傳統的經濟學理論，一般假定人是理性的動物，會作出對自已最有利的選擇。可是現實中人卻不是完全理性，總是做出一些不理性的行為。這便是行為經濟學家Dan Ariely的研究項目，他發現這些不理性行為皆有特定的規律，並可以用行為經濟學的理論去解釋和預測。「誰說人是理性的」一書是他研究成果，每章用深入淺出的文字，解釋一個日常生活中，大部份人也會做的不理性行為。每個行為也有詳細的實驗說明，實驗結果在細微之處往往出人意表。他從實驗數據分析出其背後的理論，指出人類心理上的盲點。他在每章中也會並提出一些意見，讓我們善用這些行為經濟學的規律，把缺點轉化為長處。

人天性喜歡比較，但面對兩個差不多的選擇時，卻會猶疑不決。這時候如果有一個明顯比較差的偽選擇，讓其中一個選擇看起來較好，人便很容易被引導去選擇。有些商店有些高價貨物，根本從不打算買出，其作用只是讓其他貨物看起來更吸引。近二十年CEO薪金大幅上升，罪魁禍首源於證監所公開所有上市公司的CEO薪金資料，CEO們可以互相比較，誰也不想自已的薪比別人低，結果形做成惡性循環推高一眾CEO的薪金。

經濟學課本教價格由供求曲線決定，可是買方肯付出多少錢，卻有很大的非理性因素。隨意決定的定錨價格，甚至眼前無相干的一組數字，也可以左右價格的決定。人總是以為昂貴的東西比廉價的好，願意付出的價格與買來的價值不成比例。自由市場假定人是理性，才可以達至最合理的價格，然而事實上人並非理性，那某些服務如教育和醫療，或許有政府監管的必要，才不至價格不合理地高升。

人對免費的東西沒有免疫力，免費是吸引人流的不二法門，即使不是最好的選擇，人會無視機會成本和時間成本，不理非地去拿免費的東頭。網上書店免費郵寄，目的就是讓消費者買多些書。有些人為了免費入場花二個小時排隊，而其他時間的入場費才不過十元八塊，他們忘記了時間也是金錢，排隊的時間其實很昂貴。

俗語有云講錢傷感情，原來行為經濟學理論有證明。人有兩個不同的思考模式，第一個模式是講感情的社會倫理，第二個模式是冷冰的理性計算。買小禮物請食飯可以增進感情，思考時便不會斤斤計較。當提及赤祼祼的金錢回報，人們轉市場角度去思考，錢變成是成本最昂貴的工作動力。而且一但用了市場角度去思考，便很難回頭再計人情。

性慾讓人喪失理智，會令人做錯事。想不到作者竟然有實驗，可以用行為經濟學理論，去證明這個人所共知的常識。人一般沒有自制力，所以用外在力量為自已訂下死線，這樣才能更有工作效率。如果學期尾才要交的論文功課，大部份學生會拖到最後一刻才做。如果整學期中一路要交論文進度，學生會寫出來更好的論文。人不願放棄擁有的東西，已經到手便會錯誤地高估其價值。人喜歡擁有選擇的權利，但總是忘記保留選擇所須的成本，有時快刀斬亂麻作出決定更有效率。預期會改變個人觀感和感受，預期甚至可以影響身邊別人的行為和決定。

大部份人有時會不誠實，尤其是在無傷大雅的小事情上。不過只要提及聖經十戒，或專業道德約章，便可以鼓勵道德行為。拿別人放在冰箱的汽水喝不是偷，汽水很快便不見了。可是在冰箱中放同等價值的錢幣，錢卻可以原封不動沒有人偷。金錢讓人直視自已良心，不再是沒有所謂的灰色地帶，金錢的神聖價值，讓人沒有辨法找藉口，為自已的貪念開脫，金錢反且讓人更加誠實。

人這些不理性的天性，可是市場行銷學的天條。如何打廣告，如何作出定價，才能吸引消費者使錢，不知不覺間攻破他們的理性防線。不過同樣也可以把行為經濟學套用在推行政策上，去鼓勵入民去做有益行為。承認人類並非百分百理性，才能夠認清楚我們的行為原因，整理出理論並善加利用。看完這本書，我要常常反思警剔自已，不要墮入不理性思考的陷阱，並要思考如何應用在別人身上。

上次去印度時買了這本《金錢的故事》﹐想不到閱讀進度甚慢﹐時隔半年又回到印度出差﹐才有時間讀全本書寫書評。雖有這本書的名稱說是關於金錢﹐正確點來說是關係金融體係發展的歷史。作者是哈佛大學教授﹐應PBS電視台邀請﹐拍攝講述金融歷史的記錄節目。電視節目叫好叫座﹐作者亦順勢把節目內容整理出書﹐六集節目變為書中的六章。由於從電視節目改篇成書的關係﹐這本書讀起來十分容易﹐不過內容則受原裝電視節目結構的限制﹐每一章也是個獨立單元﹐讀起來缺乏連貫性。內容為遷就電視觀眾的水平﹐加入很多有趣的歷史故事﹐但前因後果的歷史分析則相對較弱。

第一章開完名義﹐講述金錢的歷史和銀行的誕生﹐從古代銅錢貨幣開始說起﹐到中世紀以貴重金屬作為媒介﹐到來各國發行紙幣取代金屬﹐到近代索性取消貨幣黃金本位﹐到最後金錢連實體也失去﹐變成電腦內的一堆數字。作者引用大量歷史資料﹐指出金錢在歷史中的重要性﹐十字東征是其中一個原因﹐是歐洲大量流失貴重金屬﹐導致貨幣供應短缺。到殖民地時代的西班牙﹐因發現印卡王國的白銀寶庫﹐一船船把白銀運回國引致嚴重通貨棚漲﹐最後弄至經濟一廞不振﹐衰失海上霸主的地位。後半段介紹文藝復興時期的Mediccis家族﹐當年的銀行主要是做貨幣對換的生意﹐利用消息靈通時間上的優勢﹐以猶太人的身份和一個家族的緊密連繫﹐發展出橫跨歐洲各國﹐富可敵國的跨國銀行。最初銀行只做存錢和商業交數﹐到了十七世紀端士銀行發明借錢﹐在假定有存戶不會同時間提出所有存款的前題下﹐銀行可以把收到的存款借出賺取利息。以前銀行主要收入靠收取手續費﹐現代的銀行已轉型變為資產和風險管理。

第二章講述債卷的誕生﹐債卷是國家向人民或外國的借錢的工具﹐最初發行主要用來支付戰爭開支。戰勝國自然有能力償還債卷﹐戰敗國的債卷則變成癈紙﹐當年買債卷可以說是在賭那個國家會打勝仗。在歐洲各國還在打來打去的年代﹐出了一名債卷專家Rothschild﹐包攬各國債卷的發行和行銷。因為戰爭說到底也是在拼財力﹐Rothschild的債卷決定足以左右一個國家的命運﹐美國內戰中南方運戰敗的其中一個原因﹐便是因為經濟實力比北方差﹐而又借不所行軍打仗所需的資金。到了十九世紀殖民地時代﹐殖民地發行的債卷﹐竟然比宗主國還有更高的評級。債卷的評級取決於還款能大﹐宗主國軍力強大很難迫他還錢﹐但殖民地債卷在宗主國有很多債主﹐宗主國有實際統治權﹐不怕殖民地走數壞賬。

第三章講述股票﹐在股票出現以前﹐公司與擁有公司的那個人關係不可分割﹐有了股票能分散公司的擁有權﹐識公司可以在市場上集資。最初的股票發行的是荷蘭的遠洋商船隊﹐因為風險大但利潤高﹐才想到以發行股票的形式去集資﹐發放股息分享利潤﹐並設立股票交易市場﹐讓想套現的人買賣股票。因為荷蘭海軍實力強大﹐遠洋商船隊是很好的投資﹐直致荷蘭的海上霸權被英國取代﹐股票的升幅高達每年27%。有股票自然會有泡沬﹐史上第一個泡沬由英國人John Law發明﹐他游說到法國皇帝給他北美殖民地的貿易專營權。他的公司用優厚股票吸引投資者﹐但本身只是一個錢滾錢的龐底騙局。他的公司因為有皇帝撐腰﹐吸引很多貴族投資﹐讓他結交政治勢力﹐還讓他當了法國的財相。泡沬最後爆煲是經濟定律﹐他既然身為法國財相﹐有能力左右法國的貨幣政策﹐便想透過貶值來阻止泡沬爆破﹐結果把法國的經濟弄得一團糟﹐埋下法國大革命的導火線。這章最後一節﹐講述本世紀華爾街股票的興衰﹐不過這些陳年歷史因為近年金融海嘯﹐早已給傳媒翻炒了多次。

第四章講述保險的發明。現在保險推銷員人見人憎﹐想不到最初保險竟然教會發明﹐用意是照顧意外離世牧師﹐遺留下來的弧兒寡婦。後來蘇格蘭人把保險應用在航運上﹐為出航的船隻提供天災人禍的保障。在發明統計學以前﹐賣保險與賭錢沒有分別﹐蘇格蘭人精於計算﹐很快便把統計學應用在保險上﹐以人口壽命計算出風險與保費的關係。蘇格蘭的寡婦基金﹐更一度是英國最大的投資公司﹐後來演變成今天的保險公司。醫療保險和年老退休保險﹐今天是左派社會福利主義的招牌﹐估不到竟然是極右派納萃德國和軍國主義的日本發明。社會福利制度的邏輯很簡單﹐國民要身體健康軍隊才會強大﹐對未來生活有潼景﹐才會為國家效忠。賣命。本世紀統計數學上有重大突破﹐直接速成風險管理基金的興起。

第五章講樓市﹐香港地產只有個炒字。估不到在歷史上﹐地產與民主原來有直接關係。英美的民主發展﹐很大程度上是源於市民要保護個人資產的需求。而民主推行的初期﹐只有樓在手的市民﹐才擁有投票權。金融海嘯源於次按﹐作者也花了很長篇幅講述按揭市場的歷史﹐並追朔美國兩大房貸公司﹐最初以追求全民有樓政治任務才成立的歷史。市民擁有房屋不單是經濟問題﹐更可以影響社會文化﹐對自由和個人權利的取態。

最後一章有點雜亂﹐講下第一代全球化即舊殖民時代的全球經濟﹐第一代全球化直到第一次世界大戰才結束。。接下來講下經濟殺手又講下索羅斯﹐不過我讀看經濟殺手的原著﹐這一節的內容沒有新意。當然不能不提諾貝爾經濟獎得主的LTCM基金﹐以為他發明的數學可以預測一切﹐卻計算漏了自身的行為會影響市場﹐結果鑲成八九年的金融風暴。最後一節講下現在全球經濟﹐中美兩大經濟巨頭的較量﹐這部文章內容水分大多﹐內容與平時報章看到的大同小異。

最後全書總結金融體系的發展歷史﹐並指出雖有經濟系統幾百年的經歷不斷進化﹐人類並不是全然經濟理性的動物﹐很多時不能作出最合適的決定。現代經濟體系複雜無比﹐但同時亦十分脆弱﹐只要爆發全球性戰爭﹐便足以破壞幾百年的經濟進化。

被騙一次怪別人存心不良﹐被騙二次只好怪自己蠢。上次給張五常的《新賣桔者言》騙了﹐竟然還再上當真金白銀買了這本《貨幣戰略論》﹐心想這本是硬皮系列經濟學書﹐應該內容言之有物﹐不會像上次本散文那麼馬虎﹐豈料還是失望而回﹐憑著無比耐性才啃完這本書。

平心而論這本書也不是全無可取之處﹐第一部份分析中國改革開放初期﹐人民幣和外匯卷一幣二率的問題﹐評論外匯管制壞處的文章﹐可說是眼光獨到有先見之明。談及港元與美元掛鈎聯繫匯率﹐更讓我增擴見聞大開眼界﹐知道聯繫匯率根本不是匯率管制﹐而是決定港幣鈔票發行量的貨幣制度。

可是餘下來整本書幾十篇文章﹐講來講去也是那三幅被﹐討論人民幣升值和貨幣下錨的問題。在序言中張五常自辯﹐說要原汁原味的保留舊文章﹐美其名讓讀者了解他思想的變化。在我看來不過是他懶躲﹐沒有好好花時間重新編輯舊文才出版。文章的內容算是很扎實﹐我認同他提出經濟學的大路原則。不過如果他肯重新編寫舊文﹐把理論重點分類整理﹐去掉多餘重覆的部份﹐大慨四分一篇幅就足夠了。

張五常在文章中經常提到以一籃子物品作貨幣之錨﹐我認為理論上是很理想的貨幣制度﹐只是他沒有花多解釋推行時的實際考慮。一籃子物品為錨的最大問題﹐是假定了貨物的供應和需求大至穩定﹐至少一籃子物品中﹐不同物品價格升跌能夠互相扺消。可是如果出現全球性的黑天鵝事件﹐影響全線物品正常的生產和運輸﹐那物品格價便按供求定律上升﹐堅守的話便要付上沉重的經濟代價﹐那一籃子物品貨幣之錨還是會守不住。如果真的這出現個情況﹐帶來的經濟恐慌比普通貨幣貶值更厲害。如果以一籃子外幣作錨﹐貨幣只是國與國間交易的媒介﹐匯率變動由貿易順差逆差決定﹐至少沒有把貨幣釘死在實質物品上﹐要考慮現實中有可能出現供求失衡的問題。

最近每天的經濟新聞﹐也講關於中美匯率的問題﹐氣氛緊張得中美要展開貿易戰。張五常對於人民幣對美元匯率的分析﹐還是停留只在中國和美國的著眼點上﹐看不見中美匯率並不只是兩國間的事﹐而是牽一髮會動全身﹐會影響所有國家的匯率。換個角度去看問題﹐不再說要人民幣迫升值﹐而是說美元對其他國家所有貨幣也要貶值﹐解決問題便簡單很多了。美國人存款率低﹐國家債台高築﹐貿易逆差大﹐還能維持高幣值才違反經濟學定律呢。

張五常是我經濟學的啟蒙老師﹐我中學唸理科班﹐會考沒有修讀經濟科﹐本與經濟學無緣。某年在家父的書房中﹐找到張五常的舊作《賣桔者言》﹐讀畢驚為天人﹐方知很多日常事物可以用經濟學去解釋。讀大學時更一口氣買了差不多張五常所有藉作﹐他那三卷《經濟解釋》深入淺出地講解經濟學﹐可謂中文經學讀物之寶。可惜近年他的文章了無新意﹐不斷重覆地自吹自擂﹐講風雪月講他玩書法玩攝影多﹐正正經經講經濟學的少﹐於是我漸漸便對他失去興趣。

上次去印度在香港轉機時﹐剛好在機場書店看見張五常的新作《新賣桔者言》。隨便匆匆地翻看目錄﹐看見這本書全部也是經濟學的文章﹐加上既然冠上《賣桔者言》之招牌﹐便草率地決定買下來。不經深思熟慮的決定總會帶來後悔﹐機場書店賣書要付正價﹐回程時去逛旺角樓上書店﹐才發現可以便宜一大截。《新賣桔者言》開頭五分一本書﹐竟然把前作《賣桔者言》的舊文搬字過紙﹐賣桔者言變成混吉者言。

第二部談論中國改革開放﹐那些兩篇文章寫於改革初期﹐觀點現在看起來有點過時。張五常的分析對中國經濟發展太過樂觀﹐只看到改革的好處﹐卻沒有看到只改革經濟﹐不改革政治埋下的炸爆。經濟學建立在信任的基礎上﹐可是張五常似乎看不到中國誠信破產導致的龐大交易費用。

第三部講經濟學定律﹐可是分析寫得太過膚淺﹐而有些定律我認為張五常更是說錯了。張五常批評股票圖表派吹水﹐但他忽略了股市短期上落最終是人為心理因素所決定。當全世界的至基金的電腦也用圖表分析去決定買賣﹐那圖表在絕大部份時間便會成為自我實現的預言。不知道張五常自大學以後﹐還有沒有進修過博奕理論﹐我便上學期剛剛讀過 。他說博奕理論是空中樓閣沒有實際用途﹐但他大慨不知道博奕理論在制度設計中的威力。工資定律我倒認同他的理論﹐可是他講一半不講一半﹐害我讀不到完整推論意猶未盡。

第四部份從觀察日常生活中﹐發掘出經濟學的規律。Freakonomic,Undercover Economist這類書在外國很流行﹐張五常的文章與其比較實屬小兒科。從香口膠說風俗習慣可以減低交易費用﹐但他卻沒有多走一步﹐指出交易費用反過來也可以影響風俗習慣。玊石拍賣過程很好奇﹐我想知過外國的玉石拍賣是否也是同樣運作﹐還是用博奕理論去設計更有效率的交易制度。中國市場的假貨現像﹐那些分析不用讀經濟學都懂﹐他怎麼又不研究吃了會死人的假蛋假鼓油。炒黃牛票的經濟分析有可取之處﹐不過文章寫得不盡不實﹐看完了還不明白如何把黃牛票抄落﹐到底老闆可不可以繞過黃牛黨﹐取回價格分歧蝕了給黃牛黃黨的租值。

第五部份講獨裁的遊戲﹐張五常對微軟壟斷一案﹐分析完全不著邊際。重點根本不在微軟有沒在壟斷OS市場﹐而是在於有沒有不公平地用OS市場的壟斷﹐去打壓其他市場的競爭對手。張五常長年在中國居住﹐可能他寫文章要附合中國國情﹐不敢正面批評共產黨﹐甚至給共產黨塗脂抹粉﹐說獨裁比民主好﹐實在看不過眼。

第六部份講國際貿易﹐他流於未免閉門造車。日日貿易似是道聽途說﹐我懷疑有沒有經得起驗證的數據。成衣配額的故事﹐我看他是馬後炮抽油水居多﹐他的思維還是停留在貨品鬥平鬥賤的水平。第七部份講中國農村﹐張五常把農村生活浪漫化﹐他好像不知道民間疾苦。就算今天餓不死﹐那明天又如何。留在中國農村生活﹐根本對未來沒有希望。第八和九部份講土地使用和公司合約本質。我認同張五常的理論﹐但嫌文章的理論不夠詳細。他亦沒有解決土地和公司中﹐權力不平衡這個問題。書本兩章講考古講未日﹐屬張五常吹水不抹嘴之言﹐只是勉強與經濟學扯上關係。

這本將會是我買的最後一本張五常的散文﹐他現在的文章給我江郎才盡的感覺。不用錢借來翻翻沒有所謂﹐但付出真金白銀便很不值﹐倒不好買外國的經濟學流行讀物好過。不過張五常始終經濟學教授﹐他寫那硬皮書系列的經濟學課本﹐我還是會照舊捧場。

去年金融海嘯華爾街投資銀行傷亡慘重﹐可是卻捧紅了「黑天鵝理論」這本書和其作者Nassim Nicholas Talech。此君投資眼光獨到甚有遠見﹐在一眾基金經理還沉醉在經濟沫的時候﹐他已經預言金融海嘯無可避免﹐來臨只是遲早的問題。金融海嘯令不少投資者一舖清袋﹐他的基金卻逆市狂賺一百二十億。Talech並非普通的華爾街基金經理﹐除了管理基金外﹐他還在大學當哲學教授﹐研究隨機率的認知論。

「黑天鵝理論」因為金融海嘯被受追捧﹐財經界人手一本在閱讀惡補。其實「黑天鵝理論」不過是在重覆他舊作Fooled by Randomness的內容。這本書早在「黑天鵝理論」登上暢銷書排行榜前﹐已被譽為華爾街奇書﹐自組成cult有一群忠實追隨者。這本書中文譯作「隨機致富的傻瓜」﹐不過我認為中文名稱譯很差﹐完全偏離了該書的原意﹐因為這本書根本和致富無關。這本書的主旨很簡單﹐一句說話可以說完﹐但同時亦挑戰大部份人的世界觀。人們以為成功全因一己努力或眼光﹐看不清楚自己命運的背後﹐往往受到隨機事件擺佈的事實。

這本書嚴格來說可以歸類為哲學書藉﹐作者通過他們華爾街打滾多年的經驗﹐輔以人類學和心理學的理論﹐說出人類腦袋總是不理解隨機率的事實。人類總是以為因果有既定關係﹐甚至自己把虛線連結﹐把沒有關係的東西憑空想像出關係。這本書分為三個部份﹐第一個部先說服讀者隨機率無處不在。在市場上很多基金經理看似很成功﹐他們以為自己投資眼光過人﹐其實他們只不過是運氣好。他們不明的隨機率﹐無視那個很細微﹐但足以令他們傾家蕩產的黑天鵝風險。在生存者偏見下(survivor bias)﹐他們看似年年賺錢﹐不過亦可以一舖輸清光。用廣東話彥語說﹐他們在玩「贏粒糖﹐輸間廠」的高風險遊戲。

第二部份作者從認知論的角度﹐去解釋隨機率是什麼﹐為什麼大部份人也掌握不到。作者引用哲學家Popper和Hume的理論﹐推翻所有金融工具的意義﹐那些全不過是在築沙子上的玩意﹐完全不能代表現實世界。書中嘗試解釋人類為什麼總是受隨機率的迷惑﹐非要找出某種因果關係才心安理得。以前我總是想不通﹐那些分析每天市場上落的財經分析員﹐到底如何知道某件新聞或公佈數據與市場上落幾十點的關係。看完此書後﹐我更加肯定那些財經分析員只不過是隨口亂說。市場每天幾個百份點的上落﹐不過是市場的雜音﹐沒有任何市場資訊﹐亦與新聞沒有任何關係。單天上落的數據不能告訴我們什麼﹐重要的是要分析趨勢。很人誤以為能夠預測等同能夠控制﹐可是預測沒有百份百的準確。若只按照預測去計劃﹐出現在控制以外的情況時﹐便會成為黑天鵝大災難。

第三部是隨機率的人生哲理﹐作者總結他的人生智慧﹐談論我們應該如何面對這個充滿隨機性的世界。結果非我們可以決定﹐但我們可以決定自己的態度。成功一定要靠運氣﹐但我們不知道運氣何時會來﹐若沒有充份的準備﹐便不能捕捉運氣來臨的一刻。明白因果關係並非必然後﹐我們要學懂抽象思考去作風險管理﹐要保障黑天鵝災難發生時的逃生門。當聽到別人說﹐這件事在歷史上從沒發生過﹐便要小心了。因為所有黑天鵝災難在發生之前﹐也是在歷史上從沒發生過。只要有可能發生的話﹐便一定遲早會發生﹐還未發生過只是時間的問題。我們要學習把隨機率應用在日常生活中﹐不要凡事也以為可以追求最大化﹐隨機率讓我們滿足既成事實的結果﹐生活要留有無法預知的空間才會快樂。

可能我當年讀碩士時﹐研究課題與隨機率有關﹐曾痛下苦功學習隨機率﹐隨機率早己融入我的思維模式﹐我覺得這本書的內容很理所當然。對於隨機率認識不深的讀者﹐這書不停衡擊讀者的固有思維﹐挑戰和覆顛讀者的世界觀。若只看介簡或撮要﹐這書的內容聽起來很玄,讀者要自己仔細讀閱咀嚼﹐才能領悟書中的道理。

上個學期沒有修讀哲學的課﹐改行走了去讀經濟學。我一直對博奕理論(game theory)深感興趣﹐可惜多次嘗試看書自修也半途而癈﹐結果還是要找人教才是最有效的學習方法。博奕理論與我主修的道德和政治哲學也有密切關係﹐哲學家正嘗試利用博奕理論去解釋社會契約的建立﹐用理性的架構去推論何謂道德和公義。

其實這個學期我沒有付學費﹐博奕理論是大班上堂﹐一個演講廳三四百個學生﹐可以偷偷地走進課室內旁聽。反正這科不用教授改文章﹐功課只是計數還逢送答案﹐我既然不需要拿學分﹐便無謂花費冤枉錢了。不過我偷上堂倒也大膽﹐不單坐第一行舉手問問題﹐教授邀請學生當博奕理論實驗的白老鼠時﹐我還膽粗粗問教授我不是學生可不可以參加。讓我親身感受博奕理論的實驗﹐順帶還贏了十二元作午飯錢。

博奕理論聽落很高深難懂﹐當中要涉及數學或許真的很難﹐又要用微積分又要用機遇率﹐不過博奕理論的慨念其實簡單易明。要找量化找出最佳平衡點不容易﹐若果只是借用其慨念作粗略估計﹐博奕理論教懂我用一個全新的角度看世界。博奕理論不單只是悶蛋經濟學﹐其原理甚至可以應用日常生活中需要作出的決擇﹐這讀課真的我讓我大開眼界﹐可以說是上了人生寶貴的一課。

上第一堂時教授已向我們說清楚﹐博奕理論並不等同現實﹐只是世界的完美模疑。但是分析這個完美世界﹐是認識清楚現實世界的第一步。先要打好理論的基礎﹐才能應付現實中不同的變化。課程的安排由淺入深﹐先讓我們學習簡單完全脫離現實的博奕賽局﹐明白最重要的幾個基礎慨念後﹐才慢慢加入越來越複雜﹐和越來越像現實的賽局變化。

博奕理論假定所有參加者(player)也是理性和小心﹐即是他們一定會作出最大回報的選擇﹐不會不小心計錯數。但博奕理論不需要假定參加者自私﹐因為利他因素也可以包括在回報的計算內。任何人學習博奕理論的起點﹐也必定是囚徒困局(prisoner dilemma)﹐兩個囚犯決定招或不招供。這是一個完美全知動態單次賽局(perfect complete static single game)﹐亦是最最最簡單的賽局模式。

納殊平衡(Nash equilibrium)是博奕理論最常聽到的名詞。納殊平衡是指所有參加者都不能作出任何單方面行動去增加自己的回報。即是賽局處於一個平衡狀態﹐你可以去預測對手的選擇﹐因為對手只不可能有更加好的選擇。數學上證實了納殊平衡必然地存在﹐教授雖然曾寫出了證明算式﹐不過那條數實在太深奧了﹐幸好我來旁聽不用考試。

劣勢策略(dominated strategy)是指不論在任何條件下﹐也有更加好選擇的選擇。一個理性的參加者﹐是永遠不會選擇劣勢策略﹐因為另一個選擇有更好回報嘛。所以我們可以用反覆刪減法(iterated elimination)﹐除去賽局中的劣勢策略﹐簡化賽局的分析﹐甚至找出賽局的答案(solution)﹐亦即是賽局納殊平衡點。

很多時賽局沒有純種策略(pure strategy)﹐即是一個可百搭所有條件的選擇﹐但一定會有至少一個混合策略(mix strategy)。混合策略是指你的最好選擇﹐便是按計算出來的機會率﹐隨機地作出某一個選擇。對手不論如何回應你的選擇﹐他的遇期回報(expected return)也不會超過納殊平衡點。

只要明白納殊平衡的慨念後﹐重覆賽局(finite game)無窮賽局(infinite game)和動態賽局(dynamic game)只是更加複雜賽局﹐其解答原理與基本賽局一樣。利用反向歸納法(backward induction)﹐找出每個子賽局的納殊平衡(sub-game Nash equilibrium)﹐再反覆推論找出整個賽局的納殊平衡。無窮賽局最特別的地方﹐是採用懲罰策略(punishment)﹐用損己損兩敗俱傷的方法﹐去迫對手不作出某些選擇。博奕理論便可以用來計算﹐最有效的懲罰策略﹐在自己損失最小的情況下﹐收到最大的阻嚇作用。在靜態賽局中﹐每一局的條件也是不變﹐而動態博奕的條件則受上一局選擇影響。

不完美賽局(imperfect information game)和不完全賽局(incomplete information game)是兩個不同變化﹐這兩個變化很容易混淆。前者是指參加者知道對手的選擇條件﹐但不知道對手曾經作出甚麼選擇。後者則是指參加者並不知道對手的選擇條件﹐只知道對手所有選擇條件的可能性。不完美賽局的解答原理同上﹐但不完全賽局則要使用貝氏納殊平衡(Bayes-Nash equilibrium)來解答。其他有趣的單元不能逐一詳例﹐如零和賽局(zero-sum game)﹐道德風險(moral hazard)﹐賽局設計(mechanical design)﹐訊息賽局(signaling game)﹐每種賽局也各有特性和用途。不過說穿了萬變不離其宗﹐納殊平衡就是解答的關鍵所在。

課程除了空談理論外﹐還有分析一些現實例子﹐好讓學生見識博奕理論的實際應用。當然那些例子中使用數據經過簡化﹐但已足以說服我博奕理論的威力。引用石油輸出國組織(OPEC)和七十年代的石油危機﹐解釋為什麼引入競爭會令市價下跌﹐而壟斷不利消費者。分析NASDAQ股市和政府債卷﹐指出金融機構私下互通狽狙為奸的害處﹐以及如何防止他們聯手造市。最令我感到如夢初醒﹐是分析英式拍賣和荷式拍賣不同﹐並指出賣方在兩者的預期收入均等。

儘管修讀了博奕理論的課﹐我不敢說自己懂博奕理論﹐我只略懂博奕理論的皮毛。我雖然不懂如可計算運用﹐但還是可以看穿那些不懂經濟學的社會學者﹐拿著博奕理論當晃子的把戲﹐不怕人家拋幾個博奕理論專有名詞便被嚇倒。讀博奕理論最有用的地方﹐還是提升我玩樸克牌的心理素質。以納殊平衡來決定如何下注﹐知道對手不可能有更好的預期回報﹐剩下來是便是賭運氣﹐看看誰的牌較大。再不用擔心對手是否偷雞作大﹐因為長線而言誰拿大牌的機會率是均等。若果對手不是以納殊平衡下注﹐在機會率上他已經輸了。真的很神奇地﹐以前我玩牌輸多贏少﹐近來玩牌就算不贏﹐也不會大輸。不講不知﹐樸克世界賽的冠軍就是個數學博士﹐是他發明了納殊平衡的玩法﹐當然他計算如何下注比我複雜很多。

說起經濟學很多人會聯想起報章上沉悶的經濟數字﹐又或者認為經濟學只是炒股票賺錢的學問。若科普讀物將科學普及化﹐那經普讀物便是將經濟學普及化﹐用一般人也看得懂的文字﹐介紹經濟學的理論和新研究﹐讓讀者醒察經濟學與日常生活息息相關。Tim Harford的前作「臥底經濟學家」﹐是簡易經濟學入門的第一課﹐新作「生命的邏輯」繼續深入淺出地為讀者解釋何謂經濟學和其功用。

經濟學的基本並不數字或方程式﹐甚至亦與金錢沒有直接關係。經濟學是解釋人類行為的學問﹐假定人類大體上按理性思考﹐並懂得計算衡量得失和成本﹐從而推論出人類作出的選擇和其原因。作者在書中每一章也提出不同的生活現像﹐抽絲剝繭地用經濟學的方法﹐讓讀者明白表面看似毫無道理的事情﹐原來背後也是跟隨經濟學的定律運行。

愛滋病橫行導至青少年口交上升。經濟學博士用博奕理論﹐奪取世界樸克冠軍。公司總裁無甚作為卻收取天價薪酬。租屋樓宇地區比自置物業地區﹐治安和社會設施較差。民主制度被小數利益團體騎劫政策。甚至連種族歧視和殖民統治這些不公義的社會現。在經濟學下原來也有合理的解釋。要改變現狀先要明白成因才能對病下藥。若果不理解清楚因果關係﹐胡亂出於好意亂投藥石﹐恐怕只會帶來始料不及的更壞情況。

例如種族歧視源於微小無意識的個人偏好﹐因為經濟定律的關係被放大而陷入惡性循環。研究指出只需在起源處作微小的改變﹐便會得出完全不同的結果。書中最實用是博奕理論玩樸克的例子﹐以前我玩樸克輸多贏少﹐不過學懂利用納殊平衡來下注﹐不受對手的心理策略影響﹐減低在牌局中犯錯的機會﹐不求一舖大勝而把每局機會率優勢的積少成多﹐慢慢逐少逐少地贏錢。

作者是個說故事的能手﹐不知不覺間便輕輕鬆鬆讀完整本書。看著作者解決書中的經濟問題趣味橫溢﹐不過其中的經濟學解釋過份簡化﹐只說明研究的結果略去全部數據。閱讀時看似言之成理﹐但細想下來那些經濟學推論﹐有點太過一廂情願想當然矣。不過這類經普讀物要照顧讀者程度和可讀性﹐不能夠詳細例出數據和推論﹐幸好書後例出所有參考資料﹐讓有興趣的讀者去自行引證。

若果我們在討論社會問題時﹐能夠用運書中的經濟學方法﹐尋找客觀可信的解釋﹐相信可以讓社會變得更美好。可是不論經濟學解釋如何充份﹐還不能夠說服立場先於道理的對手。如果宗教人士認定青少年口交上升是因為道德腐敗﹐平權人士認定種族歧視是因為白人沙文主義﹐儘管經濟學提供解釋之餘也有改變的方法﹐他們也不一定能夠虛心接受。這讓我想起香港爭取最低工資的支持者﹐他們有沒有遵守理性的指引﹐先從經濟學的角度去理解他們想要解決的問題呢。

Is it the death of efficient market hypothesis, or are we just missing some human variables from the equations?

Jul 16th 2009 – The Economist
The efficient-markets hypothesis has underpinned many of the financial industry’s models for years. After the crash, what remains of it?

IN 1978 Michael Jensen, an American economist, boldly declared that “there is no other proposition in economics which has more solid empirical evidence supporting it than the efficient-markets hypothesis” (EMH). That was quite a claim. The theory’s origins went back to the beginning of the century, but it had come to prominence only a decade or so before. Eugene Fama, of the University of Chicago, defined its essence: that the price of a financial asset reflects all available information that is relevant to its value.

From that idea powerful conclusions were drawn, not least on Wall Street. If the EMH held, then markets would price financial assets broadly correctly. Deviations from equilibrium values could not last for long. If the price of a share, say, was too low, well-informed investors would buy it and make a killing. If it looked too dear, they could sell or short it and make money that way. It also followed that bubbles could not form—or, at any rate, could not last: some wise investor would spot them and pop them. And trying to beat the market was a fool’s errand for almost everyone. If the information was out there, it was already in the price.

On such ideas, and on the complex mathematics that described them, was founded the Wall Street profession of financial engineering. The engineers designed derivatives and securitisations, from simple interest-rate options to ever more intricate credit-default swaps and collateralised debt obligations. All the while, confident in the theoretical underpinnings of their inventions, they reassured any doubters that all this activity was not just making bankers rich. It was making the financial system safer and the economy healthier.

That is why many people view the financial crisis that began in 2007 as a devastating blow to the credibility not only of banks but also of the entire academic discipline of financial economics. That verdict is too simple. Granted, financial economists helped to start the bankers’ party, and some joined in with gusto. But even when the EMH still seemed fresh, economists were picking holes in it. A strand of sceptical thought, behavioural economics, has been booming. There are even signs of a synthesis between the EMH and the sceptics. Academia thus moved on, even if Wall Street did not. Nonetheless, the extent to which politicians and regulators trying to reform finance can trust financial economists is an open question.

The EMH, to be sure, has loyal defenders. “There are models, and there are those who use the models,” says Myron Scholes, who in 1997 won the Nobel prize in economics for his part in creating the most widely used model in the finance industry—the Black-Scholes formula for pricing options. Mr Scholes thinks much of the blame for the recent woe should be pinned not on economists’ theories and models but on those on Wall Street and in the City who pushed them too far in practice.

Financial firms plugged in data that reflected a “view of the world that was far more benign than it was reasonable to take, emphasising recent inputs over more historic numbers,” says Mr Scholes. “Apparently, a lot of the models used for structured products were pretty good, but the inputs were awful.” Indeed, the vast majority of derivative contracts and securitisations have performed exactly as their models said they would. It was the exceptions that proved disastrous.

Mr Scholes knows whereof he speaks. Long-Term Capital Management (LTCM), a hedge fund he founded with, among others, Robert Merton, a fellow Nobel laureate, skidded off the road in 1998. Since then, he has been pointing out dangers ignored or underestimated in the finance industry, such as the risk that liquid markets can dry up far faster than is typically assumed. (That did not stop Platinum Grove, the latest hedge fund in which he is involved, taking a big hit during the recent meltdown.)

He has also been “criticising for years” the “value-at-risk” (VAR) models used by institutional investors to work out how much capital they need to set aside as insurance against losses on risky assets. These models mistakenly assume that the volatility of asset prices and the correlations between prices are constant, says Mr Scholes. When, say, two types of asset were assumed to be uncorrelated, investors felt able to hold the same capital as a cushion against losses on both, because they would not lose on both at the same time. However, as Mr Scholes discovered at LTCM and as the entire finance industry has now learnt for itself, at times of market stress assets that normally are uncorrelated can suddenly become highly correlated. At that point the capital buffer implied by VAR turns out to be woefully inadequate.

Even as financial engineers were designing all sorts of clever products on the assumption that markets were efficient, academic economists were focusing more on how markets fall short. Even before the 1987 stockmarket crash gave them their first real-world reminder of markets’ capriciousness, some of them were examining the flaws in the theory.

In 1980 Sanford Grossman and Joseph Stiglitz, another subsequent winner of a Nobel prize, pointed out a paradox. If prices reflect all information, then there is no gain from going to the trouble of gathering it, so no one will. A little inefficiency is necessary to give informed investors an incentive to drive prices towards efficiency. For Mr Scholes, it is the belief that markets tend to return prices to their efficient equilibrium when they move away from it that gives the EMH its continuing relevance.

Economists also began to study “institutional frictions” in markets. For instance, the EMH’s devotees had assumed that smart investors would be able to trade against less well-informed “noise traders” and overwhelm them by driving prices to reflect true value. But it became clear that there were limits to their ability to arbitrage folly away. Andrei Shleifer, a Harvard economist, among others, pointed out that it could be too costly for informed investors to borrow enough to bet against the noise traders. Once it is admitted that prices can move away from fundamentals for a long time, informed investors may do best by riding the trend rather than fighting it. The trick then is to get out just before momentum shifts the other way. But in this world, rational investors may contribute to bubbles rather than preventing them.

In the early years of the EMH, researchers spent little time worrying about the workings of financial institutions—a weakness of macroeconomics too. In 2000, in his presidential address to the American Finance Association, Franklin Allen, of the University of Pennsylvania’s Wharton School, asked: “Do financial institutions matter?” Lay people, he said, “might be surprised to learn that institutions play little role in financial theory.” Indeed they might. Mr Allen’s explanation was partly that the dominant theories had been shaped at a time when America, especially, was spared financial crises.
Illustration by Brett Ryder

In the past decade or so, financial economists have been paying more attention to institutional questions, such as how bankers should be paid. Many of these researchers broadly accept the EMH, but see their role as uncovering sources of inefficiency that can be addressed to make markets more efficient.

However, a second branch of financial economics is far more sceptical about markets’ inherent rationality. Behavioural economics, which applies the insights of psychology to finance, has boomed in the past decade. In particular, behavioural economists have argued that human beings tend to be too confident of their own abilities and tend to extrapolate recent trends into the future, a combination that may contribute to bubbles. There is also evidence that losses can make investors extremely, irrationally risk-averse—exaggerating price falls when a bubble bursts.

Behavioural economists were among the first to sound the alarm about trouble in the markets. Notably, Robert Shiller of Yale gave an early warning that America’s housing market was dangerously overvalued. This was his second prescient call. In the 1990s his concerns about the bubbliness of the stockmarket had prompted Alan Greenspan, then chairman of the Federal Reserve, to wonder if the heady share prices of the day were the result of investors’ “irrational exuberance”. The title of Mr Shiller’s latest book, “Animal Spirits” (written with George Akerlof, of the University of California, Berkeley), is taken from John Maynard Keynes’s description of the quirky psychological forces shaping markets. It argues that macroeconomics, too, should draw lessons from psychology.

“In some ways, we behavioural economists have won by default, because we have been less arrogant,” says Richard Thaler of the University of Chicago, one of the pioneers of behavioural finance. Those who denied that prices could get out of line, or ever have bubbles, “look foolish”. Mr Scholes, however, insists that the efficient-market paradigm is not dead: “To say something has failed you have to have something to replace it, and so far we don’t have a new paradigm to replace efficient markets.” The trouble with behavioural economics, he adds, is that “it really hasn’t shown in aggregate how it affects prices.”

Yet EMH-ers and behaviouralists are increasingly asking the same questions and drawing on each other’s ideas. For instance, Mr Thaler concedes that in some ways the events of the past couple of years have strengthened the EMH. The hypothesis has two parts, he says: the “no-free-lunch part and the price-is-right part, and if anything the first part has been strengthened as we have learned that some investment strategies are riskier than they look and it really is difficult to beat the market.” The idea that the market price is the right price, however, has been badly dented.

Mr Thaler also says that only some of the recent problems were behavioural. Many were due to things that are open to non-behavioural economics, “like better risk analysis, how we identify hidden correlations.” It will be no surprise if, thanks to the catalytic power of the bubble and market meltdown, the distinctions between the two camps disappear and a new paradigm emerges.

One economist leading the effort to define that new paradigm is Andrew Lo, of the Massachusetts Institute of Technology, who sees merit in both the rational and behavioural views. He has tried to reconcile them in the “adaptive markets hypothesis”, which supposes that humans are neither fully rational nor psychologically unhinged. Instead, they work by making best guesses and by trial and error. If one investment strategy fails, they try another. If it works, they stick with it. Mr Lo borrows heavily from evolutionary science. He does not see markets as efficient in Mr Fama’s sense, but thinks they are fiercely competitive. Because the “ecology” changes over time, people make mistakes when adapting. Old strategies become obsolete and new ones are called for.

The finance industry is in the midst of a transformative period of evolution, and financial economists have a huge agenda to tackle. They should do so quickly, given the determination of politicians to overhaul the regulation of financial markets.

One task, also of interest to macroeconomists, is to work out what central bankers should do about bubbles—now that it is plain that they do occur and can cause great damage when they burst. Not even behaviouralists such as Mr Thaler would want to see, say, the Fed trying to set prices in financial markets. He does see an opportunity, however, for governments to “lean into the wind a little more” to reduce the volatility of bubbles and crashes. For instance, when guaranteeing home loans, Freddie Mac and Fannie Mae, America’s giant mortgage companies, could be required to demand higher down-payments as a proportion of the purchase price, the higher house prices are relative to rents.

Another priority is to get a better understanding of systemic risk, which Messrs Scholes and Thaler agree has been seriously underestimated. A lot of risk-managers in financial firms believed their risk was perfectly controlled, says Mr Scholes, “but they needed to know what everyone else was doing, to see the aggregate picture.” It turned out that everyone was doing very similar things. So when their VAR models started telling them to sell, they all did—driving prices down further and triggering further model-driven selling.

Several countries now expect to introduce a systemic-risk regulator. Financial economists may have useful advice to offer. Many of them see information as crucial. Data should be collected from individual firms and aggregated. The overall data should then be published. That would be better, they think, than a system based solely on the micromanagement of individual institutions deemed systemically significant. Mr Scholes favours relying less on VAR to calculate capital reserves against losses. Instead, each category of asset should have its own risk-capital reserves, which could not be shared with other assets, even if prices had not been correlated in the past. As experience shows, correlations can change suddenly.

Financial economists also need better theories of why liquid markets suddenly become illiquid and of how to manage the risk of “moral hazard”—the danger that the existence of government regulation and safety nets encourages market participants to take bigger risks than they might otherwise have done. The sorry consequences of letting Lehman Brothers fail, which was intended to discourage moral hazard, showed that the middle of a crisis is not the time to get tough. But when is?

Mr Lo has a novel idea for future crises: creating a financial equivalent of the National Transport Safety Board, which investigates every civil-aviation crash in America. He would like similar independent, after-the-fact scrutiny of every financial failure, to see what caused it and what lessons could be learned. Not the least of the difficulties in the continuing crisis is working out exactly what went wrong and why—and who, including financial economists, should take the blame.

I am taking game theory not only because I am interested in economics, it is also I need this knowledge for more advance moral or political philosophy. Utilitarianism is always and will always be an important moral or justice theory. There are new research to field on applying game theory concept to calculate the utility function to determine whether something is moral or evil. Knowing game theory will give allow me to give more quantitative argument when I am making a moral claim.

In this course, I am using Wiki to take lecture notes. My ultimate goal is to create a knowledge database for my studies and I am experimenting with Wiki. Here is my lecture notes

這本書在大陸的譯名叫魔鬼經濟學﹐此書的觀點理論雖然和傳統經濟學不同﹐但內容十分正派並不是在妖言惑眾。在台灣的譯名叫蘋果橘子經濟學﹐名字有點無厘頭﹐取名的原因只不過是封面畫了個切開是橙的蘋果。若果給我選擇譯名﹐我會譯為古靈精怪經濟學﹐簡單而直接沒有嘩眾取寵。這本書去年在經濟學人雜誌已經有介紹﹐那時已加入我那長長的想看書單上。早幾個星期看見梁文道寫的書評﹐不知何解心血來潮立即想要看﹐於是放工走去書局打書釘自了兩章﹐回家馬上從網上訂本寄來。

作者是經濟學重鎮芝加哥大學的教授﹐他和紐約時報的記者合著這書。書中的論點是他多年分析經濟數據﹐得出幾個很令人意不到的結果。那個記者的主要工作﹐就是如何把那些可能悶死人的經濟理論﹐用說故事的方法富有趣味地表達出來。其實這本書的重點可以幾句說完﹐不過吸引讀者的地方﹐是運用簡單的經濟理論﹐把數劇抽絲剝繭﹐像偵探查案般一步步找出結論。書中每章是一個獨立案例﹐最為人津津樂道是開頭的幾個案例﹐教師為什麼會學生出貓﹐3K黨和地產經紀的相同之處﹐以及這本書賣廣告的重點主打﹐毒犯多數為什麼和母親同住。

第四章的論點十分具爭議性﹐差點讓這本書在某些保守地方列為禁書。過去十幾年美國犯罪率下降的主要原因﹐是因為幾十年前墮胎合法化。母親沒法墮胎而生下來的小孩﹐很多是在貧窮的單親家庭長大﹐長大後變為罪犯機會率特別高。墮胎合法化一個讓人想不到的副作用﹐就是那些末來罪犯沒有機會出世。兩者看似沒有直接關係﹐但作者提出的數據不得不讓人至少認真考慮這個理論的可能性。作者多次強調經濟學只是指出事實的因果關係﹐不涉及道德對錯的判斷。他只是負責計數﹐大慨少生一百個沒人要的罪犯﹐就可以減少一完謀殺案。一百個未出世的胎兒﹐還是一條實在活生生的人命重要﹐讀者請自行判斷。

最後兩章是講為人父母望子成龍﹐用濟經分析去探討一下兩個常見的現像。很多父母在子女出世時﹐攪盡腦汁替子女改個好名﹐希望日後可以飛黃騰達。到了子女年紀大一些﹐要千辛萬苦送子女入名校﹐還要管接管送上課外活動。父母為子女所做的一切﹐究竟有沒有用呢﹖結論相當然不是像表面那樣簡單﹐固然不能否定父母的功勞﹐但原來教仔也是大有學問﹐結論頗為曲折離奇﹐不然也不用特別收錄在這本古怪經濟學當中了。

看這本書的最大得著﹐不是止於僅僅知道到書中研究的那幾個案例。而是研究的過程讓我大開眼界﹐跳出既定的思維模式﹐廣闊思考水平。書中很多道理說出來其實很簡單﹐不過平常人就是想不到。有時看完結論後會哦的一聲﹐有點像發現每天見的朋友原來是外星人。原來日常生活身邊的事物﹐只要用心觀察平凡中也會有新發現。
看起來荒謬的假設﹐在細心驗證推敲下﹐竟然才是事實的真相。