[大師冇點你] 真係咪Q講笑,以前我返星展,都應該寫啲咁嘅嘢,仲要冇後面咩每日一圖 Good Read嗰啲。甚至我而家寫得仲好過當年,詳細過當年。仲要我而家係6點鐘已經寫完send 埋,換著以前?下午四五點啦
當然一個關鍵係,我寫完陣間食埋早餐就瞓,星展唔會畀我咁做。但亦證明根本佢哋以為高薪厚職,但啲繁文縟節係完全拖低生產力,又要跟格式呀又要乜柒。我肯定當年啲客寧願我半夜寫完然後瞓覺,好過我返到公司先寫。「最理想梗係你4點起身寫完然後返公司開會添」,係呀可。但,why join the navy when you can be pirate?而家我就有資格講啦!既然根本我自己直接賣畀讀者都得,咁以前啲錢咩人拎走?
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勞蘇講完,講正題。萬眾期待聯儲局議息會議。
講到尾,睇你點睇,都係narrative,fit story.我見報紙嘅頭條係:聯儲局2023年加2次息,股市重挫,債息狂升。
但,講真,邊個care 2023年發生嘅事?股市當然炒預期,但我當呢個月股災都好,咁接下嚟2021年下半年你可以做乜?繼續擔心2年之後未必會出現嘅加息?點講都唔合符常識。市場反映嘅「預期」可以幾遠?唔易量化,但目測最多咪一年半年?
Patreon入面,我同你睇返聯儲局嘅 點陣圖。冇錯,2023年加兩次息,3月嗰時冇講。但,上次一樣都有幾條友(圖中一粒粒豆鼓)覺得2023年加息,只係今次開始夠半數,變成共識。非常正路
另外,Patreon我有同你睇晒聯儲局兩次嘅經濟數據預測。個個只係留意2021年佢上調咗,但鬼唔知咩,上半場入咗2球你全場開入球小個賠率當然變晒啦。
個重點係:2022 2023嘅通脹預測,差不多完全冇郁!根本完全符合返聯儲局覺得通脹只係暫時嘅劇本。
仲有,福爾摩斯話齋,唔好睇有乜發生,睇有乜冇發生。局方完全冇討論收水,亦冇打算停買債。
咁你話,跌乜?痴線,即使最深時都不過係400點,1.5%都唔夠。咁又話大跌嘅,返屋企食老少平安啦,股市好危險架!況且,你可以睇下時間,根本係出聲明前跌,出完收復唔少失地。
仲有,你不妨望下個VIX,唔知發生咩事嘅,Patreon入面有講。
債息呢?冇錯係彈升,1.50%彈到1.60%,都算多。但亦不過返返月頭嘅水平。呢下亦都幾合理,因為擺明短期聯儲局唔會做啲乜了,通脹短期會持續。
至於最後一個問題?既然短期通脹會上,咁影唔影響企業盈利?用個好簡單嘅例子答你:人類N咁多年嘅歷史都係通脹,但企業盈利亦係越升越高,企業盈利部份咪嚟自通脹咯!股價係nominal thing嘛。企業盈利都係。
你話:唔係喎,成本會上升喎。成本上升?當然係轉嫁落去消費者身上。你以為你加人工 收支票嘅錢,企業會唔渣乾你?
當然,唔係所有企業有咁嘅能力。但,就係最大嘅公司咪有啲能力,而指數入面就係最大嘅公司。都係嗰句,NetFlix下個月加價10%,你係咪轉睇TVB?
應下景,每日一圖甚至Good Read都係經濟嘢。
第一個圖,見到美國企業負債比率(相對GDP)去到70年新高!咁末日論嘅又會覺得,加息你仲唔仆街?但根本係本末倒置:就係因為你低息我先借咁多錢嘛!做回購又好,買嘢又好,乜都得。成件事係掉轉睇:咁情況下,可以有幾多加息空間?唔好忘記政府嘅情況都係咁!
仲唔信嘅,我嘅理論係好似乒乓波或藍球彈地咁,越彈越冇力。2005一浸加息加到5%,2015上一浸只係加到3%左右。下次呢?你覺得點?
第二個圖,講返有幾多通脹,係嚟自舊年嘅低基數效應。舊年呢個時間,好多價格都跌落去(機票錢,酒店租之類)。所以聯儲局嗰套「只係暫時」似乎合理的。詳情就睇文啦。
Good Read 兩篇。第一篇講 High frequency Indicator,唔係高頻交易,而係經濟指票。實情你去數下有幾多人搭地鐵,有幾多人訂餐廳,咪知個recovery係點咯。我根本唔使等到第二季完晒之後再多一個月,政府出嚟公佈,我先知經濟得唔得。咁呢啲嘢有乜Implication?就文入面講
第二篇,教你如何做sell side economist,十分正點。我特別鍾意講圖嘅一段,搞錄如下:
Mastering Chartism: It is possible to show a relationship between almost any two variables in macroeconomics as long as you can display them on two axes and are willing to spend enough time manipulating the second axis, experimenting with data lags, inversions or various moving averages. If you still can’t make the relationship work, extend your history to cover the Global Financial Crisis; everything looks correlated during the GFC.
係喎,你可以Google返篇文出嚟,貼得出嚟唔怕畀你搵,反正都係免費文。但冇我嘅導讀,「冇我嘅練馬師,你嘥咗隻馬喎」。快啲重金禮聘個練馬師,即係我啦。正如咩聯儲局議息聲明,點陣圖,呢啲全部都公開資料啦。但,冇我嘅導讀,「嘥咗隻馬喎」。
佢冇話你知咩?
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同時也有4部Youtube影片,追蹤數超過0的網紅暮らし。すきなもんちゅーぶ,也在其Youtube影片中提到,ご視聴ありがとうございます♡ 今回はお掃除動画です✨ この日は母の日。 パパと子供がお手伝いしてくれました。 お掃除・家事は 出来る人がやれば良い。 ママだけがやることじゃない。 みんなでやれば 早く終わるし、気持ちも良い。 そんな考えなわたしです。 定期的に 100均購入品紹...
averages 3 在 Team Juicy Facebook 的最佳解答
@fitbitsg Sense - your health data powerhouse all wrapped up into this smartwatch✌🏻what a game changer💥💕#FitbitSG
It brims with sensors designed to put you in touch with the inner workings of your body and mind. Truly taking the holistic approach to your health🌈👍👯♀️
There’s so much to love about this smartwatch but here are some of my favourites:
1. Heart rate tracking during a workout - You can now receive real-time alerts when you've changed zones, which can help you take action during your workout, whether that's pushing yourself a bit more or easing off depending on your goals.
2. EDA sensor to determine stress levels- this entire process only takes 2 minutes and I’ve been pretty consistent, doing it twice a week to help reset and recharge.
3. Sleep tracking now includes temperature tracking as well. You'll need to log about three nights of sleep for the Sense to establish a baseline from which to go by. How cool is that!
4. Battery life is about 4 days for me - considering the fact that I clock ⏰ 45 minutes workout and at least 10,000 steps daily.
Here are some key Singapore findings that has revealed how @fitbitsg users in Singapore adapted to the pandemic:
- Singaporeans improved their sleep, which increased by 25 minutes during lockdown, and 20 minutes post- lockdown vs 2019 sleep averages
- Meditation alone emerged as the go-to activity amongst Fitbit users in Singapore with an increase in uptake by 6.128%.
averages 3 在 軟體開發學習資訊分享 Facebook 的最佳解答
本課程將引導你了解使用 Python 進行財務和演算法交易所有需要的知識!我們首先學習 Python的基礎知識,然後繼續了解 Py-Finance 生態系統中使用的各種核心程式庫 (libraries),包括 jupyter 、numpy、pandas、matplotlib、statsmodels、zipline、Quantopian等等!
從這 17 小時的課程,你會學到
1 使用 NumPy 快速運用數值資料
2 運用 Pandas 做分析並視覺化資料
3 使用Matplotlib建立自定義的繪圖(plots)
4 學習如何使用 statsmodels 做時間序列分析
5 計算金融統計,比如日收益、累計收益率、波動率等
6 使用指數加權移動平均值(Exponentially Weighted Moving Averages)
7 在時間序列資料上使用 ARIMA 模型
8 計算 Sharpe 比率
9 優化投資組合分配
10 了解資本資產定價模型
11 學習有效市場假說
12 進行 Quantopian 的演算法交易
https://softnshare.com/python-for-finance-and-trading-algorithms/
averages 3 在 暮らし。すきなもんちゅーぶ Youtube 的精選貼文
ご視聴ありがとうございます♡
今回はお掃除動画です✨
この日は母の日。
パパと子供がお手伝いしてくれました。
お掃除・家事は
出来る人がやれば良い。
ママだけがやることじゃない。
みんなでやれば
早く終わるし、気持ちも良い。
そんな考えなわたしです。
定期的に
100均購入品紹介しているので
良かったら
チャンネル登録していただけると喜びます✩
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アラフォー主婦。一応ワーママ。
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関西在住。
マイホームですが古いお家です。
趣味(好きな事)⋆ インテリア・買い物・収納・掃除。基本シンプルでナチュラルが好き。
そしてプチプラ、100均が好き。
掃除好きだけどズボラな面もあります。
座右の銘は【適当が一番】ってくらい適当に過ごしています。
暮らしを撮りつつ
『すきなもん』をどんどん配信したいと思っております。
掃除に収納・料理・ルーティンなどLIFE STYLEを共有したいと思います。
Nice to meet you.Living SukiyamoChubu.
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averages 3 在 Team Secret Youtube 的精選貼文
Watch how our boy Miracle Uhigh averages 3 Kills a minute in this map. Watch until the end of the video for the unexpected twist!
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averages 3 在 Rayner Teo Youtube 的最佳解答
The Moving Average Crossover is one of the first strategies I’ve traded.
If you’re not familiar with it, here’s how it works…
You buy when the “fast” Moving Average crosses above the “slow” Moving Average (and sell when it crosses below it).
Anyway, I made money when the market is trending strongly.
But in a range market, it killed me.
So, I concluded the Moving Average Crossover doesn’t work.
But as my trading mature, I looked back and asked myself…
“Why didn’t it work?”
I did some research and that’s when I realized I was doing it all WRONG.
And I reveal my findings in today's video, so go watch it right now...
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