太多週遭的朋友或是讀者問說今年上市的臉書(Facebook), 該不該買, 因為根本沒有太多的歷史數據或是圖表來判斷, “該不該買”這個簡單的問題我還真的說不上來. 我們今天來換個方向聊聊, 既然大家都在問該不該買, 代表大家都想要趕熱潮湊一咖, 那我們今天就當做”該買”是你想聽的答案, 然後我們來談談這個”該買”之後該”怎麼買”才可以立於不敗之地吧.

今天提供大家我自己已經交易FB一陣子的三招, 第一招最簡單, 第二招次之, 第三招最複雜, 但是別誤會, 這不代表第一招就比後兩招賺的少或是遜, 不論黑貓還是白貓, 會抓老鼠就是好貓, 招不分好不好, 自己用的順心賺到錢就是好招. 閒話休說, 讓我們一招一招看下去.(以下舉例數據是按照12月份選擇權數據)

1. 第一招-固守城池: 簡單, 利用賣裸賣權(sell naked put)進股的觀念, 在歷史低點的價位賣裸賣權. 以12月份的選擇權來說, 賣在strike price = 17, 今天可以收取約35 or 40USD的權利金, 因為你計畫如果價格跌下來要進股, 所以不論保證金的要求多少, 你每賣一口, 請留1700USD最為可能進股的準備, 所以你的ROI = 35or40/1700. 如果到了17後悔了, 不想進, 請轉倉(Rolling), 轉倉我不重複了, 你可以看我之前教轉倉的文章.

選擇權轉倉 Rolling(上)
選擇權轉倉 Rolling(下)

2. 第二招-前後夾攻: 第一招稍微保守了一點, 如果你想要稍微積極一點的策略, 這一招可能適合你, 一樣是在strike price=17賣裸賣權, 得權利金35USD每口, 再去買strike price=25 買權(call)花費差不多也是35USD每口, 因為如果價位跌到17要進股, 所以一樣每口要保留1700USD現金, 這一方法, 股價在DEC到期前沒到25, 你就是沒來, 只要超過25的都是你的, 這一方法很容易就沒來, 主要用在你認為他會大漲, 用賣裸賣權(sell naked put)的錢來買買權(buy call), 沒有成本的賭一局, 屬於積極強攻型的策略選擇, 如果股價跌到17以下, 按照第一招方法執行.

3. 第三招-瞻前顧後: 如果你用第一招覺得太保守, 第二招又覺得太積極, 這瞻前顧後之招可能適合你, 基本上, 當你做完第二招(賣裸賣權@17, 買買權@25)之後, 再做一件事, 就是賣買權@27(sell call), 27只是例子, 你也可以賣在26, 以strike price=27為例, 今天可以收取大約15USD權利金, 也就是說, DEC到期時, 如果價位在17-25之間, 你賺15USD/口, 25-27之間, 你每口賺15USD + (股價-25)*100. 超過27, 不管多少, 你每口只賺215USD. 這一招的壞處就是限制你的獲利上限, 但是當股價沒有大漲時, 你還有權利金可以賺一賺, 算是第一招和第二招的綜合之招.

如果股價真的到了17, 你可以做轉倉, 也可以進股, 如果你進股, 參考之前教的小資練金術, 利用抵補銷售買權(Covered Call, 保護性買權)來收租就是了, 而且17應該是相當合理長期持有的價位, 你可以按照自己不同的需求設止損點.

小資賣肝族煉金術之我就是沒時間(上)!
小資賣肝族煉金術之我就是沒時間(下)!

靈活利用這三招加上之前的選擇權轉倉技巧, 小資收租練金術, 大概可以立於不敗之地了. 當然facebook只是一個 剛好的例子, 你可以靈活的應用於其他適合的股票.

說到facebook, 如果你支持權傾天下無私分享理念和精神, 別忘了Like我們的文章或是Page喔!

 

Previous Related Posts, please click on part 1 on how to utilize this list

Morgan Stanley(股票代號: MS): 42 secular growth stocks 2012 part 1

Morgan Stanley(股票代號: MS): 42 secular growth stocks 2012 part 2

Panera Bread Co.(股票代號: PNRA)

EPS growth: 21.4%
PE 2012: 29.5
PEG ratio: 1.4
Panera Bread like the rest of the “quick casual” restaurants is looking at a long-term growth story as it gains market share from typical fast food and casual dining restaurants with better quality, according to John Glass.

PetSmart Inc.(股票代號: PETM)

EPS growth: 22.0%
PE 2012: 20.2
PEG ratio: 0.9
The pet supply market is expected to grow three – five percent in the coming years and PetSmart is expected to grow market share, according to David Gober.

Priceline.com(股票代號: PCLN)

EPS growth: 23.3%
PE 2012: 20.6
PEG ratio: 0.9
Priceline.com is expected to gain from the rising trend of booking hotel rooms online, according to Scott Devitt.

QLIK Technologies(股票代號: QLIK)

EPS growth: 29.0%
PE 2012: 73.0
PEG ratio: 2.5
“As a market leader in in-memory analytics, QlikTech should disproportionally benefit from the growth in data and data-related spending, gaining share in the analytics platform,” according to Adam Holt.

Rackspace Hosting Inc.(股票代號: RAX)

EPS growth: 35.3%
PE 2012: 87.0
PEG ratio: 2.5
Rackspace is expected to benefit from outsourcing in the IT sector, according to Simon Flannery.

Red Hat Inc.(股票代號: RHT)

EPS growth: 16.3%
PE 2012: 47.4
PEG ratio: 3.2
Red Hat is expected to gain from its exposure to long-term growth drivers “around virtualization and the cloud” while and its growing range of products, according to Adam Holt.

Salesforce.com(股票代號: CRM)

EPS growth: 25.2%
PE 2012: 101.7
PEG ratio: 4.0
Salesforce.com is “one of the best secular stories in software” as long-term demand for mobile, social and cloud grows, according to Adam Holt.

Splunk Inc.(股票代號: SPLK)

EPS growth: NM
PE 2012: NM
PEG ratio: NA
Splunk is a “scare pure-play on Big Data” and the company is expected to see strong growth in coming years, according to Adam Holt.

Teradata(股票代號)

EPS growth: 16.9%
PE 2012: 26.4
PEG ratio: 1.6
Teradata gains from being able to gear more of its budget towards data analytics and warehousing, according to Katy Huberty.

Tesla Motors(股票代號: TSLA)

EPS growth: NM
PE 2012: NM
PEG ratio: NA
Tesla Motors’ disruptive technology i.e. an innovation that disrupts an existing market, can exploit premium car growth, according to Adam Jonas.

Under Armour(股票代號: UA)

EPS growth: 34.5%
PE 2012: 45.1
PEG ratio: 1.3
Under Armour could see revenue grow 20 percent or more over the next several years through product innovation, wider distribution and an increase in the number of factory outlets, according to Joseph Parkhill.

Visa Inc.(股票代號: V)

EPS growth: 17.5%
PE 2012: 21.9
PEG ratio: 1.3
Like Mastercard, Visa is expected to gain from the global shift to electronic payments from cash/checks, according to Glenn Fodor.

VMware Inc.(股票代號: VMW)

EPS growth: 21.6%
PE 2012: 35.3
PEG ratio: 1.6
VMware still has room for deeper penetration of the sever virtualization market and has a strong, long-term growth story according to Adam Holt.

Whole Foods Market(股票代號: WFM)

EPS growth: 22.2%
PE 2012: 39.8
PEG ratio: 1.8
Like Fresh Market, Whole Foods should benefit from the consumer trend in natural and organic foods and in health and wellness, according to Mark Wiltamuth.

Source: Morgan Stanley; Repost from www.Businessinsider.com

 

由於颶風Sandy逼近紐約市, 今天跟明天美股都將要休市, 這兩天大家可以輕鬆一下, 也來放個交易颱風假. 在輕鬆的同時, 我們也來順便充實一下自己吧! 今天權傾天下再次免費送你原始碼, 希望可以在交易的路途上助你一臂之力!

很多的讀者有問我們類似的問題, 我們常常說到隱含波動率偏高, 或是偏低, 到底有沒有什麼準則可以用來判斷到底是偏高還是偏低呢? 答案是, 有, 但也沒有, 為什麼呢? 因為所謂的隱含波動率, 就是大家對股票波動的期待, 期待越高, 隱含波動率就越高, 但是事出必有因, 空穴不來風, 大家有期待, 就很有可能有重要的事件像是最常見的財報, 新產品發表, 官司等等影響股價巨大的因素, 所以你說他”高”, 他也是高的有其價值的, 不可以簡單的就說這是所謂的”over priced”, 同樣的道理也適用於所謂的”under priced”, 用這樣的角度來說, 隱含波動率並沒有一定的基準或法則來判斷所謂的高低.

但是, 如果我們用圖形的觀點來分析, 每一支股票都有其股性, 也就是說, 一般而言, 同一支股票的隱含波動率會在一定的”範圍”之中震盪, 所以當他到這個範圍的”高點”時, 就有很大的機率要回落, 同樣的, 如果到了低點, 那可以很合理的猜測將要回漲, 依照這樣歷史圖形分析的觀點, 我們是可以來定義所謂高低的. 今天我們就要針對這一種觀點, 送給大家一個可以在ThinkorSwim交易平台中的原始碼, 讓大家可以很快的判斷一下當下隱含波動率的情形, 這對於擬定交易策略是有很大的幫助的. 如果你不會在你的ThinkorSwim的平台中加一個新的Study, 你可以參考一下之前的文章.

好了, 閒話休說, 重點來了, 把下面的原始碼加到你的ThinkorSwim平台中吧!

declare lower;
input days = 252;
input upperRange = 20;
input midUpperRange = 40;
input midLowerRange = 40;
input lowerRange = 20;
plot iv = round(impVolatility()*100);
plot hv = round(historicalVolatility()*100);
plot highIV = highest(iv, days);
plot lowIV = lowest(hv, 252);
def upperPct = upperRange/100;
def midUpperPct = midUpperRange/100;
def midLowerPct = midLowerRange/100;
def lowerPct = lowerRange/100;
def yearlyRange = highIV - lowIV;
plot upperPlot = highIV - yearlyRange*upperPct;
plot midUpperPlot = highIV - yearlyRange*midUpperPct;
plot midLowerPlot = lowIV + yearlyRange*midLowerPct;
plot lowerPlot = lowIV + yearlyRange*lowerPct;
addCloud(highIV, upperPlot, color.GREEN);
addCloud(lowIV, lowerPlot, color.RED);
addcloud(midUpperPlot, midLowerPlot, color.Yellow);
highIV.setDefaultColor(color.GREEN);
lowIV.setDefaultColor(color.RED);
upperPlot.setDefaultColor(color.GREEN);
midUpperPlot.setDefaultColor(color.Black);
midLowerPlot.setDefaultColor(color.Black);
lowerPlot.setDefaultColor(color.RED);

加完之後你會看到類似以下的圖:
圖中淺粉紅色的是歷史波動率(History Volatility,HV), 淺青色的是隱含波動率, 綠色的區域表示所謂”高”隱含波動率, 紅色是低隱含波動率, 淺黃色就是中等. 這個圖有兩種觀點的看法, 第一個是, 你可以由隱含波動率和歷史波動率差距的距離大小來判斷隱含波動率目前是高或是低, 另一個更簡單的看法就是看看淺青色的Implied Volatility是在綠色, 紅色, 或是黃色的區間來做判斷. 當然, 大家也要了解, 這只是根據歷史數據的一種推測, 並不是100%確定的結果, 雖然如此, 我個人還是覺得這是一個很好的參考指標, 大家可以試著用用看, 你也可以根據自己的需求, 更改一些參數, 但是基本的理論都是一樣的. 大家利用休市的颱風假, 花時間了解一下吧!

 

In part1, we defined that the AR(1) model and its formula has a form:

CurrentPrice = ConstantA + ConstantB x LastPrice + Model Error

CurrentPrice is today close price; i.e. at time T=0.
LastPrice is previous close price; i.e. at time T-1.
ConstantA is the intercept of a linear relationship between CurrentPrice and LastPrice
ConstantB is the slope of a linear relationship between CurrentPrice and LastPrice

This equation suggests that the today’s close price and previous close price has a linear relationship. The term “linear” maybe thought as that a straight line is drawn to express the relationship. Using an example is best to illustrate this relationship. Consider Dow Jones Industrial Average Jul19th 2012 to Oct10th 2012 as shown in the table.

Column “Price T+0” is the closing price on the date that is indicated in the “Date” column. Column “Price T-1” is closing price of the corresponding previous date. We can plot the Price at T+0 and Price at T-1 on a graph as shown. The graph suggests that the prices at T+0 and T-1 have a pattern and a straight line (aka linear regression line) can be drawn to approximate this relationship. This line is drawn such that, in average, all data points are as close as possible from the line that approximates them. The line can be represented with a linear equation y = 0.9516x + 634.63. 634.63 is the ConstantA, and 0.9516 is the ConstantB of the AR(1) formula. This suggests that today’s close can be approximated using previous close times 0.9516 and then plus 634.63:

Today’s Close = 634.63 + 0.9516 x Previous’s Close

Readers can Google “excel graph add trendline” for details approximating the linear relationship using excel. One should note that the above formula is estimated (via least mean square regression technique) using data from Jul19th 2012 to Oct10th 2012. Should one be interest in another other time interval, the corresponding data set should be used otherwise.

As shown in the graph, the linear model cannot perfectly represent the data set. The difference between the line and the dataset are known as “model error”. The model error is how inaccurate the linear model representing the data set.
For example, consider Oct5th, 2012 has a closing price of 13610.15. Using the linear regression relationship, we can approximate (or forecast) Oct8th price:

Oct8th, 2012 = 634.63 + 0.9516 x 13610.15 = 13586.05

However, in reality the Oct8th price was 13583.65. And the “model error” is 13586.05 – 13583.65 = -2.4
Higher the model error, worse the line can approximate data points. Understand the overall model error of a model can enable us to from simple trading strategies. However, it requires simple understand of standard distribution, which we will go over in part3.

 

Dollar-Yen(美元-日元滙率) 之前相關文章:
– 2012/6/21 – Run Forrest Run!
– 2012/6/25 – 阿甘等你一起來慢跑

** 當時有提醒過, 這次會是一個長期慢跑. 對更習慣性做長期性投資的人, 4個月的等待可能還不會太久. 不過對習慣了做中短期的投資或交易的人, 4個月的打底再突破似乎是有點長, 會等得不太耐煩吧. 很可能有不少人早已止損出, 這其實也是個不錯的決定, 因為這必須全憑當時入場點及投資組合的分配而定. 當時如果下的比例不同, 會影響能等待的時間; 耐心等待也是成功交易法的關鍵之一. 之後也應繼續跟進, 看看形態何時才算真的改變確認, 若沒變, 還可考慮重新進場.

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