00:00
even though most people like to think that they are rational most humans aren't very rational
儘管大多數人喜歡認為自己是理性的，但大多數人其實並不那麼理性
00:05
especially when money is on the line and time is scarce human decision making can be very flawed
尤其是在涉及金錢且時間緊迫時，人類的決策往往充滿缺陷
00:11
trading is one of the fields where erroneous and irrational behavior patterns are especially common
交易正是錯誤及非理性行為模式特別常見的領域之一
00:16
in this video we're going to look at the most common cognitive biases and irrational decision making patterns
在本影片中，我們將探討最常見的認知偏誤與非理性決策模式
00:22
and how to avoid them being aware of these thinking flaws has two main advantages
以及如何避免它們。意識到這些思維缺陷有兩大好處
00:27
firstly it helps you avoid them in your own trading and secondly it can help you identify and explain
第一，幫助你在自己的交易中避免它們；第二，幫助你識別並解釋
00:33
seemingly irrational market behaviors caused by these biases most of these so-called cognitive biases
由這些偏誤所導致的市場看似非理性的行為。大多數所謂的認知偏誤
00:40
were discovered and introduced by the nobel winning daniel kahneman and amos tversky
是由諾貝爾獎得主丹尼爾·卡尼曼（Daniel Kahneman）與阿摩司·特沃斯基（Amos Tversky）發現並提出的
00:45
with that being said let's jump right into it the first cognitive bias that i want to talk about
說到這裡，我們馬上開始吧。我想談的第一個認知偏誤
00:51
is the gambler's fallacy the gambler's fallacy is incorrectly over or understating the likelihood
是「賭徒謬誤」（Gambler's Fallacy）。賭徒謬誤是指根據過去的一系列事件，錯誤地高估或低估某事件發生的可能性
00:58
of an event based on a series of past events this can be illustrated with a simple example of a coin flip
這可以用拋硬幣的簡單例子來說明
01:04
the probability that a coin will land on heads is 50 percent no matter how often you flip a coin this
不論你拋多少次硬幣，正面朝上的機率都是 50%。這個機率
01:10
probability does not change so even if your coin just landed on heads 10 times in a row
不會改變。所以，即使你的硬幣剛剛連續 10 次正面朝上
01:15
this does not affect the probability of the next coin flip like the name implies the gambler's
這也不會影響下一次拋硬幣的機率。如其名所示，賭徒謬誤
01:21
fallacy is especially common in gambling but this pattern of thinking is quite common in trading as well
在賭博中特別常見，但這種思維模式在交易中也相當普遍
01:27
let me give you some examples have you ever opened a long position because a stock had many consecutive down days or
讓我給你一些例子。你是否曾經因為一支股票連續下跌多日而開立多頭部位，或者
01:33
vice versa if so you have fallen prey to the gambler's fallacy
反之亦然？如果是，你就落入了賭徒謬誤的陷阱
01:37
another example would be the reaction to a losing or winning streak if you ever felt that after many
另一個例子是對連勝或連敗的反應。如果你曾覺得在連續多次
01:43
consecutive wins the chances of losing increased and you decreased your position size you have been guilty of
獲勝後，虧損的機率增加了，因此你縮減了部位規模，那你就是犯了
01:49
the gambler's fallacy the odds of winning on a trade don't magically change just because you had
賭徒謬誤。交易獲勝的機率並不會因為你剛剛有過
01:54
multiple losses or wins before this trade speaking of winning streaks if we assume
在這筆交易之前多次虧損或獲勝 說到連勝 如果我們假設
02:00
that you found a trading strategy that guarantees you a 70 chance of winning
你找到了一種交易策略 能保證你在每筆交易中都有 70% 的勝率
02:05
on every single trade what do you think the odds of winning 10 times in a row are the answer is
你認為連續贏 10 次的機率是多少 答案是
02:11
under three percent in fact even the probability that you will have two consecutive wins with this strategy
低於 3% 事實上 即使是使用這項策略 連續贏兩次的機率
02:18
is under 50 percent this means it is less likely that you will have two consecutive winners than that you won't
也低於 50% 這意味著你連續贏兩次的可能性 比無法連續贏兩次的可能性還要低
02:25
and remember this is with a strategy that guarantees you 70 chance of success on each trade most
請記住 這是在一項能保證你每筆交易都有 70% 成功機率的策略下 大多數
02:31
strategies won't have nearly as good odds to calculate the probability of n
策略的勝率都沒有這麼好 要計算連續贏 n 次的機率
02:36
consecutive wins you simply have to take the estimated odds of your trading strategy
你只需要將你的交易策略的預估勝率
02:40
to the power of n note that this assumes that the trades are independent from each other
取 n 次方 請注意 這假設了各筆交易之間是相互獨立的
02:45
and the probability of winning is constant if we look at the odds of losing streaks we get a similar picture
且贏的機率是固定的 如果我們來看看連續虧損的機率 會得到類似的情況
02:51
here's a diagram that shows the probabilities of multiple consecutive losses
這裡有一張圖 顯示了連續多次虧損的機率
02:55
with a trading strategy that has a 40 chance of losing on any single trade as you can see
這項交易策略在任何一筆交易中都有 40% 的虧損機率 如圖所示
03:02
with a 40 chance of losing it is extremely unlikely that you will have more than a handful of losses in a row
在 40% 的虧損機率下 你極不可能連續出現多次虧損
03:08
so what can we learn from this firstly no matter how good your strategy is losses do happen you can't win all your
那麼我們能從中學到什麼 首先 不論你的策略多好 虧損還是會發生 你不可能贏得所有
03:15
trades therefore you have to implement solid risk management practices and keep the size of your losses under control
的交易 因此 你必須執行穩固的風險管理實務 並控制好你的虧損部位
03:21
next up the odds of having many losses or wins in a row is quite low so if you often have more
接著 連續出現多次虧損或獲勝的機率相當低 所以如果你經常連續出現
03:27
than 10 major consecutive losses you should seriously start doubting the quality of your trading strategy
超過 10 次的重大虧損 你就該開始認真懷疑你的交易策略品質
03:33
but always remember even though the probability of winning 10 trades in a row is very low
但永遠記住 即使連續贏 10 筆交易的機率非常低
03:38
the probability of winning on any single trade is not lower just because you won on the last 10
任何一筆交易的勝率並不會因為你前 10 筆都贏而變低
03:44
trades next up let's take a look at our next cognitive bias namely the confirmation
接下來 讓我們看看下一個認知偏誤 也就是確認偏誤
03:50
bias confirmation bias is the tendency to seek out information that confirms your
確認偏誤（confirmation bias）是指傾向於尋找能證實既有信念的資訊
03:56
pre-existing beliefs this is a bias that without a doubt the vast majority of traders have been
這種偏誤無疑是絕大多數交易者都曾犯過的錯誤
04:01
guilty of after opening a trade it is only natural to continually seek out information
在開倉後，自然會不斷尋找能支持自己交易想法的資訊
04:07
that confirms your trading idea you might look at dozens of indicators or social media posts and only focus on
你可能會查看數十種指標或社群媒體貼文，卻只關注那些
04:14
those that confirm your beliefs finding something that agrees with you
能印證自身信念的內容，找到與自己觀點一致的資訊
04:18
is a good feeling and certainly can boost your confidence in a position the problem is that by doing this you
確實令人愉快，也肯定能提升對部位的信心
04:24
often ignore signs that your trade wasn't the best idea and something might be wrong
但問題在於，這樣做往往會忽略交易決策可能欠佳或出現異常的警訊
04:29
instead you convince yourself more and more that everything is fine by searching twitter for a ticker symbol
反而會透過各種方式說服自己一切正常，例如在推特上搜尋某個股票代碼
04:34
you're almost guaranteed to find at least a few people that have the same market assumption as you
你幾乎肯定能找到至少幾位與你市場預期相同的人
04:39
but this doesn't mean anything one way to avoid confirmation bias in trading is by having a clear set of
但這並不能代表任何事。要避免交易中的確認偏誤，可以為交易設定明確的
04:46
indicators and rules to follow for your trades if you have such a clear set of rules
指標與規則。若已有這套清晰的規則與指標
04:50
and indicators there is no need for you to go out and look for any other confirming signs
就沒有必要再去尋找其他佐證信號
04:55
furthermore it is best to avoid social media as a trade decision making guide that said let's move on to our next
此外，最好避免將社群媒體當作交易決策的參考。那麼，我們接著探討下一個
05:02
fallacy the next fallacy is the law of small numbers you might have heard about the law of
謬誤。下一個謬誤是「小數法則」。你可能聽過「大數法則」
05:07
large numbers that states that the average of a growing sample size converges to the actual mean
它指出隨著樣本數增加，平均值會趨近於母體的真實平均
05:12
of the total population this is a very powerful rule in probability theory
這是機率論中非常強大的法則
05:17
that allows you to estimate a population's parameters with large enough samples but like the
能讓你在樣本夠大的情況下估計母體參數
05:24
name implies this only works for big sample sizes this is where the fallacy of the law of
但如其名所示，這僅適用於大樣本
05:29
small numbers comes into play most people intuitively use the law of large numbers incorrectly
而「小數法則」的謬誤就在此產生
05:35
namely with two small sample sizes let me give you an example have you ever tried a trading strategy
大多數人會直覺地誤用大數法則，也就是在樣本數過小時套用
05:41
for a handful of trades and then concluded that it doesn't work if so you have been guilty of using the
如果只做了幾筆交易就下結論說它無效，那麼你可能犯了「小數定律」的錯誤
05:46
law of small numbers a few traits is not a big enough sample size to give you any significant
少量的交易並不足以作為樣本來評估一個交易策略的品質
05:52
information about the quality of a trading strategy let me now tell you how you can avoid
現在讓我告訴你如何避免小數定律，並展示如何有效測試交易系統的成效
05:58
the law of small numbers by showing you how to efficiently test the effectiveness of a trading system
目標是使用這個交易系統進行至少 20 筆交易
06:03
the goal is to use this trading system for at least 20 trades it might seem scary to use a new trading
在不知道表現好壞的情況下，使用新交易系統進行超過 20 筆交易可能聽起來很可怕
06:10
system for over 20 trades when you have no idea how good or bad it might perform
因此，你應該將風險降低到一個你能輕易承受這 20 筆交易全部虧損的程度
06:15
therefore you should trim down your risk to a level so that you can easily afford to lose on
這 20 筆交易的目標不是賺錢，而是測試該交易策略
06:20
all these 20 trades your goal with these trades is not to make money but to test out the given trading
在進行這 20 筆交易時，盡可能保持機械化
06:25
strategy when making these 20 trades try to be as mechanical as possible
為所有能想像到的市場狀況建立明確的規則，並在每筆交易中遵循這些規則
06:30
create clear rules for every market scenario imaginable and follow these rules on every trade
如果你沒有一套明確的規則可以遵循，就無法可靠地測試你的策略
06:36
if you don't have a clear set of rules to follow you can't reliably test your strategy
因為根本沒有策略可供測試。此外，務必在每筆交易後保留詳細且完整的交易日記
06:40
since there is no strategy to test furthermore make sure to keep a detailed and
追蹤進場價格、出場價格、潛在利潤、承擔風險的金額、持倉時間等等
06:45
thorough trade journal after every trade track entry prices exit prices profit
如果你想要關於如何建立最有效交易日記的詳細指南，請查看下方描述欄位中的連結
06:50
potential money at risk time in a trade and more if you want a detailed guide on how to
在你遵循所有這些步驟並完成至少 20 筆交易後，你就可以開始評估策略了
06:55
create the most effective trade journal check out my link in the description box below after you've followed all these
理想情況下，你現在應該擁有關於此策略的豐富數據，以便進行評估並做出明智的決定
07:01
steps for at least 20 trades you're ready to evaluate the strategy ideally you should now have a rich
我知道光是測試交易系統似乎就需要做很多工作
07:07
collection of data on this strategy to evaluate it and make an informed decision on how effective this trading
但如果沒有足夠大的樣本數，你無法真正評估任何東西
07:13
system is i know that this might seem like a lot of work just to test the trading system
根據一兩次的結果就做決定，就像是說輪盤有 100% 的勝率一樣荒謬
07:17
but without having a big enough sample size you can't really evaluate anything
但若沒有足夠大的樣本數，你根本無法真正評估任何事情
07:22
making a decision based on one or two occurrences is like saying roulette has a 100 win
僅憑一兩次的結果就做決定，就像是說輪盤有 100% 勝率一樣荒謬
07:27
rate because you won one round the next cognitive bias that we're going to look at
因為你贏了一輪的關係，我們接下來要探討的認知偏誤
07:32
is the survivorship bias wikipedia defines survivorship bias as the logical error of concentrating on
是「倖存者偏差」。維基百科將倖存者偏差定義為一種邏輯謬誤，即過度專注
07:39
the people or things that made it past some selection process and overlooking those that did not
於通過某個篩選過程的人或事物，而忽略了那些沒有通過的人或事物，
07:45
typically because of their lack of visibility let's once again look at a couple of examples to better understand
通常是因為後者缺乏能見度。讓我們再次透過幾個例子來更深入了解
07:51
what this means if you look around it is easy to arrive at the conclusion that most etfs
這意味著什麼。如果你環顧四周，很容易得出結論，認為大多數 ETF、
07:57
mutual funds and even individual stocks go up over time but in reality this is a wrong
共同基金，甚至個股都會隨著時間上漲；但實際上，這是一個錯誤的
08:02
conclusion that's because the universe of funds and stocks that you look at is already skewed in one direction one
結論。這是因為你所觀察的基金和股票範圍，已經朝向某個方向傾斜。某些
08:09
reason why stock did not go up but instead fell is that it went bankrupt and a bad performing fund
股票沒有上漲反而下跌的原因之一，是因為它破產了；而表現不佳的基金
08:15
usually gets closed after a few years in other words only those funds survive that performed well enough
通常在幾年後就會被清算。換句話說，只有那些表現足夠好的基金才能存活下來。
08:20
so when you say that most stocks or funds go up over time you aren't considering all those that didn't
因此，當你說大多數股票或基金會隨著時間上漲時，你並未將所有未能
08:25
survive therefore the results obtained by only looking at survivors can be vastly
存活的基金納入考量。因此，僅觀察倖存者所得到的結果可能存在極大的
08:30
flawed to give you some data a vanguard group study recently found that an investor in
謬誤。給你一些數據：Vanguard 集團最近的一項研究發現，1997 年投資
08:36
a large cap growth or value fund in 1997 stood just a 22 percent chance of finding a fund
於大型成長型或價值型基金的投資人，到了 2011 年，僅有 22% 的機率能找到
08:42
that would survive and outperform its benchmark through 2011.
一檔存活下來且表現超越其基準指數的基金。
08:47
the problem of only considering a universe of investments that survived a certain selection process
僅考量通過某個篩選過程而存活下來的投資範圍，這個問題在
08:52
is especially common when back-testing and analyzing trading strategies on historical data
根據歷史數據進行回測和分析交易策略時尤其常見，
08:57
but also when analyzing success stories outside of trading survivorship bias can be a big problem
但在分析交易以外的成功案例時也是如此。倖存者偏差可能是一個大問題。
09:03
the results of looking at shared trades of highly successful people doesn't actually yield very significant
觀察極為成功人士的共同特質，實際上並不能產生非常顯著的
09:08
results typically many unsuccessful people also share these traits but they weren't
結果。通常，許多不成功的人也具備這些特質，但他們並未
09:13
considered in such a study which can dramatically skew the results often successful people
被納入此類研究中，這會嚴重扭曲結果。通常，成功人士
09:18
succeed in spite of certain traits not because of them the phrase that history is written by
儘管具備某些特質，但成功並非因為這些特質，而是儘管有它們
09:23
winners very much also applies in business and financial markets in general when looking at and analyzing
歷史是由勝利者書寫的這句話，在商業和金融市場中也非常適用
09:30
investments make sure to think about that what you can't see is there a seemingly invisible filter
在觀察和分析投資時，務必思考你看不見的東西
09:35
that you are missing if so your results can be vastly skewed in an unwanted direction
是否存在一個你遺漏的、看似隱形的過濾器？如果是的話，你的結果可能會嚴重偏離預期方向
09:41
this brings us to our next common fallacy namely mistaken correlation for causality correlation does not imply
這就引出了我們下一個常見的謬誤，即混淆相關性與因果關係
09:48
causation but sadly it is often treated as if it does there are different types of this
相關性並不蘊含因果關係，但遺憾的是，它經常被當作蘊含因果關係來對待
09:53
fallacy i will now cover three of the most prominent causation fallacies
這種謬誤有不同類型，我現在將介紹其中最顯著的三種因果謬誤
09:57
the first is reverse causation an easy example of this is the correlation between rainy days
第一種是反向因果關係，一個簡單的例子是下雨天與雨傘使用量之間的相關性
10:03
and the usage of umbrellas when it rains people tend to use umbrellas much more does that mean that
下雨時，人們傾向於更多地使用雨傘，這是否意味著使用雨傘會導致下雨？
10:08
using umbrellas causes it to rain of course not it's the other way around this might seem like an obvious mistake
當然不是，事實正好相反。這看起來像是一個顯而易見的錯誤
10:14
but often things aren't as clear if for instance stock a and stock b are heavily correlated does
但事情往往並非如此清晰。例如，如果股票A和股票B高度相關
10:20
that mean that an opt move in a's price causes a reaction in b's price or the other way around
這是否意味著A股價格的變動會引起B股價格的反應，或者反之亦然？
10:26
another causation bias is neglecting the fact that the third variable might be the cause of two correlated
另一種因果偏誤是忽略了第三個變數可能是兩個相關變數的原因
10:31
variables for example two oil stocks might be highly correlated but this doesn't mean that a
例如，兩檔石油股可能高度相關，但這並不意味著其中一檔股票的變動
10:37
move in one of the stocks causes a move in the other stock instead a third variable namely the
會導致另一檔股票的變動。相反，第三個變數，即石油價格
10:42
price of oil might be the cause for the moves in both of these stocks last but not least two variables can
可能是這兩檔股票變動的原因。最後但同樣重要的是，兩個變數也可能
10:49
also be correlated without having any causal link in fact if you have a big enough set of
相關而沒有任何因果關係。事實上，如果你有足夠大的數據集
10:54
data you're almost guaranteed to find some variables that are correlated purely by chance
你幾乎肯定會發現一些純粹因偶然而相關的變數
10:59
one example of such a coincidental correlation is the correlation between per capita consumption of chicken
這種巧合相關性的一個例子是人均雞肉消費量與美國原油進口量之間的相關性
11:05
and u.s crude oil imports these two variables have a historic correlation of almost 90 percent over about 10 years
在過去約10年間，這兩個變數的歷史相關性接近90%
11:13
nevertheless i wouldn't use chicken consumption data to try to predict u.s crude oil imports
儘管如此，我不會用雞肉消費數據來試圖預測美國原油進口
11:19
there are countless similar examples of seemingly nonsensical correlations so going forward never assume that
有無數看似荒謬的相關性例子，所以今後永遠不要假設
11:25
correlation means causality proving correlation is very straightforward but proving
相關性意味著因果關係，證明相關性非常直接，但證明
11:30
causality is a totally different story with that being said let's move on to the next cognitive bias
因果關係則完全是另一回事。既然如此，讓我們繼續下一個認知偏誤
11:37
namely hindsight bias hindsight bias is the tendency of overstating the odds of an event that has already
即事後諸葛（hindsight bias）。事後諸葛是指高估已經
11:43
happened here is a great quote from nobel prize winning daniel kahneman about hindsight buyers
發生事件機率的傾向。以下是諾貝爾獎得主丹尼爾・卡尼曼關於事後諸葛的精闢引述：
11:50
a stupid decision that works out well becomes a brilliant decision in hindsight
一個愚蠢的決定若結果很好，在事後看來就會變成一個英明的決定
11:54
in my opinion hindsight bias is especially common amongst traders way too many traders evaluate the
在我看來，事後諸葛在交易者中尤其常見。太多交易者根據
12:00
quality of their trades based on their outcome this is a very flawed way of evaluating
結果來評估他們交易的品質。這是一種非常有缺陷的評估
12:05
your trades a trade that has a 70 chance of making 200 and a thirty percent chance of losing one hundred
交易的方式。一筆有 70% 機率賺 200 元，和 30% 機率虧 100
12:11
dollars is without a doubt a great trade no matter its outcome
美元的交易，無論結果如何，都無疑是一筆好交易
12:16
even this trade won't work out three out of ten times but that doesn't make it a bad trade
即使這筆交易十次中有三次不會成功，但這並不使其成為一筆壞交易
12:21
sadly this is how many traders evaluate their trades hindsight bias is also the reason why technical analysis seems so
可悲的是，這就是許多交易者評估交易的方式。事後諸葛也是技術分析看起來如此
12:28
attractive finding chart patterns on historical charts is very easy
迷人的原因。在歷史圖表上尋找圖表形態非常容易
12:33
but without the benefit of hindsight things aren't nearly as easy if you ever felt that the past price
但若沒有事後諸葛的優勢，事情就沒那麼容易了。如果你曾覺得過去的價格
12:39
move seemed so obvious you have fallen prey to the hindsight buyers to avoid hindsight bias you need some
走勢看起來如此明顯，你就已經成為事後諸葛的受害者。為了避免事後諸葛，你需要某種
12:45
way of evaluating your trades not based on their outcome instead you should focus on the quality of your
評估交易的方式，不是基於結果，而是應該專注於過程中你決策的品質
12:50
decisions along the way did you have a clear trade plan and strategy if so did you follow it
你是否有明確的交易計畫和策略？如果有，你是否遵循了它？
12:56
if not why not and what could you do better next time in general it is best to have a
如果沒有，為什麼沒有？下次你可以做哪些改進？一般來說，最好有一套
13:01
consistent way of evaluating your trades that is not affected by the outcome of your trades
一致的交易評估方式，不受交易結果的影響
13:06
another common bias is the recency bias recency bias is the illogical way of putting more weight and importance to
另一個常見的偏誤是近因偏誤，近因偏誤是一種不合邏輯的方式，將更多權重和重要性
13:13
recent events compared to historical ones this can easily be observed by looking at the
加諸於近期事件，而非歷史事件。這可以很容易地從觀察市場的
13:19
cyclical nature of markets the longer a bull market is the more and more people forget that
循環性質中看出。牛市持續越久，越來越多的人就會忘記
13:24
prices don't only go up thus investors pay less and less attention to their risk
價格並非只會上漲。因此，投資者對其風險的關注度越來越低，
13:29
even though it should be the other way around since the further prices rise the more they can fall
儘管情況應該恰恰相反，因為價格漲得越高，下跌的空間就越大。
13:35
the same is the case directly after market crashes this is when people typically over manage their risk because
市場崩盤後的情況也是如此。這通常是人們過度管理風險的時候，因為
13:40
they overestimate the odds of future drops this can be a great time to sell
他們高估了未來下跌的機率。這可能是出售
13:44
overpriced insurance products such as options and volatility a different bias that can be observed in
過高定價的保險產品（如期權和波動率）的好時機。另一種可以在
13:51
the trading news business is the attribution bias the attribution bias is the bias of constantly trying to
交易新聞領域觀察到的偏誤是歸因偏誤。歸因偏誤是指不斷試圖
13:58
assign some reason to an event even if your reason has nothing to do with reality
為某個事件賦予某種原因，即使你的原因與現實毫無關聯。
14:03
financial news companies are in the business of satisfying this bias they seem to have an explanation for
財經新聞公司正是透過滿足這種偏誤來營利的。他們似乎對
14:09
every single price move even if their explanations sometimes are contradictory
每一次價格波動都有解釋，即使他們的解釋有時是相互矛盾的。
14:14
sometimes you can't break down a price move into a simple cause and effect relationship
有時你無法將價格波動分解為簡單的因果關係，
14:19
but this doesn't stop us from trying the problem is that humans are very good at finding
但這並不能阻止我們嘗試。問題在於，人類非常擅長為
14:24
an explanation for almost anything even if the explanation doesn't make sense basic traits on these explanations can
幾乎任何事情找到解釋，即使該解釋毫無道理。基於這些解釋進行交易
14:30
do more harm than good so make sure to be careful when looking at the reasons that financial
可能弊大於利。因此，在查看財經
14:35
news organizations assign to certain price moves the best explanation for an up move will
新聞機構對特定價格波動所賦予的原因時，務必謹慎。對於上漲走勢最好的解釋
14:41
always be that they are simply more buyers than sellers last but not least let's briefly look at
永遠都是：買方數量 simply 超過了賣方。最後但同樣重要的是，讓我們簡單看看
14:47
the song cost fallacy if you ever held onto a position far longer than you should you have been
沉沒成本謬誤。如果你曾經持有某個部位的時間遠超過應有的長度，那你就是犯了
14:53
guilty of this fallacy the sunk cost fallacy is the tendency to refuse to stop an action
這種謬誤。沉沒成本謬誤是指拒絕停止某項行動的傾向
14:58
because you've already sacrificed a good amount of money and or time into it sometimes it's best to just
因為您已經投入了可觀的金錢和時間，有時最好的做法是
15:04
cut your loss than to further waste money and time on a project or trade
認賠出場，而不是在一個專案或交易上繼續浪費金錢和時間
15:10
some costs should not be a reason for you to stay in a trade if you wouldn't open your trade at its
沉沒成本不應該成為您留在交易中的理由，如果您不會在當前價格水平
15:15
current price level you should not stay in it regardless of how much you already have
開立新倉，那麼無論您已經虧損多少，都不應該繼續持有
15:19
lost one way of combating the song cost fallacy is by having a clear trade plan with
對抗沉沒成本謬誤的一種方法，是在進場前就制定明確的交易計畫
15:24
clearly defined exit points before you enter a trade we have now covered a wide variety of different
並設定清晰的出場點，我們已經涵蓋了許多不同的
15:31
cognitive biases that can dramatically impact your trading and decision making in general
認知偏誤，這些偏誤會嚴重影響您的交易和整體決策
15:36
let us now briefly look at how you can avoid these biases first and foremost it is already a good
讓我們現在簡要看看如何避免這些偏誤，首先，意識到
15:42
step in the right direction to be aware of that these biases exist but sadly simply being aware
這些偏誤的存在，已經是朝正確方向邁出的一大步，但遺憾的是，僅僅意識到
15:49
isn't enough to completely avoid them in fact it is almost impossible to fully eliminate these biases from your life
並不足以完全避免它們，事實上，要從生活中完全消除這些偏誤幾乎是不可能的
15:56
since they are so deep ingrained in your human psychology that said you can definitely do things
因為它們深植於您的人類心理中，話雖如此，您絕對可以採取措施
16:01
that can reduce the frequency of them and thereby improve the quality of your decisions one thing
來降低它們出現的頻率，從而提高決策的品質，嘗試在時間壓力下
16:07
that can dramatically increase the likelihood of using these cognitive biases
做決定，會顯著增加使用這些認知偏誤的可能性
16:11
is trying to make a decision under time pressure so avoiding time pressure is another step in the right direction
因此，避免時間壓力是另一個朝正確方向邁進的步驟
16:17
one way of avoiding time pressure in trading is by preparing beforehand instead of trying to improvise and rely
在交易中避免時間壓力的一種方法是事先做好準備，而不是試圖即興發揮並依賴
16:23
on your intuition always have a clear trade plan before you open a trade
您的直覺，在開立交易前，始終要有一個清晰的交易計畫
16:28
the trade plan should have all the information you need to mechanically carry out your entire trade
交易計畫應包含您機械化執行整個交易所需的所有資訊
16:33
i highly recommend checking out my entry and exit guide video in which i break down how to create an effective trade
我強烈建議您查看我的進出場指南影片，我在其中詳細說明了如何建立有效的交易
16:39
plan besides a trade plan a good trade journal is another way for you to
計畫，除了交易計畫，良好的交易日記是另一種
16:43
improve upon your decision making and trading otherwise try to actively monitor
改進決策和交易的方法，否則，試著積極監控
16:48
yourself for these cognitive biases especially in situations where the likelihood of a bias is high
在偏誤可能性高的情況下，要特別為這些認知偏誤做好準備
16:54
step back and rethink the entire situation from another perspective furthermore avoid making important
退一步並從另一個角度重新思考整個情況，此外要避免在心情不好
17:00
decisions when you're in a bad mood or not fully focused due to a lack of sleep for instance
或因睡眠不足而無法完全專注時做出重要決定
17:06
if you are interested in learning more about this topic i highly recommend checking out daniel kahneman's book
如果你有興趣了解更多關於這個主題的內容，我強烈推薦閱讀丹尼爾·康尼曼的書
17:11
thinking fast and slow you can check out my link to it in the description box below
《快思慢想》，你可以在下方的說明欄位查看我提供的連結
17:16
that said i really hope you enjoyed this video and learned something new i'd love to hear whether you could
話雖如此，我真心希望你喜歡這支影片並學到新東西，我很想聽聽你是否
17:21
recognize yourself in some of these cognitive biases if you did definitely let me know in the
在某些認知偏誤中看到了自己的影子，如果有，請務必在下方的
17:26
comment section below otherwise make sure to smash the like button subscribe and turn on the
留言區告訴我，否則請記得按讚、訂閱並開啟
17:31
notification bell for more content like this
新片通知鈴鐺，以獲取更多此類內容
17:34
thanks for watching
感謝收看
