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    2008-02-29

    Clear FSLR Puts and Long DELL Calls

    Clear my put positions on FSLR yesterday since I think a short-term bound may be possible. I am longing some DELL calls after its earnings call since I think technically there would be some rebound.

    Pure gut feeling.

    2008-02-28


    ---舒婷

      我无法反抗墙
      只有反抗的愿望

    ... ...

      我终于明白了
      我首先必须反抗的是
      我对墙的妥协,和
      对这个世界的不安全感

    一切

    一切
    -- 北岛

    一切都是命运
    一切都是烟云
    一切都是没有结局的开始
    一切都是稍纵即逝的追寻
    一切欢乐都没有微笑
    一切苦难都没有泪痕
    一切语言都是重复
    一切交往都是初逢
    一切爱情都在心里
    一切往事都在梦中
    一切希望都带着注释
    一切信仰都带着呻吟
    一切爆发都有片刻的宁静
    一切死亡都有冗长的回声

    2008-02-27

    Short FSLR

    I bought some put on it yesterday. My only problem now is undercapitalization. Really frustrated if you just can't do more on an opportunity.

    2008-02-25

    Some topics

    希望最近能有时间完成几个topic的写作:
    1. Parallel and distributed computation, theory and practice;
    2. Garbage underlying and valuable derivative;
    3. Business models in social networks era;
    4. Negative bubble.

    Film Review - The Assasination of Jessie James

    以后把一些感想写在这上边,简单方便。

    The assasination of jessie james不错,虽然称不上伟大。整部影片烘托出了紧张的气氛,表现手法类似教父,没有陷入繁琐的J. James的犯罪历史,而是用一些代表性的场景来刻画人物性格。

    Brad Pitt表演的Jessie James稍微有点不妥的地方,在我看来,他还是适合A river runs through it里面的桀骜的Paul MacLean,而缺乏James应有的沉稳,矛盾的性格特征,当然随着年龄的增长,这方面已经改进了很多。也许中年的Robert de Niro会是不错的人选。

    Casey Affleck饰演的Robert Ford很不错,角色的匹配让他的表演感觉比在Gone baby gone里面好得多。

    整个配乐虽然没有什么特别留下印象的主旋律,但确实营造出了气氛。

    2008-02-21

    Inside the house of money

    Edited by Steven Drobny.

    A wonderful book composed of valuable thoughts. They show not only what works but also what doesn't work. They not only talk about philosophy, but also practice and experience. Overall, they tell what is a true trader's instinct, no devalue nor overvalue.

    Highly recommended.

    The Alchemy of Finance

    A good book by George Soros.

    The book is not well organized and seems too wordy. But there truly are some pearls buried in those lengthy statements. They alone are enough to justify the value of the book.

    Recommend.

    引援之惑

    引援之惑

    当长春,上海,北京这些竞争对手都相继确定了外援,加紧队伍磨合的时候,鲁能还在扭扭捏捏的和大家玩捉迷藏(我不太明白就这点破事,捂着掖着干什么),问题是时间越长,期望越大,结果刚来个外援,就谣言满天飞,曼联的,特别注明是南美的,以便和董替补区分开来,有人就在猜测是不是海因策,当然这也不是没可能,把鲁能全队卖了把海因策买过来也行,不过这样,如果海因策每场不救出10个必进球,来50次抢断,顺便进七八个球,也对不起大家的殷切期望。最后结果出来,是一个而立之年的委内瑞拉国脚,现效力于保加利亚一个中流球队,真真对不起观众。

    鲁能引援一塌糊涂,不过也是情有可原。

    先说为什么一塌糊涂。

    主教练享有引援权,这没什么好说的。就好象主厨统管厨房一样,主教练当然要根据球队需要和自己的战术打法引援,这就是国法,就是家规。你说图拔引援不行,任人唯亲,还可能拿回扣。之前图拔引援是不是通过俱乐部同意的?那俱乐部是不是要负连带责任。所谓水货,又如何鉴定,比如丹丘内斯库,我相信如果之前没有来过,现在引进来,照样会被吹成欧冠大牌,这怎么说?按泰山的打法,难道因扎吉来就能一年进三四十个球么。图拔是塞尔维亚人,当然引进塞尔维亚球员,这无论是从沟通还是说教练对球员的信息掌握来说都没有问题,就跟鲁能俱乐部管理层补充进来的难道不是鲁能集团的人?再说俱乐部,图拔“不会”引援,俱乐部就会?哪位仁兄懂?干脆让他来当主教练得了,不更省钱。引援和战术打法本来就息息相关,一方面继续留任图拔又另一方面否认他对球队的改造,这么做不是自相矛盾么。图拔拿回扣,俱乐部就不拿么?现在足坛那个不拿回扣,这已经成为了一个规则,完全禁止不可能也没有必要,一个好外援的引进会对球队战绩提升起到作用,反映到俱乐部盈利的提升,那么作为主教练拿些bonus也是合理的。俱乐部合理的做法是利用合约条款来达到最优化,如果图拔通过引援的利益不如战绩提升的利益大,那么他自然会让俱乐部和自己利益统一。但干涉主教练的引援权,无异于越俎代庖,由此导致的战绩下降,将帅不和等潜在损失谁来负责?将来如果出了矛盾也授人以柄。

    南美外援?可笑之极。现在来的几个确实都是南美的,不过查查老底,哪个不是在东欧国家效力的。为什么,还不是因为鲁能所谓的专用经纪人温嘉庆的脉络在东欧。跑到东欧找南美外援,等于绕半个地球跑到到美国享受中餐,除了满足虚荣感,实际是三道贩子的买卖。当然我不否认全球化的今天,东欧作为原本的本地人才出口,出于盈利以及本地资源匮乏的多重目的,现在也开始做南美和非洲物美价廉球员的倒买倒卖的生意,哪的土豆不是卖呢?不过整体水平的期望值还是差点意思。再者说,好货不便宜,放之四海而皆准。东欧国家也不是没好货,大部分在俄罗斯囤积着,鲁能可以去问问价,看看买得起么?从这个角度说,所谓的放开选援只是挂羊头卖狗肉而已,没有源头活水,何来清渠。

    所有球员都要试训?大概鲁能是让丹丘内斯库吓怕了,好容易信心十足的买了个欧冠认证免试训产品,结果成了史上最大水货,于是采用不见兔子不撒鹰的策略。不过说实话,是个人都明白好球员不用试训,鲁能这么说也不过是管理层留条后路,严重低估球迷智商。鲁能这么做是因为信息严重不对称,害怕受骗所以只能采取最保守的策略,也就是说所谓的目标百年俱乐部,到今天仍然没有参与到国际市场。国际足坛就是一个巨大的经济系统,而转会市场是其中最重要的一块,不参与其中,又怎么能说国际化俱乐部。就算试训,也没见说鲁能就因此杜绝水货了,事实证明一切,鲁能的方法只是掩耳盗铃罢了。

    再说为什么情有可原。

    鲁能是烂,但有中国足协在那垫着,再烂也烂不过他。政策的指令化,不合理性,中国足协不遑多让,不但没一点与时俱进的表现,还越活越抽抽。覆巢之下,安有完卵。在如此大环境下,鲁能也没有一个外部动力促进机制的改革。

    我倒期望鲁能没拿当年的双冠王,因为现在看来,由此导致的固步自封,远比一个虚名头衔有害的多,因为我们当年根本不知道为什么成功,所以无论是扩张还是维持,都缺乏目的性,只图虚名。比如和查尔顿签订的所谓合作协定,没有任何实际意义。出口球员到查尔顿?开什么玩笑,英格兰又不是阿拉斯加,要出口日韩的球员早就批发了,还等鲁能。引进先进经验?这又不是查尔顿的专利,那些先进的管理经验和训练经验早都已经教材化,真正的改革在于鲁能内部人员的改进,改了这么多年也没有太多效果。这非一日之功,更不是简单的自我加压就能完成的。所谓的合作协议也不是签了一回两回了,又有哪一次落到实处,不过是浮云罢了。

    08年对于鲁能不会是轻松的,可能又会是一个周期的结束,加上鲁能的紧缩银根,必然导致更多的矛盾,不过这恰恰也是重新整合的机会,在有限资源的条件下,资源的利用率反而会更高。套用业已消失的曾经的中国著名企业爱多的一句话:我们一直在努力。

    但一定要努力对了方向。

    2008-02-15

    On Randomness

    On Randomness

    RNG

    We start from RNG (random number generator), which can be seen in almost every utility program today. It’s like the representative we employ in computer systems to shows our awe to the powerful reality. And by a better designed RNG, we hope we would be able to predict God’s next move.

    I’ve been TA for simulation course for several times and RNG is always a core part in simulation programming. There are dozens of algorithms for random sequence generation, starting from simplest LCG (linear congruential generator) to “unpredictable” trapdoor function. Correspondingly there are dozens of back-test methods to ensure the sequence we generate looks random as well as normative.

    But the problem is if the volume of memory is limited, the computer, theoretically, is just a FSM (finite-state machine). Then there is no way to generate a truly random sequence by such a deterministic system. Randomness should be totally memoryless and independent. What we are trying to do is just to make the generated repetitive sequence as long, chaotic, as possible. Anyway, what you need is what you should generate. So I always told the students, the best way is to know the simulation systems, to feed them what they want. That’s why in most cases, LCG is fine enough.

    I further go on thinking about where RNG can be improved. Can we break repetitiveness? Yes. Think about the irrational number, square root of 2.

    We know it can be approximated by Taylor’s series to any precision as we like. And the coefficients in Taylor’s series regular which means we can express them by finite information.

    But you can’t rush to your boss and tell him you just discover a true RNG. Since if your boss is stupid enough to believe you and use your algorithm for some highly confidential data, it would take long to be cracked. The problem is non-repetitiveness is far from randomness. So can all irrational numbers be generated with finite information? That’s a little beyond this article’s scope. Let’s put it aside. The conclusion now is we can’t make a true RNG by computer. Maybe someday, and the day we achieve this, is the day we solve Turing test.

    But that’s not the end of the story. Randomness is still like a buzzword to me. I don’t like buzzwords.

    What’s Randomness Anyway?

    Random, by Webster, means “relating to, having, or being elements or events with definite probability of occurrence”.

    This definition should be familiar since that’s what we are taught in probability course. In my view, randomness, belongs to topology more than to pure numbers (of course you can say all mathematics can be cracked down to number theory). It not only is some gift from observation, but also has been widely applied in practices. The jump from deterministic number to functional can bring many unexpected and surprising benefit.

    History repeats but never in the same way. Paul Samuelson once nicely put it in this way: we have only one sample of history. We are living in a world we don’t know completely. Even someone declares the world is deterministic, it’s more philosophical instead of “scientific”. But we desperately want to know the world since we are clear about the pay-off of predictability. Unpredictability and predictability, are like twins.

    Randomness is our solution. More specifically, we use probability theory to get ourselves some clue. We “price” unpredictability by measures such as Sharpe ratio. We make ourselves a cozy home in the dark cold universe.

    But if you pay a little attention to the definition, you can see a word “definite”. How come a definite thing in definition of a certainly indefinite thing?

    Look back the way probability theory goes. It starts with gambling and now, has expanded to every area. But some basic principles haven’t changed. It needs preassumed distributions like Gaussian, to generate the whole topological structure, and needs some mapping rules like VaR, to help our decision. Both are strong assumptions and “definite”.

    We get those definite things from data. But recent study is questioning both (for example, see Kahneman, Tversky, Mandelbrot’s writings). In my point of view, this is good but still wrong in direction.

    Harold Hardy once said compared to physics, mathematics seems more “real” to him. Absolutely right. Given the randomness theory, itself forms a complete and beautiful system. Just like given gravity and other basic rules, we have our real world. In probability universe, we have rules like optimality, equilibrium, etc. Every entity can enter the universe but if it doesn’t show respect to the game rule, it’s going to be eliminated theoretically. To be specific, this is called arbitrage opportunity in finance.

    But as Samuelson said, we can’t believe a model simply because it’s beautiful. Does randomness serve its purpose?

    Why We Need Randomness?

    We need randomness to make a better understanding of the real world, like Milton Friedman said, “prescribe what should be done in the light of what has been done”. Is the beautiful randomness really helpful in our reality?

    Assume you are gambling with an idiot. You two pick 0 or 1 each time. And rule is as follows: If you two pick the same number, nothings happens. Otherwise, the 1 guy wins a million. Obviously, in this zero-sum matrix game, only one Nash equilibrium exists: 1-1.

    But what if that idiot keeps picking 0? Are you going to be lured by the million reward? In other words, do you have confidence to tell determinacy by past data?

    This simple example shows the gap between theoretical and real worlds. The strong assumptions and lack of details specifications make the theory hard and dangerous to apply. What if everyone truly regards the world as random? Is this going to lead to a limit or a never-converged distribution? Is the whole system resulted robust to its rules? By continuing such discussions, you would find it goes more and more theoretical and useless.

    As John Milnor said about Nash’s work on game theory: “However, when mathematics is applied to other branches of human knowledge, we must really ask a quite different question: To what extent does the new work increase our understanding of the real world? On this basis, Nash's thesis was nothing short of revolutionary.” From this angle, probability theory is only a limited, micro-level theory. It sets up a set of rules about how people should play the game but doesn’t explain. What we are doing is to prove the completeness of the universe and seek black holes, etc.

    In conclusion, there is no such thing called “randomness” in this world. What we face are only known and unknown.

    Unknown is Unmeasurable

    Randomness is still deterministic. It’s just a tool we use to treat the unpredictable world. Given circumstances, given uses, it’s useful. If people are stuck in it, they may lose the chance to realize the real world.

    Unknown is unmeasurable. We have no idea what it is. Sure we can’t handle this kind of stuff. That’s why we turn to things like probability theory. We need to know the prior knowledge, the time, the frequency, the sample size, the utility, et al. But you can’t say a 99.9% VaR portfolio is secure since you don’t know how the system runs. We are dusts in a dessert and we need to see the big picture.

    Think Big

    My probability theory is poor and only limited to certain areas like finance. The learning of probability theory did improve my realization of the world. But the trading experience tells me to be a non-believer, i.e., probability theory is merely part of the tools we human being has invented along our history.

    For financial world, I want to model it as a dynamical system. However, the complexity, theoretically, is beyond my current capacity and I also don’t have enough resources to practise my theory now. Anyway, I can use some intuitive and straight ways to experiment in small scale. Though they seem not so mathematically beautiful and even hard to express by words, they are better than orthodox finance engineering stuff because they are “big”.

    Yes, think big and think different. We are not what we are taught but certainly we are what we think.

    2008-02-13

    Some beautiful lines

    The Road Not Taken
    -Robert Frost

    TWO roads diverged in a yellow wood,
    And sorry I could not travel both
    And be one traveler, long I stood
    And looked down one as far as I could
    To where it bent in the undergrowth;

    Then took the other, as just as fair,
    And having perhaps the better claim
    Because it was grassy and wanted wear;
    Though as for that, the passing there
    Had worn them really about the same,

    And both that morning equally lay
    In leaves no step had trodden black.
    Oh, I marked the first for another day!
    Yet knowing how way leads on to way
    I doubted if I should ever come back.

    I shall be telling this with a sigh
    Somewhere ages and ages hence:
    Two roads diverged in a wood, and I,
    I took the one less traveled by,
    And that has made all the difference.