全球化和蝴蝶效应 - 兄弟财经外汇返佣十七年信誉保障

随着全球化继续增强资本市场的联系，蝴蝶效应的概念在金融世界变得重要起来。国际市场中一个小区域的波动可以迅速增长并蔓延到其他市场，一个小角落的市场波动可以引起全球波动。科技的进步和广泛的互联网使用增加了国际市场的互相影响。这导致了更多极端的市场波动。

蝴蝶效应在流行文化中已经众所周知，这一概念也被应用到了金融领域。它和混沌理论可以为资本市场的不可预测性提供部分解释。

蝴蝶效应的起源和意义

蝴蝶效应一词最初出现在1972年的一次科学会议上。是科学家Edward Lorenz在他的天气预测模型中提出了这一词汇。这一词的含义是日本一只蝴蝶煽动翅膀引起的小型大气变化可能最终导致德克萨斯州的一场龙卷风。

Lorenz在麻省理工学院研究了最小初值的变化是怎样引起大规模天气模型的不同的。1961年，他用初始条件为0.506的天气模型得出了与精确数值0.506127天气模型完全不同的和不可预测的天气模式。1963年，他撰写了关于这一概念的报告，名为《决定性的非周期流》。蝴蝶效应的概念表明动态系统是非常难预测的，例如天气和金融市场。蝴蝶效应的研究导致了混乱理论的发展。

混乱理论在市场中的应用

资本市场中包含平稳和剧烈波动的交替。然而，这些交替不总是无序的，他们之间的转换通常是突然和不可预测的。一些人相信混乱理论的概念能够用于理解金融市场是怎么运行的。

市场倾向于增加泡沫并最终导致极端的结果。金融泡沫经常因为积极的反馈而产生。当一些投资者在一个金融市场的上涨阶段中赚钱，其他观察者认为这些投资者一定是做出了明智的决定，导致这些观察者把自己的资金也投入到市场中。结果将是买家增多使股价继续上涨。这一积极反馈导致价格超过合理水平。在循环结束时，最终剩下的投资者将会遭受损失。

相同的概念可以解释不稳定的熊市。市场可能因为外部因素突然转移，导致投资者只关注负面新闻。最初的出售可以导致投资者在清算仓位时更多的抛售。负面反馈生效非常快，最终导致整体市场股票价值被低估。

分型学和市场

著名科学家Benoit Mandelbrot把分型学应用到金融市场中。他发现自然界中的混乱例子，例如海岸线或者云朵的形状，通常拥有高度的秩序。这些分型形状也能用于解释混乱系统，包括金融市场。Mandelbrot指出资产价格可以没有明显原因的突然跳动。

大多数市场中极端事件发生的概率不到5%。Mandelbrot认为这些异常值非常重要并在金融市场走势中扮演了重要的角色。传统的投资组合理论倾向于低估这些高波动性事件发生的频率。虽然分型学不能预测价格波动，但他认为可以更加现实的预测市场风险。

市场中蝴蝶效应的例子

尽管科技增加了蝴蝶效应在全球市场中的影响，但是还是有一个历史悠久的金融泡沫，那就是17世纪荷兰的郁金香市场泡沫。郁金香是一个精英身份的象征。它们在荷兰城市和村镇交易所交易。人们出售财产进行郁金香投机。然而，价格开始下降，恐慌抛售随之而来。

近期市场泡沫的例子更多。在1987年的黑色星期一中，道琼斯工业指数在一个交易日中下跌了约22%，这是有史以来最大的单日跌幅。虽然在一周前道琼斯工业指数出现过几天大幅下跌并且海湾地区有国际事件发生，但是下跌没有明显的原因。回想起来，也许程式交易是恐慌性抛售的一部分原因。

2015年，中国股票市场出现剧烈波动，在一个交易日中下跌8%。与黑色星期一类似，也没有出现下跌的明显原因。这一波动很快蔓延到了其他市场，标准普尔和日经指数下跌了4%左右。还是和黑色星期一一样，在前几个月中国市场也出现了疲软。

当时中国政府已经开始进行人民币贬值。然而，主要原因可能是中国散户开始大量使用保证金。当价格开始下跌，投资者受到追加保证金要求。散户被迫平仓以满足追加保证金要求，导致了抛售的负面反馈循环。在之前的几年，中国政府鼓励人们将资金投放入市场。随着技术的进步和提高，市场的连通性会进一步提高，蝴蝶效应将继续是全球市场的一个影响因素。

Globalization and the Butterfly Effect

By John Edwards

The butterfly effect concept has become important in the finance world as globalization continues to increase and capital markets connect. Volatility in one small area of the international markets can grow rapidly and bleed into other markets, and a hiccup in one corner of the international markets can have global consequences. Improvements in technology and wider access to the Internet has increased the degree to which international markets influence each other. This has led to more episodes of extreme market volatility.

The butterfly effect has become well-known in popular culture, and the concept has clear applications to finance. It and chaos theory may provide a partial explanation for the unpredictability of capital markets.

Origin and Meaning of Butterfly Effect

The phrase "the butterfly effect" was first coined during a scientific meeting in 1972. Scientist Edward Lorenz gave a talk on his work regarding weather prediction models. The phrase suggests that the flap of a butterfly's wings in Japan could create a small change in the atmosphere that might eventually lead to a tornado in Texas.

Lorenz studied how small differences in initial values led to large differences in weather models at the Massachusetts Institute of Technology. In 1961, he had entered an initial condition in a weather model as 0.506, rather than the precise number of 0.506127, which resulted in a completely different and unexpected weather pattern. In 1963, he wrote a paper on this concept, titled "Deterministic Nonperiodic Flow." The butterfly effect concept shows how difficult it is to predict dynamic systems, such as weather and financial markets. Study of the butterfly effect has led to advances in chaos theory.

Application of Chaos Theory to Markets

Capital markets go through alternating periods of calm and storminess. However, they are not always chaotic, and the shift between calm and chaos is often sudden and unpredictable. Some believe that these concepts of chaos theory can be used to understand how financial markets operate.

Markets tend to grow bubbles that eventually pop with drastic consequences. Financial bubbles often grow because of positive feedback. When investors make money during a rise in the financial markets, other observers think the investors must have made a smart decision, which leads the observers to invest their own money in the markets. The result is more buying and stock prices going higher. The positive feedback loop leads to prices beyond any logical or justifiable level. The loop eventually ends, and the last investors in are left hanging with the worst positions.

The same concept can explain volatile bear markets. The markets can suddenly shift due to outside factors, which causes investors to pay attention only to negative news. Initial selling leads to more selling as market participants liquidate their positions. The negative feedback loop tends to accelerate quickly, often resulting in a market full of undervalued stocks.

Fractals and the Markets

Prominent scientist Benoit Mandelbrot applied his work in fractals in nature to financial markets. He found that examples of chaos in nature, such as the shape of shorelines or clouds, often have a high degree of order. These fractal shapes can also explain chaotic systems, including financial markets. Mandelbrot noted that asset prices can jump suddenly with no apparent cause.

Many in the markets tend to dismiss the extreme events that occur less than 5% of the time. Mandelbrot argued that these outliers are important and play a significant role in financial market movements. Traditional portfolio theory tends to underestimate how often these high-volatility events occur. While his fractals cannot predict price movements, he argued that they could create a more realistic picture of market risks.

Examples of the Butterfly Effect in Markets

Although technology has increased the impact of the butterfly effect in global markets, there is a long history of financial bubbles going back to the tulip market bubble in Holland during the 17th century. Tulips were a status symbol among the elite. They were traded on exchanges in Dutch towns and cities. People sold their belongings to begin speculating on tulips. However, prices began to drop and panic selling ensued.

There are more recent examples of bubbles. On October 1987, known as Black Monday, the Dow Jones Industrial Average (DJIA) lost around 22% in one trading day, the largest percentage drop ever for that market. There was no apparent cause for the drop, though the DJIA had some large down days the week before, and there were international issues in the Persian Gulf. In retrospect, issues with panic selling and perhaps program trading might be partly to blame.

In 2015, the Chinese stock market encountered significant volatility, dropping over 8% in one day. Similar to Black Monday, there was no single event or cause for the drop. This volatility quickly spread to other markets, with the S&P500 and the Nikkei losing around 4%. Also like Black Monday, there had been weakness in the Chinese markets in prior months.

Chinese officials had begun devaluing the renminbi. However, the main cause was likely the high degree of margin used by Chinese retail investors. When prices began to drop, investors received margin calls from their brokers. Retail investors were forced to liquidate their positions quickly to meet the margin calls, leading to a negative feedback loop of selling. In years prior, the Chinese government encouraged people to put their money in the market. Markets will only become more interconnected as technology continues to improve, and the butterfly effect will continue to be a factor in global markets.

本文翻译由兄弟财经提供

文章来源：http://www.investopedia.com/articles/investing/021716/globalization-and-butterfly-effect.asp