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Didier Sornette 談如何預測下一場金融危機

Didier Sornette: How we can predict the next financial crisis

 

Photo of three lions hunting on the Serengeti.

講者:Didier Sornette

2013年6月演講,2013年6月在TEDGlobal 2013上線

 

翻譯:洪曉慧

編輯:朱學恆

簡繁轉換:洪曉慧

後製:洪曉慧

字幕影片後制:謝旻均

 

影片請按此下載

MAC及手持裝置版本請按此下載

閱讀中文字幕純文字版本

 

關於這場演講

你或許認為2007至2008年的金融危機是無法預知的一次性崩潰。但Didier Sornette和他的金融危機觀測台繪製一系列早期警訊,顯示不穩定發展系統,追踪泡沫即將破滅的時刻。(如今他再次目睹這個現象)

 

關於Didier Sornette

Didier Sornette研究是否可能預測複雜系統的巨大變化或危機。

 

為什麼要聽他演講

雖然金融崩潰、經濟衰退、地震和其他極端事件的出現往往出人意料,Didier Sornette的研究著重於找出它們是否能進行預測。他認為這些事件的發生往往出人意料,但並非無中生有:最極端的風險(及收益)就是他所謂的「龍王」,幾乎總是來自可觀察、逐漸邁向不穩定的過程。在他的假設中,這種不穩定具有可衡量的技術或社會經濟前兆。他說:「危機並非來自外部衝擊。」

 

身為複雜系統專家的Sornette是瑞士聯邦理工學院企業風險系主任,及金融危機觀測台主任,這是測試「市場可進行預測,尤其處於泡沫階段」這項假設的計畫。他是《股市為何崩盤:複雜金融系統中的危機事件》(Why Stock Markets Crash: Critical Events in Complex Financial Systems)作者。

 

Didier Sornette的英語網上資料

Home: www.er.ethz.ch

TED Blog Q&A: "Turbulent times ahead"

 

[TED科技‧娛樂‧設計]

已有中譯字幕的TED影片目錄(繁體)(簡體)。請注意繁簡目錄是不一樣的。

 

Didier Sornette 談如何預測下一場金融危機

 

曾幾何時,我們生活在金融繁榮發展的經濟體系中,這就是所謂的「大穩健」時期。這是大多數經濟學家、政策制定者及中央銀行的誤導性看法:我們已演變成一個永不衰退、永保繁榮的新世界。這個看法似乎根據穩健的GDP成長、掌控中的低通貨膨脹率、低失業率和掌控中的低金融波動率。

 

但2007和2008年的大蕭條、經濟大崩盤打破了這個幻象。金融產業損失數千億美元,全世界GDP流失5兆美元,全球股市損失將近30兆美元。

 

因此人們對大蕭條的認知是-這完全出乎意料,彷彿晴天霹靂,就像眾神的憤怒,沒人能為此負責。因此為了因應這種危機,我們成立了金融危機觀測台。我們的目標是:即時判斷金融泡沫化情形,預先界定其中的臨界點。

 

金融觀測台的架構及科學基礎為何?我們開發了一個名為「龍王」的理論。龍王代表各類體系中的極端事件;它們是特殊的、異常的;它們衍生於特定機制,因此或許可進行預測及控制。

 

考慮金融價格時間序列,特定股票,你最佳的股票或全球指數,其中存在高低起伏的波動。峰谷線是衡量金融市場風險極佳的工具,可呈現最糟的情況-當你在高點買入、低點賣出-可觀察這些統計,不同規模峰谷線出現的頻率都呈現在這張圖表中。好,有趣的是,99%不同振幅的峰谷線,都可藉由這條紅線所呈現的通用冪次定律反映。更有趣的是其中存在離群值,即例外情形,位於紅線上方,其發生頻率至少比根據其餘99%峰谷線校正後所預測的情形大100倍,其中存在極強的關聯性,導致損失連續發生。大多標準風險管理工具都忽略了這種關聯性;當它們該留意「龍王」時,卻視而不見,只看見蜥蜴。龍王理論的根本機制是緩慢邁向不穩定的過程,這就是泡沫,泡沫擴張到極限往往潰堤。這類似於緩慢加熱試管中的水、使其達到沸點。水分子逐漸變得不穩定,最後變成氣相。這個過程絕非線性,無法藉由標準技術預測;這是集體突發行為的反射,基本上源於內部。因此潰堤的根源、危機的根源必須從系統內不穩定狀態中察覺,任何細微的擾動都可能造成不穩定。

 

好,在座有些人或許會想,這是否和你常聽見的黑天鵝效應有關?記住,黑天鵝是稀有鳥類,只要見過一次,便瞬間粉碎你對所有天鵝都應該是白色的信念,因此其涵蓋無法預測、無法得知的概念,認為基本上極端事件是無法預知的。沒有任何事物能脫離我提出的「龍王理論」範疇,其中觀點完全相反:大多數極端事件確實是可獲知、可預測的。因此我們獲得授權,擔負起重責大任,對這些事件進行預測。就讓我的龍王燒毀黑天鵝吧!

 

(笑聲)

 

許多早期警訊可藉由這個理論預測,我不妨先舉個例子。超指數成長伴隨正向回饋,這是什麼意思?想像你進行一項投資,第一年獲利5%、第二年10%、第三年20%、第四年40%,棒透了吧?這就是超指數成長。標準指數成長符合固定線性成長率,例如10%。重點在於,泡沫化期間出現多次正向回饋,導致前次成長幅度增加,推動下次成長幅度。在這種超指數成長過程中,變化相當激烈,並非穩定狀態。主要概念在於,這種模型的數學解呈現有限時間奇異點,意味著在某個臨界時間點,這個系統將崩解、改變狀態;或許是崩盤、或許只是持平,或其他可能。關鍵在於在臨界時間點,臨界時間點的資訊包含在超指數成長的早期發展中。

 

我們早期曾應用這個理論,這是我們第一次成功診斷出雅利安火箭破裂的關鍵因素。藉由聲音發射裝置,你可以聽見這個結構發出微弱的噪音,當它承受壓力、開始出現損傷時,其中存在集體正回饋現象;越多損傷將導致更多損傷。因此你可在可能範圍內預測裂縫何時產生,現在這個理論成功應用在飛行初期階段。

 

也許更令人驚訝的是,同類理論可應用於生物及醫學領域,例如懷孕、生產過程、癲癇發作等。懷孕七個月起,母親開始感到間歇性子宮收縮前兆,這是邁向不穩定、即將生產過程的徵兆,即龍王理論。因此如果測量這些前兆,就可預先判斷事件發生前後的問題。癲癇發作亦呈現眾多不同形式,當大腦進入超臨界狀態時,龍王理論可進行一定程度的預測,協助病患處理這種疾病。我們將這個理論應用在許多系統中:土石流、冰川崩塌,甚至成功預測時事動態,例如賣座鉅片、YouTube影片、電影等等。但也許最重要的應用在於金融。我認為這個理論闡明了我們經歷過的金融危機中的深層原因,根植於三十年來的泡沫歷史中,始於1980年。全球泡沫於1987年破裂,眾多其他泡沫隨之產生,最大的是2000年的「新經濟」網路泡沫,於2000年破裂,還有許多國家的房地產泡沫。金融衍生產品泡沫隨處可見,股市泡沫亦無所不在,商品與各種泡沫、債務與信貸泡沫-層出不窮的泡沫。

 

我們擁有全球性泡沫。這是全球市場被高估的程度,顯示我所謂的「永久印鈔機幻覺」突然於2007年崩盤。

 

問題在於我們目睹相同過程,特別是藉由量化寬鬆政策。自2008年起,各國政府想藉由「永久印鈔機」解決金融危機,美國、歐洲、日本皆然,這對於瞭解量化寬鬆及財政緊縮政策失敗之處有十分重要的意義-只要我們直擊核心,即「永久印鈔機」想法的結構性原因。

 

好,這些都是大膽的主張。你們為何相信我?好,也許是因為過去15年間,我們已走出象牙塔,開始「ex ante」公布-我強調「ex ante」這個詞,意思是「預先」-在經濟崩盤證實泡沫或金融過度存在之前,這些是近期歷史中我們經歷過的一些主要泡沫。同樣地,每種泡沫都蘊含許多有趣的故事,不妨告訴各位一兩個如何因應大規模泡沫的故事。

 

我們都知道中國奇蹟。圖表顯示大規模股市泡沫,差距高達三倍;短短數年間,指數跳漲300%。2007年9月,我應邀於宏觀對沖基金管理人會議進行演講,我在會議中提出一項預測:2007年底前,這顆泡沫就會發生改變,或許是崩盤;肯定不會持續發展。好,你們認為這群聰明、積極、見多識廣的宏觀對沖基金經理人對這項預測有何反應?知道嗎?目前為止,僅靠著在這顆泡沫上「衝浪」,他們已賺進數十億美元。他們對我說:「Didier,沒錯,市場或許被高估,但你忘了一件事:北京奧運即將來臨,就在2008年8月,顯然中國政府正控制經濟,採取一切手段,避免任何波動,並控制股票市場。」

 

演講結束後三週,市場蒸發了20%,經歷劇烈的波動。到了當年年底,總市值已蒸發70%。

 

我們怎麼會犯下這種集體錯誤?誤判或忽略這個科學事實:當不穩定系統已發展成熟時,任何波動都會使局面失控。

 

中國市場崩盤,但再次復甦。2009年,我們也辨識出這個新泡沫;規模較小、不穩定的泡沫。因此我們再次發表預測:2009年8月前,市場將開始修正,不會持續目前的軌跡。讀到這個預測的批評家說,「不,這是不可能的,還有中國政府呢!他們已學到教訓,他們會進行控制,他們想從這波成長中撈些好處。」也許這些批評家並未學到之前的教訓;因此危機確實發生,市場發生改變。

 

同一批批評家改口說,「啊,是的,但你公佈這項預測,影響了市場,這算不上什麼預測。」

 

也許我有超凡的影響力。好,這很有趣,顯示到目前為止,經濟科學根本不可能有所發展。因為我們是擁有期待情緒的物種,還存在「自我應驗預言」的問題。

 

因此我們發明了一種新科學方法。我們創造了金融泡沫實驗,方法如下:我們監測市場,辨識出過度化、泡沫化情形,進行我們的工作,撰寫報告,寫下我們預測的臨界時間點。我們不釋出報告,保持機密,但我們藉由現代加密技術,以hash加密。我們公佈一個公用金鑰,六個月後,我們釋出報告,並可進行驗證。這一切都在國際檔案庫中進行,這樣我們就不會遭受影響市場的指控。

 

讓我告訴各位一項最近的分析。2013年5月17日,僅僅兩週前,我們辨識出美國股市正邁向變動的道路。我們於5月21日將這個訊息發佈在我們的網站上,說市場將發生變化。隔天,市場開始發生變化;這並非崩盤,只是大規模泡沫形成過程中第三或第四步驟。我們將討論擴展到全球範圍,我們目睹相同的現象,無論觀察何種領域都可看見。在生物圈、大氣層、海洋,都呈現這種超指數變化軌跡,顯示變動的途徑,預告變遷的情形。右邊這張圖表顯示非常精細的整合資訊,暗示未來數十年間確實可能發生非線性轉變。

 

因此泡沫隨處可見。一方面來說,這令人興奮,對於我這個追尋泡沫的教授、一位屠龍者-這是媒體有時對我的稱呼。

 

但我們真的能屠龍嗎?最近我們與合作對象共同研發了一個動態系統,龍王相當於這些大迴圈。我們可在恰當時機加入細微擾動,當情況在掌控中時,可除去這些龍王。

 

「Gouverner, c'est prevoir」-統治是計畫和預測的藝術-但難道不是人類最大的缺陷之一?當面臨層出不窮的挑戰和危機時,我們有責任使社會和地球邁向穩定的道路。

 

但龍王理論帶來了希望。我們學習到多數系統具有可預測性,開發預先診斷危機的方法是可能的。因此我們可預作準備、採取對策、擔負責任,如此一來,大蕭條或歐債危機這種極端事件和危機再也無法令我們措手不及。

 

謝謝。

 

(掌聲)

 

以下為系統擷取之英文原文

About this talk

The 2007-2008 financial crisis, you might think, was an unpredictable one-time crash. But Didier Sornette and his Financial Crisis Observatory have plotted a set of early warning signs for unstable, growing systems, tracking the moment when any bubble is about to pop. (And he's seeing it happen again, right now.)
 
About Didier Sornette
Didier Sornette studies whether it is possible to anticipate big changes or predict crises in complex systems.
 
About the transcript
Once upon a time we lived in an economy of financial growth and prosperity. This was called the Great Moderation, the misguided belief by most economists, policymakers and central banks that we have transformed into a new world of never-ending growth and prosperity. This was seen by robust and steady GDP growth, by low and controlled inflation, by low unemployment, and controlled and low financial volatility.
 
But the Great Recession in 2007 and 2008, the great crash, broke this illusion. A few hundred billion dollars of losses in the financial sector cascaded into five trillion dollars of losses in world GDP and almost $30 trillion losses in the global stock market.
 
So the understanding of this Great Recession was that this was completely surprising, this came out of the blue, this was like the wrath of the gods. There was no responsibility. So, as a reflection of this, we started the Financial Crisis Observatory. We had the goal to diagnose in real time financial bubbles and identify in advance their critical time.
 
What is the underpinning, scientifically, of this financial observatory? We developed a theory called "dragon-kings." Dragon-kings represent extreme events which are of a class of their own. They are special. They are outliers. They are generated by specific mechanisms that may make them predictable, perhaps controllable.
 
Consider the financial price time series, a given stock, your perfect stock, or a global index. You have these up-and-downs. A very good measure of the risk of this financial market is the peaks-to-valleys that represent a worst case scenario when you bought at the top and sold at the bottom. You can look at the statistics, the frequency of the occurrence of peak-to-valleys of different sizes, which is represented in this graph. Now, interestingly, 99 percent of the peak-to-valleys of different amplitudes can be represented by a universal power law represented by this red line here. More interestingly, there are outliers, there are exceptions which are above this red line, occur 100 times more frequently, at least, than the extrapolation would predict them to occur based on the calibration of the 99 percent remaining peak-to-valleys. They are due to trenchant dependancies such that a loss is followed by a loss which is followed by a loss which is followed by a loss. These kinds of dependencies are largely missed by standard risk management tools, which ignore them and see lizards when they should see dragon-kings. The root mechanism of a dragon-king is a slow maturation towards instability, which is the bubble, and the climax of the bubble is often the crash. This is similar to the slow heating of water in this test tube reaching the boiling point, where the instability of the water occurs and you have the phase transition to vapor. And this process, which is absolutely non-linear -- cannot be predicted by standard techniques -- is the reflection of a collective emergent behavior which is fundamentally endogenous. So the cause of the crash, the cause of the crisis has to be found in an inner instability of the system, and any tiny perturbation will make this instability occur.
 
Now, some of you may have come to the mind that is this not related to the black swan concept you have heard about frequently? Remember, black swan is this rare bird that you see once and suddenly shattered your belief that all swans should be white, so it has captured the idea of unpredictability, unknowability, that the extreme events are fundamentally unknowable. Nothing can be further from the dragon-king concept I propose, which is exactly the opposite, that most extreme events are actually knowable and predictable. So we can be empowered and take responsibility and make predictions about them. So let's have my dragon-king burn this black swan concept.
 
(Laughter)
 
There are many early warning signals that are predicted by this theory. Let me just focus on one of them: the super-exponential growth with positive feedback. What does it mean? Imagine you have an investment that returns the first year five percent, the second year 10 percent, the third year 20 percent, the next year 40 percent. Is that not marvelous? This is a super-exponential growth. A standard exponential growth corresponds to a constant growth rate, let's say, of 10 percent The point is that, many times during bubbles, there are positive feedbacks which can be of many times, such that previous growths enhance, push forward, increase the next growth through this kind of super-exponential growth, which is very trenchant, not sustainable. And the key idea is that the mathematical solution of this class of models exhibit finite-time singularities, which means that there is a critical time where the system will break, will change regime. It may be a crash. It may be just a plateau, something else. And the key idea is that the critical time, the information about the critical time is contained in the early development of this super-exponential growth.
 
We have applied this theory early on, that was our first success, to the diagnostic of the rupture of key elements on the iron rocket. Using acoustic emission, you know, this little noise that you hear a structure emit, sing to you when they are stressed, and reveal the damage going on, there's a collective phenomenon of positive feedback, the more damage gives the more damage, so you can actually predict, within, of course, a probability band, when the rupture will occur. So this is now so successful that it is used in the initial phase of [unclear] the flight.
 
Perhaps more surprisingly, the same type of theory applies to biology and medicine, parturition, the act of giving birth, epileptic seizures. From seven months of pregnancy, a mother starts to feel episodic precursory contractions of the uterus that are the sign of these maturations toward the instability, giving birth to the baby, the dragon-king. So if you measure the precursor signal, you can actually identify pre- and post-maturity problems in advance. Epileptic seizures also come in a large variety of size, and when the brain goes to a super-critical state, you have dragon-kings which have a degree of predictability and this can help the patient to deal with this illness. We have applied this theory to many systems, landslides, glacier collapse, even to the dynamics of prediction of success: blockbusters, YouTube videos, movies, and so on. But perhaps the most important application is for finance, and this theory illuminates, I believe, the deep reason for the financial crisis that we have gone through. This is rooted in 30 years of history of bubbles, starting in 1980, with the global bubble crashing in 1987, followed by many other bubbles. The biggest one was the "new economy" Internet bubble in 2000, crashing in 2000, the real estate bubbles in many countries, financial derivative bubbles everywhere, stock market bubbles also everywhere, commodity and all bubbles, debt and credit bubbles -- bubbles, bubbles, bubbles.
 
We had a global bubble. This is a measure of global overvaluation of all markets, expressing what I call an illusion of a perpetual money machine that suddenly broke in 2007.
 
The problem is that we see the same process, in particular through quantitative easing, of a thinking of a perpetual money machine nowadays to tackle the crisis since 2008 in the U.S., in Europe, in Japan. This has very important implications to understand the failure of quantitative easing as well as austerity measures as long as we don't attack the core, the structural cause of this perpetual money machine thinking.
 
Now, these are big claims. Why would you believe me? Well, perhaps because, in the last 15 years we have come out of our ivory tower, and started to publish ex ante -- and I stress the term ex ante, it means "in advance" — before the crash confirmed the existence of the bubble or the financial excesses. These are a few of the major bubbles that we have lived through in recent history. Again, many interesting stories for each of them. Let me tell you just one or two stories that deal with massive bubbles.
 
We all know the Chinese miracle. This is the expression of the stock market of a massive bubble, a factor of three, 300 percent in just a few years. In September 2007, I was invited as a keynote speaker of a macro hedge fund management conference, and I showed to the conference a prediction that by the end of 2007, this bubble would change regime. There might be a crash. Certainly not sustainable. Now, how do you believe the very smart, very motivated, very informed macro hedge fund managers reacted to this prediction? You know, they had made billions just surfing this bubble until now. They told me, "Didier, yeah, the market might be overvalued, but you forget something. There is the Beijing Olympic Games coming in August 2008, and it's very clear that the Chinese government is controlling the economy and doing what it takes to also avoid any wave and control the stock market."
 
Three weeks after my presentation, the markets lost 20 percent and went through a phase of volatility, upheaval, and a total market loss of 70 percent until the end of the year.
 
So how can we be so collectively wrong by misreading or ignoring the science of the fact that when an instability has developed, and the system is ripe, any perturbation makes it essentially impossible to control?
 
The Chinese market collapsed, but it rebounded. In 2009, we also identified that this new bubble, a smaller one, was unsustainable, so we published again a prediction, in advance, stating that by August 2009, the market will correct, will not continue on this track. Our critics, reading the prediction, said, "No, it's not possible. The Chinese government is there. They have learned their lesson. They will control. They want to benefit from the growth." Perhaps these critics have not learned their lesson previously. So the crisis did occur. The market corrected.
 
The same critics then said, "Ah, yes, but you published your prediction. You influenced the market. It was not a prediction."
 
Maybe I am very powerful then. Now, this is interesting. It shows that it's essentially impossible until now to develop a science of economics because we are sentient beings who anticipate and there is a problem of self-fulfilling prophesies.
 
So we invented a new way of doing science. We created the Financial Bubble Experiment. The idea is the following. We monitor the markets. We identify excesses, bubbles. We do our work. We write a report in which we put our prediction of the critical time. We don't release the report. It's kept secret. But with modern encrypting techniques, we have a hash, we publish a public key, and six months later, we release the report, and there is authentication. And all this is done on an international archive so that we cannot be accused of just releasing the successes.
 
Let me tease you with a very recent analysis. 17th of May, 2013, just two weeks ago, we identified that the U.S. stock market was on an unsustainable path and we released this on our website on the 21st of May that there will be a change of regime. The next day, the market started to change regime, course. This is not a crash. This is just the third or fourth act of a massive bubble in the making. Scaling up the discussion at the size of the planet, we see the same thing. Wherever we look, it's observable: in the biosphere, in the atmosphere, in the ocean, showing these super-exponential trajectories characterizing an unsustainable path and announcing a phase transition. This diagram on the right shows a very beautiful compilation of studies suggesting indeed that there is a nonlinear -- possibility for a nonlinear transition just in the next few decades.
 
So there are bubbles everywhere. From one side, this is exciting for me, as a professor who chases bubbles and slays dragons, as the media has sometimes called me.
 
But can we really slay the dragons? Very recently, with collaborators, we studied a dynamical system where you see the dragon-king as these big loops and we were able to apply tiny perturbations at the right times that removed, when control is on, these dragons.
 
"Gouverner, c'est prévoir." Governing is the art of planning and predicting. But is it not the case that this is probably one of the biggest gaps of mankind, which has the responsibility to steer our societies and our planet toward sustainability in the face of growing challenges and crises?
 
But the dragon-king theory gives hope. We learn that most systems have pockets of predictability. It is possible to develop advance diagnostics of crises so that we can be prepared, we can take measures, we can take responsibility, and so that never again will extremes and crises like the Great Recession or the European crisis take us by surprise.
 
Thank you.
 
(Applause)

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