SKYWALKER 2046

Just jumpped into the trading world

geographic economy 2009/03/29

Filed under: market indicators — rogerwang2046 @ 03:59

TOTAL STATE TAX

map16701829031

GDP BY STATE

map4927744521

house ownship

map1011180746

CORPORATION TAX

map1231366410

GENERAL SALES TAX

map626063253

property tax 

map224610890

totally income tax

map863622738

Advertisements
 

【哈佛笔记四十四】美国经济危机的两个成因

Filed under: market indicators — rogerwang2046 @ 02:08

《财经》特约作者 陈晋    [2009年02月09日 16:52]  

费尔德斯坦曾在里根时期担任经济顾问委员会主席,他说,美国的危机源于资产价格和借贷杠杆过高,但他相信美国经济会恢复繁荣

  【《财经网》专稿/特约作者 陈晋】波士顿的冬天寒冷而漫长,一场雪还没化,甚至路面还没来得及打扫干净,紧接着又是一场雪。路边的残雪堆积如山,勉强给行人打扫出来的小路大多又覆盖着一层冰,中午时融化一部分,夜里再冻一层。人们步履谨慎,小心翼翼,常常绕道而行。
  美国经济的坏消息也像是波士顿的冬雪,一个接着一个,没有人确切地知道何时会见底。
  在这冰雪覆盖的严冬,哈佛大学于1月28日开始了春季课程。经济系教授马丁•费尔德斯坦(Martin Feldstein)曾在里根政府时期担任经济顾问委员会主席(Chairman of the Council of Economic Advisors,1982-1984),他照例给本科生开一门课,讲美国经济政策,很受学生欢迎。
  以前和他合讲这门课的肯尼迪政府学院的Jeffrey Liebman教授已经进了奥巴马政府, 成了管理和预算办公室(Office of Management and Budget)的第二号人物。“我们可以看看,他以前在这门课中教的和他在政府中做的是不是一致。” 费尔德斯坦说。
  Liebman 的授课部分会由其他三位教授顶替。

长期前景良好
  简短地介绍课程设置和教学大纲之后,费尔德斯坦切入了正题。他说,目前的经济危机是1930年代大萧条之后最严重的经济危机。在2007年以前的五年中,主要经济指标都显示,美国经济非常健康:年均GDP增长3.1%,低通胀高就业(失业率仅仅4.6%),联邦政府赤字大约是GDP的1.5%。“这样的大好形势不是偶然的,而是和适当的财政、货币政策息息相关。”费尔德斯坦说,“当然,当时也有一些隐患,大约7000亿美元的贸易赤字(占GDP的5%)和人口老龄化给国家预算带来了负担。”
  相比之下,现在的失业率是7.2%,有人预计失业率会达到9%,甚至10%。 
  失业率从4.6% 增长一倍,意味着大约700万美国人会失业。2008年第四季度,GDP下滑3.8%,而且面临通货紧缩(deflation)的危险。
  通货紧缩会带来两个问题:一是给美联储带来难题。当美联储减息时,其真正想做的是减少真实利率,通货紧缩只会增加真实利率。二是对贷款人不利。通货紧缩增加了债务的实际价值。
  一般来说,走出经济衰退大约需要8到12个月的时间,但这次衰退从2007年12月份算起已经经历了13个月,所以很有可能需要24个月的时间,还有人认为需要更长的时间。尽管美国现在是一个病人,费尔德斯坦相信,美国仍然可以再现2007年前良好的长期经济增长势头。

危机缘何爆发?
  应对经济衰退,通常主要用货币政策。但由于这次危机的一些特点,仅靠货币政策已经不够,财政刺激必须起主要作用。在费尔德斯坦看来,这是一个非常重要的思想上的变化。
  他说,经济衰退经常是由紧缩货币政策造成的。当美联储由于各种原因判断有通胀的趋势,然后提高基准利率(Federal Funds Rate),经济随即冷却,甚至衰退。但这次危机的起因不同。美联储的利率一直很低,却爆发了危机,这是什么原因呢?
  费尔德斯坦认为有两个原因。一是资产价格过高,资产管理的专业人员出于行业竞争的压力和低利率的大环境,过于追求仅仅高几个百分点的回报,从而低估了风险,压低了风险差异(risk premium,即风险投资和无风险投资回报率之间的差异,后者通常指国债),抬高了资产价格。
  追求高回报是专业资产管理人员的本职工作,他们的工作就是高风险,高回报。如果没有高回报,投资者就会把钱放在其他资产管理公司。而且,这些专业人士常常认为自己比别人聪明,一旦资本市场有风吹草动,自己会比别人跑得快,“只要按电脑上的一个键,马上撤资。”
  但他们的风险机率中有一部分是尾分布(tail distribution),也就是说,他们失败的可能性很小,但一旦失败,损失会极大。这就像保险公司卖地震保险,地震的发生频率很小,一旦发生,损失很大。保险公司在很长时间内的收入都会非常可观,公司的高管层都会收入颇丰。因为出现损失的时候,主要是股民的损失,所以高管层有很大的动力去追求高风险。
  二是借贷比例过高。一些投资银行的资产和股本(equity)的比例是30比1。也就是用每一块钱的本金借了29块钱。在经济形势好的时候,杠杆效应会带来超乎寻常的高利润和高收入;在经济形势不好的时候,只要资产价格下跌4%,公司就会资不抵债。
  这次危机的爆发点是房地产市场的次贷风波。从2000年到2006年中期,房产价格增长了60%。人们普遍认为这种增长势头会持续下去,于是你争我赶地买房,或者从小房换大房。再加上布什政府在本世纪初鼓励拥有房产(ownership society),银行借贷系统通过降低房贷门槛,减少首期付款,然后把房贷打包分割证券化,再转手销售。
  于是,原本买不起房子的人也成了房主。当他们不能如期偿付贷款时,一系列连锁效应发生了。那些拥有房产抵押证券(mortgage backed securities)的金融机构首先受损。巨型投资银行先后被收购、倒闭、转型。资本市场马上出现信贷紧缩,流动性减少,价格很难确定。几乎所有的金融机构都不能确定自己损失了多少投资,还有多少本金,更无法融资。信贷紧缩导致与房地产不相干的证券价格下跌,股票市场普遍遭到重创。
  房产价格从2006年中期的顶端到现在已经下跌了25%,股市从峰值下跌了40%。美国人从房地产中损失了4万亿美元,从股市中损失了8万亿美元。美国人的财富转眼间减少了12万亿美元。
  一般来说,财富对消费的影响是4%。也就是说,美国的消费要减少将近5000亿美元。房地产业本身已供大于求,还要减少大约2000亿美元的房屋生产。这样,总共会减少7000亿美元,这会导致GDP会负增长大约5%。
  1月30日数据显示,美国经济2008年第四季度的GDP比第三季度下滑3.8%,小于经济学家预测的5.5%, 原因是库存增加,生产减少的还没有像需求减少的那样快。这意味着美国上半年的经济数据会更加糟糕。
  有经济学家认为,房产价格还有15%的下降空间。这一预测如果真的发生,那么美国三分之一以上的房主(大约1200万个家庭)会发现,他们房子的贷款大于他们房子的市场价格,他们每个月要付的房贷大于他们出租差不多的房子的租金。他们会更有动力拒付房贷,迫使银行没收房子(即foreclosure)。2008年银行没收的房子数量比2007年多了一倍。市场上的银行没收的房子增加了房屋供给,再次压低房价,加速恶性循环。房价在去年一年就降低了18%。

没有追索权
  还有一点很重要,在以前的《哈佛笔记》中没有强调过,即美国的房屋贷款与其他国家有法律上的区别,美国更加注意保护借钱人的利益。美国的房屋贷款几乎都是没有追索权的(non-recourse loans),也就是说,如果借款人拒付每个月的房贷,银行只能把房屋收回来,不能从借款人的其他收入中截流。即使有个别州的房屋贷款是有追索权的(recourse loans),美国的个人破产法也基本保证了借款人的利益,这就给借款人更大的动力拒付房贷。
  我们可以试想,在2003到2006年间,那些只付10%、或5%、甚至更少的首期付款的人,在房价普遍下跌25%的时候,他们的贷款远远大于房子的市价。当他们发现,用小于他们每个月还银行的按揭款可以租到差不多的房子的时候,他们完全可以放弃他们的房子,让银行拿去。即使他们并不穷,每个月还有不错的收入,他们也愿意选择放弃房子。因为房屋贷款是没有追索权的(non-recourse loans), 银行只能眼睁睁地看着他们用每个月的收入租房子或做其他事情,没有任何办法。
  更严重的是几年以前,银行为了鼓励人们买房子,发明了一种“2-28贷款”:前两年付很少的贷款,从第三年开始每个月的房贷骤然提升,弥补前两年的低息贷款,旧账新账加在一起。如果房价持续上升,这是一笔不错的买卖。即使第三年支持不住每个月的房贷,房主还可以把房子卖了,赚一笔钱走人。
  但是现在房市垮了,那些有“2-28贷款”的人有更多的理由拒付房贷(无论付得起还是付不起),让银行没收。正是这些原因,德意志银行不知不觉地就成了俄亥俄州一个小城镇的最大的房主。所有和房产有关的银行都面临同样的命运。
  这些房产抵押证券又被切割打包,按不同等级卖给投资银行,投资银行又卖给无数的投资者。于是无数的投资者——机构投资者、个人投资者,男女老少,有经验的,没经验的——全被卷了进去。
  危机从银行扩展到所有的金融机构,又从金融机构扩展到非金融机构,从房市扩展到股市和所有资本市场,又从资本市场扩展到实体经济,一发不可收拾。
  无怪乎费尔德斯坦在开课伊始就说,“现在讲美国经济政策,是一个非常有意思的时刻,也是一个令人忧心忡忡的时刻。”

 

【哈佛笔记之五十】从经济学角度分析环境问题

Filed under: market indicators — rogerwang2046 @ 02:01

【哈佛笔记之五十】从经济学角度分析环境问题

本文来源于《财经网》 2009年03月24日 14:23  

环境是公共产品,很易产生“搭便车”现象,即不承担治理环境的成本,却享受治理环境的好处。经济学家考虑的是,用什么方式才能最经济地解决问题
《财经》特约作者 陈晋  环境是公共产品,很易产生“搭便车”现象,即不承担治理环境的成本,却享受治理环境的好处。经济学家考虑的是,用什么方式才能最经济地解决问题

  【《财经网》专稿/特约作者 陈晋】21世纪的人们已经愈加认识到了环境的重要性,包括清洁环境的价值和治理环境的成本。这其中有巨大的经济利益,很多产品价格只反映了其内部的经济成本,但没有包括生产过程中的社会成本(social cost),即对环境的污染,或负面的外部性(negative externality)。环境是一个公共产品(public good),有公共产品的特征,很容易产生“搭便车”(free rider problem)的现象,即不承担治理环境成本,却享受治理环境的好处。
  如何使产品价格体现经济成本和社会成本的总和;谁承担成本、谁享受好处都是非常复杂的政治经济问题。任何政策选择和取向都会有深远的影响,影响一大片人的经济利益,以及更多人的生产和生活方式。什么样的政策是最佳选择呢?
  马丁•费尔德斯坦教授讲完开放经济部分(美元与贸易赤字)以后,请来了肯尼迪政府学院环境与资源项目的经济学教授罗伯特•斯达温思(Robert N. Stavins)来讲环境问题,一共四堂课。
  斯达温思于1988年获哈佛大学经济系博士,是环境问题专家,曾任美国环境保护局(U.S. Environmental Protection Agency)环境经济顾问委员会主席(1997-2002)。
  斯达温思开门见山,他的主要目的就是向学生介绍,经济学家是如何分析环境问题的,并如何利用经济学框架及理论帮助设置解决环境问题的机制。
  他原以为每节课有90分钟(肯尼迪政府学院的课程大多是90分钟一堂),走进教室以后,助教才告诉他只有55分钟,所以不得不消减他准备好的30%以上的内容。即使如此,最后一节课讲气候问题时,他也只能蜻蜓点水,非常仓促。

两个层面
  介绍任何领域都是从定义和分类开始的。讨论环境污染有两种层面:一个是时间层面,一个是地域层面。
  从时间层面上说,污染排放量在任何一个时间都等于存量加增量,减自然分解或消失的部分(decay)。二氧化碳在空气中会存在几十年,所以一般来说,只考虑它的存量和增量。
  从地域层面上说,有的污染源只是就近污染,对附近造成危害,例如一氧化碳。有的污染源会传的比较远,对较远的区域造成危害,例如二氧化硫和酸雨。我们时常会看到有的工厂的烟筒建造得出奇的高,为什么呢?因为他们不想让排出的废气影响周围的空气质量,而希望把二氧化硫等废气排入高空,随风带到更远的地方。
  还有的污染源会在全球范围内造成危害,例如二氧化碳和其他有温室效应的气体。解决这种污染很棘手的其中一个原因就是“搭便车”的问题:没有为减排付出努力,却可以享受到别人减排使得空气清新的成果。

思维框架
  经济学家总是考虑,用什么方式才能最经济地解决问题。根据边际成本递增,边际收益递减的微观经济学原理,我们得出结论,当边际成本等于边际收益时,总收益最大。
  具体到环境问题,当减少排污的边际成本等于减少排污的边际好处时,减少排污的好处总量最大。
  但是,减少排污的好处很难定义,更难量化,所以经济学家就把问题加以转换,变为如何减少减排成本的问题。
  

  衡量环境政策手段(environmental policy instruments)的好坏,有多种标准:政策是否达到预期目标;是否成本最小;政府是否有作决策需要的信息;执行和监督的力度有多大;在科技日新月异的今天,政策是否有随科技变化的灵活性;分配经济和环境影响时的公正性如何(谁多承受成本,谁少承受成本;谁多享受好处,谁少享受好处);政策的目的和性质是否可以比较容易地解释给公众等等。
  现在假设我们只考虑一种污染源,而且污染源是均匀混合的,例如二氧化碳。每个排出二氧化碳废气的厂家都有非常不同的随减排量而变化的成本结构,他们甚至自己也不清楚自己减排的成本曲线是什么样的。
  假设政府的政治任务是减排x立方米,这个减排指标应该如何分配呢?
  如果把这个指标平均分配给所有产生这个污染源的厂家,表面看起来,每个厂家都是平等的,但问题是这种办法没有把每个厂家不同的减排成本考虑进去,所以整体来说,这不是完成这个政治任务成本最小的方法。直觉告诉我们,那些减排成本更小的厂家应该承担更多的减排任务,成本更大的厂家承担更小的减排任务。数学证明显示,只有当这些厂家减排的边际成本都一样时,各个厂家的减排成本之和是最小的。

行政命令与经济手段
  这种方法与其他环境政策手段有什么不同呢?通过行政命令达到环保目的的方法有很多问题,最主要的就是“一刀切”,不灵活机动。
  一种行政命令的方式是规定必须使用的技术标准(technology standard),例如每个汽车上都必须装有废气监测器。这种方法的好处是监管容易,坏处是不能直接地达到目标;而且只能用现在的技术,不能够灵活地随科学技术的变化而变化,而且不是最经济划算的。
  另一种行政命令的方式是规定业绩标准(performance standard),即根据技术指标,看看各个厂家是否达标。一般来说,这样做都不是成本最小化的,因为政府没有办法知道厂家减排的成本曲线。如果政府询问他们,即使他们自己也不知道自己的成本结构,他们肯定也会说,减排的成本高得难以承受。所以这不是最好的方式。
  经济学家更倾向,通过给予经济鼓励政策(economic-incentive approach),让经济个体酌情而定,从而在整体层面达到减排目的。经济学家通过两种方式改变经济个体的决策动机,一种是对排污征税,也就是经济个体要向政府购买污染环境的权利;另一种是限制排放总量,经济个体之间可以自由买卖排放配额(cap-and-trade system)。前者是通过征税,调整价格(price control);后者是通过配额,调整数量(quantity control)。
  假设政府对每单位数量的污染征税额为t,那么每个厂家就要选择排放多少污染和自己解决消化多少污染。每个厂家的目的是使缴污染税和自己消化污染的成本之和最小化。数学证明显示,每个厂家都会选择减排的边际成本等于t时所相对应的减排数量。通过设置t,政府使所有厂家减排的边际成本都相等了,所以通过征税减排可以达到成本最小化。而且当有新的科学技术出现时,厂家有动力采用新技术以减少自己消化污染的成本和污染税。这和行政命令有显著区别。■(未完待续)

 

Elliott Wave Theory 2009/03/28

Filed under: market indicators — rogerwang2046 @ 23:22
Tags:

Elliott Wave Theory

R. N. Elliott believed markets had well-defined waves that could be used to predict market direction. In 1939, Elliott detailed the Elliott Wave Theory, which states that stock prices are governed by cycles founded upon the Fibonacci series (1-2-3-5-8-13-21…).

According to the Elliott Wave Theory, stock prices tend to move in a predetermined number of waves consistent with the Fibonacci series. Specifically, Elliott believed the market moved in five distinct waves on the upside and three distinct on the downside. The basic shape of the wave is shown below.

Elliott Wave example image from StockCharts.com

Waves one, three and five represent the ‘impulse’, or minor up-waves in a major bull move. Waves two and four represent the ‘corrective,’ or minor down-waves in the major bull move. The waves lettered A and C represents the minor down-waves in a major bear move, while B represents the one up-wave in a minor bear wave.

Elliott proposed that the waves existed at many levels, meaning there could be waves within waves. To clarify, this means that the chart above not only represents the primary wave pattern, but it could also represent what occurs just between points 2 and 4. The diagram below shows how primary waves could be broken down into smaller waves.

Embedded Elliott Wave example image from StockCharts.com

Elliott Wave theory ascribes names to the waves in order of descending size:

  1.  Grand Supercycle
  2.  Supercycle
  3.  Cycle
  4.  Primary
  5.  Intermediate
  6.  Minor
  7.  Minute
  8.  Minuette
  9.  Sub-Minuette

The major waves determine the major trend of the market, and minor waves determine minor trends. This is similar to the way Dow Theory postulates primary and secondary trends. Elliott provided numerous variations on the main wave, and placed particular importance on the golden mean, 0.618, as a significant percentage for retracement.

Trading using Elliott Wave patterns is quite simple. The trader identifies the main wave or Supercycle, enters long, and then sells or shorts, as the reversal is determined. This continues in progressively shorter cycles until the cycle completes and the main wave resurfaces. The caution to this is that much of the wave identification is taken in hindsight and disagreements arise between Elliott Wave technicians as to which cycle the market is in.

Here is an example of an Elliott Wave cycle. Ideally, Wave Two would not retrace more than 66%, but you can get a real sense of the wave patterns in action from the chart, just as well.

For more information, check out Elliott Wave Principle: Key to Market Behavior by Robert Prechter.


 

Dow Theory

Filed under: market indicators — rogerwang2046 @ 23:20
Tags:

Dow Theory

Introduction

The Dow theory has been around for almost 100 years, yet even in today’s volatile and technology-driven markets, the basic components of Dow theory still remain valid. Developed by Charles Dow, refined by William Hamilton and articulated by Robert Rhea, the Dow theory addresses not only technical analysis and price action, but also market philosophy. Many of the ideas and comments put forth by Dow and Hamilton became axioms of Wall Street. While there are those who may think that it is different this time, a read through The Dow Theory will attest that the stock market behaves the same today as it did almost 100 years ago.

The Dow theory presented below has been taken from Robert Rhea’s book, The Dow Theory. Although Dow theory is attributed to Charles Dow, it is William Hamilton’s writings that serve as the corner stone for this book and the development of the theory. Also, it should be noted that most of the theory was developed with the Dow Jones Rail and Industrial averages in mind. Even though many concepts can be applied to individual stocks, please keep in mind that these are broad concepts and best applied to stocks as a group or index. When possible, we have also attempted to link some of the realities of today’s market with the Dow theory as explained by Dow, Hamilton and Rhea.

Background

Charles Dow developed the Dow theory from his analysis of market price action in the late 19th century. Until his death in 1902, Dow was part owner as well as editor of The Wall Street Journal. Although he never wrote a book on the subject, he did write some editorials that reflected his views on speculation and the role of the rail and industrial averages.

Even though Charles Dow is credited with developing the Dow theory, it was S.A. Nelson and William Hamilton who later refined the theory into what it is today. Nelson wrote The ABC of Stock Speculation and was the first to actually use the term “Dow theory.” Hamilton further refined the theory through a series of articles in The Wall Street Journal from 1902 to 1929. Hamilton also wrote The Stock Market Barometer in 1922, which sought to explain the theory in detail.

In 1932, Robert Rhea further refined the analysis of Dow and Hamilton in The Dow Theory. Rhea read, studied and deciphered some 252 editorials through which Dow (1900-1902) and Hamilton (1902-1929) conveyed their thoughts on the market. Rhea also referred to Hamilton’s The Stock Market BarometerThe Dow Theory presents the Dow theory as a set of assumptions and theorems.

Assumptions

Before one can begin to accept the Dow theory, there are a number of assumptions that must be accepted. Rhea stated that for the successful application of the Dow theory, these assumptions must be accepted without reservation.

Manipulation

The first assumption is: The manipulation of the primary trend is not possible. When large amounts of money are at stake, the temptation to manipulate is bound to be present. Hamilton did not argue against the possibility that speculators, specialists or anyone else involved in the markets could manipulate the prices. He qualified his assumption by asserting that it was not possible to manipulate the primary trend. Intraday, day-to-day and possibly even secondary movements could be prone to manipulation. These short movements, from a few hours to a few weeks, could be subject to manipulation by large institutions, speculators, breaking news or rumors. Today, Hamilton would likely add message boards and day-traders to this list.

Hamilton went on to say that individual shares could be manipulated. Examples of manipulation usually end the same way: the security runs up and then falls back and continues the primary trend. Examples include:

  •  PairGain Technology rose sharply due to a hoax posted on a fake Bloomberg site. However, once the hoax was revealed, the stock immediately fell back and returned to its primary trend.
  •  Books-A-Million rose from 3 to 47 after announcing an improved web site. Three weeks later, the stock settled around 10 and drifted lower from there.
  •  In 1979/80, there was an attempt to manipulate the price of silver by the Hunt brothers. Silver skyrocketed to over 50$ per ounce, only to come back down to earth and resume its long bear market after the plot to corner the market was unveiled.

While these shares were manipulated over the short term, the long-term trends prevailed after about a month. Hamilton also pointed out that even if individual shares were being manipulated, it would be virtually impossible to manipulate the market as a whole. The market was simply too big for this to occur.

Averages Discount Everything

The market reflects all available information. Everything there is to know is already reflected in the markets through the price. Prices represent the sum total of all the hopes, fears and expectations of all participants. Interest rate movements, earnings expectations, revenue projections, presidential elections, product initiatives and all else are already priced into the market. The unexpected will occur, but usually this will affect the short-term trend. The primary trend will remain unaffected.

The chart below of Coca-Cola (KO)[Ko] is a recent example of the primary trend remaining intact. The downtrend for Coca-Cola began with the sharp fall from above 90. The stock rallied with the market in October and November 1998, but by December started to decline again. According to Dow theory, the October/November rally would be called a secondary move (against the primary trend). It is likely that the stock was caught up in the general market advance at the time. However, when the major indices were hitting new highs in December, Coca-Cola was starting to flounder and resume its primary trend.

Coca Cola Co. (KO) Reaction Rally example chart from StockCharts.com

Hamilton noted that sometimes the market would react negatively to good news. For Hamilton, the reasoning was simple: the market looks ahead. By the time the news hits the street, it is already reflected in the price. This explains the old Wall Street axiom, “buy the rumor, sell the news”. As the rumor begins to filter down, buyers step in and bid the price up. By the time the news hits, the price has been bid up to fully reflect the news. Yahoo! (YHOO)[Yhoo] and the run up to earnings is a classic example. For the past three quarters, Yahoo! has been bid up leading right up to the earnings report. Even though earnings have exceeded expectations each time, the stock has fallen by about 20%.

Yahoo Inc. (YHOO) Rumor example chart from StockCharts.com

Theory Not Perfect

Hamilton and Dow readily admit that the Dow theory is not a sure-fire means of beating the market. It is looked upon as a set of guidelines and principles to assist investors and traders with their own study of the market. The Dow theory provides a mechanism for investors to use that will help remove some of the emotion. Hamilton warns that investors should not be influenced by their own wishes. When analyzing the market, make sure you are objective and see what is there, not what you want to see. If an investor is long, he or she may want to see only the bullish signs and ignore any bearish signals. Conversely, if an investor is out of the market or short, he or she may be apt to focus on the negative aspects of the price action and ignore any bullish developments. Dow theory provides a mechanism to help make decisions less ambiguous. The methods for identifying the primary trend are clear-cut and not open to interpretation.

Even though the theory is not meant for short-term trading, it can still add value for traders. No matter what your time frame, it always helps to be able to identify the primary trend. According to Hamilton (writing in the early part of the 20th century), those who successfully applied the Dow theory rarely traded more than four or five times a year. Remember that intraday, day-to-day and possibly even secondary movements can be prone to manipulation, but the primary trend is immune from manipulation. Hamilton and Dow sought a means to filter out the noise associated with daily fluctuations. They were not worried about a couple of points, or getting the exact top or bottom. Their main concern was catching the large moves. Both Hamilton and Dow recommended close study of the markets on a daily basis, but they also sought to minimize the effects of random movements and concentrate on the primary trend. It is easy to get caught up in the madness of the moment and forget the primary trend. After the October low, the primary trend for Coca-Cola remained bearish. Even though there were some sharp advances, the stock never forged a higher high.

Market Movements

Dow and Hamilton identified three types of price movements for the Dow Jones Industrial and Rail averages: primary movements, secondary movements and daily fluctuations. Primary moves last from a few months to many years and represent the broad underlying trend of the market. Secondary (or reaction) movements last from a few weeks to a few months and move counter to the primary trend. Daily fluctuations can move with or against the primary trend and last from a few hours to a few days, but usually not more than a week.

Primary Movement

Primary movements represent the broad underlying trend of the market and can last from a few months to many years. These movements are typically referred to as bull and bear markets. Once the primary trend has been identified, it will remain in effect until proved otherwise. (We will address the methods for identifying the primary trend later in this article.) Hamilton believed that the length and the duration of the trend were largely indeterminable. Hamilton did study the averages and came up with some general guidelines for length and duration, but warned against attempting to apply these as rules for forecasting.

Many traders and investors get hung up on price and time targets. The reality of the situation is that nobody knows where and when the primary trend will end. The objective of Dow theory is to utilize what we do know, not to haphazardly guess about what we don’t know. Through a set of guidelines, Dow theory enables investors to identify the primary trend and invest accordingly. Trying to predict the length and the duration of the trend is an exercise in futility. Hamilton and Dow were mainly interested in catching the big moves of the primary trend. Success, according to Hamilton and Dow, is measured by the ability to identify the primary trend and stay with it.

Secondary Movements

Secondary movements run counter to the primary trend and are reactionary in nature. In a bull market a secondary move is considered a correction. In a bear market, secondary moves are sometimes called reaction rallies. Earlier in this article, a chart of Coca-Cola was used to illustrate reaction rallies (or secondary movements) within the confines of a primary bear trend. Below is a chart illustrating a correction within the confines of a primary bull trend.

Dow Jones Industrial Average ($INDU) Market Movement example chart from StockCharts.com

In Sept-96, the DJIA ($INDU)[$INDU] recorded a new high, thereby establishing the primary trend as bullish. From trough to peak, the primary advance rose 1988 points. During the advance from Sept-96 to Mar-97, the DJIA never declined for more than two consecutive weeks. By the end of March, after three consecutive weeks of decline, it became apparent that this move was not in the category of daily fluctuations and could be considered a secondary move. Hamilton noted some characteristics that were common to many secondary moves in both bull and bear markets. These characteristics should not be construed as rules, but rather as loose guidelines to be used in conjunction with other analysis techniques. The first three characteristics have been applied to the example above.

  1.  Based on historical observation, Hamilton estimated that secondary movements retrace 1/3 to 2/3 of the primary move, with 50% being the typical amount. In actuality, the secondary move in early 1997 retraced about 42% of the primary move. (7158 – 5170 = 1988; 7158 – 6316 = 842, 842/1988 = 42.35%).
  2.  Hamilton also noted that secondary moves tend to be faster and sharper than the preceding primary move. Just with a visual comparison, we can see that the secondary move was sharper that the preceding primary advance. The primary move advanced 38% (1988/5170 = 38%) and lasted from Jul-96 to Mar-97, about 8 months. The secondary move witnessed a correction of 11.7% (842/7158 = 11.7%) and lasted a mere five weeks.
  3.  At the end of the secondary move, there is usually a dull period just before the turnaround. Little price movement, a decline in volume, or a combination of the two can mark this dullness. Below is a daily chart focusing on the Apr-97 low for the secondary move outlined above.

    Dow Jones Industrial Average ($INDU) Market Movement (detail) example chart from StockCharts.com

    April 7 through 10 marked the dull point (red line on volume). There was little price movement and volume was the lowest since the decline began. TheDJIA ($INDU)[$INDU] then gapped down on an increase in volume. After the down gap, there was a reversal day and then the DJIA proceeded with a gap up and breakout to a reaction high on increasing volume (green line on volume). The new reaction high combined with the increase in volume indicated that the secondary move was over and the primary trend had resumed.

  4.  Lows are sometimes accompanied by a high-volume washout day. The September/October lows in 1998 were accompanied by record volume levels. At the time, the low on Sept-1 witnessed the highest volume ever recorded and the Oct-8 low recorded the second highest volume ever. Although these high-volume lows were not a signal in and of themselves, they helped form a pattern that preceded a historical advance. This advance took the DJIA ($INDU)[$INDU] from below 8000 to over 11000 in less than one year. Further confirmation of a change in trend came in the form of a new reaction high with high volume on Oct-15.

    Dow Jones Industrial Average ($INDU) Market Movement (detail) example chart from StockCharts.com

Dow Theory Note

There is still debate as to whether the crash of 1998 was a bear market or merely a secondary move within the confines of a larger bull market. In hindsight, it would appear to be a secondary move. Even though the DJIA recorded a lower low on August 4 and had lost just over 20% by September 4, the two-month time frame makes it difficult to justify as a bear market.

Hamilton characterized secondary moves as a necessary phenomenon to combat excessive speculation. Corrections and counter moves kept speculators in check and added a healthy dose of guesswork to market movements. Because of their complexity and deceptive nature, secondary movements require extra careful study and analysis. Investors often mistake a secondary move for the beginning of a new primary trend. How far does a secondary move have to go before the primary trend is affected? This issue will be addressed in Part 3 of this article, when we analyze the various signals based on Dow theory.

Daily Fluctuations

Daily fluctuations, while important when viewed as a group, can be dangerous and unreliable individually. Due to the randomness of the movements from day to day, the forecasting value of daily fluctuations is limited at best. At worst, too much emphasis on daily fluctuation will lead to forecasting errors and possibly losses. Getting too caught up in the movement of one or two days can lead to hasty decisions that are based on emotion. It is vitally important to keep the whole picture in mind when analyzing daily price movements. Think of the pieces of a puzzle. Individually, a few pieces are meaningless, yet at the same time they are essential to complete the picture. Daily price movements are important, but only when grouped with other days to form a pattern for analysis. Hamilton did not disregard daily fluctuations, quite to the contrary. The study of daily price action can add valuable insight, but only when taken in context of the larger picture. There is little structure in one, two or even three days’ worth of price action. However, when a series of days is combined, a structure will start to emerge and analysis becomes better grounded.

The Three Stages of Primary Bull Markets and Primary Bear Markets

Hamilton identified three stages to both primary bull markets and primary bear markets. These stages relate as much to the psychological state of the market as to the movement of prices. A primary bull market is defined as a long sustained advance marked by improving business conditions that elicit increased speculation and demand for stocks. A primary bear market is defined as a long sustained decline marked by deteriorating business conditions and subsequent decrease in demand for stocks. In both primary bull markets and primary bear markets, there will be secondary movements that run counter to the major trend.

Primary Bull Market – Stage 1 – Accumulation

Hamilton noted that the first stage of a bull market was largely indistinguishable from the last reaction rally of a bear market. Pessimism, which was excessive at the end of the bear market, still reigns at the beginning of a bull market. It is a period when the public is out of stocks, the news from corporate America is bad and valuations are usually at historical lows. However, it is at this stage that the so-called “smart money” begins to accumulate stocks. This is the stage of the market when those with patience see value in owning stocks for the long haul. Stocks are cheap, but nobody seems to want them. This is the stage where Warren Buffet stated in the summer of 1974 that now was the time to buy stocks and become rich. Everyone else thought he was crazy.

In the first stage of a bull market, stocks begin to find a bottom and quietly firm up. When the market starts to rise, there is widespread disbelief that a bull market has begun. After the first leg peaks and starts to head back down, the bears come out proclaiming that the bear market is not over. It is at this stage that careful analysis is warranted to determine if the decline is a secondary movement (a correction of the first leg up). If it is a secondary move, then the low forms above the previous low, a quiet period will ensue as the market firms and then an advance will begin. When the previous peak is surpassed, the beginning of the second leg and a primary bull will be confirmed.

Primary Bull Market – Stage 2 – Big Move

The second stage of a primary bull market is usually the longest, and sees the largest advance in prices. It is a period marked by improving business conditions and increased valuations in stocks. Earnings begin to rise again and confidence starts to mend. This is considered the easiest stage to make money as participation is broad and the trend followers begin to participate.

Primary Bull Market – Stage 3 – Excess

The third stage of a primary bull market is marked by excessive speculation and the appearance of inflationary pressures. (Dow formed these theorems about 100 years ago, but this scenario is certainly familiar.) During the third and final stage, the public is fully involved in the market, valuations are excessive and confidence is extraordinarily high. This is the mirror image to the first stage of the bull market. A Wall Street axiom: When the taxi cab drivers begin to offer tips, the top cannot be far off.

Primary Bear Market – Stage 1 – Distribution

Just as accumulation is the hallmark of the first stage of a primary bull market, distribution marks the beginning of a bear market. As the “smart money” begins to realize that business conditions are not quite as good as once thought, they start to sell stocks. The public is still involved in the market at this stage and become willing buyers. There is little in the headlines to indicate a bear market is at hand and general business conditions remain good. However, stocks begin to lose a bit of their luster and the decline begins to take hold.

While the market declines, there is little belief that a bear market has started and most forecasters remain bullish. After a moderate decline, there is a reaction rally (secondary move) that retraces a portion of the decline. Hamilton noted that reaction rallies during bear markets were quite swift and sharp. As with his analysis of secondary moves in general, Hamilton noted that a large percentage of the losses would be recouped in a matter of days or perhaps weeks. This quick and sudden movement would invigorate the bulls to proclaim the bull market alive and well. However, the reaction high of the secondary move would form and be lower than the previous high. After making a lower high, a break below the previous low would confirm that this was the second stage of a bear market.

Primary Bear Market – Stage 2 – Big Move

As with the primary bull market, stage two of a primary bear market provides the largest move. This is when the trend has been identified as down and business conditions begin to deteriorate. Earnings estimates are reduced, shortfalls occur, profit margins shrink and revenues fall. As business conditions worsen, the sell-off continues.

Primary Bear Market – Stage 3 – Despair

At the top of a primary bull market, hope springs eternal and excess is the order of the day. By the final stage of a bear market, all hope is lost and stocks are frowned upon. Valuations are low, but the selling continues as participants seek to sell no matter what. The news from corporate America is bad, the economic outlook bleak and not a buyer is to be found. The market will continue to decline until all the bad news is fully priced into stocks. Once stocks fully reflect the worst possible outcome, the cycle begins again.

Signals

Through the writings of Dow and Hamilton, Rhea identified 4 separate theorems that addressed trend identification, buy and sell signals, volume, and trading ranges. The first two were deemed the most important and serve to identify the primary trend as bullish or bearish. The second two theorems, dealing with volume and trading ranges, were not considered instrumental in primary trend identification by Hamilton. Volume was looked upon as a confirming statistic and trading ranges were thought to identify periods of accumulation and distribution.

Identification of the Trend

The first step in identifying the primary trend is to identify the individual trend of the Dow Jones Industrial Average (DJIA), and Dow Jones Transportation Average (DJTA), individually. Hamilton used peak and trough analysis in order to ascertain the identity of the trend. An uptrend is defined by prices that form a series of rising peaks and rising troughs (higher highs and higher lows). In contrast, a downtrend is defined by prices that form a series of declining peaks and declining troughs (lower highs and lower lows).

Once the trend has been identified, it is assumed valid until proved otherwise. A downtrend is considered valid until a higher low forms and the ensuing advance off of the higher low surpasses the previous reaction high. Below is a chart of the Dow Jones Transportation Average in 1992. Even though Hamilton and Dow did not make specific references to trend lines, a line has been drawn to emphasize the downward trajectory of the trend. Since the peak in February, a series of lower lows and lower highs formed to make a downtrend. There was a secondary rally in April and May (green circle), but the March high was not surpassed.

Dow Jones Transportation Average ($TRAN) Trend example chart from StockCharts.com

The DJTA ($TRAN)[$TRAN] continued down until the high volume washout day (red arrow). As discussed in this article, high volume days signal that a possible change is looming. Alone, a high volume washout day is not a buy signal, but rather an indication to monitor price action a little closer. After this high volume day, the DJTA dipped again and then moved above 1250, creating a higher low (green arrow). Even after the higher low is in place, it is still too early to call for a change in trend. The change of trend is not confirmed until the previous reaction high is surpassed (blue arrow).

Conversely, an uptrend is considered in place until a lower low forms and the ensuing decline exceeds the previous low. Below is a line chart of the closing prices for the DJIA. An uptrend began with the Oct-98 lows and the DJIA formed a series of higher highs and higher lows over the next 11 months. Twice, in Dec-98 (red circle) and Jun-99 (blue arrows), the validity of the uptrend came into question, but the uptrend prevailed until late September. (The Dec-98 price action is addressed below.) There were lower highs in Jun-99, but there were never any lower lows to confirm these lower highs and support held. Any bears that jumped the gun in June were made to sit through two more all-time highs in July and August. The change in trend occurred on September 23 when the June lows were violated. Some traders may have concluded that the trend changed when the late August lows were violated. This may indeed be the case, but it is worth noting that the June lows represented a more convincing support area. Keep in mind that the Dow theory is not a science and Hamilton points this out numerous times. The Dow theory is meant to offer insights and guidelines from which to begin careful study of the market movements and price action.

Dow Jones Industial Average ($INDU) Trend example chart from StockCharts.com

Looking at the line chart above (DJIA ($INDU)[$INDU] 1998/1999 daily close semi-log scale), it may be difficult to distinguish between a valid change in trend and a simple correction. For instance: Was a change in trend warranted when the December low penetrated the November low? (red circle) After the November peak, a lower high formed in December and then the November reaction low was broken. In order to eliminate false signals, Hamilton suggested excluding moves of less than 3%. This was not meant to be a hard and fast rule, but the idea is worth noting. With the increased volatility of today’s markets comes the need to smooth the daily fluctuations and avoid false readings.

Hamilton and Dow were interested in catching the big moves and would have been apt to use weekly charts to establish reaction highs and lows. However, in today’s fast moving markets, weekly charts may not portray the detail that investors need. One possible solution is to apply a short moving average to the price plot. Although not mentioned by Hamilton and Dow, a 5-day moving average could be applied to smooth the price series and still allow for detail. The chart below (DJIA ($INDU)[$INDU] 1998/1999 daily close 5-EMA) uses a 5-day exponential moving average to smooth the price plot. Notice that the November reaction low now appears quite immaterial. Also, the September reaction high (red arrow) still shows up.

Dow Jones Industial Average ($INDU) Reaction High example chart from StockCharts.com

Averages Must Confirm

When the Dow theory was being developed at the turn of the century, the railroads were a vital link in the economy. Hamilton argued that many times activity would begin in the Rail Average before the Industrial Average. He attributed this to the fact that before economic activity began, raw materials would have to be moved from the suppliers to manufacturers. Before General Motors could increase production, more steel would need to be transported. Therefore, an increase in activity among the rail stocks would foreshadow an increase in business activity for the industrial stocks.

Why the Rails?

There is no doubt that today’s economy is much different and the makeup of the DJTA has changed to favor the airlines. However, there is still some credibility in using the DJTA to confirm movements in the DJIA. Transport stocks are much more dependent on the economic environment than the average stock and will likely foreshadow economic growth.

  •  The airline business is cyclical and revenues are highly susceptible to economic changes.
  •  Airline companies typically carry above average levels of debt and will be more vulnerable to changes in interest rates.
  •  Energy and Labor costs form a large portion of expenses.

To reflect the added risks above, airline stocks have traditionally sold significantly below market multiples. If the PE for the S&P 500 is 28, the average airline might sell for only 8-10 times earnings.

Even though we are possibly entering into a “new economy,” the majority of businesses will somehow be affected by changes in economic activity, interest rates, energy costs and labor costs. Airline companies, bearing the burden of all of the above, are still likely to act as a leading indicator of the general economic environment.

However, one caveat must be added as well. Possibly the greatest fear of the airlines is that people will stop flying in airplanes. Business travel accounts for a large portion of airline revenues, especially the high margin revenues. With the development of the Internet and networking, the need for business travel could be greatly reduced in the future. Federal Express has already experienced a slowdown in the quantity of business documents being shipped. This could ultimately spill over into the business of the airlines.

How Averages Confirm

Hamilton and Dow stressed that for a primary trend buy or sell signal to be valid, both the Industrial Average and the Rail Average must confirm each other. If one average records a new high or new low, then the other must soon follow for a Dow theory signal to be considered valid.

DJTA and DJIA Confirmed Averages example chart from StockCharts.com

Combining the guidelines set forth for trend identification with the theorem on confirmation, it is now possible to classify the primary trend of the market. The chart above shows an array of signals that occurred during a 7-month period in 1998.

  1.  In April, both the DJIA ($INDU)[$INDU] and DJTA ($TRAN)[$TRAN] recorded new all-time highs (blue line). The primary trend was already bullish, but this confirmation validated the primary trend as bullish.
  2.  In July, trouble began to surface when the DJTA failed to confirm the new high set by the DJIA. This served as a warning sign, but did not change the trend. Remember, the trend is assumed to be in force until proved otherwise.
  3.  On July 31, the DJTA recorded a new reaction low. Two days later, the DJIA recorded a new reaction low and confirmed a change in the primary trend from bullish to bearish (red line). After this signal, both averages went on to record new reaction lows.
  4.  In October, the DJIA formed a higher low while the DJTA recorded a new low. This was another non-confirmation and served notice to be on guard for a possible change in trend.
  5.  After the higher low, the DJIA followed through with a higher high later that month. This effectively changes the trend for the average from down to up.
  6.  It was not until early November that the DJTA went on to better its previous reaction high. However, at the same time the DJIA was also advancing higher and the primary trend had changed from bearish to bullish.

Volume

The importance of volume was alluded to above with the chart of the Apr-97 bottom in the DJIA. Rhea notes that while Hamilton did analyze volume statistics, price action was the ultimate determinant. Volume is more important when confirming the strength of advances and can also help to identify potential reversals.

Volume Confirmation

Hamilton thought that volume should increase in the direction of the primary trend. In a primary bull market, volume should be heavier on advances than during corrections. Not only should volume decline on corrections, but participation should also decrease. As Hamilton put it, the market should become “dull and narrow” on corrections, “narrow” meaning that the number of declining issues should not be expanding dramatically. The opposite is true in a primary bear market. Volume should increase on the declines and decrease during the reaction rallies. The reaction rallies should also be narrow and reflect poor participation of the broader market. By analyzing the reaction rallies and corrections, it is possible to judge the underlying strength of the primary trend.

Volume and Reversals

Hamilton noted that high volume levels could be indicative of an impending reversal. A high volume day after a long advance may signal that the trend is about to change or that a reaction high may form soon. In his StockCharts.com commentary on 25-Jun-99, Rex Takasugi discusses the correlation between volume and peaks in the market. Even though his analysis reveals a lag time between volume peaks and market reversals, the relationship still exists. Takasugi’s analysis reveals that since 1900 there have been 14 cycles and volume peaked on average 5.6 months ahead of the market. He also notes that the most recent volume peak occurred in Apr-99.

Trading Ranges a.k.a. Lines

In his commentaries over the years, Hamilton referred many times to “lines.” Lines are horizontal lines that form trading ranges. Trading ranges develop when the averages move sideways over a period of time and make it possible to draw horizontal lines connecting the tops and bottoms. These trading ranges indicate either accumulation or distribution, but it was virtually impossible to tell which until there was a break to the upside or the downside. If there were a break to the upside, then the trading range would be considered an area of accumulation. If there were a break to the downside, then the trading range would be considered an area of distribution. Hamilton considered the trading range neutral until a breakout occurred. He also warned against attempting to anticipate the breakout.

Dow Jones Industrail Average ($INDU) Tranding Ranges example chart from StockCharts.com

Performance of the Dow Theory

Mark Hulbert, writing in the New York Times – 6-Sept-98, notes a study that was published in the Journal of Finance by Stephen Brown of New York University and William Goetzmann and Alok Kumar of Yale. They developed a neural network that incorporated the rules for identifying the primary trend. The Dow theory system was tested against buy-and-hold for the period from 1929 to Sept-98. When the system identified the primary trend as bullish, a long position was initiated in a hypothetical index fund. When the system signaled a bearish primary trend, stocks were sold and the money was placed in fixed income instruments. By taking money out of stocks after bear signals, the risk (volatility) of the portfolio is significantly reduced. This is a very important aspect of the Dow theory system and portfolio management. In the past few years, the concept of risk in stocks has diminished, but it is still a fact that stocks carry more risk than bonds.

Over the 70-year period, the Dow theory system outperformed a buy-and-hold strategy by about 2% per year. In addition, the portfolio carried significantly less risk. If compared as risk-adjusted returns, the margin of out-performance would increase. Over the past 18 years, the Dow theory system has under-performed the market by about 2.6% per year. However, when adjusted for risk, the Dow theory system outperformed buy-and-hold over the past 18 years. Keep in mind that 18 years is not a long time in the history of the market. The Dow theory system was found to under-perform during bull markets and outperform during bear markets.

Criticisms of Dow Theory

The first criticism of the Dow theory is that it is really not a theory. Neither Dow nor Hamilton wrote proper academic papers outlining the theory and testing the theorems. The ideas of Dow and Hamilton were put forth through their editorials in the Wall Street Journal. Robert Rhea stitched the theory together by poring over these writings.

Secondly, the Dow theory is criticized for being too late. The trend does not change from bearish to bullish until the previous reaction high has been surpassed. Many traders feel that this is simply too late and misses much of the move. Dow and Hamilton sought to catch the meat of the move and enter during the second leg. Even though this is where the bulk of the move will take place, it is also after the first leg and part way into the second leg. And, if one has to wait for confirmation from the other average, it could even be later in the move.

Thirdly, because it uses the DJIA and DJTA, the Dow theory is criticized as being outdated and no longer an accurate reflection of the economy. This may be a valid point, but as outlined earlier, the DJTA is one of the most economically sensitive indices. The stock market has always been seen as a great predictor of economic growth. To at least keep the industrials up to speed, Home Depot, Intel, Microsoft and SBC Corp have been added to the average to replace Chevron, Goodyear, Sears and Union Carbide, as of 1-Nov-99.

Conclusions

The goal of Dow and Hamilton was to identify the primary trend and catch the big moves. They understood that the market was influenced by emotion and prone to over-reaction both up and down. With this in mind, they concentrated on identification and following: identify the trend and then follow the trend. The trend is in place until proved otherwise. That is when the trend will end, when it is proved otherwise.

Dow theory helps investors identify facts, not make assumptions or forecast. It can be dangerous when investors and traders begin to assume. Predicting the market is a difficult, if not impossible, game. Hamilton readily admitted that the Dow theory was not infallible. While Dow theory may be able to form the foundation for analysis, it is meant as a starting point for investors and traders to develop analysis guidelines that they are comfortable with and understand.

Reading the markets is an empirical science. As such there will be exceptions to the theorems put forth by Hamilton and Dow. They believed that success in the markets required serious study and analysis that would be fraught with successes and failures. Success is a great thing, but don’t get too smug about it. Failures, while painful, should be looked upon as learning experiences. Technical analysis is an art form and the eye grows keener with practice. Study both successes and failures with an eye to the future.


Send us your Feedback!
 
 

The Pre-Holiday Effect

Filed under: market indicators — rogerwang2046 @ 23:14
Tags: ,

The Pre-Holiday Effect

Over the past century, there have been nine holidays during which the Exchanges have traditionally been closed. Historical research shows that stock prices often behave in a specific manner in each of the two trading days preceding these holidays. By becoming aware of this behavior, both short-term traders and longer-term investors can benefit.

The general strategy is to purchase equities one or two days prior to a holiday. Short-term traders would look to sell just after the holiday while longer-term investors would wait until year end. Both strategies have proven to be profitable plays. The theory behind this effect is that traders are lightening up their holdings (selling) prior to the three day holiday in order to avoid any unexpected bad news. The selling pressure drives stock prices down, making those days a good opportunity for buying lower in the range.

Here is the average pre-holiday results for the last 50 years, based on the S&P 500 Index:

Holiday Buy two days before, sell at year end Buy one day before, sell at year end
President’s Day* -0.1% 12.2%
Good Friday 7.3% 17.8%
Memorial Day -4.7% 22.8%
Independence Day 13.3% 37.3%
Labor Day 16.8% 33.7%
Election Day 17.9% 4.6%
Thanksgiving 4.3% 1.1%
Christmas -7.1% 15.2%
New Year’s 31.1% 19.6%

*Note: President’s Day data is comprised of the aggregate of both Washington and Lincoln’s Birthday prior to 1998.

The original research was based on the behavior of the S&P 500 Index around the 419 holiday market closings that occurred from 1928 to 1975.

To put those returns in perspective, if you had invested $10,000 in the S&P 500 Index in January 1928 and sold it all in December 1975, you would have ended up with $51,441. However, if you had invested one-ninth of your money just before each pre-holiday period (selling everything at the end of the year), you would have finished with $1,440,716. Not bad!

The Short Term Trading Strategy

Short term trading using the this pre-holiday effect can provide excellent results. In the chart for General Electric (GE)[GE], below, we see that a buy near open on June 30th would be accomplished around $47.75. Selling at open on July 5th at $50.25 provided excellent returns.

General Electric Co. (GE) Pre-Holiday example chart from StockCharts.com

It is important to note that there are two holidays which often have a partial trading day during the holiday weekend – the day before Independence Day and the day after Thanksgiving. These days usually have a shorten trading session that can be extremely volatile. While they can be traded, volume is always very light and it may be difficult to get limit orders filled.

In the chart below for Motorola (MOT)[Mot], we can see that a buy at $30 on June 30th would have been a flat trade July 3rd, but rose $2 and $3 a share in the two days following the July 4th holiday.

Motorola, Inc. (MOT) Pre-Holiday example chart from StockCharts.com

For Realty Income (O)[O], we have a buy near close at $21.2, and a sell just after the open on July 5th at $22. The volume is less than 50,000 shares on average, and the stock is generally down-trending, but the method is still viable.

Realty Income Corp. Md. (O) Pre-Holiday example chart from StockCharts.com

The Long Term Trading Strategy

Again, the theory says that stocks generally fall on those days because traders offload their holdings in order to avoid the risk of significant news appearing while the markets are closed. Longer-term investors who are willing to ride out any short-term negative news are rewarded with lower entry prices.

Here are four examples from the 2000 Memorial Day holiday (May 26th) where excellent entry points appeared:

Microsoft Corp. (MSFT) Pre-Holiday example chart from StockCharts.com 
Microsoft Corp. (MSFT)[Msft]

Rambus, Inc. (RMBS) Pre-Holiday example chart from StockCharts.com 
Rambus, Inc. (RMBS)[Rmbs]

CIENA Corp. (CIEN) Pre-Holiday example chart from StockCharts.com 
CIENA Corp. (CIEN)[Cien]

Hewlett-Packard Co. (HPQ) Pre-Holiday example chart from StockCharts.com 
Hewlett-Packard Co. (HPQ)[Hpq]

Investors that took advantage of those dips should be rewarded by year end.

 

Gap Trading Strategies

Filed under: market indicators — rogerwang2046 @ 23:13
Tags: ,

Gap Trading Strategies

Gap trading is a simple and disciplined approach to buying and shorting stocks. Essentially one finds stocks that have a price gap from the previous close and watches the first hour of trading to identify the trading range. Rising above that range signals a buy, and falling below it signals a short.

What is a Gap?

A gap is a change in price levels between the close and open of two consecutive days. Although most technical analysis manuals define the four types of gap patterns as Common, Breakaway, Continuation and Exhaustion, those labels are applied after the chart pattern is established. That is, the difference between any one type of gap from another is only distinguishable after the stock continues up or down in some fashion. Although those classifications are useful for a longer-term understanding of how a particular stock or sector reacts, they offer little guidance for trading.

For trading purposes, we define four basic types of gaps as follows:

Full Gap Up occurs when the opening price is greater than yesterday’s high price.

In the chart below for Cisco (CSCO)[Csco], the open price for June 2, indicated by the small tick mark to the left of the second bar in June (green arrow), is higher than the previous day’s close, shown by the right-side tick mark on the June 1 bar.

Cisco Systems, Inc. (CSCO) Gap example chart from StockCharts.com

Full Gap Down occurs when the opening price is less than yesterday’s low. The chart for Amazon (AMZN)[Amzn] below shows both a full gap up on August 18 (green arrow) and a full gap down the next day (red arrow).

Amazon.com, Inc. (AMZN) Gap example chart from StockCharts.com

Partial Gap Up occurs when today’s opening price is higher than yesterday’s close, but not higher than yesterday’s high.

The next chart for Earthlink (ELNK)[Elnk] depicts the partial gap up on June 1 (red arrow), and the full gap up on June 2 (green arrow).

EarthLink, Inc. (ELNK) Gap example chart from StockCharts.com

Partial Gap Down occurs when the opening price is below yesterday’s close, but not below yesterday’s low.

The red arrow on the chart for Offshore Logistics (OLG)[Olg], below, shows where the stock opened below the previous close, but not below the previous low.

Offshore Logistics, Inc. (OLG) Gap example chart from StockCharts.com

Why Use Trading Rules?

In order to successfully trade gapping stocks, one should use a disciplined set of entry and exit rules to signal trades and minimize risk. Additionally, gap trading strategies can be applied to weekly, end-of-day, or intraday gaps. It is important for longer-term investors to understand the mechanics of gaps, as the ‘short’ signals can be used as the exit signal to sell holdings.

The Gap Trading Strategies

Each of the four gap types has a long and short trading signal, defining the eight gap trading strategies. The basic tenet of gap trading is to allow one hour after the market opens for the stock price to establish its range. A Modified Trading Method, to be discussed later, can be used with any of the eight primary strategies to trigger trades before the first hour, although it involves more risk. Once a position is entered, you calculate and set an 8% trailing stop to exit a long position, and a 4% trailing stop to exit a short position. A trailing stop is simply an exit threshold that follows the rising price or falling price in the case of short positions.

Long Example: You buy a stock at $100. You set the exit at no more than 8% below that, or $92. If the price rises to $120, you raise the stop to $110.375, which is approximately 8% below $120. The stop keeps rising as long as the stock price rises. In this manner, you follow the rise in stock price with either a real or mental stop that is executed when the price trend finally reverses.

Short Example: You short a stock at $100. You set the Buy-to-Cover at $104 so that a trend reversal of 4% would force you to exit the position. If the price drops to $90, you recalculate the stop at 4% above that number, or $93 to Buy-to-Cover.

The eight primary strategies are as follows:

Full Gaps

Full Gap Up: Long

If a stock’s opening price is greater than yesterday’s high, revisit the 1-minute chart after 10:30 am and set a long (buy) stop two ticks above the high achieved in the first hour of trading. (Note: A ‘tick’ is defined as the bid/ask spread, usually 1/8 to 1/4 point, depending on the stock.)

Full Gap Up: Short

If the stock gaps up, but there is insufficient buying pressure to sustain the rise, the stock price will level or drop below the opening gap price. Traders can set similar entry signals for short positions as follows:

If a stock’s opening price is greater than yesterday’s high, revisit the 1-minute chart after 10:30 am and set a short stop equal to two ticks below the low achieved in the first hour of trading.

Full Gap Down: Long

Poor earnings, bad news, organizational changes and market influences can cause a stock’s price to drop uncharacteristically. A full gap down occurs when the price is below not only the previous day’s close, but the low of the day before as well. A stock whose price opens in a full gap down, then begins to climb immediately, is known as a “Dead Cat Bounce.”

If a stock’s opening price is less than yesterday’s low, set a long stop equal to two ticks more than yesterday’s low.

Full Gap Down: Short

If a stock’s opening price is less than yesterday’s low, revisit the 1-minute chart after 10:30 am and set a short stop equal to two ticks below the low achieved in the first hour of trading.

Partial Gaps

The difference between a Full and Partial Gap is risk and potential gain. In general, a stock gapping completely above the previous day’s high has a significant change in the market’s desire to own or sell it. Demand is large enough to force the market maker or floor specialist to make a major price change to accommodate the unfilled orders. Full gapping stocks generally trend farther in one direction than stocks which only partially gap. However, a smaller demand may just require the trading floor to only move price above or below the previous close in order to trigger buying or selling to fill on-hand orders. There is a generally a greater opportunity for gain over several days in full gapping stocks.

If there is not enough interest in selling or buying a stock after the initial orders are filled, the stock will return to its trading range quickly. Entering a trade for a partially gapping stock generally calls for either greater attention or closer trailing stops of 5-6%.

Partial Gap Up: Long

If a stock’s opening price is greater than yesterday’s close, but not greater than yesterday’s high, the condition is considered a Partial Gap Up. The process for a long entry is the same for Full Gaps in that one revisits the 1-minute chart after 10:30 am and set a long (buy) stop two ticks above the high achieved in the first hour of trading.

Partial Gap Up: Short

The short trade process for a partial gap up is the same for Full Gaps in that one revisits the 1-minute chart after 10:30 am and sets a short stop two ticks below the low achieved in the first hour of trading.

Partial Gap Down: Long

If a stock’s opening price is less than yesterday’s close, revisit the 1 minute chart after 10:30 am and set a buy stop two ticks above the high achieved in the first hour of trading.

Partial Gap Down: Short

The short trade process for a partial gap down is the same for Full Gap Down in that one revisits the 1-minute chart after 10:30AM and sets a short stop two ticks below the low achieved in the first hour of trading.

If a stock’s opening price is less than yesterday’s close, set a short stop equal to two ticks less than the low achieved in the first hour of trading today.

If the volume requirement is not met, the safest way to play a partial gap is to wait until the price breaks the previous high (on a long trade) or low (on a short trade).

End-of-day Gap Trading

All eight of the Gap Trading Strategies can also be applied to end-of-day trading. Using StockCharts.com’s Gap Scans, end-of-day traders can review those stocks with the best potential. Increases in volume for stocks gapping up or down is a strong indication of continued movement in the same direction of the gap. A gapping stock that crosses above resistance levels provides reliable entry signals. Similarly, a short position would be signaled by a stock whose gap down fails support levels.

What is the Modified Trading Method?

The Modified Trading Method applies to all eight Full and Partial Gap scenarios above. The only difference is instead of waiting until the price breaks above the high (or below the low for a short); you enter the trade in the middle of the rebound. The other requirement for this method is that the stock should be trading on at least twice the average volume for the last five days. This method is only recommended for those individuals who are proficient with the eight strategies above, and have fast trade execution systems. Since heavy volume trading can experience quick reversals, mental stops are usually used instead of hard stops.

Modified Trading Method: Long

If a stock’s opening price is greater than yesterday’s high, revisit the 1 minute chart after 10:30 am and set a long stop equal to the average of the open price and the high price achieved in the first hour of trading. This method recommends that the projected daily volume be double the 5-day average.

Modified Trading Method: Short

If a stock’s opening price is less than yesterday’s low, revisit the 1 minute chart after 10:30 am and set a long stop equal to the average of the open and low price achieved in the first hour of trading. This method recommends that the projected daily volume be double the 5-day average.

Where do I find gapping stocks?

Members of StockCharts’ Extra service can run scans against daily data that is updated on an intraday basis. This is perfect for finding gapping stocks. Simply run the pre-defined gap scans using the Intraday data setting around 10AM Eastern. StockCharts.com also publishes lists of stocks that fully gapped up or fully gapped down each day based on end-of-day data. This is an excellent source of ideas for longer term investors.

Although these are useful lists of gapping stocks, it is important to look at the longer term charts of the stock to know where the support and resistance may be, and play only those with an average volume above 500,000 shares a day until the gap trading technique is mastered. The most profitable gap plays are normally made on stocks you’ve followed in the past and are familiar with.

How successful is this?

In simple terms, the Gap Trading Strategies are a rigorously defined trading system that uses specific criteria to enter and exit. Trailing stops are defined to limit loss and protect profits. The simplest method for determining your own ability to successfully trade gaps is to paper trade. Paper trading does not involve any real transaction. Instead, one writes down or logs an entry signal and then does the same for an exit signal. Then subtract commissions and slippage to determine your potential profit or loss.

Gap trading is much simpler than the length of this tutorial may suggest. You will not find either the tops or bottoms of a stock’s price range, but you will be able to profit in a structured manner and minimize losses by using stops. It is, after all, more important to be consistently profitable than to continually chase movers or enter after the crowd.