we avoid the chaos and financial injuries that are inevitable when the wheels come off. I’ve said this dozens of times throughout this book, but I’ll say it again: bubbles don’t correct. They crash and burn. If you try to time the peak, you’ll lose, because the first rapid crash can see 50% of the total disappear in just a matter of months.
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Even the few people who see bubbles rarely see the extent of the downside risks. They think that such bubbles in financial asset values can plane out for a while or correct 20% to 50%, like what you see during normal longer-term bull markets. That NEVER happens! So, to create the first ever Bubble Model, I identified five key principles… Key Principle #1: Bubbles begin when stocks or any financial asset start growing faster than the linear or fundamental trends, most often well after the bottom of the last major correction or crash. As this trend builds, investors increasingly buy just because a market is going up faster than usual, for a long enough period of time to give them confidence in their decision. Greed and speculation start to take hold. Fundamentals fly the coup. I call this point the Bubble Origin. Key Principle #2: Bubbles then build exponentially for several years – typically five to six years in stocks and longer in real estate. Key Principle #3: The greater the bubble, the greater the burst. Bubbles vary in intensity, which determines both their height and the how big their crash. I calculate the Bubble Intensity by taking the “Times Gain” – how much it increased in value expressed as a ratio (instead of a percentage) – and dividing that by the length of time from origin to peak. So, for example, if a bubble took five years from bottom to top to triple (a 3-times gain), the Bubble Intensity is 0.60. This allows me to compare bubbles in different asset sectors to historical ones, especially if their durations differ. Key Principle #4: Bubbles then burst at least twice as fast as they build, more-so with stocks than commodities or real estate.
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The typical stock bubble is about five to six years in length, with a 2.5 to three-year crash after the peak. This was the case with the stock bubbles in the late Roaring ’20s in the U.S., the Japan Nikkei bubble in the ’80s, and the ’90s in tech stocks. The typical real estate bubble is about eight to 10 years, taking about as long to unwind because they’re far less liquid than stocks. Key Principle #5: Most important, bubbles tend to go back to where they started, at what I call the Bubble Origin. Sometimes they’ll not make it all the way down. Other times they’ll drop lower. That’s why it’s so important to identify where a bubble started. Knowing that, along with several other factors, gives us a good idea of where the crash will end. At this point, I need to take you on a quick, and important, detour…
How Simple Linear Trends Always Go Exponential My first principle of bubbles is that all long-term growth is exponential, not linear. Then I say that when we get an exponential trend from the fundamental linear trend, that’s the Bubble Origin. Sounds a little contradictory, I’ll admit. But it’s not. The best and easiest way to think about this is with the principal of compound interest or growth… If you take a constant 3% growth rate, which is apparently linear, and compound that growth – which means that 1% becomes 1.03% and then 1.06% and so on – that seemingly linear trend becomes exponential over time. That 3% trend is building on an increasingly larger base, like that mound of sand being built one grain at a time. Your experience in investing is linear if you just watch your annual gains or withdraw your gains every year and spend them. If you reinvest them, they ultimately become exponential.
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Figure 21-1 : Simple vs. Compound Growth Rates
Compound Annual Rate of 3%
Simple Annual 3% Rate
$190,000 $170,000 $150,000 $130,000 $110,000 $90,000 $70,000 $50,000 $30,000 $10,000
0
5
10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 Years
Source: Dent Research
That’s why systematic saving is so important to building wealth longer term. That’s why you can achieve unbelievable wealth if you just invest consistently from a young age, and then reinvest those gains and dividends. Knowledge and evolution is also exponential in the long-term. They build on themselves and compound naturally. The more knowledge grows the more it builds on itself. Ultimately, it comes down to perspective. If you look at the horizon when both your feet are planted firmly on the ground, the Earth looks flat. Go up just a hundred miles and immediately you can see Earth’s curve. Look at a trend close up and it’ll look linear. Step away and take a longer-term view, and you’ll see that it’s actually exponential (and cyclical). When bubbles pop up in the late stages of a long-term growth trend, they’re simply reflecting the late and most extreme stages of such compounded growth. This always comes in the fall (peak)
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economic season of any four-stage cycle… like the colors of leaves morphing to their greatest beauty before they die in winter. So, when the seemingly linear trend of 7% real stock growth shifts gears and races to 15% or 20%-plus, you know it’s nearing the end. I’ll repeat this chart here because it makes this point so clearly… Figure 21-2 : Stock Prices Since 1700
Great Resets Throughout History 100,000 Annual Average Prices, Semi Log Scale 10,000
1,000 British Stock Prices
100
U.S. Stock Prices
!
10
Great Resets
1
1700
1730
1760
1790
1820
1850
1880
1910
1940
1970
2000
2030
In this logarithmic chart, we see three clear bubbles and crashes (or resets). We also see we’re clearly in the fourth one. Source: Conquer the Crash by Robert Prechter, pg. 33, Dent Research
Bubbles always burst. And the greater the bubble, the greater the burst. With all that said, let’s return to the point of this chapter: my Bubble Model.
Creating the Base Lines My model starts with the male orgasm chart from Masters and Johnson, which I introduced to you in Chapter 4. To it, I add several
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key average parameters. Note that this model is specifically for stocks. It’s slightly different for real estate and commodities. Figure 21-3 : Bubble Model for Stocks
Masters and Johnson Sexual Response Cycle: Male Times Gain From Origin
Orgasm
Excitement & Plateau (Arousal)
Crash Percent Bubble Intensity = Times Gain / Duration
Desire (Appetitive) Bubble Origin
Bubble Duration (Years)
Crash Duration = 50% Bubble Crashes Back to Origin
a bubble has begun to form, I draw a trend line through Source: After Dent Research the linear fundamental trend going back to the last bottom. Where the markets diverge above those trends – and keep diverging exponentially – is the Bubble Origin, as you can see in Figure 21-3. The bubble accelerates into the last blow-off and that’s when we know the peak is getting close (we saw this clearly in late 1998 to early 2000, in the dramatic tech bubble). As that top approaches, I can calculate the intensity of the bubble and compare it to other current or past bubbles. Well before the actual top, I know the downside potential because the sector should return at least near the Bubble Origin. Once the bubble starts to burst – and it typically does so violently, with 30% to 50% of the total decline occurring in the first
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sharp crash – I can estimate about how long the overall crash will take by calculating how long it took to rise from the Bubble Origin to the peak and taking 50% of that. Again, this calculation is for stocks only (it’s different for commodities and real estate, which I’ll get to in a few minutes). That’s why calculating the Bubble Origin is more important than just looking at the last long-term low before the bull market began. There you have it. As my model shows (and as I’ll demonstrate in the next few pages), bubbles aren’t so complicated and unpredictable. The hardest thing is predicting the peak because everything involved in the bubble gets so irrational at the top. This has clearly been the case since late 2008, when governments began moving to extreme lengths to prevent the bubbles from bursting. Since then, bad news has become good news because governments have convinced people that they will only stimulate harder and drive more free money into the financial markets, driving speculation and mutating the bubble ad-infinitum. What no one seems to realize is that it all eventually collapses in on itself because bubbles always defeat themselves from their very extremes, no matter what’s actually driving it.
The Model in Action The Japanese stock market enjoyed the first major baby boom bubble from late 1984 through late 1989. Then it crashed dramatically into late 1992, just as the rest of the world was living large through the greatest boom in modern history. I alone predicted that bubble crash back in 1988-1989 in my presentations and my book, Our Power to Predict. Here’s that Nikkei Bubble chart again, but this time with my Bubble Model applied…
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Figure 21-4 : Japan Nikkei Bubble and Burst: Late 1984 - Mid 1992
4.4 Times Gain
40,000
35,000 Bubble Instensity = 0.80 4.4 Times Gain / 5.5 Duration 30,000
25,000
20,000 Actual Crash -64%
15,000 (50%) 2.75 Years
5.5 Years
10,000
Forecast Crash: -77%
Bubble Origin
5,000 1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
Source: Bloomberg, Dent Research
I went back several years and drew that fundamental trend line. This showed me that the Nikkei started going exponential from around late 1984, when the index was around 8,000. That was the Bubble Origin. It then exploded into the very end of 1989, reaching 39,000. That gives it a gain of 4.4-times. The bubble lasted 5.5 years and had an intensity rating of 0.8, a bit higher than average for stocks. My model forecast that the crash would have lasted 2.75 years, with a 77% decline. The actual crash saw a loss of 64%, but very close to the bottom time estimate in late 1992. The reason the crash was a bit less than expected was because the rest of the world was in the greatest stock boom in history – as I also predicted back in 1988/89. The first, very sharp crash saw a 31% decline in less than three months, declaring that a top had finally occurred. After a brief bounce the market went down 49% in just the first eight months.
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Again, that’s why you get out a bit early! The crash lasted 2.75 years, in this case exactly 50% of the 5.5year rise, and first bottomed 64% down in July 1992, just above the Bubble Origin. The ultimate low (thus far) – down 80% at just 7,600 – came in early 2003, when Japan’s demographic trends were at their worst. Eventually this bubble did erase all of its gains and go back to the Bubble Origin. Looking at the most prominent stock bubbles in modern history in the table below, you can see we get similar dynamics and parameters to the Nikkei bubble. Stock crashes are both more rapid and predictable because investors can panic much faster than they can with real estate, which is far less liquid. Figure 21-5 : Table of Stock Bubbles Past and Present
Bubble
Start
Bubble Duration
Times Gain
Bubble Intensity
Crash Duration
Crash Severity
Nikkei, 1989
1984
5.5 Years
4.4
0.80
2.75 Years
-64%
Dow, 1929
1924
4.9 Years
3.8
0.78
2.5 Years
-89%
Nasdaq, 2000
1995
5.3 Years
6.8
1.3
2.6 Years
-78%
Shanghai, 2007
1996
1.75 Years
5.2
3.0
0.9 Years
-72%
Biotech, 2015
2011
3.75 Years
4.2
1.12
1.9 Years
S&P 500, 2016
2009
7.3 Years
3.2
0.44
3.7 Years
-75% (Est.)* -69% (Est.)*
*Est. = Estimated by Model
The major bubble preceding the Nikkei collapse was the infamous Roaring ’20s stock bubble that peaked in September 1929, a moment in history we are all too familiar with as the beginning of the Great Depression. Its Bubble Origin date was very late 1924 and it peaked in late 1929. It saw a 3.8-times gain in just five years, with a Bubble Intensity of 0.78 (similar to Japan’s bubble). My model projected that the crash would last 2.5 years and see losses as much as 74%, but the actual crash was worse! By July of 1932, the Dow had lost 89%.
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The Nasdaq bubble of 2000 had its Bubble Origin in very late 1994. It peaked in early March of 2000, building over 5.2 years. The gain was a whopping 6.8-times, so it had a Bubble Intensity of 1.31 – the highest major developed country stock bubble in modern history. The bubble took exactly half the time to unwind, losing 78% (my model projected an 85% loss). Over in China, the Shanghai Composite saw the most dramatic short-term bubble from very late 2005 into October 2007. It had a 5.2-times gain and a Bubble Intensity off the charts at 3.0. That’s the highest I’ve ever seen! The crash bottomed in early November of 2008 at 72%, only a bit above my forecast target of 81% down. That is still very close for a forecast of such a volatile event. Then came the second bubble in the Nasdaq: biotech. Its Bubble Origin was in early 2012, with a 4.2-times gain into mid-2015. It’s Bubble Intensity was 1.12, nearly as high as the first Nasdaq bubble. Its initial crash saw losses of 40% in the first 2.5 months – the classic sign of a bubble beginning to burst, and yet more evidence of why you should get out a bit early rather than later. My model projects that this bubble burst will likely end into late 2017, with losses extending to as much as 75%. (As a leading-edge sector, this biotech bubble burst strongly suggests that the broader tech sector will soon follow suit.) The last sector to peak in the U.S. – the best house in a bad neighborhood – is the S&P 500 in late 2016. Most stocks around the world peaked sometime in 2015 and have little or no chance of seeing new highs. But the prime large-cap stock indicator in the U.S. made slight new highs in July 2016, with the Dow and Nasdaq following. This index saw its third and final bubble origin in early March 2009, enjoying a 3.2-times gain into August 2016. Its bubble
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intensity is at a lower and more typical 0.44. The first bubble was the most dynamic. Every one since then has been less intense, given slower demographic and technological trends, not to mention steadily worsening geopolitical trends. The current bubble is the worst because it’s totally artificial, driven by 0% interest rates and endless QE. My model here projects a 69% crash into early 2020. Since my demographic cycle doesn’t turn up again until early 2023, I think the markets could continue to be volatile and move sideways or lower into mid- to late-2022… and ultimately be down as much as 80% to get back to the origin of the first bubble, at 450 on the S&P 500 and 3,800 on the Dow by late 2022.
Real Estate Bubbles: A Different Beast When applying my new Bubble Model to real estate, I had to make some adjustments because it’s a different beast to the stock market. Stocks fit the orgasm model the best because they’re highly liquid (mostly). Real estate, on the other hand, is highly illiquid so when bubbles burst in this sector, they take much longer to unwind. Also, when real estate crashes, it has a greater impact on the economy and banking system because it’s such a highly leveraged asset through mortgages. Perhaps the three biggest differences in the real estate bubble model are: 1. The crashes are more symmetrical and tend to last about as long as the bubble build. Remember, stock bubbles deflate in half the time it took them to build. 2. Real estate bubbles vary more because of larger differences in regional supply and demand.
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3. Thanks to limited supply in most coastal areas, crashes tends to go back only about 85% to the Origin Point, not 100% like they do for stocks. Let’s look at the largest and the first real estate bubble to illustrate. Figure 21-6 : Japan Residential Real Estate Bubble of 1991
4.9 Times Gain Bubble Intensity = 0.38 4.9 Times Gain / 13 Duration
200
-68% Forecast
Index 100=200
150
100 -70% 13 Years
13 Years
50 Bubble Origin
0
1964
1969
1974
1979
1984
1989
1994
1999
2004
2009
2014
Source: Land Institute of Japan, 6-City Real Estate Index, Dent Research
This one was a doozy! Japan’s residential real estate went up 4.9-times from its Origin in 1978. That took 13 years. Then it crashed 70% into 2004, taking as long to unwind as it did to build. My model forecast that the crash should have been 68%, very close to the actual. The country’s commercial real estate bubble was worse. It gained 6.2-times and crashed 87%. Why did I start out with this extreme example? To counter the ultimate baby boom generation delusion. Most members of this
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generation believe that real estate can never go down because they ain’t making any more of it. That’s just plain wrong. History proves their belief to be untrue. For centuries in Europe, real estate went up and down almost as violently as stocks. We have lived in a rare period where the first middle-class generation after WWII bought homes en-masse. They were followed by the largest generation in history, who bought even more property. Except for rare minor bubbles in regional areas like California, Texas or Florida, real estate enjoyed a long period of appreciation since its major bottom in 1933! But as I showed you earlier in this book, those two trends are over. Demographics tells us that there will be more sellers than buyers into 2039, hence net demand for houses will continue to slow and real estate “will never be the same.” Here’s a comparison of other residential bubbles around the developed world, as seen through my model. The downside projections would startle most people, even when I allow for only an 85% decline back towards the Origin Point. While typically only stocks go all the way back to that starting point, a 100% decline in real estate is possible… but it’s just the worst case scenario. Figure 21-7 : Real Estate Bubbles in Developed Countries
Bubble
Start
Bubble Duration
Times Gain
Bubble Intensity
Crash Duration
Crash Severity
Japan, 1991
1978
13 Years
4.9
0.38
13 Years
-70%
London, 2016
1999
17.25 Years
4.0
0.23
Vancouver, 2016
2002
14.2 Years
2.9
0.21
Sydney, 2016
2000
14.75 Years
2.8
0.19
Shanghai, 2016
2001
15.5 Years
8.0
0.52
Mumbai, 2016
2009
6.25 Years
2.1
0.33
*Est. = Estimated by Model
17.25 Years -64% (Est.)* 14.2 Years -55% (Est.) 14.75 Years -55% (Est.) 15.5 Years -77% (Est.) 6.25 Years -44% (Est.)
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Japan’s housing bubble roared to life way back in mid-1978, as its baby boom peak in 1949 came 12 years before it did in North America and 15 years before Europe. It rose an astounding 4.9-times in 13 years, with a bubble intensity of 0.38. That’s high for real estate, which typically doesn’t climb as fast as stocks do. Then it collapsed, right on schedule, into mid-2004… and it has never recovered. Nor will it, considering the country faces more dyers than buyers into 2033. Again, the actual crash was 70% while my model forecast losses of about 68%! As for London, the richest people there are convinced that property in that city could never go down… because it’s a “special place.” It may have some unique attributes and definitely limited space, but history shows that those “special places” always bubble the most and then crash the worst. London’s bubble started around early 1999, just ahead of the U.S. It went up 4-times but over 17.25 years. That’s the longest I’ve seen. The more typical real estate bubble grows anywhere between six and 10 years. Because of how long it’s taken the London property bubble to build, it’s intensity is 0.23, much less than Japan’s. According to my model, the projected crash would be 64%, taking prices back to within 15% of the Origin. And that decline could last well into 2033, although I think we may see the bottom sooner than that. Remember that Europe overall has declining demographics and London may not continue to be the clear major financial center after Brexit and the ultimate dissipation and restructuring of the Eurozone and euro. Since Vancouver is “so special,” it has bubbled big time. The typical, crappy little home now goes for $1.2 million! Vancouver’s Bubble Origin was around late 2002. It’s seen a 2.9-times gain into 2016 and a bubble intensity of 0.21. That doesn’t
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sound so high, but consider that the home prices in the city were already very expensive before the bubble began to inflate. As I predicted they would, Vancouver copied Singapore and slapped a major tax on foreign buyers in August 2016. This move will destroy their bubble and it was down 24% just in the first five months. My model projects a collapse of as much as 55% into mid2031, if not sooner. Then there’s my favorite city in the developed world: Sydney. You don’t know how unpopular I am to many there given my forecasts. No one thinks Australian real estate can ever go down because it’s a large desert with a few wonderful cities and great weather. People there are always telling me: “Harry, you don’t understand Australian real estate.” My reply is always: “I lived in California for 22 years. I saw THAT bubble build and burst… and Australia is exactly like California… except with better long-term demographics.” Sydney’s real estate boom started around early 2000 and lasted 14.75 years. It’s had an intensity of only 0.21. But like California, Vancouver and Tokyo, it was already expensive before the bubble began. At this point, it’s downright unaffordable except to foreign buyers (who are largely laundering their money out of China). My model projects a loss of 55% in Sydney by 2033. Demographics may soften that decline a little. As I said earlier in this book, if I had to own real estate in a first-class city and sit out the greatest financial crisis since the early 1930s, it would be in Sydney. The bubble in Melbourne is even greater, and the bubbles in Brisbane, Perth and Adelaide are a little less so. But all of Australia is in for a rough ride, despite its better demographic trends. Its government debt may be the lowest in the developed world, but its
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banks’ and households’ exposure to high real estate costs are among the highest. Before moving on to look at the double property bubble in the U.S., let’s consider the two more prominent emerging-world cities, starting with Shanghai... Its Bubble Origin was around early 2001, and it has seen a whopping 8.0-times gain in 15.5 years. A long bubble with a high intensity at 0.52, it’s greater than Japan’s bubble. My model projects a crash of 77% into late 2021. And finally, India. The Asian Tiger has some of the most favorable demographic trends into 2060-plus, and has much urbanization to exploit for decades. But, it too faces a real estate bubble burst. Mumbai’s property bubble only started around early 2010 and has advanced 2.1-times over the last 6.25 years. The intensity is a bit less than China’s, but it’s still a decent 0.33. Here, my model projects a crash of 44% into mid-2023. After that, India is an ideal place to invest in because it faces the boom of the century ahead (more about this in Chapter 24)!
Double Trouble in the U.S. Just as stocks saw an unprecedented three major bubbles before peaking between 2015 and 2016, real estate from the U.S. to Spain, to Ireland to Singapore, to the United Arab Emirates have seen two bubbles. That makes the analysis a bit different. I took three cities from around the world and broke them into Bubble #1 and Bubble #2. The range of downsides is more varied because there are two scenarios here. The first one is that the second and final bubble burst takes them back to the bottom of the first bubble. The second one is that these cities go to within 15% of the first Bubble Origin.
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I use a chart of the twin San Francisco bubbles to illustrate… Figure 21-8 : Double Bubble in San Francisco
Bubble #1
230
3.0 Times Gain
Bubble #2
1.8 Times Gain Bubble Intensity = 0.42 1.8 Times Gain / 4.25 Duration
210 190
Bubble Intenstiy= 0.34 3.0 Times Gain / 8.75
100=2000
170 150 130 110
-47% Best Case
-45% Actual -57% Forecast
-58% Forecast
90 70
5.75 Years
4.25 Years
4.25 Years
1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
50
8.75 Years Bubble Origin
Source: St. Louis Federal Reserve, S&P/Case-Shiller, Dent Research
Just like in Vancouver, you don’t want to have to buy a condo in downtown San Francisco at 2016 prices! The city’s first Bubble Origin was in mid-1997. It saw a bubble into early 2006 that lasted 8.75 years with a 3-times gain for an intensity of 0.35. The crash was faster than usual, losing 45% in just 5.75 years compared to my model’s projected losses of 56%. The second bubble started in early 2009 and went up 1.8-times into early 2016 – reaching substantial new highs. That lasted 4.25 years, with an intensity a bit higher at 0.42. The best-case projection here is that this latest bubble sheds 47% by around late 2020. The more likely scenario is that it will lose as much as 58%, going within 15% of its 1997 Bubble Origin. I show two other double bubbles to compare to San Francisco in the table below.
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Figure 21-9 : Table of Stock Bubbles Past and Present
Bubble
Start
Bubble Duration
Times Gain
Bubble Intensity
Crash Duration
Crash Severity
San Francisco, Bubble #1, 2006 San Francisco, Bubble #2, 2016 Singapore, Bubble #1, 1996 Singapore, Bubble #2, 2013 Dubai, Bubble #1, 2008 Dubai, Bubble #2, 2014
1997
8.75 Years
3.0
0.34
5.75 Years
-45%
2012
4.25 Years
1.8
0.42
4.25 Years
-47% to -58% (Est.)*
2.7
0.70
2.5 Years
-48%
1992
3.75 Years
2009
4.25 Years
1.9
0.40
4.25 Years
-47% to -50% (Est.)*
2008
2.25 Years
2.1
0.94
2.75 Years
-35%
2014
3.75 Years
1.7
0.46
3.75 Years
-42% to -49% (Est.)*
*Est. = Estimated by Model
Singapore has one of the highest per-capita incomes in the developed world and is unique in that the country is just one large city. It has no rural areas. It’s 100% urban! Its government was the first to slap a heavy surcharge of 26% on foreign buyers, with an additional 12% to 16% if they flip in one to two years. Ouch! Not surprisingly, since then, prices have fallen 22% from their highs. Singapore’s first real estate bubble started way back in late 1992 and saw a 2.7-times gain with a high intensity of 0.70 over a brief 3.75 years. The crash lost 48% in just 2.5 years. That is exactly as my model forecast. Bubble #2 then went up 1.8-times into late 2013. My crash forecast is that, at best, Singapore property prices will lose 47% into late 2017 or so. More likely, though, is loses closer to 50% (bringing it within 15% of the original 1997 starting point). The worst-case scenario is that Singapore real estate could go down 59% to its first bubble low. Then there’s Dubai, which I was fortunate to visit right near its peak in late 2007. No one in the large and global audience there could see real estate going down. Except me. It’s first bubble was really brief, from early 2006 into early 2008 (just 2.25 years) at a strong intensity of 0.94. The fall was -35% into
The Sale of a Lifetime
early 2011. My model projected losses as high as 45%. The second bubble went up 1.7-times into late 2014, over 3.75 years, with a lower intensity of 0.46. The best-case projection here is that Dubai real estate will see losses up to 42% by mid-2018… it may go even lower, to 49% to reach 15% from the first Bubble Origin. Strong demographics in Dubai and Singapore should cushion their downside risk. But oil is the wild card for Dubai. It has already seen the bulk of its potential decline, but given that we could see oil going at low as $10 to $20 a barrel, Dubai real estate could go back down 59% to its first Bubble Origin.
Commodity Bubbles: The Drama Queens Commodities have more extreme bubbles and crashes. They collapse faster during the initial burst. They are more likely to bottom at the Origin Point or lower. And there is more variation between different sectors, making an apples-to-apples comparison essential. Because of this, commodity bubbles are perhaps hardest to predict – that’s why the best traders are commodity traders! Look at the broader commodity bubble in the chart below.
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Figure 21-10 : Global Commodities Bubble, CRB Index
500
3.1 Times Gain
450 Bubble Intensity = 0.48 3.1 Times Gain / 6.4 Duration
400
350
300
250
200
First Crash 58%
6.4 Years
150
100 1994
7.6 Years -67% Back to Origin
Bubble Origin
1996
1998
2000
2002
2004
2006
2008
2010
2012
2014
or 74%
2016
2018
Source: Bloomberg, Dent Research
CRB is the most basic commodities index. Just look at the bubble from around late 2003 into early 2008! Over 6.4 years, it went up 3.1-times with an intensity of 0.48. And look at that first dramatic burst! The index lost 58% and in just eight months, from March 2008 to November 2008. That’s just 12% of the time it took the bubble to build! The low thus far has already been -67%, and should be lower still into at least early 2018. I’m talking down a total of 74% or more. Commodities were among the first to crash in this global bubble environment, and they’ll likely be the first to bottom as well. Oil’s bubble and crash was the most extreme of the lot, going from $32 in late 2014 to $147 in mid-2008 (just 3.6 years) and then crashing back down to $32 in just 4.5 months. I have never seen a bubble crash that hard and fast! Oil advanced 5.4-times in a short period, so its Bubble Intensity was 1.13 – very high. Then it crashed 79% in just 4.5 months. That’s the fastest and greatest bubble burst I have ever seen!
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Oil is likely to bottom somewhere between $8 and $20 by late 2017 (maybe a little later). That will mean as much as a 95% decline from its peak in mid-2008. However, typical commodity bubbles are more like real estate bubbles and tend to take about the same time to reach their ultimate bottom as it took the bubble to build. I summarize some of the other key bubbles in the table below. Figure 21-11 : Commodity Bubbles: Past and Present
Bubble
Start
Bubble Duration
CRB, 2008
2002
6.4 Years
Copper, 2011
2003
Oil, 2008
2003
Gold, 2011 Iron Ore, 2011 Corn, 2012
Times Gain
Bubble Intensity
Crash Duration
Crash Severity
3.1
0.48
7.6 Years
-67% Actual or -74% (Est.)*
7.75 Years
4.6
0.59
7.75 Years
-84% (Est.)
4.8 Years
5.4
1.13
7.6 Years
-82% Actual or -88% (Est.)
2005
6.25 Years
3.5
0.56
6.25 Years
-78% (Est.)
2007
3.25 Years
4.1
1.26
4.5 Years or 7.9 Years
-76% Actual or -88% (Est.)
2006
6 Years
3.3
0.55
6 Years
-70% (Est.)
*Est. = Estimated by Model
Copper is the more typical industrial metal that follows the economy because it goes into so many different products. Its Bubble Origin was in mid-2003 and it peaked in early 2011, with a 4.6-times gain and an intensity of 0.59 over 7.75 years. Its My model projects copper’s crash will continue into around late 2019/early 2020, ultimately losing as much as 84% from its peak. It has seen a loss of 43% recently, so it has a lot farther to go before this one’s over… more than many other industrial or energy-related commodities. Then we come to one of the areas of greatest interest: gold. Firstly, gold is, at its core, a commodity. The greatest consumers are the two countries with the largest population, China and India!
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Secondly, gold has been in a bubble like all other commodities. The last time gold bubbled was into 1980, along with the broader commodity sector. Thirdly, gold correlates most with inflation, as commodities in general do. It is NOT a safe place to be during deflationary times, which we face ahead (as I’ve already explained). Gold’s latest bubble started around mid-2005, when the yellow metal was close to $400 (its ultimate low was at $250 back in 2001). From 2005 though, it went up 3.5-times over 6.25 years into late 2011, giving it a Bubble Intensity of 0.56. (From the 2001 low, it went up 7.7-times.) Either way folks, that’s a bubble! Gold has already been down 46% in early 2016, despite the greatest money-printing spree in history. The most likely bottom target, according to my model – taking the metal back to its Origin – would be $400 by early 2018. That would represent a 79% crash from its September 2011 high. The commodity bubble with the most extreme Bubble Intensity and most persistent crash is iron ore. That bubble started in late 2007 and exploded into early 2011, with a higher intensity than oil at a whopping 1.26. That was a 3.25-times gain in just 4.5 years, So, of course there would be a big crash. It’s already lost as much as 76% by early 2016. It could lose as much as 88% by early 2018 or so, when all is said and done. And finally, corn. I keep hearing people say that the one thing people can’t stop doing in a downturn is eating, so there’s little downside in agricultural commodities. Well, tell that to corn prices! In six years, corn bubbled up 3.3-times into late 2012 and has crashed 63% already. It’s likely headed lower, down a total of 70%plus in the years ahead, especially with sunspot cycles suggesting a bout of cooling into late 2019/early 2020.
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And that’s a big reason that farmland in Iowa has started to crack, although not as much as you would think given such a sharp fall in corn prices. I get a lot of questions about whether farmland is in a bubble or not. The answer unfortunately is that it is! I chose to illustrate this point using Iowa farmland instead of other states like Illinois or Indiana, or Ohio, because Iowa is more rural. It has fewer large, sprawling cities. Farmland prices are still edging up in those other states due to suburban sprawl. But farmland in Iowa peaked in late 2012/early 2013, more in-line with their largest crop, which is corn. Figure 21-12 : Iowa Farmland Bubble, 2013
$10,000 3.8 Times Gain
Bubble Intensity = 0.38 3.8 Times Gain / 10 Duration
$9,000 $8,000
-63%
Price per Acre
$7,000 $6,000 $5,000 $4,000 $3,000 10 Years
$2,000
85% Back to Origin
10 Years
Bubble Origin
2023
2022
2021
2020
2019
2018
2017
2016
2015
2014
2013
2011
2012
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
$1,000
Source: Farmland Value Survey Lowa State University, Dent Research
Between early 2003 and early 2013, the state’s farmland went up 3.8-times, giving the bubble an intensity of 0.38 (not an extreme bubble). But my model projects that it could deflate 63% by early 2023… right when I see the next global boom emerging and commodity prices rising sharply again on my 30-Year Commodity Cycle. This means other Midwestern states and farm areas have even
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more downside since their prices are still going up due to suburban sprawl that is not as prevalent.
And So… I hope at this point I’ve shown you that major stock bubbles tend to come every 60 to 80 years, in-line with the average human lifetime. Commodity bubbles rise into the high point of the 29- to 30-Year Commodity Cycle. And real estate bubbles come on the 80year generation and economic cycle, but real estate also has its own 18-year cycle. We are in the twilight of the greatest and most pervasive bubble in modern history. Commodities burst first, and then real estate in selective areas follow suit. This third major bubble in stocks globally is last, and it’s set to burst by early 2017 at the latest with a global real estate crash this time around led by China. This is the time to understand bubbles – how they build, how they crash – because there’s no time in your life when they’ll affect you more… and if you’re ready, you can make a fortune in a matter of years by buying financial assets at the lowest prices you will see in your lifetime. So let's move on to that...
