少年：我能先回答你第一个问题吗。。不能。
Sep 24, 2015
Sep 2, 2015
Sep 1, 2015
Aug 30, 2015
Aug 9, 2015
#无题 2015/08/09
一年来，少年都在游说姑娘放弃使用多年的Thinkpad；“你可以用我的chromebook嘛！” 终于老thinkpad在升级win10之后招架不住，被姑娘宣布寿终正寝。“太好了，”少年抑制不住笑容，“我可以给他装上Linux了！”
Jul 8, 2015
May 14, 2015
#记一件小事 2015/05/14
Trade review 一而再再而三delay，反反复复折腾到了快十点，想着打个车回家直接钻被窝看书，结果叫了出租车迟迟不来，接线员每次都说，就在附近了就在附近了，最后等了四十五分钟也没等到车。一气之下，不坐了！
回到家楼下看到不知哪家订的鲜花快递，突然触动了哪根筋，大哭起来。不走运的时候，果然看什么都悲观起来了。
一进家门，手机显示少年的未接来电。“你到家了吗？我在你楼下了。”
这不是所有姑娘梦寐以求的那句台词嘛！还有什么想不开的呢？
May 10, 2015
Apr 5, 2015
Mar 15, 2015
Mar 5, 2015
Feb 24, 2015
#Course Review# Energy 101: The Big Picture
This course is provided by Georgia Institute of Technology (via Coursera). The instructor is Dr. Sam Shelton, a nationally recognized expert in energy systems and the founding director of the Georgia Tech Strategic Energy Institute.
Summary of the course:
* US primary energy issues:
1) Carbon emissions;
China and US are the top 2 carbon emission countries: in 2010, China ~ 8000 million metric tons; US ~ 6000 million metric tons (annual emissions).
2) Oil dependence
By 2010, ~60% US oil consumption is imported. US is energy-independent for coal and gas (used for electricity power generation).
* How to solve?
Understand US energy details -> Develop energy technology -> Deploy solutions
Energy flow: Natural fuel -> Conversion process -> Society use
First law of thermodynamics: Energy is conserved. Total energy cannot be created or destroyed.
Second law of thermodynamics: All forms of energy do Not have equal value ("energy quality").
* US energy use
Total energy consumption: Buildings 41%; Manufacturing 31%; Transportation 28%
(US) Energy consumption and GDP are highly correlated.
US oil price is set by world supply and demand.
US oil consumption by sector: Transportation 72%; Manufacturing 23%
How to reduce carbon emission?
- Solar / Wind / Nuclear electric power generation
- High MPH vehicles
- Ethanol fuel for transportation
- Higher efficiency electric heating / air conditioning
In US, wind power density variation from region to region: a factor of 10
For solar, it is only a factor of 2 (more uniform nationwide)
US total energy source:
Coal > Natural Gas > Oil > Nuclear > Biomass > Hydro > Wind > Geothermal > Solar
Energy policy should be based on fact, not industry lobby.
Summary of the course:
* US primary energy issues:
1) Carbon emissions;
China and US are the top 2 carbon emission countries: in 2010, China ~ 8000 million metric tons; US ~ 6000 million metric tons (annual emissions).
2) Oil dependence
By 2010, ~60% US oil consumption is imported. US is energy-independent for coal and gas (used for electricity power generation).
* How to solve?
Understand US energy details -> Develop energy technology -> Deploy solutions
Energy flow: Natural fuel -> Conversion process -> Society use
First law of thermodynamics: Energy is conserved. Total energy cannot be created or destroyed.
Second law of thermodynamics: All forms of energy do Not have equal value ("energy quality").
* US energy use
Total energy consumption: Buildings 41%; Manufacturing 31%; Transportation 28%
(US) Energy consumption and GDP are highly correlated.
US oil price is set by world supply and demand.
US Oil Trend
US oil consumption by sector: Transportation 72%; Manufacturing 23%
Oil vs Petroleum: petroleum includes oil, natural gas liquids and ethanol
- Solar / Wind / Nuclear electric power generation
- High MPH vehicles
- Ethanol fuel for transportation
- Higher efficiency electric heating / air conditioning
In US, wind power density variation from region to region: a factor of 10
For solar, it is only a factor of 2 (more uniform nationwide)
US total energy source:
Coal > Natural Gas > Oil > Nuclear > Biomass > Hydro > Wind > Geothermal > Solar
Energy policy should be based on fact, not industry lobby.
Feb 23, 2015
Feb 16, 2015
情人节快乐！
2015年的情人节，姑娘受邀来到了位于波士顿剑桥区的小李魔法厨房。当晚，先由司机小李亲自带着（菜市场买的）花儿（why not），冒着巨大的风雪，千里迢迢来到布鲁克莱区接上姑娘。一路上，姑娘拐弯抹角地追问Tasting Menu有些什么，小李却只是神秘地笑笑。姑娘知道，小李一半是出于专业司机兼保镖的professional discretion，另一半，则是挂记着厨房里没关火的锅呀。
终于到了！魔法厨房的门开启了。Bar Tender小李给姑娘倒上了一杯上好的威士忌。为了照顾姑娘的口味，小李贴心地在酒中浸入了橘子，以中和威士忌的苦与烈。
今晚的第一道菜是沙拉，是主厨小李的原创菜品。饱满的龙虾肉，配上甜脆的榛仁、鲜嫩的蔬菜，用白葡萄醋略加调味，尤其爽口开胃。草食动物的姑娘凭着超人自制力，才忍住没要second serving。
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| 巨大的风雪 （示意图） |
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| 香橙威士忌与菜市场花 |
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| 第一道 龙虾榛子沙拉 |
第二道菜是热汤，暖暖的正合适这糟糕的鬼天气。蘑菇煮到软烂再经blender打得细碎，在百里香的点缀下，一股浓浓的欧洲田园风情伴着香气，从汤碗里一跃而出。值得一提的是，为搭配这道texture上略显单一的菜品，小李惊喜地变出来了几枚可爱的烤鱿鱼圈，作为汤的佐食。
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| 第二道 蘑菇浓汤 |
沙拉和汤过后，就进入到主菜的阶段了。首先是一道白酒奶香海虹。这道菜看似简单，但味道极具层次感。白酒、柠檬、洋葱、香菜巧妙地平衡了海虹本身的鲜腥，而炖煮中酸奶油的使用更是点睛之笔：奶油的浓郁给整道菜增加了质感，而酸酸的味道又不让人觉得腻烦。小李本人认为这是当晚最成功的菜品！
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| 第三道 白酒奶香海虹 |
今晚的压轴菜是海鲜墨鱼意面。主厨小李为了采购新鲜的墨鱼面，不远万里驱车去了Somerville的一家历史悠久的意大利专营粮店。在店里老板的推荐下，小李选择了秘制的复合型番茄酱，搭配带子和鱿鱼碎。相比其他店里的墨鱼面，这道菜毫不油腻，面的整体口感偏软，有Asian-fusion的感觉。
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| 第四道 墨鱼意面 |
一顿海鲜大餐过后，考虑到食客的饭量，小李没有准备甜点，而是端上了三枚巧克力，可谓四两拨千斤。Barista小李当场制作了手冲咖啡，为整顿饭画上了完美的句点。
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| 巧克力和咖啡 |
第二天一早，恋爱中的小李从冰箱里取出深夜制作的提拉米苏作为早餐。
“嘿，我的pastry chef也不差嘛！”
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| 自以为是马蒂尼的提拉米苏 |
By 姑娘，
小李魔法厨房 Eater / Food Critic / Sous Chef / Pastry Chef
无题 2015/02/15
少年说起Mega Millions彩票。
少年：“每个人中奖的概率都是0，但所有人加在一起的中奖概率却是1……”
姑娘（想）：少年这是要讨论数学问题还是哲学问题呢
少年：“……这就说明我就是那个1啊！我不去买彩票实在是可惜了。”
少年：“每个人中奖的概率都是0，但所有人加在一起的中奖概率却是1……”
姑娘（想）：少年这是要讨论数学问题还是哲学问题呢
少年：“……这就说明我就是那个1啊！我不去买彩票实在是可惜了。”
Jan 30, 2015
纽约：2014/15冬日行美食篇
最近一个月好任性！说走就走跑去纽约玩了两趟，基本文青路线：白天逛博物馆、看演出、轧马路，晚上宵夜、喝酒，末了回SOHO小清新酒店一觉睡到日上三竿。文艺方面的心得就留给风流倜傥的副博主啦，博主还是专门来说说好吃的 =)
【Restaurants】
Korchma Taras Bulba
357 West Broadway
约了四五个在纽约生活的同学聚餐，于是他们推荐了这家位于SOHO的乌克兰餐厅。
这家店走的是东欧田园风情，服务员都穿传统民族服饰，从口音和长相看应该都是土生土长的乌克兰人。帮我们点餐的小哥介绍起Chicken Kiev还自豪地说：“所有乌克兰小孩都吃过祖母做的这道菜”，颇有一种四川人说起回锅肉的感觉。这里还提供各种语言写的菜谱，不过有些翻译实在让人哭笑不得：“暴打三文鱼乌克兰语沙拉在床上”？
前菜cured herring under a vegetable coat (Shuba)是一种卖相独特的沙拉，由生鱼碎、胡萝卜、甜菜、土豆鸡蛋沙拉一层一层地叠起来组成，上菜的时候切成块状，看起来好像蛋糕一样。这里也能吃到高大上的新鲜鱼子，好这口的可以尝试鱼子煎饼（blini）或者主菜中的鱼子酱佐三文鱼（salmon royale）。
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| Shuba |
15 East 15th Street
米其林一星日本料理。朋友叮嘱预约时要要求served by Chef Masato at the sushi bar，可惜这次计划的比较仓促，所以最后就订在dining room。据网友透露，这家店dining room的菜由学徒全权负责，不经chef之手，所以并不能体现这家店的水平。不得不说，我们这次吃到的寿司拼盘着实并没有被惊艳到，甚至让（付账的）少年发出了“看来好的寿司也就这样了”的感叹。看来不能以偏概全、丧失信心，要继续探索下去呀！
特别推荐的是这家的前菜，烟熏黑猪肉（smoked Kurobuta）。五花肉软烂丰腴，配上碾碎的茶叶和微甜的苹果，温软的口感中和了略重的口味，让不吃肥肉的博主都忍不住多吃了两口。点到这道菜还要特别感谢当晚的服务员推荐，一位鞠躬永远鞠成直角的精瘦美国大叔，真是客气得叫人脊背阵阵发凉呢。
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| Smoked Kurobuta |
【Cafe / Bakery / Desserts】
189 Spring Street
终于来到了大名鼎鼎的cronut的诞生地！Cronut真是当代烘焙界一大神话，据说还有投行为了impress clients（呵呵），派小实习生天没亮就来排队买。“有钱，就是任性！”
早上11点左右到店，想买Cronut是没希望啦，于是尝试了Serious Eats大力推荐的DKA和Frozen S'more。DKA即Dominique's Kouign Amann：Kouign Amann是一种传统法式糕点，质地上结合了croissant的酥脆和brioche的软润，外面裹有一层薄薄的焦糖，甜甜的恰到好处（速冻版Trader Joe's有售）。Frozen S'more外表看起来是一个插在长木棍上的巨型棉花糖，点餐后服务员会当场用高温喷枪来烤制。棉花糖里包有一方香草冰激淋，但略有点解冻不足，吃的时候还是硬邦邦的。但让人惊喜的是棉花糖和冰激淋中间夹着的巧克力脆饼屑，让本来白乎乎软塌塌的一款甜点一下就有了精气神，可谓是神来之笔。 名不虚传，博主立志把这里所有的原创单品都尝一个遍！
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| Frozen S'more |
198 9th Avenue
日本“贵妇级”甜品店HARBS在纽约开的分店，主打花式蛋糕，兼营各种饮品和轻食。小店让人一进门就感觉很舒服，属于低调的复古西洋风；就餐区域也十分很宽敞，很适合女孩子们聊天小聚。蛋糕都是做好的10寸庄，摆在点餐区玻璃柜台里，现卖现切现取。店员向我们推荐了可丽饼蛋糕，基本就是夹了水果的Lady M，相比原版少了一些甜腻，但整体还是略显死板单调，不做特别推荐。不过看到一款带栗子茸的蛋糕（Waguri Tarte），心里颇为长草，下次要来尝试！反倒是配的柚子煎茶（Yusu Sencha）让人印象深刻：绿茶配柚子的清香尤其招人喜欢，只可惜茶叶店里不卖 =(
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| Mille Crepe & Yuzu Sencha |
【Late Night】
DBGB Kitchen and Bar
299 Bowery Street
DBGB是米其林三星厨师Daniel Boulud旗下的一家美法混血Casual Dinning，比起他家的主店来，菜品和价格走的都是亲民路线。不过我们这次来的目的明确：（姑娘）Dessert +（少年）Cocktail！到店的时候都已经是深夜了，结果两个人在吧台一直坐到了后厨打烊，美美的。
上来先点了两杯当家的招牌调酒：White Cosmo (vodka, st. germain elderflower liqueur, white cranberry, lime)和DB Tea (earl grey vodka, lemon juice, soda)。结果一喝就震惊了：好喝！妙就妙在酒中各种味道相生相克、非常balanced，整体既不会overpowering、也不会boring。Bar tender小哥更是料事如神，第二杯自由发挥给少年调了杯old fashioned；已然微醺的少年激动地对bar tender表白道，“你是懂我的！” ——喂，少年你这也太容易被收买了吧！
在小哥的推荐下，甜点选择了热舒芙蕾（Souffle Chaud）。其实点的时候颇为犹豫，因为博主对souffle一直不太感冒，认为就是fold in奶制品的打发鸡蛋糕，“有个微波炉就可以做嘛”。但这次吃到的这道Souffle Chaud彻底拯救了它在博主心目中的形象：souffle向上膨胀得均匀服帖，糕体更是轻盈得就像一小团空气，淋上温热的英式香草奶油酱之后吃上一口，心里都觉得柔软起来了。
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| White Cosmo + DB Tea |
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| Souflle Chaud |
Katz's Delicatesse
205 East Houston Street
DBGB两杯酒下肚之后已经是凌晨，两个人判断力尽失，又及其嚣张地跑来了24小时营业的Katz's Deli。这是家纽约老字号，以熏肉（Pastrami）三明治闻名于世，据说早年间学(sheng)生(huo)时(jie)代(ju)的艾未未也常常光顾这里。在这里吃饭的流程好像食堂/粮店一样，要凭饭票去窗口点餐，现点现做；让人惊讶的是，大半夜居然还要排队点餐，可见这里平时得有多火爆！我们慕名而来，就要了一份Pastrami sandwich：毋庸置疑这里的Pastrami是吃到过最好吃的，多汁柔软、不柴不腻、风味十足。喜欢熏肉的千万不要错过！
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| Pastrami sandwich (half) |
Jan 26, 2015
#波士顿周边＃ P|E|M (Peabody Essex Museum)
P|E|M位于距离Boston车程35分钟的小镇Salem。提到Salem，大家最先联想到的是女巫镇。殊不知在这个历史悠久的小镇上还坐落着一个别有味道的美术馆 P|E|M，十分适合打发一个懒散的冬日下午。
P|E|M的面积不大，3个小时足够粗略的转一圈。听说新馆的扩建工程还在进行中，到2019年完工时，P|E|M将跻身全美前10的美术馆行列。P|E|M的展品非常有特色，而且展品的摆放体现了新一代美术馆的特色。相比于MoMA和MFA等传统艺术馆按年代摆放作品，P|E|M的展品是按主题陈列，同一个主题下的相邻作品常常有几百年的跨度，让观者在移步换景时有时间穿越的感觉。
P|E|M展品的亮点主要有三个：
1) 荫餘堂，一座建于清代年间 (~1800) 的安徽民宅。这座两层的建筑被完完整整地从安徽搬到P|E|M。
2）以航海为主题的展品，包括精致的船模，船首像，航海导航的工具等等。
3）一两百年前通过航海贸易从中国，日本和印度出口的瓷器，首饰，家具等工艺品。
Jan 19, 2015
#读书笔记 #2 Asset Management
Author: Andrew Ang, Professor at Columbia Business School.
主要观点：
PART 1 - THE ASSET OWNER
Chapter 1 Asset Owners
以贫困的Timor-Leste（东帝汶民主共和国）为例子，引出asset management的重要性。进而分类探讨几类asset owner：主权财富基金(sovereign wealth fund)，养老基金(pension fund)，捐赠受托基金(foundations and endowments)，个人与家庭。
东帝汶的例子很有趣。这是个很穷的国家，人均GDP仅有1000美元左右，但其主权基金却有高达120亿美元的资产！这些钱主要来自东帝汶的石油产业。一个穷得叮当响国家，为什么把卖油赚的钱了存起来，而没有“花在刀刃上”呢？一个重要的考虑是预防荷兰病(Dutch disease)：中小国家发现自然资源后大力开采，容易导致其他产业相继衰落，并且货币升值、国际竞争力下降。一旦所依赖的大宗商品价格下跌，对经济的影响将是致命的。历史上，挪威就曾经吃过大亏：80年代油价下跌，依赖石油出口的挪威马上被打入了一段漫长的零增长。如果在大宗商品繁荣时期对外汇有所储备，困难时期就可以拿出来实施经济政策和扶植其他产业。有趣的是，东帝汶的主权基金正是在挪威人的建议下创建的，而挪威自己时至今日仍然拥有着世界上最大的主权基金。
Chapter 2 Preferences
Mean-variance utility有许多不足。比如，它并不要求return服从正态分布；而当return不是正态分布时，仅仅依赖first 2 moments是不够的。又如方差不区分涨和跌，而投资者对涨和跌是不对称的。
Chapter 3 Mean-Variance Investing
讨论diversification benefits和mean-variance optimization。作者比较了几种不同的portfolio construction（用4 broad asset classes）的Sharpe ratio：
为什么unconstrained mean-variance表现差？需要估计的东西太多，而对first moments的估计非常noisy。事实上，Sharpe ratio高的几种策略本质上就是CONSTRAINED mean-variance portfolio，三者都避开了对expected return的估计：
此外，仅依靠历史数据来算各资产的mean和variance是危险的，尤其当sample比较短的时候（pro-cyclicality）：最近return高，意味着现在价格高，E(r)应该更低才对。
Chapter 4 Investing for the Long Run
Re-balance是一种short volatility的投资策略，有negative convexity（lower/higher exposure when price is high/low），和selling put option类似。和所有short volatility strategy一样，re-balancing earns risk premium。
Rebalance有premium可以赚的另一个原因是liquidity provision。股价下跌，是因为有人想要卖掉该股票，而此时去买它就是提供了liquidity。
本章案例讲的是金融危机后的private wealth management。有趣的是，在重大损失之后，人们往往会改变投资策略，但其中的原因很少是因为risk aversion变化，而是因为expectation的变化。
PART 2 - FACTOR RISK PREMIUMS
Chapter 6 Factor Theory
作者以CAPM为切入点，讨论了它的不足和启示。值得注意的是，虽然这一模型有很多问题，但75%的CFO在capital budgeting的时候会使用它：What the market uses to price asset is the correct asset pricing model?
Chapter 7 Factors
本章依次介绍了几个常见Factor。
首先介绍了Macro Factor：经济增长、通货膨胀、Volatility等。这些因素之所以成为factor因为他们和average投资者的“BAD TIME”息息相关：低增长/高通胀是坏消息。一般而言宏观factor的变化，尤其是非预期的变化（shock），比水平（level）更重要。需要注意的是，资产回报对这些factor的反应是contemporaneous的。
作者尤其强调了volatility as a risk factor。历史上，volatility和stock return呈负相关，这一相关性的渠道有二：其一是leverage effect，当股票下跌时，公司的D/E变大，使得其股票风险更大、volatility更高；其二是time-varying risk premium，volatility变高时，discount rate变高，进而导致股票下跌。Volatility的price of risk是负的；collect risk premium的方式是short volatility。
接下来介绍了dynamic factors。和Macro factor最根本的不同：macro factor都是long-only portfolio，dynamic factor是long-short，且确实tradable。
Chapter 14 Factor Investing
Factor的定义：investment styles that deliver high returns over the LONG RUN，而他们有higher return的原因是因为他们可能underperform in the SHORT RUN. 后者即所谓的"bad times"。
因此，投资决策中最重要的问题应该是：How different am I from average？我比一般人更能/更不能接受哪些bad times？一个完全average的人应该hold market。不同hedging needs的人则应该有选择性的take on risk factors。发散一点说，这帮资产管理从业者回答了一个更基本的、道德层面的问题：active management不是"loser's game"。表面上看市场是零和游戏，winner背后必有loser，但如果看risk-return profile，everybody might be better-off.
如果和mean-variance investing做比较的话，factor investing对risk的定义是bad time，而不是volatility。更重要的是，expected return根本没有进入讨论的框架内。根据Ch.3的讨论我们知道mean-variance在实际使用中很糟糕的主要原因就是无法准确对expected return进行估计；factor investing显然避开了这一问题。
作者最后特别探讨了safe assets，即各种sovereign bonds。和一般的股票和债券不同，government bond是zero net supply，只体现了cross-generation liability borrowing/lending，不能代表任何real wealth。因此，不能用其market weights作为portfolio weights。
PART 3 - DELEGATED PORTFOLIO MANAGEMENT
Chapter 15 Delegated Investing
从principle-agent问题出发，探讨了资产管理产业的一些结构性问题。作者提出了几点建议：
Chapter 16 Mutual Funds and Other 40-Act Funds
作者认为部分基金经理是有资产管理才能的，但这一才能不能为投资者带来回报，只能时基金经理本身获益。
这是因为investor chase past return，好的基金经理会得到inflow。（此外，投资mutual fund的钱还相当sticky，当表现不好时的outflow比表现好时的inflow慢。）。根据decreasing return to scale，好的基金最终会成长到一定大小，使得return和market return相当。因此，投资者并不能持续的从这些基金中获得超额回报。
但是这个过程中，这些有才能的基金经理将从AUM-based fee中获得可观收益。事实上，基金公司本身的收益非常可观，operating margin能达到30%左右。
Chapter 17 Hedge Funds
作者认为hedge fund不过是repackaged risk factors，其中又以equity factor + volatility factor为主。考虑到他们高昂的费用，作者把他们称为expensive betas。
相应的，作者认为资产管理的未来在cheap alternative betas，用new generation of factor (index) funds to gain access to dynamic factor risk premiums.
几点思考：
主要观点：
- Investment is about BAD TIMES. （非常同意）
- RE-BALANCE, re-balance, re-balance. （保留看法）
- The future of asset management: CHEAP exposure to DYNAMIC factors.
Chapter 1 Asset Owners
以贫困的Timor-Leste（东帝汶民主共和国）为例子，引出asset management的重要性。进而分类探讨几类asset owner：主权财富基金(sovereign wealth fund)，养老基金(pension fund)，捐赠受托基金(foundations and endowments)，个人与家庭。
东帝汶的例子很有趣。这是个很穷的国家，人均GDP仅有1000美元左右，但其主权基金却有高达120亿美元的资产！这些钱主要来自东帝汶的石油产业。一个穷得叮当响国家，为什么把卖油赚的钱了存起来，而没有“花在刀刃上”呢？一个重要的考虑是预防荷兰病(Dutch disease)：中小国家发现自然资源后大力开采，容易导致其他产业相继衰落，并且货币升值、国际竞争力下降。一旦所依赖的大宗商品价格下跌，对经济的影响将是致命的。历史上，挪威就曾经吃过大亏：80年代油价下跌，依赖石油出口的挪威马上被打入了一段漫长的零增长。如果在大宗商品繁荣时期对外汇有所储备，困难时期就可以拿出来实施经济政策和扶植其他产业。有趣的是，东帝汶的主权基金正是在挪威人的建议下创建的，而挪威自己时至今日仍然拥有着世界上最大的主权基金。
Chapter 2 Preferences
Mean-variance utility有许多不足。比如，它并不要求return服从正态分布；而当return不是正态分布时，仅仅依赖first 2 moments是不够的。又如方差不区分涨和跌，而投资者对涨和跌是不对称的。
Chapter 3 Mean-Variance Investing
讨论diversification benefits和mean-variance optimization。作者比较了几种不同的portfolio construction（用4 broad asset classes）的Sharpe ratio：
- risk parity > equal weights / MinVol >> mean-variance
为什么unconstrained mean-variance表现差？需要估计的东西太多，而对first moments的估计非常noisy。事实上，Sharpe ratio高的几种策略本质上就是CONSTRAINED mean-variance portfolio，三者都避开了对expected return的估计：
- MinVol假设所有资产的mean return一样
- Risk parity假设所有资产的mean return一样且correlation = 0
- Equal weight假设所有资产一模一样
此外，仅依靠历史数据来算各资产的mean和variance是危险的，尤其当sample比较短的时候（pro-cyclicality）：最近return高，意味着现在价格高，E(r)应该更低才对。
Chapter 4 Investing for the Long Run
Re-balance是一种short volatility的投资策略，有negative convexity（lower/higher exposure when price is high/low），和selling put option类似。和所有short volatility strategy一样，re-balancing earns risk premium。
Rebalance有premium可以赚的另一个原因是liquidity provision。股价下跌，是因为有人想要卖掉该股票，而此时去买它就是提供了liquidity。
本章案例讲的是金融危机后的private wealth management。有趣的是，在重大损失之后，人们往往会改变投资策略，但其中的原因很少是因为risk aversion变化，而是因为expectation的变化。
PART 2 - FACTOR RISK PREMIUMS
Chapter 6 Factor Theory
作者以CAPM为切入点，讨论了它的不足和启示。值得注意的是，虽然这一模型有很多问题，但75%的CFO在capital budgeting的时候会使用它：What the market uses to price asset is the correct asset pricing model?
- Rational: high return compensate for losses during bad times。因此，如果投资者对某些bad time不那么敏感，就可以获得超额回报。
- Behavioral + barrier of entry: 一个超级无敌理性的投资者和一个能绕过投资壁垒的投资者均可以获得超额回报。
本章依次介绍了几个常见Factor。
首先介绍了Macro Factor：经济增长、通货膨胀、Volatility等。这些因素之所以成为factor因为他们和average投资者的“BAD TIME”息息相关：低增长/高通胀是坏消息。一般而言宏观factor的变化，尤其是非预期的变化（shock），比水平（level）更重要。需要注意的是，资产回报对这些factor的反应是contemporaneous的。
作者尤其强调了volatility as a risk factor。历史上，volatility和stock return呈负相关，这一相关性的渠道有二：其一是leverage effect，当股票下跌时，公司的D/E变大，使得其股票风险更大、volatility更高；其二是time-varying risk premium，volatility变高时，discount rate变高，进而导致股票下跌。Volatility的price of risk是负的；collect risk premium的方式是short volatility。
接下来介绍了dynamic factors。和Macro factor最根本的不同：macro factor都是long-only portfolio，dynamic factor是long-short，且确实tradable。
- Size：略讲。SmL premium自1985年以来并不明显。
- Value：背后的bad time和market risk类似，但不完全相同，更侧重LONG-TERM investment / consumption growth。理论解释：Firm investment risk，value firm有更多的unproductive capital（体现为高book-to-price），当bad time时不够flexible，high and asymmetric adjustment cost。行为解释：over-extrapolation/overreaction，投资者认为过去的growth可以继续，使得growth stock被高估。
- Momentum：回报远远高于size和value。很多声称自己是growth investing的基金其实是momentum investing（毕竟growth其实是negative risk premium）。和value不同，momentum有positive feedback，越涨越买，越买越涨，这种destabilizing的投资策略往往会有大crash。Momentum至今没有好的理论解释，大多数解释都是行为方面的：delayed over-reaction和initial under-reaction。
Chapter 8 Equities
一直以来有equity premium puzzle：股票为什么有如此高的超额回报（相比债券）？SP500自1947年以来的mean nominal return是10.4%。这样的超额回报不能完全用宏观factor如consumption解释。有几大主流的理论：
- Time-varying risk aversion：基于habit utility，当原来生活富裕的人的消费水品降低时，marginal utility会变得极高，导致非常高的local risk aversion。股票价格急剧下降，未来的return变高。
- Disaster risk：reward to compensate for rare catastrophes。此外，衡量equity premium本身有survivor-ship bias，历史上出现过若干次国家的stock market整个消失的情况。
- Long-run risk：如果model中fundamental consumption factor是一个changing process且有time-varying volatility，equity premium可被解释。(Bansal and Yaron, 2004)
- Heterogeneous investors: 重要的不是average investor，而是marginal investor。Asset price depends on the XSec distribution of agents.
股票不是好的inflation hedge。可能的理论原因：高通胀减低了real production，或升高了discount rate。行为方面，人们有money illusion，用nominal discount rate来discount real dividend。
要预测equity premium很难。在诸多变量里，唯一有一些预测能力的是10-yr Shiller earnings yield和5-yr dividend yield；而且predictability也随时间变化，市场好的时候难预测，坏的时候好预测（Henkel, Martin, Nardari, 2011）。需要注意的是，以上两个被证明略有预测力的变量都是negative feedback的，当股市涨的时候，E/Y和D/Y都会变低，对未来的equity premium期望减低，应该减持。这一特性使得rebalance是好的。
Chapter 10 Alpha
本章主要讲active management。
关于Alpha的几点零散notes：
- 如果定义alpha = r(portfolio) - r(bmrk)，所隐含的假设是产品对该benchmark的beta为一，但很多情况下并非如此。
- Alpha，尤其是CAPM alpha，是在linear framework下定义的。如果所持资产有non-linear payoff，则不能使用alpha。
- “Alpha是否真的存在？”是一个joint hypothesis问题，取决于benchmark。只有当benchmark对该投资者确实tradable/accessible时，alpha才有意义。
本章的例子是low volatility和low beta anomaly：
- realized volatility和未来回报负相关。事实上，它和contemporaneous回报也是负相关。
- realized beta和未来sharpe ratio负相关（主要因为高volatility）。与CAPM相符的是，它和contemporaneous return是正相关。由此推论，beta有一定的mean-reversion。
可能的原因有data mining, leverage constraints, agency problem, lottery preference.
 |
| Agency Problem: Focus on TE "Do not invest in A because it introduces large TE" |
Chapter 14 Factor Investing
Factor的定义：investment styles that deliver high returns over the LONG RUN，而他们有higher return的原因是因为他们可能underperform in the SHORT RUN. 后者即所谓的"bad times"。
因此，投资决策中最重要的问题应该是：How different am I from average？我比一般人更能/更不能接受哪些bad times？一个完全average的人应该hold market。不同hedging needs的人则应该有选择性的take on risk factors。发散一点说，这帮资产管理从业者回答了一个更基本的、道德层面的问题：active management不是"loser's game"。表面上看市场是零和游戏，winner背后必有loser，但如果看risk-return profile，everybody might be better-off.
如果和mean-variance investing做比较的话，factor investing对risk的定义是bad time，而不是volatility。更重要的是，expected return根本没有进入讨论的框架内。根据Ch.3的讨论我们知道mean-variance在实际使用中很糟糕的主要原因就是无法准确对expected return进行估计；factor investing显然避开了这一问题。
作者最后特别探讨了safe assets，即各种sovereign bonds。和一般的股票和债券不同，government bond是zero net supply，只体现了cross-generation liability borrowing/lending，不能代表任何real wealth。因此，不能用其market weights作为portfolio weights。
PART 3 - DELEGATED PORTFOLIO MANAGEMENT
Chapter 15 Delegated Investing
从principle-agent问题出发，探讨了资产管理产业的一些结构性问题。作者提出了几点建议：
- 单纯使用linear contracts/fees是很糟糕的（Irrelevance results理论认为这样的contract对delegated portfolio management没有任何作用）。Linear contract：根据manager beat static benchmark的多少按比例提成。
- Incentive payment不应该成为这个行业的主流。根据理论，当agent需要multitask时，incentive payment和fixed payment没什么区别，因为agent会选择性完成任务。
- 改进：
- dynamic/factor-based benchmark，而不是static
- Non-linear/option-like compensation
- 加入constraints
- 更多的transparancy
- 按收费方式，尽量减少AUM-based fee。Retail investor应该付flat fees by the hours.
资产管理收费的历史：早年，大多数资产管理公司赚的都是commission-based fee，即客户交易所产生的佣金。直到1960年，Morgan Bank才开始率先收取AUM-based fee；当时人们都预测它会丢掉很多客户，但最终只有一个客户离开了Morgan。有趣的是，虽然这个行当竞争日益激烈，但AUM-based收费标准反而越来越高：60年仅有25bps，而现在大概在1%（散户）、50bps（机构）左右。
Agency issue对市场本身有影响，比如造成Herding。造成herding的原因可能有：大家的benchmark一样，或者仅仅因为manager的career concern。研究还表明：
- Stocks widely held by institutions have lower returns
- Institutional flow has predictive power of stock returns
- Delegated portflio management can give rise to momentum and long-term reversal in large and liquid asset class (but not OTC). 例子：一支股票因为基本面消息下跌，所以持有该股票的基金表现差，投资者认为这些基金经理不行而撤资，导致这些基金不得不抛售所持有的股票，进一步造成了股票价格下跌，而撤资的过程比较缓慢，所以股票价格在这段时间内出现了下跌的momentum。
Chapter 16 Mutual Funds and Other 40-Act Funds
作者认为部分基金经理是有资产管理才能的，但这一才能不能为投资者带来回报，只能时基金经理本身获益。
这是因为investor chase past return，好的基金经理会得到inflow。（此外，投资mutual fund的钱还相当sticky，当表现不好时的outflow比表现好时的inflow慢。）。根据decreasing return to scale，好的基金最终会成长到一定大小，使得return和market return相当。因此，投资者并不能持续的从这些基金中获得超额回报。
但是这个过程中，这些有才能的基金经理将从AUM-based fee中获得可观收益。事实上，基金公司本身的收益非常可观，operating margin能达到30%左右。
Chapter 17 Hedge Funds
作者认为hedge fund不过是repackaged risk factors，其中又以equity factor + volatility factor为主。考虑到他们高昂的费用，作者把他们称为expensive betas。
相应的，作者认为资产管理的未来在cheap alternative betas，用new generation of factor (index) funds to gain access to dynamic factor risk premiums.
几点思考：
- 市面上已经开始出现alternative beta的产品了。它们会取代active managed product吗？根据作者的观点，它们只会raise the bar for active management，而不会取代之。
- 怎么知道active management的alpha究竟是alpha，还是仅仅是beta timing？
- 从投资角度而言，自由市场无益于社会平等；社会福利必须进行再分配。穷人面对更多的bad times，避险需求更高，所能获得的投资回报非常有限。相反，富人能承担更多风险，因此也就能收获更高的投资回报。这将加剧社会的不平等。
Jan 14, 2015
#读书笔记 #1 A Random Walk Down Wall Street (Chapter 5)
Chapter 5: Technical and Fundamental Analysis
"A picture is worth ten thousand words" - Old Chinese proverb
1. Technical v.s. Fundamental Analysis
Most opt for one of two methods: technical or fundamental analysis. Technical is essentially the making and interpreting of stock charts. Fundamental analysts believe the market is usually logical. Caring little about the particular pattern of past price movement, fundamentalists seek to determine a stock's proper value.
2. What can chart tell you? The rationale for the charting method
The fist principle of technical analysis: all information about earnings, dividends, and the future performance of a company is reflected in the company's past market price.
The second principle: prices tend to move in trends. "Prices move in trends, and trends tend to continue until something happens to change the supply-demands balance." - Magee, Technical Analysis of Stock Trends
Three "most plausible" explanations of why charting is supposed to work: First, it has been argued that the crowd instinct of mass psychology makes trends perpetuate themselves. Second, there may be unequal access to fundamental information about a company. Third, investors often underreact initially to new information.
Why might charting fail to work? Market may well be a most efficient mechanism.
3. The technique of fundamental analysis
"A picture is worth ten thousand words" - Old Chinese proverb
1. Technical v.s. Fundamental Analysis
Most opt for one of two methods: technical or fundamental analysis. Technical is essentially the making and interpreting of stock charts. Fundamental analysts believe the market is usually logical. Caring little about the particular pattern of past price movement, fundamentalists seek to determine a stock's proper value.
2. What can chart tell you? The rationale for the charting method
The fist principle of technical analysis: all information about earnings, dividends, and the future performance of a company is reflected in the company's past market price.
The second principle: prices tend to move in trends. "Prices move in trends, and trends tend to continue until something happens to change the supply-demands balance." - Magee, Technical Analysis of Stock Trends
Three "most plausible" explanations of why charting is supposed to work: First, it has been argued that the crowd instinct of mass psychology makes trends perpetuate themselves. Second, there may be unequal access to fundamental information about a company. Third, investors often underreact initially to new information.
Why might charting fail to work? Market may well be a most efficient mechanism.
3. The technique of fundamental analysis
In estimating the firm-foundation value of a stock, the fundamentalist's most important job is to estimate the firm's future stream of earnings and dividends.
Because the general prospects of a company are strongly influenced by the economic position of its industry, the obvious starting point for the security analyst is a study of industry prospects.
Four basic determinants to help estimate the proper value for any stock:
(1) The expected growth rate
Hazardous as projections may be, share prices must reflect differences in growth prospects if any sense is to be made of market valuation. Also, the probable length of the growth phase is very important. ("the rule of 72": number of years to double your money ~= 72 divided by the interest rate you earn)
Rule 1: A rational investor should be willing to pay a higher price for a share the larger the growth rate of dividends and earnings or the longer an extraordinary growth rate is expected to last.
It is the P/E multiple, not the price, that really tells you how a stock is valued in the market. High P/E ratios are associated with high expected growth rates.
(2) The expected dividend payout
Many companies tends to buy back their shares rather than increasing their dividends, If expected growth rates are the same, you are better off with the one whose dividend payout is higher.
Rule 2: A rational investor should be willing to pay a higher price for a share, other things being equal, the larger the proportion of a company's earnings that is paid out in cash dividends.
(3) The degree of risk
Rule 3: A rational and risk-averse investor should be willing to pay a higher price for a share, other things being equal, the less risky the company's stock.
A "relative volatility" measure may not fully capture the relevant risk of a company (see Chapter 9).
(4) The level of market interest rates
To attract investors from high-yielding bonds, stock must offer bargain-basement prices. In the early 1980s, when yields on prime-quality corporate bonds soared to close to 15%, the expected returns of stocks had trouble matching these bond rates. Again in 1987, interest rates rose substantially, preceding the stock market crash of October 19. However, the relationship between interest rates and stock prices is somewhat more complicated than this discussion may suggest.
Rule 4: A rational and risk-averse investor should be willing to pay a higher price for a share, other things being equal, the lower the interest rates.
4. Three important caveats of fundamental analysis
The mathematical precision of fundamental-value formula is based on treacherous ground: forecasting the future.
Caveat 1: Expectation about the future cannot be proven in the present.
Caveat 2: Precise figures cannot be calculated from undetermined data.
Caveat 3: What's growth for the goose is not always growth for the gander.
It would be very dangerous to use any one year's valuation relationship as an indication of market norms.
5. Why might fundamental analysis fail?
(1) incorrect information and analysis
(2) estimate of "value" might be faulty
(3) the stock price may not converge to its value estimate
Example: the market may revalue its estimate of what growth stocks are worth. Not only can the average multiple change rapidly for stocks in general, but so can the premium assigned to growth.
6. Using fundamental and technical analysis together
Rule 1: Buy only companies that are expected to have above-average earnings growth for five or more years.
Rule 2: Never pay for a stock than its firm foundation of value.
There are important advantages to buying growth stocks at reasonable earnings multiple - "double bonus". Peter Lynch's strategy: PEG (P/E-to-growth) ratio!
Rule 3: Look for stocks whose stories of anticipated growth are of the kind on which investors can build castle in the air.
Ask yourself whether the story about your stock is one that is likely to catch the fancy of the crowd.
Jan 2, 2015
#记一件小事 2015/01/02
姑娘：“快夸我的羽绒服好看！这样我今年就不用买新的了。”
少年：“那我得先看看它暖不暖和！”
题记：喜迎2015年！博主隆重推出“记一件小事”系列，旨在记录少年和姑娘日子里的真、善、美，是对“无（tu）题（cao）”系列赤裸裸的挑战 :)
Jan 1, 2015
#读书笔记 #1 A Random Walk Down Wall Street (Chapter 4)
Chapter 4: The Explosive Bubbles of the Early 2000s
1. The Internet Bubble
Most bubbles have been associated with some new technology (as in the tronics and biotech booms) or with some new business opportunity (as when the opening of profitable new trade opportunities spawned the South Sea Bubble). The Internet was associated with both: it represented a new technology, and it offered new business opportunities that promised to revolutionize the way we obtain information and purchase goods/service.
Bubbles are "positive feedback loops" - Robert Shiller (Irrational Exuberance).
In the first quarter of 2000, 916 venture capital firms invested $15.7 billion in 1,009 startup Internet companies. An astonishing 159 IPOs had been completed in the previous quarter. As happened during the South Sea Bubble, many companies that received financing were absurd. IN earlier times, one needed actual revenues and profits to come to market with an IPO. Some Internet companies had neither. We learned that investors would throw money at businesses that only five years before would not have passed normal due diligence hurdles.
Security Analyst $peak Up
Security analysts always find reasons to be bullish. They seldom utter the "sell" word, because they do not want to endanger current or future investment banking relationship or to offend corporate chief financial officers. Traditionally, ten stocks were rated "buys" for each one rated "sell". But during the bubble, the ratio was almost 100:1.
New Valuation Metrics
Somehow, in the new Internet world, sale, revenues, and profits were irrelevant. In order to value Internet companies, analyst looked instead at "eyeballs" - the number of people viewing a Web page or "visiting" a Web site. Particularly important were numbers of "engaged shoppers" - those who spent at least 3 minutes on a website. "Mind share" was another popular non-financial metric.
Special metrics were established for telecom companies. Security analysts clambered into tunnels to count the miles of fiber-optic cable in the ground rather than examining the tiny fraction that was actually lit up with traffic.
The Writes of the Media
The bubble was aided and abetted by the media, which turned us into a nation of traders. Like the stock market, journalism is subject to the laws of supply and demand.
The Internet itself became the media. The Internet had democratized the investment process, and it played an important enabling role in perpetuating the bubble. Online brokers were also a critical factor in fueling the Internet boom. Trading was cheap, at least in terms of the small dollar amount of commissions charged.
Cable networks such as CNBC and Bloomberg became cultural phenomena. Across the world, health clubs, airports and bars were permanently tuned into CNBC.
Fraud Slithers In and Strangles the Market
Speculative manias , such as the Internet bubble, bring out the worst aspects of our system. Many businesses were managed not for the creation of long-run vale but for the immediate gratification of speculators - "obliged" high short-term earnings, "creative accounting, etc.
Enron was only one of a number of accounting frauds. Various telecom companies overstated revenues through swaps of fiber-optic capacity at inflated prices.
Should We Have Known the Dangers?
Fraud aside, we should have known better. We should have known that investments in transforming technologies have often proved unrewarding for investors. In the 1850s, the railroad was widely expected to greatly increase the efficiency of communications and commerce. It certainly did so, but it did not justify the prices (collapses in August 1857). History tells us that eventually all excessively exuberant markets succumb to the laws of gravity.
Many villains: fee-obsessed underwriters; research analysts that could be pushed by commission-hungry brokers; corporate executives using "creative accounting" to inflate their profits. It was the infectious greed of individual investors and their susceptibility to get-rich-quick schemes that allowed the bubble to expand.
2. The US Housing Bubble and Crash of the Early 2000s
This bubble was undoubtedly the biggest US real estate bubble of all time. Moreover, the boom and later collapse in house prices had far greater significance for the average Americans than any gyrations in the stock market.
In order to understand how this bubble was financed and why it created such far-reaching collateral damage, we need to understand the fundamental changes in the banking and financial systems.
The New System of Banking
Old system is "originate and hold" system. Banks would make mortgage loans and hold those loans as assets until they were repaid. In such an environment, bankers were very careful about the loans they made. This system fundamentally changed in the early 2000s. New system is the "originate and distribute" model of banking - e.g. mortgage-backed securities, CDS (second-order derivatives), etc.
Looser Lending Standards
The financiers created structured investment vehicles, or SIVs, that kept derivative securities off their books, in places where the banking regulators couldn't see them. In the new system loans were made with no equity down in the hopes that housing prices would rise forever. NINJA loans were common - loans to people with no income, no job , and no asset.
The government itself played an active role in inflating the housing bubble. Under pressure by Congress to make mortgage loans easily available, the FHA was directed to guarantee the mortgages of low-income borrowers. Indeed, almost 2/3 of the bad mortgages on the financial system as of the start of 2010 were bought by government agencies or required by government regulations. No accurate history of the housing bubble can fail to recognize that it was not simply "predatory lenders" but the government itself that caused many mortgage loans to be made to people who cannot afford them.
3. Bubble and Economic Activity
The bursting of bubbles has invariably been followed by severe disruptions in real economic activity. The fallout from asset-price bubbles has not been confined to speculators. Bubble are particularly dangerous when they are associated with a credit boom and widespread increases in leverage both for consumers and for financial institutions. Credit boom bubbles are the ones that pose the greatest danger to real economic activity.
Are the markets inefficient?
"The stock market is not a voting mechanism but a weighing mechanism." - Benjamin Graham (Security Analysis). Valuation metrics have not changed. Eventually, every stock can only be worth the present value of the cash flow.
Market prices must always be wrong to some extent. But at any particular time, it's not obvious to anyone whether they are too high or too low. Markets are not always or even usually correct. But no one person or institution consistently knows more than the market. (???)
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