讀講稿心得與發問

謝謝Mike跟同學們給我的警惕
其實我想探討的並不是AI股，而是整個世代，也就是AI這個風潮是否可以帶領所有各種產業的EPS上升、毛利上升、本益比上升?
據我所知很多銀行已經都導入AI的系統，相信很多傳產也都會陸續導入AI
不過如同Mike所說的，去想30年後的長線似乎是沒有意義的，這個議題其實也不會影響我目前投資的規則，只是想跟同學們探討探討而已
針對現在的AI股早已經過熱太多，我完全不會想要去買在超貴價
30年後呢，希望我還有機會能夠見證當初這個時候AI對往後世界造成的改變

http://mikeon88.blogspot.com/2018/08/1121.html

選股的重點不在看未來會如何，
而在確定現在會不會變。

The key to stock selection lies not in predicting the future, but in determining whether the current dominance will change.


研究員除了拜訪公司之外還會去做產業研究，
從產業裡找出哪些是未來的明星產業，
若該產業最具發展潛力，裡頭的公司應該會快速成長，
可是卻常常發現，產業前景看好
跟公司會不會賺錢其實沒有必然的關係！
過去大家曾看好太陽能、面板、DRAM這些產業
後來發展趨勢跟當時所預料的其實差不多，
當初認為電視機和電腦螢幕都將換成面板，趨勢的確如此，
可是沒想到做面板的公司沒幾家賺錢。
這一點在年報上巴菲特也提到，
祂小時候萊特兄弟駕飛機飛越大西洋，
當時大家認為飛機工業的產值將變得很大，
果然如此，可是製造飛機的公司能獲利者寥寥可數。

In addition to visiting companies, analysts also conduct industry research to identify the future star industries. If an industry has significant potential, the companies within that industry should experience rapid growth. However, I have often noticed that a bright future for an industry does not necessarily guarantee profitability for the companies within it.
In the past, industries such as solar, LCD panels, and DRAM were highly optimistic. While the industry trends aligned with expectations at the time, few companies were able to turn a profit. For instance, we believed that both TV and computer screens would be replaced by panels, which turned out to be true. Nevertheless, only a few companies could make a profit from this trend.
Mr. Buffett addressed this issue in his annual report. He mentioned how the Wright brothers flew across the Atlantic when he was a kid, and at that time, people believed that the output value of the aircraft industry would be enormous. While the industry followed the expected trend, few companies were able to achieve profitability.

mikeon88 寫到:貴的股票可不可以買？當然可以，
不過請先告訴我們什麼時候要賣？

對上述這句話深有同感
因為我有買Google、Meta及Apple，現在盈再表報酬率都已成負的了
雖然Mike桑講過「股票貴了不賣是傻了嗎..」，還舉了他當初賣中碳的例子
可是..可是..
我怕賣了那幾支，它們還會再高，我就追不回來了(哭哭==)
最近有賣了Meta一半，理由是我很早就不看臉書了，問了旁邊的朋友也一樣，所以決定先賣一半^^..。
其實都是AI這2個英文字，讓我很糾結==...
有哪位大師能開釋小生呢^^..

wale0823桑不用糾結，秘笈就是便宜買貴賣。
捨不得賣就是後果自負，如果你購分散且後果自負，我覺得就沒有太大問題
想賣又捨不得賣，我覺得賣一半的確也是折衷的辦法
能睡得好就好了

貴的股票最大的問題就是不知何時賣⋯去年10月左右手癢買了台機電，395左右，這個價錢早就超過盈再表的貴價，現在看來賺很多，但是我真的不知何時該賣，又不想被其他派污染，睡不著覺，375左右賣出了，當然也被我家老公唸死了

所以廣達200.5盈再表顯示貴了，不留戀全賣，雖然今天已經265了。

有明確的依據買賣，我覺得很幸福，當年三秒內信教，解決了心中最大的疑問，就是想知道何時淑買貴賣

盈再表已能涵蓋大部分的股票，就不必單戀一支花了

70%股票淑買貴賣績效會最好，
5%股票貴了還會更貴
請問怎麼操作最好？
A. 遵守淑買貴賣
B. 貴了也不賣

這又是一個幼稚園問題

http://mikeon88.blogspot.com/2018/08/1321irr.html

最近選舉民調滿天飛，
很多人都在問一個統計名詞
「信心水準95%，抽樣誤差3%」是何意思？
我的統計學得很差，重新複習了一下
https://web.ntnu.edu.tw/~494402345/CI/CI.pdf

選股就是統計學的抽樣，
選對股機率p 70%
可是抽樣得到的結果不會每次剛好70%，
而是有偏差，很可能落在正負2個標準差之內。

Stock selection is akin to statistical sampling.
Probability of accurately selecting the right stock, denoted as p, is 70%.
Nonetheless, the results of the sampling will not consistently align with the precise 70%.
Instead, they tend to show a bias, highly likely falling within a range of plus or minus two standard deviations.

以上換成統計術語為：
信心水準95%之信賴區間為正負2個標準差s
[p - 2s, p + 2s] = [70% - 2s, 70% + 2s]
信心水準95%即白話文的「很可能」

The above can be translated into statistical terminology as follows:
The confidence interval at a 95% confidence level is ±2 standard deviations (s).
[p - 2s, p + 2s] = [70% - 2s, 70% + 2s]
A 95% confidence level is colloquially referred to as "highly likely."

標準差指資料之間的平均距離
＝[px(1-p)/n]^0.5 = [70%x30%/n]^0.5
樣本數n

The standard deviation refers to the average distance between data points.
= [px(1-p)/n]^0.5 = [70%x30%/n]^0.5
Sample size n

n=1,  [-22%, 162%]
n=5,  [29%, 111%]
n=10,  [41%, 98%]
n=30,  [53%, 87%]
n=50,  [57%, 83%]
n=100, [61%, 79%]
n=200, [64%, 76%]
n=300, [65%, 75%]
n=500, [66%, 74%]
n=1,000, [67%, 73%]

n=1,  [-22%, 162%]
n=5,  [29%, 111%]
機率在0到100%之間，故上式應改為
n=1,  [0, 100%]，單押1支選對股機率很可能為0或100%
n=5,  [29%, 100%]，僅押5支選對股機率很可能落於29%到100%之間
n=10,  [41%, 98%]，買10檔選對股機率很可能落於41%到98%之間，表示績效大好大壞

For different sample sizes:
n=1, [-22%, 162%].
n=5, [29%, 111%].
Since the probability ranges from 0% to 100%, the formula above requires adjustment.
n=1, [0, 100%]: When selecting only 1 stock, the probability of selecting the correct stock is likely to be either 0% or 100%.
n=5, [29%, 100%]: By selecting only 5 stocks, the probability of correctly identifying the stocks is very likely to fall between 29% and 100%.
n=10, [41%, 98%]: Buying 10 stocks, the probability of selecting the correct stocks is highly likely to fall within the range of 41% to 98%, indicating a wide range of performance outcomes.

n=100, [61%, 79%]，買100支選對股機率很可能落於61%到79%之間，至少61%這是我們建議至少買100支持股的原因

n=100, [61%, 79%]: When purchasing 100 stocks, the probability of selecting the correct stocks is very likely to fall within the range of 61% to 79%. With a minimum threshold of 61%, this is the rationale behind our recommendation to acquire a minimum of 100 stocks.

上述至少買100檔持股的統計證明相當重要，
分散或集中持股不再是見仁見智沒有結論的議題，
而是必須遵守的準則。
也給足大家信心，
持股100支以上績效大壞的可能性很低，
不必每天緊張兮兮關注股市，
有更多時間去吃喝玩樂

The above statistical evidence underscores the significance of holding a minimum of 100 stocks in your portfolio. Whether to diversify or concentrate one's holdings is no longer a debatable issue, but a guideline that must be followed. This also gives everyone confidence that the likelihood of poor performance with holding more than 100 stocks is very low. There is no need to be nervous and pay close attention to the stock market every day, instead, we can spend more time enjoying life.

http://mikeon88.blogspot.com/2018/08/1221.html