Didier Sornette: How we can predict the next financial crisis

157,980 views ใƒป 2013-06-17

TED


์•„๋ž˜ ์˜๋ฌธ์ž๋ง‰์„ ๋”๋ธ”ํด๋ฆญํ•˜์‹œ๋ฉด ์˜์ƒ์ด ์žฌ์ƒ๋ฉ๋‹ˆ๋‹ค.

00:00
Translator: Joseph Geni Reviewer: Morton Bast
0
0
7000
๋ฒˆ์—ญ: K Bang ๊ฒ€ํ† : ๋ฏผ์„ ์ตœ
00:12
Once upon a time
1
12818
1510
ํ•œ๋•Œ ์šฐ๋ฆฌ๋Š” ์žฌ์ •์ ์œผ๋กœ ์„ฑ์žฅํ•˜๋Š”
00:14
we lived in an economy of financial growth and prosperity.
2
14328
6651
ํ’์š”๋กœ์šด ๊ฒฝ์ œ ์•ˆ์—์„œ ์‚ด์•˜์Šต๋‹ˆ๋‹ค.
00:20
This was called the Great Moderation,
3
20979
3695
์ด ์‹œ๊ธฐ๋ฅผ ๋Œ€์•ˆ์ •๊ธฐ๋ผ๊ณ  ํ•ฉ๋‹ˆ๋‹ค.
00:24
the misguided belief by most economists,
4
24674
3406
๋Œ€๋‹ค์ˆ˜์˜ ๊ฒฝ์ œํ•™์ž, ์ •์ฑ… ์ž…์•ˆ์ž, ๊ทธ๋ฆฌ๊ณ  ์ค‘์•™ ์€ํ–‰๋“ค์ด
00:28
policymakers and central banks
5
28080
3303
๋์—†๋Š” ์„ฑ์žฅ๊ณผ ํ’์š”์˜ ์ƒˆ๋กœ์šด ์„ธ์ƒ์œผ๋กœ ๋“ค์–ด์„ฐ๋‹ค๊ณ 
00:31
that we have transformed into a new world
6
31383
3331
์ž˜๋ชป ํŒ๋‹จํ•œ
00:34
of never-ending growth and prosperity.
7
34714
3857
๋ฏฟ์Œ์ด์—ˆ์Šต๋‹ˆ๋‹ค.
00:38
This was seen by robust and steady GDP growth,
8
38571
4743
GDP ์„ฑ์žฅ์€ ๊ฐ•๊ฑดํ•˜๊ณ  ๊พธ์ค€ํ–ˆ๊ณ ,
00:43
by low and controlled inflation,
9
43314
3000
์ธํ”Œ๋ ˆ์ด์…˜๋„ ๋‚ฎ๊ณ  ํ†ต์ œ๋„ ๋˜์—ˆ์œผ๋ฉฐ,
00:46
by low unemployment,
10
46314
2239
์‹ค์—…์œจ๋„ ๋‚ฎ์•˜๊ณ ,
00:48
and controlled and low financial volatility.
11
48553
3906
์žฌ์ •์ ์ธ ๋ถˆ์•ˆ์ •์„ฑ๋„ ๋‚ฎ๊ณ  ํ†ต์ œ๋˜๊ณ  ์žˆ๋Š” ๊ฒƒ์ฒ˜๋Ÿผ ๋ณด์˜€์Šต๋‹ˆ๋‹ค.
00:52
But the Great Recession in 2007 and 2008,
12
52459
6632
ํ•˜์ง€๋งŒ 2007๋…„๊ณผ 2008๋…„์˜ ๋Œ€์นจ์ฒด๊ธฐ,
00:59
the great crash, broke this illusion.
13
59091
3479
๋Œ€๋ชฐ๋ฝ์ด ์ด๋Ÿฐ ํ™˜์ƒ์„ ๊นจ๋ถ€์ˆ˜์—ˆ์Šต๋‹ˆ๋‹ค.
01:02
A few hundred billion dollars of losses in the financial sector
14
62570
5024
๊ธˆ์œต ๋ถ€๋ฌธ์—์„œ์˜ ๋ช‡ ์ฒœ์–ต ๋‹ฌ๋Ÿฌ์˜ ์†์‹ค์ด
01:07
cascaded into five trillion dollars
15
67594
4080
์—ฐ์‡„์ ์œผ๋กœ ์„ธ๊ณ„ GDP๋ฅผ 5์กฐ ๋‹ฌ๋Ÿฌ ๊ฐ€๋Ÿ‰
01:11
of losses in world GDP
16
71674
1884
๋‚ฎ์ถ”๋Š” ๊ฒฐ๊ณผ๋ฅผ ๋‚ณ์•˜๊ณ ,
01:13
and almost $30 trillion losses
17
73558
3803
์„ธ๊ณ„ ์ฆ๊ถŒ ์‹œ์žฅ์€
01:17
in the global stock market.
18
77361
3945
๊ฑฐ์˜ 30์กฐ ๋‹ฌ๋Ÿฌ์˜ ์†์‹ค์„ ์ž…์—ˆ์Šต๋‹ˆ๋‹ค.
01:21
So the understanding of this Great Recession
19
81306
5195
๊ทธ๋ž˜์„œ ์ด ๋Œ€์นจ์ฒด๊ธฐ๋ฅผ ์™„์ „ํžˆ
01:26
was that this was completely surprising,
20
86501
5361
๋œฌ๊ธˆ ์—†๋Š” ๊ฒƒ์œผ๋กœ ์ƒ๊ฐํ–ˆ์Šต๋‹ˆ๋‹ค.
01:31
this came out of the blue,
21
91862
1346
์ด๋Š” ์•„๋‹Œ ๋ฐค ์ค‘์— ํ™๋‘๊นจ ๊ฒฉ์ด์—ˆ๊ณ ,
01:33
this was like the wrath of the gods.
22
93208
2917
๋งˆ์น˜ ์‹ ์˜ ๋ถ„๋…ธ์™€๋„ ๊ฐ™์•˜์ฃ .
01:36
There was no responsibility.
23
96125
1791
์ฑ…์ž„์„ ๋ฌผ์„ ์ˆ˜๊ฐ€ ์—†์—ˆ์Šต๋‹ˆ๋‹ค.
01:37
So, as a reflection of this,
24
97916
1923
๊ทธ๋ž˜์„œ ์ด์— ๋Œ€ํ•œ ์ˆ™๊ณ  ๋์— ์ €ํฌ๋Š”
01:39
we started the Financial Crisis Observatory.
25
99839
3609
์žฌ์ • ์œ„๊ธฐ ๊ด€๋ฆฌ์†Œ(Financial Crisis Observatory)๋ฅผ ์ถœ๋ฒ”์‹œํ‚ค๊ฒŒ ๋˜์—ˆ์Šต๋‹ˆ๋‹ค.
01:43
We had the goal to diagnose in real time
26
103448
3938
์ €ํฌ๋Š” ์žฌ์ •์ ์ธ ๊ฑฐํ’ˆ์„
01:47
financial bubbles
27
107386
2371
์‹ค์‹œ๊ฐ„์œผ๋กœ ์ง„๋‹จํ•˜๊ณ 
01:49
and identify in advance their critical time.
28
109757
5857
์ •ํ™•ํ•œ ์œ„๊ธฐ ๋ฐœ์ƒ ์‹œ๊ธฐ๋ฅผ ๋ฏธ๋ฆฌ ํŒŒ์•…ํ•˜๋Š” ๊ฒƒ์„ ๋ชฉํ‘œ๋กœ ์‚ผ์•˜์Šต๋‹ˆ๋‹ค.
01:55
What is the underpinning, scientifically, of this financial observatory?
29
115614
3358
๊ทธ๋ ‡๋‹ค๋ฉด ์ด ์žฌ์ • ๊ด€์ธก์†Œ์˜ ๊ณผํ•™์ ์ธ ๊ทผ๊ฑฐ๋Š” ๋ฌด์—‡์ผ๊นŒ์š”?
01:58
We developed a theory called "dragon-kings."
30
118972
4626
์ €ํฌ๋Š” "์šฉ์™•(dragon-king)"์ด๋ผ๋Š” ์ด๋ก ์„ ๊ฐœ๋ฐœํ–ˆ์Šต๋‹ˆ๋‹ค.
02:03
Dragon-kings represent extreme events
31
123598
3206
์šฉ์™•์ด๋ž€ ๋„˜์„ ์ˆ˜ ์—†๋Š”
02:06
which are of a class of their own.
32
126804
3272
๊ทน๋‹จ์ ์ธ ์‚ฌ๊ฑด์„ ํ‘œํ˜„ํ•ฉ๋‹ˆ๋‹ค.
02:10
They are special. They are outliers.
33
130076
2843
ํŠน๋ณ„ํ•˜๊ณ  ์˜ˆ์™ธ์ ์ธ ์‚ฌ๊ฑด ๊ฐ™์€ ๊ฒƒ์ด์ฃ .
02:12
They are generated by specific mechanisms
34
132919
3440
์ด๋Ÿฐ ์œ„๊ธฐ๋Š” ์ด๋Ÿฐ ์‚ฌ๊ฑด๋“ค์„ ์˜ˆ์ธก ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•  ์ˆ˜๋„ ์žˆ๊ณ ,
02:16
that may make them predictable,
35
136359
2886
์–ด์ฉŒ๋ฉด ํ†ต์ œํ•  ์ˆ˜ ์žˆ๋„๋ก ๋งŒ๋“œ๋Š”
02:19
perhaps controllable.
36
139245
2898
ํŠน์ • ๋ฉ”์ปค๋‹ˆ์ฆ˜์— ์˜ํ•ด ์ƒ๊ฒจ๋‚ฉ๋‹ˆ๋‹ค.
02:22
Consider the financial price time series,
37
142143
3827
์ฃผ์–ด์ง„ ์ฃผ์‹, ์ฆ‰ ์—ฌ๋Ÿฌ๋ถ„์˜ ์™„๋ฒฝํ•œ ์ฃผ์‹,
02:25
a given stock, your perfect stock,
38
145970
2173
๋˜๋Š” ์„ธ๊ณ„ ์ง€ํ‘œ์™€ ๊ฐ™์€
02:28
or a global index.
39
148143
2352
์žฌ๋ฌด ๊ฐ€๊ฒฉ์˜ ์‹œ๊ณ„์—ด์„ ํ•œ ๋ฒˆ ์ƒ๊ฐํ•ด๋ณด์„ธ์š”.
02:30
You have these up-and-downs.
40
150495
2054
์ด๋ ‡๊ฒŒ ์ƒ์Šนํ•  ๋•Œ๋„, ํ•˜๋ฝํ•  ๋•Œ๋„ ์žˆ์Šต๋‹ˆ๋‹ค.
02:32
A very good measure of the risk of this financial market
41
152549
3562
์ด๋Ÿฐ ๊ธˆ์œต ์‹œ์žฅ์˜ ์œ„ํ—˜์— ๋Œ€ํ•œ ์•„์ฃผ ์ข‹์€ ์ธก์ • ๋„๊ตฌ๋Š”
02:36
is the peaks-to-valleys that represent
42
156111
2422
์ตœ๊ณ ์ ์—์„œ ์‚ฌ์„œ ์ตœ์ €์ ์—์„œ ํŒŒ๋Š”,
02:38
a worst case scenario
43
158533
2296
์ตœ์•…์˜ ์‹œ๋‚˜๋ฆฌ์˜ค๋กœ ๋Œ€๋ณ€๋˜๋Š”
02:40
when you bought at the top and sold at the bottom.
44
160829
3673
ํ”ผํฌํˆฌ๋ฐธ๋ฆฌ(peaks-to-valleys)์ž…๋‹ˆ๋‹ค.
02:44
You can look at the statistics, the frequency of the occurrence
45
164502
3749
๋‹ค๋ฅธ ํฌ๊ธฐ์˜ ํ”ผํฌํˆฌ๋ฐธ๋ฆฌ์˜ ๋ฐœ์ƒ ๋นˆ๋„์™€ ๊ฐ™์€
02:48
of peak-to-valleys of different sizes,
46
168251
2355
ํ†ต๊ณ„๊ฐ’๋ฅผ ์‚ดํŽด๋ณด์‹ค ์ˆ˜๋„ ์žˆ์Šต๋‹ˆ๋‹ค.
02:50
which is represented in this graph.
47
170606
2551
์ด ๊ทธ๋ž˜ํ”„์— ๋‚˜์™€ ์žˆ์ฃ .
02:53
Now, interestingly, 99 percent
48
173157
3032
์ž, ํฅ๋ฏธ๋กญ๊ฒŒ๋„ ์—ฌ๋Ÿฌ ๋‹ค๋ฅธ ํญ์„ ๊ฐ–๋Š” ํ”ผํฌํˆฌ๋ฒจ๋ฆฌ์˜ 99%๋Š”
02:56
of the peak-to-valleys of different amplitudes
49
176189
3793
์—ฌ๊ธฐ ์ด ๋ถ‰์€ ์„ ์œผ๋กœ ๋Œ€ํ‘œ๋˜๋Š”
02:59
can be represented by a universal power law
50
179982
3460
๋ณดํŽธ์ ์ธ ํž˜์˜ ๋ฒ•์น™์œผ๋กœ
03:03
represented by this red line here.
51
183442
3451
์„ค๋ช…๋  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
03:06
More interestingly, there are outliers, there are exceptions
52
186893
4146
๋” ํฅ๋ฏธ๋กœ์šด ์‚ฌ์‹ค์€ ์ž๋ฃŒ ๋ฒ”์œ„๋ฅผ ๋ฒ—์–ด๋‚œ ์ด์ƒ์น˜๋“ค์ด ์กด์žฌํ•œ๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.
03:11
which are above this red line,
53
191039
1903
์ด ๋ถ‰์€ ์„  ์œ—์ชฝ์œผ๋กœ ๋‚˜๋จธ์ง€ 99% ํ”ผํฌํˆฌ๋ฒจ๋ฆฌ์˜ ์กฐ์ •์— ๊ธฐ๋ฐ˜ํ•˜์—ฌ
03:12
occur 100 times more frequently, at least,
54
192942
3759
์˜ˆ์ธกํ–ˆ์„ ๋•Œ ๋ฐœ์ƒ๋  ๊ฒƒ์ด๋ผ๊ณ 
03:16
than the extrapolation would predict them to occur
55
196701
4153
๊ธฐ๋Œ€ํ•œ ๊ฒƒ๋ณด๋‹ค ์ตœ์†Œํ•œ 100๋ฐฐ๋Š”
03:20
based on the calibration of the 99 percent remaining
56
200854
3937
๋” ๋นˆ๋ฒˆํ•˜๊ฒŒ ์ผ์–ด๋‚˜๋Š”
03:24
peak-to-valleys.
57
204791
2249
์˜ˆ์™ธ๋“ค์ด ์กด์žฌํ•œ๋‹ค๋Š” ๋ง์ด์ฃ .
03:27
They are due to trenchant dependancies
58
207040
4600
์ด๋Ÿฌํ•œ ์˜ˆ์™ธ๋“ค์€ ์†์‹ค ๋’ค์— ์†์‹ค์ด ์ฐพ์•„์˜ค๊ณ ,
03:31
such that a loss is followed by a loss
59
211640
3512
๋˜ ์†์‹ค์ด ์ฐพ์•„์˜ค๊ณ , ๋‹ค์‹œ ์ฐพ์•„์˜ค๋Š” ๊ฒƒ๊ณผ ๊ฐ™์€
03:35
which is followed by a loss which is followed by a loss.
60
215152
2963
๊ฐ•๋ ฅํ•œ ์ข…์†์„ฑ์— ์˜ํ•œ ๊ฒƒ์ž…๋‹ˆ๋‹ค.
03:38
These kinds of dependencies
61
218115
3111
ํ‘œ์ค€ ์œ„ํ—˜ ๊ด€๋ฆฌ ๋„๊ตฌ๋“ค์ด ์ด๋Ÿฐ ๋ฅ˜์˜ ์ข…์†์„ฑ์„ ๋†“์นœ ๊ฒƒ์ด์ฃ .
03:41
are largely missed by standard risk management tools,
62
221226
5612
์šฉ์™•์„ ๋ณด์•„์•ผ ํ•˜๋Š” ์ƒํ™ฉ์—์„œ
03:46
which ignore them and see lizards
63
226838
2929
์šฉ์™•์€ ๋ฌด์‹œํ•˜๊ณ  ๋„๋งˆ๋ฑ€์„ ๋ณธ ๊ฒฉ์ž…๋‹ˆ๋‹ค.
03:49
when they should see dragon-kings.
64
229767
3819
์šฉ์™•์˜ ํ•ต์‹ฌ์ ์ธ ๋ฉ”์ปค๋‹ˆ์ฆ˜์€
03:53
The root mechanism of a dragon-king
65
233586
3917
๊ฑฐํ’ˆ์ด๋ผ๋Š” ๋ถˆ์•ˆ์ •์„ฑ์„ ํ–ฅํ•ด
03:57
is a slow maturation towards instability,
66
237503
3136
๋Š๋ฆฌ๊ฒŒ ๋ฌด๋ฅด์ต์–ด ๊ฐ€๋Š” ๊ฒƒ์ด์—ˆ๊ณ ,
04:00
which is the bubble,
67
240639
1622
๊ทธ๋Ÿฌํ•œ ๊ฑฐํ’ˆ์˜ ์ •์ ์—๋Š”
04:02
and the climax of the bubble is often the crash.
68
242261
2630
์ข…์ข… ์œ„๊ธฐ๊ฐ€ ์žˆ์—ˆ์Šต๋‹ˆ๋‹ค.
04:04
This is similar to the slow heating of water
69
244891
3625
์ด๋Ÿฌํ•œ ํ˜„์ƒ์€ ์‹œํ—˜๊ด€์—์„œ ๋“๋Š”์ ์„ ํ–ฅํ•ด
04:08
in this test tube reaching the boiling point,
70
248516
2903
์ฒœ์ฒœํžˆ ์˜จ๋„๊ฐ€ ์˜ฌ๋ผ๊ฐ€๋Š” ๋ฌผ๊ณผ ๊ฐ™์Šต๋‹ˆ๋‹ค.
04:11
where the instability of the water occurs
71
251419
2490
๋ฌผ์˜ ๋ถˆ์•ˆ์ •์„ฑ์ด ๋ฐœ์ƒ๋˜๋Š” ์ง€์ ์—์„œ
04:13
and you have the phase transition to vapor.
72
253909
3337
์ฆ๋ฐœ์ด๋ผ๋Š” ๋‹จ๊ณ„๋กœ ์ „ํ™˜์ด ์ผ์–ด๋‚˜์ฃ .
04:17
And this process, which is absolutely non-linear --
73
257246
3677
๊ทธ๋ฆฌ๊ณ  ํ‘œ์ค€ ๊ธฐ์ˆ ๋กœ ์˜ˆ์ธกํ•  ์ˆ˜ ์—†๋Š”,
04:20
cannot be predicted by standard techniques --
74
260923
2280
์™„์ „ํžˆ ๋น„์„ ํ˜•์ ์ธ ์ด ๊ณผ์ •์€
04:23
is the reflection of a collective emergent behavior
75
263203
4176
๊ทผ๋ณธ์ ์œผ๋กœ ๋‚ด๋ถ€์— ๊ธฐ์ธํ•˜๊ณ  ์žˆ๋Š”
04:27
which is fundamentally endogenous.
76
267379
2379
์ง‘๋‹จ์ ์ธ ๋Œ๋ฐœ ํ–‰๋™์ด ๋ฐ˜์˜๋œ ๊ฒƒ์ž…๋‹ˆ๋‹ค.
04:29
So the cause of the crash, the cause of the crisis
77
269758
3213
๋”ฐ๋ผ์„œ ์ด๋Ÿฐ ๋ชฐ๋ฝ, ๋˜๋Š” ์œ„๊ธฐ์˜ ์›์ธ์€
04:32
has to be found in an inner instability of the system,
78
272971
3184
์ฒด๊ณ„ ์ž์ฒด์˜ ๋‚ด๋ถ€์  ๋ถˆ์•ˆ์ •์„ฑ์—์„œ ์ฐพ์•„์•ผ๋งŒ ํ•ฉ๋‹ˆ๋‹ค.
04:36
and any tiny perturbation will make this instability occur.
79
276155
6036
๊ทธ๋ฆฌ๊ณ  ์•„์ฃผ ์ž‘์€ ๋ถˆ์•ˆ ์š”์†Œ๊ฐ€ ์ด๋Ÿฐ ๋ถˆ์•ˆ์ •ํ•œ ์ƒํ™ฉ์„ ์•ผ๊ธฐํ•˜๊ณค ํ•ฉ๋‹ˆ๋‹ค.
04:42
Now, some of you may have come to the mind
80
282191
3700
์ž, ์•„๋งˆ ๋ช‡๋ช‡ ๋ถ„๋“ค๊ป˜์„œ๋Š” ์ด๊ฒƒ์ด ์ž์ฃผ ๋“ค์–ด๋ณด์…จ๋˜
04:45
that is this not related to the black swan concept
81
285891
2625
๊ฒ€์€ ๋ฐฑ์กฐ(black swan)๋ผ๋Š” ๊ฐœ๋…๊ณผ๋Š”
04:48
you have heard about frequently?
82
288516
2935
ํ•˜๋“ฑ์˜ ๊ด€๋ จ์ด ์—†๋‹ค๋Š” ์ƒ๊ฐ์ด ๋“œ์…จ์„๊ฑฐ์—์š”.
04:51
Remember, black swan is this rare bird
83
291451
2417
๋ช…์‹ฌํ•˜์„ธ์š”, ๊ฒ€์€ ๋ฐฑ์กฐ๋ผ๋Š” ์ƒˆ๋Š”
04:53
that you see once and suddenly shattered your belief
84
293868
3409
ํ•œ ๋ฒˆ ๋ดค์„ ๋•Œ, ๋ชจ๋“  ๋ฐฑ์กฐ๋Š” ํ•˜์–—๋‹ค๋Š”
04:57
that all swans should be white,
85
297277
2474
์—ฌ๋Ÿฌ๋ถ„์˜ ๋ฏฟ์Œ์„ ์‚ฐ์‚ฐ์กฐ๊ฐ ๋‚ด๋Š” ํฌ๊ท€ํ•œ ์ƒˆ์ž…๋‹ˆ๋‹ค.
04:59
so it has captured the idea of unpredictability,
86
299751
3544
์ฆ‰, ๊ทน๋‹จ์ ์ธ ํ˜„์ƒ์€ ๊ธฐ๋ณธ์ ์œผ๋กœ ์•Œ ์ˆ˜ ์—†๋‹ค๋Š”
05:03
unknowability, that the extreme events
87
303295
1509
์˜ˆ์ธก ๋ถˆ๊ฐ€๋Šฅ์„ฑ, ์ธ์ง€ ๋ถˆ๊ฐ€๋Šฅ์„ฑ์˜
05:04
are fundamentally unknowable.
88
304804
2831
๊ฐœ๋…์„ ํ’ˆ๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
05:07
Nothing can be further
89
307635
1725
๋Œ€๋‹ค์ˆ˜์˜ ๊ทน๋‹จ์ ์ธ ํ˜„์ƒ๋“ค์€ ์‹ค์ œ๋กœ ์•Œ ์ˆ˜ ์žˆ๊ณ 
05:09
from the dragon-king concept I propose,
90
309360
2638
์˜ˆ์ธก ๊ฐ€๋Šฅํ•˜๋‹ค๋ฉฐ ์ œ๊ฐ€ ์ œ์•ˆํ–ˆ๋˜
05:11
which is exactly the opposite, that most extreme events
91
311998
3718
์šฉ์™•์˜ ๊ฐœ๋…์—์„œ
05:15
are actually knowable and predictable.
92
315716
3223
๋” ๋‚˜์•„๊ฐ„ ๊ฒƒ์€ ์•„์ง ์—†์Šต๋‹ˆ๋‹ค.
05:18
So we can be empowered and take responsibility
93
318939
3505
๊ทธ๋ž˜์„œ ์šฐ๋ฆฌ๋Š” ์ž์œจ๊ถŒ๊ณผ ์ฑ…์ž„๊ฐ์„ ๊ฐ€์ง€๊ณ ,
05:22
and make predictions about them.
94
322444
2219
์ด๋Ÿฐ ๊ฒƒ๋“ค์— ๋Œ€ํ•ด ์˜ˆ์ธกํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
05:24
So let's have my dragon-king burn this black swan concept.
95
324663
3200
์ž, ์ด์ œ ์ œ ์šฉ์™•์ด ์ด ๊ฒ€์€ ๋ฐฑ์กฐ๋ฅผ ํƒœ์›Œ๋ฒ„๋ฆฌ๋„๋ก ํ•˜์ฃ .
05:27
(Laughter)
96
327863
1626
(์›ƒ์Œ)
05:29
There are many early warning signals
97
329489
2940
๋งŽ์€ ์กฐ๊ธฐ ๊ฒฝ๋ณด ์‹ ํ˜ธ๊ฐ€
05:32
that are predicted by this theory.
98
332429
1879
์ด ์ด๋ก ์— ์˜ํ•ด์„œ ์˜ˆ์ธก ๋˜์—ˆ์Šต๋‹ˆ๋‹ค.
05:34
Let me just focus on one of them:
99
334308
2367
์ด ์ค‘์—์„œ ํ•˜๋‚˜์— ์ดˆ์ ์„ ๋งž์ถฐ๋ณด์ฃ :
05:36
the super-exponential growth with positive feedback.
100
336675
3152
๊ธ์ •์ ์ธ ๋ฐ˜์‘์„ ๋™๋ฐ˜ํ•œ ์ดˆ๊ธฐํ•˜๊ธ‰์ˆ˜์  ์„ฑ์žฅ์ž…๋‹ˆ๋‹ค.
05:39
What does it mean?
101
339827
1160
๋ฌด์Šจ ๋œป์ผ๊นŒ์š”?
05:40
Imagine you have an investment
102
340987
2173
์—ฌ๋Ÿฌ๋ถ„์ด ์ฒซ ํ•ด์—๋Š” 5%,
05:43
that returns the first year five percent,
103
343160
3154
2๋…„ ์งธ์—๋Š” 10%, 3๋…„ ์งธ์—๋Š” 20%,
05:46
the second year 10 percent, the third year 20 percent,
104
346314
3155
4๋…„ ์งธ์—๋Š” 40%์˜ ์ˆ˜์ต์„ ๋ณด์žฅํ•˜๋Š” ๊ณณ์—
05:49
the next year 40 percent. Is that not marvelous?
105
349469
2542
ํˆฌ์žํ–ˆ๋‹ค๊ณ  ์ƒ๊ฐํ•ด๋ณด์„ธ์š”. ๊ต‰์žฅํ•˜์ง€ ์•Š์•„์š”?
05:52
This is a super-exponential growth.
106
352011
3398
์ด๊ฒŒ ๋ฐ”๋กœ ์ดˆ๊ธฐํ•˜๊ธ‰์ˆ˜์  ์„ฑ์žฅ์ž…๋‹ˆ๋‹ค.
05:55
A standard exponential growth corresponds
107
355409
1937
ํ‘œ์ค€์ ์ธ ๊ธฐํ•˜๊ธ‰์ˆ˜์  ์„ฑ์žฅ์€
05:57
to a constant growth rate, let's say, of 10 percent
108
357346
3744
์ง€์†์ ์ธ ์„ฑ์žฅ๋ฅ ์„ ์˜๋ฏธํ•ฉ๋‹ˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด 10% ์ž…๋‹ˆ๋‹ค.
06:01
The point is that, many times during bubbles,
109
361090
3481
์š”์ ์€ ๊ฑฐํ’ˆ์ด ๋ผ์–ด์žˆ์„ ๋•Œ ๋งŽ์€ ๊ฒฝ์šฐ
06:04
there are positive feedbacks which can be of many times,
110
364571
3597
์ด์ „ ์„ฑ์žฅ์ด ์ฆ๋Œ€๋˜๊ณ , ๋‚˜์•„๊ฐ€
06:08
such that previous growths enhance,
111
368168
3699
์ดˆ๊ธฐํ•˜๊ธ‰์ˆ˜์  ์„ฑ์žฅ์„ ํ†ตํ•ด
06:11
push forward, increase the next growth
112
371867
3488
์ดํ›„์˜ ์„ฑ์žฅ์ด ์ด‰์ง„๋˜์–ด
06:15
through this kind of super-exponential growth,
113
375355
2502
๋ช‡ ๋ฐฐ๋‚˜ ๋˜๋Š” ๊ธ์ •์ ์ธ (์‹œ์žฅ)๋ฐ˜์‘์ด
06:17
which is very trenchant, not sustainable.
114
377857
3114
๋‚˜ํƒ€๋‚œ๋‹ค๋Š” ์ ์ž…๋‹ˆ๋‹ค. ์ด๋Ÿฐ ํ˜„์ƒ์€ ๊ฐ•๋ ฅํ•˜์ง€๋งŒ ์ง€์†์ ์ผ ์ˆ˜ ์—†์Šต๋‹ˆ๋‹ค.
06:20
And the key idea is that the mathematical solution
115
380971
3057
ํ•ต์‹ฌ ์•„์ด๋””์–ด๋Š” ์ด๋Ÿฐ ์ข…๋ฅ˜์˜ ๋ฌธ์ œ์— ๋Œ€ํ•œ ์ˆ˜ํ•™์ ์ธ ํ•ด๋‹ต์—๋Š”
06:24
of this class of models exhibit finite-time singularities,
116
384028
3638
์œ ํ•œ ์‹œ๊ฐ„๋‚ด์— ํŠน์ด์ ์ด ๋‚˜ํƒ€๋‚œ๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.
06:27
which means that there is a critical time
117
387666
3353
์ฆ‰, ์ด๋Ÿฐ ์ฒด์ œ๊ฐ€ ๋ถ•๊ดดํ•˜๊ณ ,
06:31
where the system will break, will change regime.
118
391019
3204
์ฒด์ œ ์ž์ฒด๋ฅผ ๋ณ€ํ™”์‹œํ‚ค๋Š” ์ž„๊ณ„ ์‹œ์ ์ด ์žˆ๋‹ค๋Š” ๊ฒƒ์ด์ฃ .
06:34
It may be a crash. It may be just a plateau, something else.
119
394223
3276
์™„์ „ํ•œ ๋ถ•๊ดด์ผ ์ˆ˜๋„, ์„ฑ์žฅ์ด ๋ฉˆ์ถ˜ ๊ฒƒ์ผ ์ˆ˜๋„, ํ˜น์€ ๋‹ค๋ฅธ ๊ฒƒ์ผ ์ˆ˜๋„ ์žˆ์Šต๋‹ˆ๋‹ค.
06:37
And the key idea is that the critical time,
120
397499
2267
์ด ์ž„๊ณ„ ์‹œ์ ์— ๋Œ€ํ•œ ์ •๋ณด๋Š” ์ดˆ๊ธฐํ•˜๊ธ‰์ˆ˜์  ์„ฑ์žฅ์ด ์‹œ์ž‘๋˜๋Š”
06:39
the information about the critical time is contained
121
399766
2529
์ดˆ๊ธฐ์— ํฌํ•จ๋˜์–ด ์žˆ๋‹ค๋Š” ๊ฒƒ
06:42
in the early development of this super-exponential growth.
122
402295
5484
๋˜ํ•œ ์ค‘์š”ํ•œ ์•„์ด๋””์–ด์ž…๋‹ˆ๋‹ค.
06:47
We have applied this theory early on, that was our first success,
123
407779
4360
์ €ํฌ๋Š” ์ด ์ด๋ก ์„ ๊ธˆ์† ๋กœ์ผ“์˜ ์ค‘์š” ๋ถ€ํ’ˆ์ด
06:52
to the diagnostic of the rupture of key elements
124
412139
3559
ํŒŒ์—ดํ•˜๋Š” ๊ฒƒ์„ ์ง„๋‹จํ•˜๋Š”๋ฐ
06:55
on the iron rocket.
125
415698
2529
์ ์šฉํ•ด ๋ณด์•˜์Šต๋‹ˆ๋‹ค. ์ฒซ ๋ฒˆ์งธ์˜ ์„ฑ๊ณต ์‚ฌ๋ก€์˜€์ฃ .
06:58
Using acoustic emission, you know, this little noise
126
418227
2822
์†Œ์Œ์˜ ๋ฐฉ์ถœ์„ ํ†ตํ•ด, ๊ตฌ์กฐ๋ฌผ์ด ์ŠคํŠธ๋ ˆ์Šค๋ฅผ ๋ฐ›์„ ๋•Œ
07:01
that you hear a structure emit, sing to you
127
421049
2297
๋ฐฐ์ถœ๋˜๋Š” ์ž‘์€ ์†Œ์Œ์ด ์šฐ๋ฆฌ์—๊ฒŒ ๊ทธ ์‹ ํ˜ธ๋ฅผ ๋“ค๋ ค์ฃผ๊ณ ,
07:03
when they are stressed, and reveal the damage going on,
128
423346
3691
์†์ƒ์ด ์ง„ํ–‰๋œ๋‹ค๋Š” ๊ฒƒ์„ ์•Œ๋ ค์ฃผ๊ณ ,
07:07
there's a collective phenomenon of positive feedback,
129
427037
2440
๋˜ ๋” ๋งŽ์€ ์†์ƒ์ด ๋˜ ๋‹ค๋ฅธ ์†์ƒ์„ ๋ถˆ๋Ÿฌ์ผ์œผํ‚ค๋Š”
07:09
the more damage gives the more damage,
130
429477
1697
์ง‘๋‹จ์ ์ธ ๊ธ์ • ๋ฐ˜์‘ ํ˜„์ƒ์ด ์กด์žฌํ•˜์—ฌ,
07:11
so you can actually predict,
131
431174
2475
์–ธ์ œ ๊ทธ๋Ÿฐ ํŒŒ์—ด์ด ๋ฐœ์ƒํ•  ์ง€
07:13
within, of course, a probability band,
132
433649
2140
์˜ˆ์ธกํ•  ์ˆ˜ ์žˆ๋Š” ๊ฒƒ์ด์ฃ .
07:15
when the rupture will occur.
133
435789
1913
๋ฌผ๋ก  ํ™•๋ฅ ์ ์ธ ๋ฒ”์œ„ ์•ˆ์—์„œ์š”.
07:17
So this is now so successful that it is used
134
437702
2435
์ด ์ด๋ก ์€ ์ƒ๋‹นํžˆ ์„ฑ๊ณต์ ์ด์–ด์„œ
07:20
in the initial phase of [unclear] the flight.
135
440137
4365
[๋ถˆํ™•์‹ค] ๋น„ํ–‰์˜ ์ดˆ๊ธฐ ๋‹จ๊ณ„์—์„œ ์‚ฌ์šฉ๋˜์—ˆ์Šต๋‹ˆ๋‹ค.
07:24
Perhaps more surprisingly, the same type of theory
136
444502
2807
๋” ๋†€๋ž๊ฒŒ๋„, ๋™์ผํ•œ ์ด๋ก ์ด
07:27
applies to biology and medicine,
137
447309
2728
์ƒ๋ฌผํ•™๊ณผ ์˜ํ•™,
07:30
parturition, the act of giving birth, epileptic seizures.
138
450037
3696
๋ถ„๋งŒ๊ณผ ๊ฐ„์งˆ์—๋„ ์ ์šฉ๋ฉ๋‹ˆ๋‹ค.
07:33
From seven months of pregnancy, a mother
139
453733
3624
์ž„์‹  7๊ฐœ์›” ์ •๋„ ๋˜์—ˆ์„ ๋•Œ๋ถ€ํ„ฐ ์–ด๋จธ๋‹ˆ๋Š”
07:37
starts to feel episodic precursory contractions of the uterus
140
457357
5664
๊ฐ„ํ—์ ์œผ๋กœ ์ž๊ถ ์ˆ˜์ถ•์˜ ์ „์กฐ๋ฅผ ๋Š๋ผ๊ธฐ ์‹œ์ž‘ํ•ฉ๋‹ˆ๋‹ค.
07:43
that are the sign of these maturations
141
463021
4104
์ด๊ฒƒ์€ ์•„์ด์˜ ์ถœ์‚ฐ์ด๋ผ๋Š” ๋ถˆ์•ˆ์ • ์ƒํƒœ๋ฅผ ํ–ฅํ•œ ์„ฑ์žฅ์˜ ์‹ ํ˜ธ์ง€์š”.
07:47
toward the instability, giving birth to the baby,
142
467125
3424
๋ถˆ์•ˆ์ • ์ƒํƒœ๋ž€ ๊ณง ์ถœ์‚ฐ์„ ๋œปํ•ฉ๋‹ˆ๋‹ค.
07:50
the dragon-king.
143
470549
2371
์šฉ์™•์ด ํƒœ์–ด๋‚˜๋Š” ๊ฑฐ์ฃ .
07:52
So if you measure the precursor signal,
144
472920
2606
๊ทธ๋ž˜์„œ ์ „์กฐ ์‹ ํ˜ธ๋ฅผ ์ธก์ •ํ•˜๋ฉด,
07:55
you can actually identify pre- and post-maturity problems
145
475526
6225
์‹ค์ œ๋กœ ์กฐ์ˆ™์•„๋‚˜ ๊ณผ์ˆ™์•„ ๋ฌธ์ œ๋ฅผ
08:01
in advance.
146
481751
1471
์‚ฌ์ „์— ํŒŒ์•…ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
08:03
Epileptic seizures also come in a large variety of size,
147
483222
3760
๊ฐ„์งˆ ๋˜ํ•œ ๋‹ค์–‘ํ•œ ๊ฐ•๋„๋กœ ๋‚˜ํƒ€๋‚˜๋Š”๋ฐ์š”,
08:06
and when the brain goes to a super-critical state,
148
486982
3280
๋‡Œ๊ฐ€ ์ดˆ์ž„๊ณ„์  ์ƒํƒœ๊ฐ€ ๋˜์—ˆ์„ ๋•Œ
08:10
you have dragon-kings which have a degree of predictability
149
490262
3573
์•ฝ๊ฐ„์˜ ์˜ˆ์ธก ํ™•๋ฅ ์„ ๊ฐ€์ง„ ์šฉ์™•์ด ๋‚˜ํƒ€๋‚˜๊ณ , ์ด๋ฅผ ํ†ตํ•ด
08:13
and this can help the patient to deal with this illness.
150
493835
5507
ํ™˜์ž๊ฐ€ ์ด ์งˆ๋ณ‘์— ๋Œ€์ฒ˜ํ•  ์ˆ˜ ์žˆ๋„๋ก ๋„์›€์„ ์ฃผ๊ธฐ๋„ ํ•ฉ๋‹ˆ๋‹ค.
08:19
We have applied this theory to many systems,
151
499342
2185
์ €ํฌ๋Š” ๋‹ค์–‘ํ•œ ์‹œ์Šคํ…œ์— ์ด ์ด๋ก ์„ ์ ์šฉํ•ด๋ณด์•˜์Šต๋‹ˆ๋‹ค.
08:21
landslides, glacier collapse,
152
501527
2855
์‚ฐ์‚ฌํƒœ์™€ ๋ˆˆ์‚ฌํƒœ์—,
08:24
even to the dynamics of prediction of success:
153
504382
3567
์‹ฌ์ง€์–ด ๋ธ”๋ก๋ฒ„์Šคํ„ฐ ์˜ํ™”๋‚˜
08:27
blockbusters, YouTube videos, movies, and so on.
154
507949
4386
์œ ํŠœ๋ธŒ ์˜์ƒ, ์ผ๋ฐ˜ ์˜ํ™” ๋“ฑ์˜ ์„ฑ๊ณต์˜ ์˜ˆ์ธก์— ๋Œ€ํ•œ ์—ญํ•™์—๊นŒ์ง€ ์ ์šฉํ•ด ๋ดค์Šต๋‹ˆ๋‹ค.
08:32
But perhaps the most important application
155
512335
3136
ํ•˜์ง€๋งŒ ์•„๋งˆ ๊ฐ€์žฅ ์ค‘์š”ํ•œ ์‘์šฉ์€
08:35
is for finance, and this theory
156
515471
2366
๊ธˆ์œต์— ๋Œ€ํ•œ ๊ฒƒ์ด์—ˆ๊ณ ,
08:37
illuminates, I believe, the deep reason
157
517837
3439
์ €๋Š” ์ด ์ด๋ก ์ด ์šฐ๋ฆฌ๊ฐ€ ๊ฒช์—ˆ๋˜ ๊ธˆ์œต ์œ„๊ธฐ์˜
08:41
for the financial crisis that we have gone through.
158
521276
2696
๊ทผ๋ณธ์ ์ธ ์ด์œ ๋ฅผ ๋ฐํ˜€์ค€๋‹ค๊ณ  ์ƒ๊ฐํ•ฉ๋‹ˆ๋‹ค.
08:43
This is rooted in 30 years of history of bubbles,
159
523972
4048
๊ทธ๊ฒƒ์€ 30๋…„ ๋™์•ˆ์˜ ๊ฑฐํ’ˆ์˜ ์—ญ์‚ฌ์— ๋ฟŒ๋ฆฌ๋ฅผ ๋‘๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
08:48
starting in 1980, with the global bubble
160
528020
3712
1980๋…„๋ถ€ํ„ฐ ์‹œ์ž‘ํ•˜์—ฌ,
08:51
crashing in 1987,
161
531732
2087
1987๋…„์— ํ„ฐ์กŒ๋˜ ์ „์„ธ๊ณ„์ ์ธ ๊ฑฐํ’ˆ,
08:53
followed by many other bubbles.
162
533819
2369
๊ทธ ๋’ค๋ฅผ ์ด์€ ๋‹ค๋ฅธ ๋งŽ์€ ๊ฑฐํ’ˆ๋“ค ๋ง์ž…๋‹ˆ๋‹ค.
08:56
The biggest one was the "new economy" Internet bubble
163
536188
2712
๊ฐ€์žฅ ํฐ ๊ฑฐํ’ˆ์€
08:58
in 2000, crashing in 2000,
164
538900
1925
2000๋…„์— ํ„ฐ์กŒ๋˜ "์‹ ๊ฒฝ์ œ" ๋‹ท์ปด๋ฒ„๋ธ”์ด์—ˆ๊ณ ,
09:00
the real estate bubbles in many countries,
165
540825
2048
๋’ค์ด์–ด ๋งŽ์€ ๋‚˜๋ผ์—์„œ ๋ถ€๋™์‚ฐ ๊ฑฐํ’ˆ์ด ์ผ์–ด๋‚ฌ์œผ๋ฉฐ,
09:02
financial derivative bubbles everywhere,
166
542873
2780
ํŒŒ์ƒ ์ƒํ’ˆ ๊ฑฐํ’ˆ๊ณผ
09:05
stock market bubbles also everywhere,
167
545653
2289
์ฃผ์‹ ์‹œ์žฅ ๊ฑฐํ’ˆ ๋˜ํ•œ ๋„๋ฆฌ ํผ์กŒ๊ณ ,
09:07
commodity and all bubbles, debt and credit bubbles --
168
547942
3951
์ƒํ’ˆ๊ณผ ๋นš, ์‹ ์šฉ ๊ฑฐํ’ˆ๋“ค๋„ ์žˆ์—ˆ์Šต๋‹ˆ๋‹ค.
09:11
bubbles, bubbles, bubbles.
169
551893
2713
์–ด๋””์—๋‚˜ ๊ฑฐํ’ˆ์ด ๋ผ์–ด์žˆ์—ˆ์ฃ .
09:14
We had a global bubble.
170
554606
2639
์ „์„ธ๊ณ„๊ฐ€ ๊ฑฐํ’ˆ ์ฒœ์ง€์˜€์Šต๋‹ˆ๋‹ค.
09:17
This is a measure of global overvaluation
171
557245
4241
์ด๊ฒƒ์€ ๋ชจ๋“  ์‹œ์žฅ์— ๋Œ€ํ•ด์„œ
09:21
of all markets, expressing what I call
172
561486
4006
์„ธ๊ณ„์ ์ธ ๊ณ ํ‰๊ฐ€๊ฐ€ ์ด๋ฃจ์–ด์กŒ๋‹ค๋Š” ํ‘œ์‹œ์—์š”.
09:25
an illusion of a perpetual money machine
173
565508
3169
์ €๋Š” ์ด๊ฑธ '์˜๊ตฌ์ ์ธ ํ˜„๊ธˆ ์ง€๊ธ‰๊ธฐ'์˜ ํ™˜์ƒ ์ด๋ผ๊ณ  ๋ถ€๋ฆ…๋‹ˆ๋‹ค.
09:28
that suddenly broke in 2007.
174
568677
3952
์ด๊ฑด 2007๋…„์— ๊ธ‰์ž‘์Šค๋Ÿฝ๊ฒŒ ๋ง๊ฐ€์กŒ์–ด์š”.
09:32
The problem is that we see the same process,
175
572629
4234
๋ฌธ์ œ๋Š” 2008๋…„ ์ด๋ž˜๋กœ
09:36
in particular through quantitative easing,
176
576863
2731
๋ฏธ๊ตญ๊ณผ ์œ ๋Ÿฝ, ์ผ๋ณธ์—์„œ ์ƒ๊ธด ์œ„๊ธฐ์— ๋Œ€์‘ํ•  ๋•Œ,
09:39
of a thinking of a perpetual money machine nowadays
177
579594
3184
๋˜๋‹ค์‹œ '์˜๊ตฌ์ ์ธ ํ˜„๊ธˆ ์ง€๊ธ‰๊ธฐ'๋ฅผ ์—ผ๋‘์— ๋‘๊ณ 
09:42
to tackle the crisis since 2008 in the U.S., in Europe,
178
582778
4403
์–‘์  ์™„ํ™”๋ฅผ ํ†ตํ•ด ํ•ด๊ฒฐํ•ด ๋‚˜๊ฐ€๋ ค๋Š”
09:47
in Japan.
179
587181
2288
๋™์ผํ•œ ๊ณผ์ •์ด ๋‚˜ํƒ€๋‚˜๊ณ  ์žˆ๋‹ค๋Š” ์ ์ž…๋‹ˆ๋‹ค.
09:49
This has very important implications
180
589469
2390
์ด๊ฒƒ์€ ์ค‘์š”ํ•œ ํ•ต์‹ฌ, ์ฆ‰ '์˜๊ตฌ์  ํ˜„๊ธˆ ์ง€๊ธ‰๊ธฐ' ๋ผ๋Š” ๊ฒƒ์— ๋Œ€ํ•œ
09:51
to understand the failure of quantitative easing
181
591859
4078
๊ตฌ์กฐ์ ์ธ ์›์ธ์„ ํ•ด๊ฒฐํ•˜์ง€ ์•Š๋Š” ํ•œ
09:55
as well as austerity measures
182
595937
1876
๊ธด์ถ•์•ˆ์„ ๋น„๋กฏํ•œ
09:57
as long as we don't attack the core,
183
597813
2809
์–‘์  ์™„ํ™”์˜ ์‹คํŒจ๋ฅผ ์ดํ•ดํ•˜๋Š”๋ฐ
10:00
the structural cause of this perpetual money machine thinking.
184
600622
5191
์•„์ฃผ ์ค‘์š”ํ•œ ํ•จ์ถ•์  ์˜๋ฏธ๋ฅผ ์ง€๋‹ˆ๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
10:05
Now, these are big claims.
185
605813
2616
์ž, ์ด๊ฑด ์ค‘๋Œ€ํ•œ ์ฃผ์žฅ์ž…๋‹ˆ๋‹ค.
10:08
Why would you believe me?
186
608429
2882
์—ฌ๋Ÿฌ๋ถ„์ด ์™œ ์ œ ๋ง์„ ๋ฏฟ์œผ์…”์•ผ ํ•˜๋Š” ๊ฑธ๊นŒ์š”?
10:11
Well, perhaps because, in the last 15 years
187
611311
2880
๊ทธ๊ฑด ์•„๋งˆ๋„ ์ง€๋‚œ 15๋…„ ๋™์•ˆ
10:14
we have come out of our ivory tower,
188
614191
3192
์ €ํฌ๊ฐ€ ์ƒ์•„ํƒ‘์—์„œ ๋ฒ—์–ด๋‚˜
10:17
and started to publish ex ante --
189
617383
2736
์ด๋Ÿฐ ์˜ˆ์ธก์„ "en ante (์‚ฌ์ „์—)" ๋ฐœํ‘œํ–ˆ๊ธฐ ๋•Œ๋ฌธ์ผ ๊ฒ๋‹ˆ๋‹ค.
10:20
and I stress the term ex ante, it means "in advance" โ€”
190
620119
3328
์ œ๊ฐ€ ๊ฐ•์กฐํ•œ "ex ante" ๋Š” "์‚ฌ์ „์—"๋ผ๋Š” ๋œป์ž…๋‹ˆ๋‹ค.
10:23
before the crash confirmed
191
623447
2138
๋‹ค์‹œ ๋งํ•ด, ๊ฑฐํ’ˆ์ด๋‚˜ ์žฌ์ •์ ์ธ ์ดˆ๊ณผ์˜ ์กด์žฌ๋ฅผ
10:25
the existence of the bubble or the financial excesses.
192
625585
2686
์œ„๊ธฐ๋ฅผ ํ†ตํ•ด ํ™•์ธํ•˜๊ธฐ ์ด์ „์ด์—ˆ๊ธฐ ๋•Œ๋ฌธ์ด์ฃ .
10:28
These are a few of the major bubbles
193
628271
3722
์ตœ๊ทผ์— ์šฐ๋ฆฌ๋Š” ๋ช‡๋ช‡์˜
10:31
that we have lived through in recent history.
194
631993
4478
์ค‘๋Œ€ํ•œ ๊ฑฐํ’ˆ๋“ค์„ ๊ฒช์—ˆ์Šต๋‹ˆ๋‹ค.
10:36
Again, many interesting stories for each of them.
195
636471
2840
๊ฐ๊ฐ์˜ ๊ฑฐํ’ˆ์— ๊ด€๋ จ๋œ ํฅ๋ฏธ๋กœ์šด ์ด์•ผ๊ธฐ๋„ ์žˆ์Šต๋‹ˆ๋‹ค.
10:39
Let me tell you just one or two stories
196
639311
2714
๊ฑฐ๋Œ€ํ•œ ๊ฑฐํ’ˆ์— ๋Œ€ํ•œ ๋Œ€์‘๊ณผ ๊ด€๋ จํ•ด์„œ
10:42
that deal with massive bubbles.
197
642025
2046
ํ•œ ๋‘ ๊ฐ€์ง€ ์ด์•ผ๊ธฐ๋ฅผ ๋“ค๋ ค ๋“œ๋ฆฌ๊ฒ ์Šต๋‹ˆ๋‹ค.
10:44
We all know the Chinese miracle.
198
644071
2336
์—ฌ๋Ÿฌ๋ถ„ ๋ชจ๋‘ ์ค‘๊ตญ์˜ ๊ธฐ์ ์„ ์•„์‹ค ๊ฒ๋‹ˆ๋‹ค.
10:46
This is the expression of the stock market
199
646407
3070
์ด๊ฒƒ์€ ์„ธ ๊ฐ€์ง€ ์š”์†Œ ์ค‘ ํ•˜๋‚˜์ธ,
10:49
of a massive bubble, a factor of three,
200
649477
2880
๋ถˆ๊ณผ ์ˆ˜๋…„ ๋™์•ˆ 300% ์‹ ์žฅํ•œ
10:52
300 percent in just a few years.
201
652357
2170
์ฃผ์‹ ์‹œ์žฅ์˜ ๊ฑฐ๋Œ€ํ•œ ๊ฑฐํ’ˆ์„ ํ‘œํ˜„ํ•œ ๊ฒƒ์ž…๋‹ˆ๋‹ค.
10:54
In September 2007,
202
654527
3202
2007๋…„ 9์›” ์ €๋Š”
10:57
I was invited as a keynote speaker of a macro hedge fund
203
657729
3647
๊ฑฐ๋Œ€ ํ—ค์ง€ ํŽ€๋“œ ๊ด€๋ฆฌ ์ปจํผ๋Ÿฐ์Šค์—
11:01
management conference,
204
661376
2449
๊ธฐ์กฐ ์—ฐ์„ค์ž๋กœ ์ดˆ์ฒญ๋ฐ›์•˜์Šต๋‹ˆ๋‹ค.
11:03
and I showed to the conference a prediction
205
663825
4055
๊ฑฐ๊ธฐ์„œ 2007๋…„ ๋ง๊นŒ์ง€๋Š”
11:07
that by the end of 2007, this bubble
206
667880
4193
์ด ๊ฑฐํ’ˆ์ด ์„ธ์ƒ์„ ๋ฐ”๊พธ๊ฒŒ ๋  ๊ฒƒ์ด๋ผ๋Š”
11:12
would change regime.
207
672073
1969
์˜ˆ์ธก์„ ์ฐธ๊ฐ€์ž๋“ค์—๊ฒŒ ๋ฐœํ‘œํ–ˆ์Šต๋‹ˆ๋‹ค.
11:14
There might be a crash. Certainly not sustainable.
208
674042
3085
ํญ๋ฝ์ผ ์ˆ˜๋„ ์žˆ์ง€๋งŒ, ํ™•์‹คํ•œ ๊ฑด ์ง€์†๋˜์ง„ ์•Š์„ ๊ฒƒ์ด๋ผ๋Š” ๊ฑฐ์˜€์ฃ 
11:17
Now, how do you believe the very smart,
209
677127
5242
์•„์ฃผ ๋˜‘๋˜‘ํ•˜๊ณ , ๋™๊ธฐ๊ฐ€ ๋ถ„๋ช…ํ•˜๊ณ ,
11:22
very motivated, very informed macro hedge fund managers
210
682369
5430
ํ’๋ถ€ํ•œ ์ •๋ณด๋ฅผ ๊ฐ€์ง„ ํ—ค์ง€ ํŽ€๋“œ ๋งค๋‹ˆ์ €๋“ค์ด
11:27
reacted to this prediction?
211
687799
1956
์ด ์˜ˆ์ธก์— ์–ด๋–ป๊ฒŒ ๋ฐ˜์‘ํ–ˆ๋‹ค๊ณ  ์ƒ๊ฐํ•˜์„ธ์š”?
11:29
You know, they had made billions
212
689755
1956
์•„์‹œ๋‹ค์‹œํ”ผ ์ด๋“ค์€ ๊ทธ ๋•Œ๊นŒ์ง€ ๊ฑฐํ’ˆ์„ ์ข…ํšก๋ฌด์ง„ํ•˜๋ฉฐ
11:31
just surfing this bubble until now.
213
691711
2835
์ˆ˜์‹ญ์–ต ๋‹ฌ๋Ÿฌ๋ฅผ ๋ฒŒ์—ˆ์Šต๋‹ˆ๋‹ค.
11:34
They told me, "Didier,
214
694546
1584
์ œ๊ฒŒ ์ด๋Ÿฐ ๋ง์„ ํ•˜๋”๊ตฐ์š”.
11:36
yeah, the market might be overvalued,
215
696130
3037
"๋””๋””์—์”จ, ์‹œ์žฅ์ด ๊ณ ํ‰๊ฐ€ ๋˜์—ˆ์„ ์ˆ˜๋„ ์žˆ์ง€๋งŒ,
11:39
but you forget something.
216
699167
1896
๋ญ”๊ฐ€๋ฅผ ์žŠ๊ณ  ๊ณ„์‹œ๋„ค์š”.
11:41
There is the Beijing Olympic Games coming
217
701063
2352
2008๋…„ 8์›”์—๋Š” ๋ฒ ์ด์ง• ์˜ฌ๋ฆผํ”ฝ์ด ์—ด๋ ค์š”.
11:43
in August 2008, and it's very clear that
218
703415
2264
๊ทธ๋ฆฌ๊ณ  ์ค‘๊ตญ ์ •๋ถ€๊ฐ€ ๊ฒฝ์ œ๋ฅผ ์กฐ์ ˆํ•˜๊ณ ,
11:45
the Chinese government is controlling the economy
219
705679
3192
์–ด๋– ํ•œ ์—ฌํŒŒ๋‚˜ ์ฃผ์‹ ์‹œ์žฅ์„ ๊ด€๋ฆฌํ•˜๋Š”๋ฐ ์žˆ์–ด์„œ
11:48
and doing what it takes
220
708871
1353
ํ•„์š”ํ•œ ๋ชจ๋“  ๊ฑธ ํ•  ๊ฒƒ์ด๋ผ๋Š” ๊ฑด
11:50
to also avoid any wave and control the stock market."
221
710224
4447
์•„์ฃผ ๋ช…๋ฐฑํ•˜๋‹ค๊ตฌ์š”."
11:54
Three weeks after my presentation,
222
714671
2471
์ œ๊ฐ€ ๋ฐœํ‘œํ•œ ๋’ค 3์ฃผ ํ›„์—
11:57
the markets lost 20 percent
223
717142
2126
์‹œ์žฅ์€ 20%์˜ ์†์‹ค์„ ์ž…์—ˆ๊ณ ,
11:59
and went through a phase of volatility,
224
719268
2261
ํ˜ผ๋ˆ๊ณผ ๋ถˆ์•ˆ์˜ ๋‹จ๊ณ„๋กœ
12:01
upheaval, and a total market loss of
225
721529
2726
์ ‘์–ด๋“ค์—ˆ์Šต๋‹ˆ๋‹ค.
12:04
70 percent until the end of the year.
226
724255
2268
๊ทธ ํ•ด ๋ง๊นŒ์ง€ ์‹œ์žฅ์˜ ์ด 70%๋ฅผ ์žƒ์—ˆ์ฃ .
12:06
So how can we be so collectively wrong
227
726523
2876
๋ถˆ์•ˆ์ •์„ฑ์ด ๋ฐœ์ƒํ•˜์—ฌ ์‹œ์Šคํ…œ์ด ๋ฌด๋ฅด์ต์„ ๋•Œ,
12:09
by misreading or ignoring the science
228
729399
4142
์•ฝํ•œ ๋ฏธ๋™์œผ๋กœ ์ธํ•˜์—ฌ ์ œ์–ด ๋ถˆ๊ฐ€๋Šฅํ•œ ํ˜ผ๋ˆ์„ ์ผ์œผํ‚ฌ ์ˆ˜ ์žˆ๋‹ค๋Š”
12:13
of the fact that when an instability has developed,
229
733541
2831
์‚ฌ์‹ค์— ์ž…๊ฐํ•œ ๊ณผํ•™์„
12:16
and the system is ripe, any perturbation
230
736372
2451
์ž˜๋ชป ์ดํ•ดํ•˜๊ฑฐ๋‚˜ ๋ฌด์‹œํ•˜๋Š”
12:18
makes it essentially impossible to control?
231
738823
3681
์ง‘๋‹จ์ ์ธ ์˜คํŒ์ด ์–ด๋–ป๊ฒŒ ๊ฐ€๋Šฅํ• ๊นŒ์š”?
12:22
The Chinese market collapsed, but it rebounded.
232
742504
4705
์ค‘๊ตญ ์‹œ์žฅ์€ ๋ถ•๊ดด๋˜์—ˆ์ง€๋งŒ ๋‹ค์‹œ ํšŒ๋ณตํ–ˆ์Šต๋‹ˆ๋‹ค.
12:27
In 2009, we also identified that this new bubble,
233
747209
4756
2009๋…„ ์ €ํฌ๋Š” ์ด ์ž‘์ง€๋งŒ ์ƒˆ๋กœ์šด ๊ฑฐํ’ˆ์ด
12:31
a smaller one, was unsustainable,
234
751965
2586
๋ถˆ์•ˆ์ •ํ•˜๋‹ค๋Š” ์‚ฌ์‹ค์„ ๋ฐœ๊ฒฌํ–ˆ์Šต๋‹ˆ๋‹ค.
12:34
so we published again a prediction, in advance,
235
754551
3632
๊ทธ๋ž˜์„œ ์ €ํฌ๋Š” ๋‹ค์‹œ ์‚ฌ์ „์— ์˜ˆ์ธก์„ ๋ฐœํ‘œํ–ˆ์Šต๋‹ˆ๋‹ค.
12:38
stating that by August 2009, the market will correct,
236
758183
4327
2009๋…„ 8์›”๊นŒ์ง€ ์‹œ์žฅ์ด ์กฐ์ •๋  ๊ฒƒ์ด๊ณ ,
12:42
will not continue on this track.
237
762510
2681
์ด ๊ถค๋„๋ฅผ ๋”ฐ๋ฅด์ง€ ์•Š์„ ๊ฒƒ์ด๋ผ๊ณ  ํ–ˆ์ฃ .
12:45
Our critics, reading the prediction,
238
765191
3152
์ด ์˜ˆ์ธก์„ ์ฝ์€ ํ•œ ๋น„ํ‰๊ฐ€๊ฐ€ ์ด๋ ‡๊ฒŒ ๋งํ•˜๋”๊ตฐ์š”.
12:48
said, "No, it's not possible.
239
768343
3913
"์•„๋‡จ, ์ ˆ๋Œ€ ์ผ์–ด๋‚˜์ง€ ์•Š์„ ๊ฒ๋‹ˆ๋‹ค.
12:52
The Chinese government is there.
240
772256
1494
์ค‘๊ตญ ์ •๋ถ€๊ฐ€ ๋„‹์„ ๋†“๊ณ  ์žˆ๊ฒ ์–ด์š”?
12:53
They have learned their lesson. They will control.
241
773750
2682
์ด๋ฏธ ๊ตํ›ˆ์„ ๋ฐฐ์› ์œผ๋‹ˆ ์ด๋ฒˆ์—๋Š” ํ†ต์ œํ•  ๊ฒ๋‹ˆ๋‹ค.
12:56
They want to benefit from the growth."
242
776432
1807
์„ฑ์žฅ์„ ํ†ตํ•ด ์ด์ต์„ ๋ณด๊ธธ ์›ํ•˜๋‹ˆ๊นŒ์š”."
12:58
Perhaps these critics have not learned their lesson previously.
243
778239
3656
์•„๋งˆ๋„ ์ด ๋น„ํ‰๊ฐ€๋“ค์€ ์•ž์„  ๊ฒฝ์šฐ์—์„œ ๊ตํ›ˆ์„ ์–ป์ง€ ๋ชปํ•œ ๊ฒƒ ๊ฐ™์•„์š”.
13:01
So the crisis did occur. The market corrected.
244
781895
3832
์œ„๊ธฐ๋Š” ์‹ค์ œ๋กœ ์™”๊ณ  ์‹œ์žฅ์—๋Š” ์กฐ์ •์ด ์ผ์–ด๋‚ฌ์Šต๋‹ˆ๋‹ค.
13:05
The same critics then said, "Ah, yes,
245
785727
2336
๋ฐ”๋กœ ๊ทธ ๋น„ํ‰๊ฐ€๋Š” "์•„, ๊ทธ๋ž˜์š”.
13:08
but you published your prediction.
246
788063
1849
๊ทผ๋ฐ ๋‹น์‹ ์ด ์˜ˆ์ธก์„ ๋ฐœํ‘œํ–ˆ์ž–์•„์š”.
13:09
You influenced the market.
247
789912
1656
์‹œ์žฅ์— ์˜ํ–ฅ์„ ์ค€๊ฑฐ์—์š”.
13:11
It was not a prediction."
248
791568
3133
๊ทธ๋Ÿฌ๋‹ˆ๊นŒ ์˜ˆ์ธก์ด๋ผ๊ณ  ํ•  ์ˆ˜ ์—†์–ด์š”." ๋ผ๊ณ  ํ•˜๋”๊ตฐ์š”.
13:14
Maybe I am very powerful then.
249
794701
3357
์•„๋งˆ ์ œ๊ฐ€ ๊ฝค๋‚˜ ์˜ํ–ฅ๋ ฅ์ด ์žˆ๋‚˜๋ด์š”.
13:18
Now, this is interesting.
250
798058
2044
์ž, ์ด๊ฑด ํฅ๋ฏธ๋กญ์Šต๋‹ˆ๋‹ค.
13:20
It shows that it's essentially impossible until now
251
800102
2937
์ด ๊ฒฝ์šฐ๋Š” ์—ฌํƒœ๊นŒ์ง€ ๊ฒฝ์ œ๋ผ๋Š” ๊ณผํ•™์„ ๋ฐœ์ „์‹œํ‚ค๋Š” ๊ฒƒ์ด
13:23
to develop a science of economics
252
803039
2128
๊ทผ๋ณธ์ ์œผ๋กœ ๋ถˆ๊ฐ€๋Šฅํ–ˆ๋‹ค๋Š” ๊ฑธ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค.
13:25
because we are sentient beings who anticipate
253
805167
3143
์™œ๋ƒํ•˜๋ฉด ์šฐ๋ฆฌ๋Š” ์˜ˆ์ƒ์„ ํ•˜๋Š” ์ง€๊ฐํ•˜๋Š” ์กด์žฌ์ด๊ณ ,
13:28
and there is a problem of self-fulfilling prophesies.
254
808310
4063
์ž๊ธฐ ์ถฉ์กฑ์ ์ธ ์˜ˆ์–ธ์˜ ๋ฌธ์ œ๊ฐ€ ์žˆ๊ธฐ ๋–„๋ฌธ์ด์ฃ .
13:32
So we invented a new way of doing science.
255
812373
3733
๊ทธ๋ž˜์„œ ์ €ํฌ๋Š” ์ƒˆ๋กœ์šด ์—ฐ๊ตฌ ๋ฐฉ๋ฒ•์„ ๊ณ ์•ˆํ•ด๋ƒˆ์Šต๋‹ˆ๋‹ค.
13:36
We created the Financial Bubble Experiment.
256
816106
2712
์ €ํฌ๋Š” ๊ธˆ์œต ๊ฑฐํ’ˆ ์‹คํ—˜(Financial Bubble Experiment)์„ ๋งŒ๋“ค์—ˆ์Šต๋‹ˆ๋‹ค.
13:38
The idea is the following. We monitor the markets.
257
818818
2672
์•„์ด๋””์–ด๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™์Šต๋‹ˆ๋‹ค. ์šฐ๋ฆฌ๊ฐ€ ์‹œ์žฅ์„ ๊ฐ์‹œํ•ฉ๋‹ˆ๋‹ค.
13:41
We identify excesses, bubbles.
258
821490
4168
์—ฌ๋ถ„, ์ฆ‰ ๊ฑฐํ’ˆ์„ ์ฐพ์•„๋‚ด์ฃ .
13:45
We do our work. We write a report
259
825658
3304
์šฐ๋ฆฌ๊ฐ€ ํ•ด์•ผํ•  ์ผ์„ ํ•ฉ๋‹ˆ๋‹ค.
13:48
in which we put our prediction of the critical time.
260
828962
4272
์ž„๊ณ„ ์‹œ์ ์„ ์˜ˆ์ธกํ•œ ๋ณด๊ณ ์„œ๋ฅผ ์ž‘์„ฑํ•ฉ๋‹ˆ๋‹ค.
13:53
We don't release the report. It's kept secret.
261
833234
2575
๊ทธ๋Ÿฌ๊ณ ๋Š” ๊ทธ ๋ณด๊ณ ์„œ๋ฅผ ๋ฐœํ–‰ํ•˜์ง€ ์•Š๊ณ  ๋น„๋ฐ€์— ๋ถ™์ž…๋‹ˆ๋‹ค.
13:55
But with modern encrypting techniques,
262
835809
2865
ํ•˜์ง€๋งŒ ํ˜„๋Œ€ ์•”ํ˜ธํ•™ ๊ธฐ์ˆ  ๋•๋ถ„์—
13:58
we have a hash, we publish a public key,
263
838674
4022
์ฃผ๋„๊ถŒ์„ ๊ฐ–๊ณ , ๊ณต๊ณต ํ‚ค๋ฅผ ๋ฐœํ–‰ํ•ฉ๋‹ˆ๋‹ค.
14:02
and six months later, we release the report,
264
842696
3955
๊ทธ๋ฆฌ๊ณ  6๊ฐœ์›” ๋’ค์— ๋ณด๊ณ ์„œ๋ฅผ ๋‚ด๋ณด๋‚ด๋ฉด
14:06
and there is authentication.
265
846651
2399
์ž…์ฆ์ด ๋˜๋Š” ๊ฒƒ์ด์ฃ .
14:09
And all this is done on an international archive
266
849050
4768
์ด ๋ชจ๋“  ๊ฒƒ๋“ค์€ ๊ตญ์ œ ๊ธฐ๋ก ๋ณด๊ด€์†Œ์—์„œ ์ž‘์—…์ด ๋˜์–ด
14:13
so that we cannot be accused of just releasing the successes.
267
853818
4200
์ด๋ฏธ ๋‚˜ํƒ€๋‚œ ๊ฒฐ๊ณผ๋ฅผ ๋ฐœํ‘œํ–ˆ๋‹ค๋Š” ๋น„๋‚œ์„ ๋ฏธ์—ฐ์— ๋ฐฉ์ง€ํ•˜๋Š” ๊ฑฐ์ฃ .
14:18
Let me tease you with a very recent analysis.
268
858018
3392
์•„์ฃผ ์ตœ๊ทผ์˜ ๋ถ„์„์œผ๋กœ ์—ฌ๋Ÿฌ๋ถ„๋“ค์„ ๊ดด๋กญํ˜€์•ผ๊ฒ ์Šต๋‹ˆ๋‹ค.
14:21
17th of May, 2013, just two weeks ago,
269
861410
3258
๋ถˆ๊ณผ 2์ฃผ ์ „์ธ 2013๋…„ 5์›” 17์ผ
14:24
we identified that the U.S. stock market
270
864668
1678
์ €ํฌ๋Š” ๋ฏธ๊ตญ ์ฃผ์‹ ์‹œ์žฅ์ด ์ง€์† ๋ถˆ๊ฐ€๋Šฅํ•œ ๊ถค๋„์—
14:26
was on an unsustainable path
271
866346
2392
์˜ฌ๋ผ์„ฐ๋‹ค๋Š” ๊ฑธ ๋ฐœ๊ฒฌํ–ˆ์Šต๋‹ˆ๋‹ค.
14:28
and we released this on our website on the 21st of May
272
868738
3802
๊ทธ๋ฆฌ๊ณ  ์‹œ์žฅ์ด ๋ฐ”๋€” ๊ฒƒ์ด๋ผ๋Š” ๋ณด๊ณ ์„œ๋ฅผ
14:32
that there will be a change of regime.
273
872540
2045
5์›” 21์ผ ์ €ํฌ ์›น์‚ฌ์ดํŠธ์— ๊ฒŒ์žฌํ–ˆ์Šต๋‹ˆ๋‹ค.
14:34
The next day, the market started to change regime, course.
274
874585
4784
๋‹ค์Œ๋‚  ์‹œ์žฅ์˜ ๊ฒฝํ–ฅ์ด ๋ฐ”๋€Œ๊ธฐ ์‹œ์ž‘ํ–ˆ์Šต๋‹ˆ๋‹ค.
14:39
This is not a crash.
275
879369
1491
ํญ๋ฝ์€ ์•„๋‹ˆ์—ˆ์ฃ .
14:40
This is just the third or fourth act
276
880860
2599
์ด๋Š” ๊ฑฐ๋Œ€ํ•œ ๊ฑฐํ’ˆ์˜ ์ƒ์„ฑ์— ์žˆ์–ด์„œ
14:43
of a massive bubble in the making.
277
883459
2863
3๋‹จ๊ณ„๋‚˜ 4๋‹จ๊ณ„์— ๋ถˆ๊ณผํ•ฉ๋‹ˆ๋‹ค.
14:46
Scaling up the discussion at the size of the planet,
278
886322
3096
์ด๋Ÿฐ ๋…ผ์˜๋ฅผ ์ง€๊ตฌ์ ์ธ ํฌ๊ธฐ๋กœ ๋„“ํ˜€๋ณด๋ฉด
14:49
we see the same thing.
279
889418
1025
๊ฐ™์€ ๊ฑธ ๋ณผ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
14:50
Wherever we look, it's observable:
280
890443
2921
์–ด๋”œ ๋ณด๋“ , ๋ˆˆ์— ๋•๋‹ˆ๋‹ค.
14:53
in the biosphere, in the atmosphere, in the ocean,
281
893364
3230
์ƒํƒœ๊ณ„, ๋Œ€๊ธฐ๊ถŒ, ํ•ด์–‘๊ถŒ ์–ด๋””์—๋‚˜
14:56
showing these super-exponential trajectories
282
896594
3904
์ง€์†๋˜์ง€ ๋ชปํ•  ๊ธธ๊ณผ
15:00
characterizing an unsustainable path
283
900498
2631
๋‹จ๊ณ„์˜ ์ „ํ™˜์˜ ํŠน์ง•์„ ๊ฐ–๋Š”
15:03
and announcing a phase transition.
284
903129
2617
์ดˆ๊ธฐํ•˜๊ธ‰์ˆ˜์ ์ธ ๊ถค์ ์ด ๋ณด์ž…๋‹ˆ๋‹ค.
15:05
This diagram on the right
285
905746
1704
์˜ค๋ฅธ์ชฝ์˜ ๊ทธ๋ฆผ์€ ํ–ฅํ›„ ์ˆ˜์‹ญ ๋…„ ์•ˆ์—
15:07
shows a very beautiful compilation of studies
286
907450
3000
๋น„์„ ํ˜•์ ์ธ ์ „ํ™˜์ด
15:10
suggesting indeed that there is a nonlinear -- possibility
287
910450
3710
๊ฒฐ๊ตญ์—๋Š” ์žˆ์„ ๊ฒƒ์ด๋ผ๋Š” ๊ฐ€๋Šฅ์„ฑ์„ ๋ณด์—ฌ์ฃผ๋Š”
15:14
for a nonlinear transition just in the next few decades.
288
914160
4149
์•„์ฃผ ์•„๋ฆ„๋‹ค์šด ์—ฐ๊ตฌ์˜ ํ†ตํ•ฉ ๊ฒฐ๊ณผ๋ฌผ์ž…๋‹ˆ๋‹ค.
15:18
So there are bubbles everywhere.
289
918309
3622
์ฆ‰, ๊ฑฐํ’ˆ์€ ์–ด๋””์—๋‚˜ ์žˆ๋‹ค๋Š” ๋ง์ž…๋‹ˆ๋‹ค.
15:21
From one side, this is exciting
290
921931
1964
์–ด๋–ค ๋ฉด์—์„œ๋Š”, ๊ฑฐํ’ˆ์„ ์ข‡๋Š” ๊ต์ˆ˜๋กœ์„œ
15:23
for me, as a professor who chases bubbles
291
923895
2760
์ด๊ฒƒ์€ ์•„์ฃผ ํฅ๋ถ„๋ฉ๋‹ˆ๋‹ค.
15:26
and slays dragons, as the media has sometimes called me.
292
926655
4758
์–ธ๋ก ์—์„œ๋Š” ์ œ๊ฐ€ ์šฉ์„ ๋ฒค๋‹ค๊ณ  ํ•˜๋”๊ตฐ์š”.
15:31
But can we really slay the dragons?
293
931413
3051
ํ•˜์ง€๋งŒ ์ •๋ง๋กœ ์šฉ์„ ๋ฒจ ์ˆ˜ ์žˆ์„๊นŒ์š”?
15:34
Very recently, with collaborators,
294
934464
2144
์•„์ฃผ ์ตœ๊ทผ์— ๊ณต๋™ ์—ฐ๊ตฌ์ž๋“ค๊ณผ ํ•จ๊ป˜
15:36
we studied a dynamical system
295
936608
2703
์ด ์ปค๋‹ค๋ž€ ๊ณ ๋ฆฌ๋กœ ๋ณด์ด๋Š” ์šฉ์™•์ด ์žˆ๋Š”
15:39
where you see the dragon-king as these big loops
296
939311
2904
๋™์  ์‹œ์Šคํ…œ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ–ˆ์Šต๋‹ˆ๋‹ค.
15:42
and we were able to apply tiny perturbations at the right times
297
942215
3921
๊ทธ๋ฆฌ๊ณ  ์ œ์–ด๋ฅผ ํ•  ๋•Œ, ์šฉ์„ ์—†์•ค ์ž‘์€ ๋ถˆ์•ˆ ์š”์†Œ๋ฅผ
15:46
that removed, when control is on, these dragons.
298
946136
4935
์ ์‹œ์— ์ ์šฉํ•  ์ˆ˜ ์žˆ์—ˆ์Šต๋‹ˆ๋‹ค.
15:51
"Gouverner, c'est prรฉvoir."
299
951071
2934
"์ ์šฉ์ด ๊ณง ์˜ˆ์ธก์ž…๋‹ˆ๋‹ค."
15:54
Governing is the art of planning and predicting.
300
954005
5794
์ง€๋ฐฐ๋ž€ ๊ณง ๊ณ„ํš๊ณผ ์˜ˆ์ธก์˜ ๋ฏธํ•™์ž…๋‹ˆ๋‹ค.
15:59
But is it not the case that this is probably
301
959799
2753
ํ•˜์ง€๋งŒ ์ด๊ฒŒ ์•„๋งˆ๋„ ์ธ๋ฅ˜๊ฐ€ ๊ฐ€์ง„
16:02
one of the biggest gaps of mankind,
302
962552
3900
๊ฐ€์žฅ ํฐ ๊ฐ„๊ทน ๊ฐ€์šด๋ฐ ํ•˜๋‚˜๊ฐ€ ์•„๋‹๊นŒ์š”?
16:06
which has the responsibility to steer
303
966452
3260
์šฐ๋ฆฌ์˜ ์‚ฌํšŒ์™€ ์ง€๊ตฌ๋ฅผ
16:09
our societies and our planet toward sustainability
304
969712
2703
๋‹น๋ฉดํ•˜๋Š” ์—ญ๊ฒฝ๊ณผ ์œ„๊ธฐ๋กœ๋ถ€ํ„ฐ
16:12
in the face of growing challenges and crises?
305
972428
4844
์ง€์† ๊ฐ€๋Šฅํ•œ ๋ฐฉํ–ฅ์œผ๋กœ ์ด๋„๋Š” ์ฑ…์ž„์„ ๊ฐ–๋Š” ๊ฒƒ ๋ง์ด์—์š”.
16:17
But the dragon-king theory gives hope.
306
977272
4495
ํ•˜์ง€๋งŒ ์ด ์šฉ์™• ์ด๋ก ์€ ํฌ๋ง์„ ์ค๋‹ˆ๋‹ค.
16:21
We learn that most systems have pockets of predictability.
307
981767
3568
์šฐ๋ฆฌ๋Š” ๋Œ€๋ถ€๋ถ„์˜ ์‹œ์Šคํ…œ์— ์•ฝ๊ฐ„์˜ ์˜ˆ์ธก ๊ฐ€๋Šฅ์„ฑ์ด ์žˆ๋‹ค๊ณ  ๋ฐฐ์› ์Šต๋‹ˆ๋‹ค.
16:25
It is possible to develop advance diagnostics of crises
308
985335
4900
์šฐ๋ฆฌ๋Š” ๊ณ ๊ธ‰ ์œ„๊ธฐ ์ง„๋‹จ ๊ธฐ์ˆ ์„ ๊ฐœ๋ฐœํ•ด์„œ
16:30
so that we can be prepared, we can take measures,
309
990235
3559
์ค€๋น„๋ฅผ ๊ฐ–์ถœ ์ˆ˜ ์žˆ๊ณ ,
16:33
we can take responsibility,
310
993794
2755
ํŒ๋‹จํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ,
16:36
and so that never again will
311
996549
2747
์ฑ…์ž„๊ฐ์„ ๊ฐ€์ง€๊ฒŒ ๋˜๊ณ ,
16:39
extremes and crises like the Great Recession
312
999296
3854
๊ทธ๋ž˜์„œ ๋Œ€์นจ์ฒด๊ธฐ๋‚˜ ์œ ๋Ÿฝ๋ฐœ ์œ„๊ธฐ๊ฐ™์€ ๊ทน๋‹จ์ ์ธ ์œ„ํ—˜์ด
16:43
or the European crisis take us by surprise.
313
1003150
4410
๊ฐ‘์ž‘์Šค๋ ˆ ์šฐ๋ฆฌ๋ฅผ ๋ฎ์น˜์ง€ ์•Š๊ฒŒ ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
16:47
Thank you.
314
1007560
1475
๊ฐ์‚ฌํ•ฉ๋‹ˆ๋‹ค.
16:49
(Applause)
315
1009035
6293
(๋ฐ•์ˆ˜)
์ด ์›น์‚ฌ์ดํŠธ ์ •๋ณด

์ด ์‚ฌ์ดํŠธ๋Š” ์˜์–ด ํ•™์Šต์— ์œ ์šฉํ•œ YouTube ๋™์˜์ƒ์„ ์†Œ๊ฐœํ•ฉ๋‹ˆ๋‹ค. ์ „ ์„ธ๊ณ„ ์ตœ๊ณ ์˜ ์„ ์ƒ๋‹˜๋“ค์ด ๊ฐ€๋ฅด์น˜๋Š” ์˜์–ด ์ˆ˜์—…์„ ๋ณด๊ฒŒ ๋  ๊ฒƒ์ž…๋‹ˆ๋‹ค. ๊ฐ ๋™์˜์ƒ ํŽ˜์ด์ง€์— ํ‘œ์‹œ๋˜๋Š” ์˜์–ด ์ž๋ง‰์„ ๋”๋ธ” ํด๋ฆญํ•˜๋ฉด ๊ทธ๊ณณ์—์„œ ๋™์˜์ƒ์ด ์žฌ์ƒ๋ฉ๋‹ˆ๋‹ค. ๋น„๋””์˜ค ์žฌ์ƒ์— ๋งž์ถฐ ์ž๋ง‰์ด ์Šคํฌ๋กค๋ฉ๋‹ˆ๋‹ค. ์˜๊ฒฌ์ด๋‚˜ ์š”์ฒญ์ด ์žˆ๋Š” ๊ฒฝ์šฐ ์ด ๋ฌธ์˜ ์–‘์‹์„ ์‚ฌ์šฉํ•˜์—ฌ ๋ฌธ์˜ํ•˜์‹ญ์‹œ์˜ค.

https://forms.gle/WvT1wiN1qDtmnspy7