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XinxinJC
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2022-02-09
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2022-02-05
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2022-02-03
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2021-09-14
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怎麼把$3200變成$50million?
@Raytroninvs:
上週很不幸被IB和CME邀請去參加了個關於 The profitability of market data analysis 的學術交流event,爲啥不幸呢?沒告知我我需要去演講,於是我啥也沒準備的就去了,到了後被一臉懵逼的請了上去,雖然我面無表情但是心理慌的一比,不過很快我就想到講什麼了:搭建個每天買spx call spread的組合,通過模型來算怎麼買和什麼價位最有可能變成百萬富翁,這樣應該能混過去 先聲明下這些數據都是臨時做的,雖然有些簡陋但請不要盜用謝謝 我抓取了spx指數在過去10年每個期權交割日的收盤價,一週三次,一共1529次(K1),J和K欄分別代表漲跌幅和次數,比如 J2和K2表示這十年內跌幅大於5%一共出現了8次。由於假定的是買方,要考慮概率成本和時間損耗,所以選格0.75%,高於0.75%出現了349次 佔十年交割總數的22.83% 至於應該用多少的本金和每次下注的金額,直接套用凱利公式,畢竟這個公式賊簡陋,只需要個贏得概率和賠率就行 我們按照預計贏率隨便選個贏率相近的組合來計算賠率和投比,比如4520/4530,成本在180塊左右,最大盈利是720塊左右,所以賠率在4.667左右,帶入公式得出投比爲6.29%,反向計算本金+2次容錯值=3179.65,代入數據後輸出結果 第一組數據按照歷史數據來統計,在此之前的600個交割日中有150個交割日SPX收盤價高於前一個交割日收盤價0.75%,假設3.8年前開始每週開倉買入三次call spread,其餘時間不做任何交易,截止到上上週,持倉本金會從一開始的$3200變成現在的$40million 接下來我們帶入隨機概率值,回測區間不變還是600個交割日(L2)在每筆交易旁邊設置一個隨機概率值(G欄),然後用一個隨機概率返回值爲TRUE的次數來統計(L3),可以理解爲假如贏率爲25%,每筆
怎麼把$3200變成$50million?
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XinxinJC
XinxinJC
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2021-08-07
Nice
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XinxinJC
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2021-08-01
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XinxinJC
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2021-07-29
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XinxinJC
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2021-07-29
Like pls
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上週很不幸被IB和CME邀請去參加了個關於 The profitability of market data analysis 的學術交流event,爲啥不幸呢?沒告知我我需要去演講,於是我啥也沒準備的就去了,到了後被一臉懵逼的請了上去,雖然我面無表情但是心理慌的一比,不過很快我就想到講什麼了:搭建個每天買spx call spread的組合,通過模型來算怎麼買和什麼價位最有可能變成百萬富翁,這樣應該能混過去 先聲明下這些數據都是臨時做的,雖然有些簡陋但請不要盜用謝謝 我抓取了spx指數在過去10年每個期權交割日的收盤價,一週三次,一共1529次(K1),J和K欄分別代表漲跌幅和次數,比如 J2和K2表示這十年內跌幅大於5%一共出現了8次。由於假定的是買方,要考慮概率成本和時間損耗,所以選格0.75%,高於0.75%出現了349次 佔十年交割總數的22.83% 至於應該用多少的本金和每次下注的金額,直接套用凱利公式,畢竟這個公式賊簡陋,只需要個贏得概率和賠率就行 我們按照預計贏率隨便選個贏率相近的組合來計算賠率和投比,比如4520/4530,成本在180塊左右,最大盈利是720塊左右,所以賠率在4.667左右,帶入公式得出投比爲6.29%,反向計算本金+2次容錯值=3179.65,代入數據後輸出結果 第一組數據按照歷史數據來統計,在此之前的600個交割日中有150個交割日SPX收盤價高於前一個交割日收盤價0.75%,假設3.8年前開始每週開倉買入三次call spread,其餘時間不做任何交易,截止到上上週,持倉本金會從一開始的$3200變成現在的$40million 接下來我們帶入隨機概率值,回測區間不變還是600個交割日(L2)在每筆交易旁邊設置一個隨機概率值(G欄),然後用一個隨機概率返回值爲TRUE的次數來統計(L3),可以理解爲假如贏率爲25%,每筆","listText":" 上週很不幸被IB和CME邀請去參加了個關於 The profitability of market data analysis 的學術交流event,爲啥不幸呢?沒告知我我需要去演講,於是我啥也沒準備的就去了,到了後被一臉懵逼的請了上去,雖然我面無表情但是心理慌的一比,不過很快我就想到講什麼了:搭建個每天買spx call spread的組合,通過模型來算怎麼買和什麼價位最有可能變成百萬富翁,這樣應該能混過去 先聲明下這些數據都是臨時做的,雖然有些簡陋但請不要盜用謝謝 我抓取了spx指數在過去10年每個期權交割日的收盤價,一週三次,一共1529次(K1),J和K欄分別代表漲跌幅和次數,比如 J2和K2表示這十年內跌幅大於5%一共出現了8次。由於假定的是買方,要考慮概率成本和時間損耗,所以選格0.75%,高於0.75%出現了349次 佔十年交割總數的22.83% 至於應該用多少的本金和每次下注的金額,直接套用凱利公式,畢竟這個公式賊簡陋,只需要個贏得概率和賠率就行 我們按照預計贏率隨便選個贏率相近的組合來計算賠率和投比,比如4520/4530,成本在180塊左右,最大盈利是720塊左右,所以賠率在4.667左右,帶入公式得出投比爲6.29%,反向計算本金+2次容錯值=3179.65,代入數據後輸出結果 第一組數據按照歷史數據來統計,在此之前的600個交割日中有150個交割日SPX收盤價高於前一個交割日收盤價0.75%,假設3.8年前開始每週開倉買入三次call spread,其餘時間不做任何交易,截止到上上週,持倉本金會從一開始的$3200變成現在的$40million 接下來我們帶入隨機概率值,回測區間不變還是600個交割日(L2)在每筆交易旁邊設置一個隨機概率值(G欄),然後用一個隨機概率返回值爲TRUE的次數來統計(L3),可以理解爲假如贏率爲25%,每筆","text":"上週很不幸被IB和CME邀請去參加了個關於 The profitability of market data analysis 的學術交流event,爲啥不幸呢?沒告知我我需要去演講,於是我啥也沒準備的就去了,到了後被一臉懵逼的請了上去,雖然我面無表情但是心理慌的一比,不過很快我就想到講什麼了:搭建個每天買spx call spread的組合,通過模型來算怎麼買和什麼價位最有可能變成百萬富翁,這樣應該能混過去 先聲明下這些數據都是臨時做的,雖然有些簡陋但請不要盜用謝謝 我抓取了spx指數在過去10年每個期權交割日的收盤價,一週三次,一共1529次(K1),J和K欄分別代表漲跌幅和次數,比如 J2和K2表示這十年內跌幅大於5%一共出現了8次。由於假定的是買方,要考慮概率成本和時間損耗,所以選格0.75%,高於0.75%出現了349次 佔十年交割總數的22.83% 至於應該用多少的本金和每次下注的金額,直接套用凱利公式,畢竟這個公式賊簡陋,只需要個贏得概率和賠率就行 我們按照預計贏率隨便選個贏率相近的組合來計算賠率和投比,比如4520/4530,成本在180塊左右,最大盈利是720塊左右,所以賠率在4.667左右,帶入公式得出投比爲6.29%,反向計算本金+2次容錯值=3179.65,代入數據後輸出結果 第一組數據按照歷史數據來統計,在此之前的600個交割日中有150個交割日SPX收盤價高於前一個交割日收盤價0.75%,假設3.8年前開始每週開倉買入三次call spread,其餘時間不做任何交易,截止到上上週,持倉本金會從一開始的$3200變成現在的$40million 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