1. 自由汇首页
  2. 交易文章

《The Man Who Solved The Market》中文版翻译连载48

投资者容易对压力过度反映 文艺复兴团队利用这一点不断盈利

《The Man Who Solved The Market》中文版翻译连载48
解决市场的人

The MAn Who Solved The Market (51)

From the EArliest days of the fund, Simons’s team had been wary of these transACtion costs, which they called slippage. They regularly compared their trades against a model that tracked how much the firm would have profited or lost were it not for those bothersome trADIng costs. The group coined a name for the difference between the prices they were getting and the theoretical trades their model made without the pesky costs. They called it The Devil.

从基金成立之初,西蒙斯的团队就一直对交易成本很谨慎,他们称之为“滑点”。他们会定期将他们的交易和一个模型做对比,以追踪如果没有这些麻烦的交易成本,公司有多少盈利或亏损。公司把他们得到的价格和在没有成本情况下模型进行的理论交易之间的差价,称之为“魔鬼”。

For a while, the actual size of The Devil was something of a guess. But, as Straus collected more data and his computers became more powerful, Laufer and Patterson began writing a computer program to track how far their trades strayed from the ideal state, in which trading costs barely weighed one the fund’s performance. By the time Patterson got to Renaissance, the firm could run a simulator that subtracted these trading costs from the prices they had receIVed, instantly isolating how much they were missing out.

有一阵子,“魔鬼”的实际规模是个谜。但是,随着斯特劳斯搜集到更多的数据,电脑性能也更好,劳弗和帕特森开始编写一个程序去追踪他们的交易偏离理想状态有多远,如果在理想状态下,交易成本几乎不会影响基金的表现。到帕特森进入文艺复兴的时候,公司可以运行一个模拟器,从他们收到的价格中减去交易成本,即可立刻得出他们将会亏损多少。

To narrow the gap, Laufer and Patterson began developing sophisticated approaches to direct trades to various futures exchanges to reduce the market impact of each trade. Now Medallion could better determine which investments to pursue, a huge advantage as it began trading new markets and investments. They added German, British, and Italian bonds, then interest-rate contracts in London, and, later, futures on Nikkei Stock Average, Japanese government bonds, and more.

为了缩窄缺口,劳弗和帕特森开始开发复杂的方法直接在各商品交易所进行交易,以降低每笔交易对市场的影响。现在大奖章可以更好地决定进行哪项投资,这在它进行新市场和新投资时是个巨大的优势。他们将德国、英国和意大利债券加入组合,然后是伦敦的利率合约,后来是日经指数期货、日本政府债券等更多品种。

The fund began trading more frequently. Having first sent orders to a team of traders five times a day, it eventually increased to sixteen times a day, reducing the impact on prices by focusing on the periods when there was the most volume. Medallion’s traders still had to pick up the phone to transact, but the fund was on its way toward faster trading.

大奖章基金开始更频繁的交易。起初是每天向一组交易员发出5次指令,最终增加到每天16次,他们会专门在交易量最大的时候进行交易,以减少对价格的影响。此时,大奖章的交易员们还是需要通过电话处理指令,但是基金正朝着更快的交易速度前进。

Until then, Simons and his colleagues hadn’t spent too much time wondering why their growing collection of algorithms predicted prices so presciently. They were scientists and mathematicians, not analysts or economists. If certain signals produced results that were statistically significant, that was enough to include them in the trading model.

在那之前,西蒙斯和他的同事们并没有花太多时间了解,为什么他们不断改进的算法可以如此有预见性的预测价格。他们是科学家和数学家,而不是分析师或经济学家。如果某种信号产生的结果引起了统计显著,就足以把它们纳入到交易模型中。

“I don’t know why planets orbit the sun,” Simons told a colleague, suggesting one needn’t spend too much time figuring out why the market’s patterns existed. “That doesn’t mean I can’t predict them.”

“我不知道为什么卫星会绕着太阳转,”西蒙斯告诉一位同事,建议他不需要花太多时间弄清楚为什么市场模式会存在。“那并不意味着我不能预测它们。”

Still, the returns were piling up so fast, it was getting a bit absurd. Medallion soared over 25 percent just in June 1994, on its way to a 71 percent surge that year, results that even Simons described as “simply remarKAble.” Even more impressive: The gains came in a year the Federal Reserve surprised investors by hiking interest rates repeatedly, leading to deep losses for many investors.

尽管如此,回报率增长的如此快,已经变得不太合理。大奖章仅在1994年6月回报率就超过了25%,年度回报率则飙升至71%,这个结果连西蒙斯都形容为“非常了不起”。更让人印象深刻的是:在这一年中美联储令人意外地多次加息,导致许多人大幅亏损。

The Renaissance team was curious by natural, as were many of its investors. They couldn’t help wonder what the heck was going on. If Medallion was emerging as a big winner in most of its trades, who was on the other side suffering steady losses?

文艺复兴团队像它的投资者一样天性好奇。他们不禁想知道到底发生了什么事。如果大奖章在大多数交易中成为大赢家,那么另一边不断遭受亏损的是谁呢?

Over time, Simons came to the conclusion that the losers probably weren’t those who trade infrequently, such as buy-and-hold individual investors, or even the “treasurer of a multinational corporation,” who adjusts her portfolio of foreign currencies every once in a while to suither company’s needs, as Simons told his investors.

随着时间推移,西蒙斯得出结论是:亏损的人可能不是那些很少交易的人,比如买完并持有的个人投资者,甚至也不是“跨国公司的财务主管”,她会每隔一段时间调整外币投资组合来适应公司的需求,正如西蒙斯告诉他的投资者的那样。

Instead, it seemed Renaissance was exploiting the foibles and faults of fellow speculators, both big and small.

相反的,文艺复兴似乎是在利用其他同行投机者的弱点和错误,无论大小。

“The manager of a global hedge fund who is guessing on a frequent basis the direction of the French bond market may be a more exploitable participant,” Simons said.

“经常地预测法国债券市场走向的一家全球性的对冲基金经理,可能是更有潜力的参与者。”西蒙斯说道。

Laufer had a slightly differfent explanation for their heady returns. When Patterson came to him, curious about the source of the money they were raking in, Laufer pointed to a different set of traders infamous for both their excessive trading and overconfidence when it came to predicting the direction of the market.

对于丰厚回报,劳弗对此有不同的解释。当帕特森来对资金来源好奇时,劳弗提到了另一组交易员,他们在预测市场走向时,因为过度交易和自负而臭名昭著。

Laufer’s explanation sounds glib, but his perspective, as well as Simons’s viewpoint, can be seen as profound, even radical. At the time, most academics were convinced markets were inherently efficient, suggesting that there were no predictable ways to beat the market’s return, and that the financial decision-making of individuals was largely rational. Simons and his colleagues sensed professors were wrong. They believed investors are prone to cognitive biases, the kinds that lead to panics, bubbles, booms, and busts.

劳弗的解释听起来很油滑,但是他的观点以及西蒙斯的看法,被视为深刻的,甚至是激进的。与此同时,大多数学者确信市场有其内在的效率,没有可预测的办法超过市场的回报率,而且个人的财务决策很大程度上是理性的。西蒙斯和他的同事们觉得教授们是错的。他们相信投资者容易产生认知偏差,从而导致过度恐慌、泡沫、繁荣和萧条。

Simons didn’t realize it, but a new strain of economic was emerging that would validate his instincts. In the 1970s, Israeli psychologists Amos Tversky and Daniel Kahneman had explored how individuals make decisions, demonstrating how prone most are to act irrationally. Later, economist Richard Thaler used psychological insights to explain anomalies investor behavior, spurring the growth of the field of behavioral economics, which explored the cognitive biases of individuals and investors. Among those identified: loss aveRSIon, or how investors generally feel the pain from losses twice as much as the pleasure from gains; anchoring, the way judgment is skewed by an initial piece of information or experience; and the endowment effect, how investors assign excessive value to what they already own in their portfolios.

西蒙斯没意识到这一点,但是一种新的经济流派正在鹊起,这将证实他的直觉。二十世纪七十年代,以色列心理学家阿莫斯·特沃斯基和丹尼尔·卡尼曼探索出个体如何做出决定的,证明了大多数人是多么容易做出不理智的行为。后来,经济学家理查德·塞勒运用心理学观点解释了异常投资者行为,推动了行为经济学领域的发展,揭示了个人和投资者的认知偏差。其中包括:损失厌恶,即投资者通常对损失感受到的痛苦是对收益愉悦的两倍;锚定效应,即判断方式将被第一印象或最初经验所扭曲;禀赋效应,即投资者赋予投资组合中已获取利润的超额价值。

Kahneman and Thaler would win Nobel Prizes for their work. A consensus would emerge that investors act more irrationally than assumed, repeatedly making similar mistakes. Investors overreact to stress and make emotional decisions. Indeed, it’s likely no coincidence that Medallion found itself making its largest profits during times of extreme turbulence in financial markets, a phenomenon that would continue for decades to come.

卡尼曼和塞勒因为他们的研究获得了诺贝尔奖。人们一致认为,投资者行为要比假设的更不理性,并会重复犯似错误。投资者会对压力反应过度并做出情绪化的决定。确实,大奖章基金发现自己是在金融市场极度动荡期间获取最大盈利,这很可能不是巧合,而这种现象将持续数十年。

(免责声明:仅供个人阅读学习及翻译参考。如有不准之处,请留言帮助改进)

发表评论

电子邮件地址不会被公开。 必填项已用*标注

分享本页
返回顶部