Movement after Extreme Strong and Weak Day

In the previous two posts I talked about average movements after 1, 3, 5, and 10 days after extreme strong and weak days separately. Here is a chart comparing the result from the posts.

In the chart, red bars red bars represents average movement after extreme weak days and green bars represent what happen after strong days.

From the chart, it is very clear that market tends to consolidate immediately after extreme strength, attempts follow through, reverse after follow through, and eventually value being accepted.

However, market tends to bounce back immediately after extreme weakness and slowly giving back the retracement after the immediate bounce.

From the historical data, the best time to enter long position is after an extreme weak day. As the chance of immediate bounce on the day after is nearly 60%. How does this information help me? Seeing weakness following an extreme day, I imagine that knowing the historical tendency would help me placing a trade against the immediate trend to secure good location and ride out the bounce.

Relevant posts:
<What Happens To SPY After Extreme Weak Day>
<What Happens To SPY After Extreme Strong Day>

What Happens To SPY After Extreme Weak Day

After looking at what happen after a strong day, let's look at what happen after an extreme weak day.

An extreme weak day in this case is defined as a drop more than -2.28%. From 2000, there have been 58 occurrences such drop took place.

• Next Day: SPY average 0.57%, 24 (41.38%) down, 34 (58.62%) up. Down day with average of -1.74%, and up day with average of 2.20%.

• 3 Days later: SPY average 0.58%, 26 (44.83%) down, 32 (55.17%) up. Down days with average of -3.16%, and up days with average of 3.62%.

• 5 Days later: SPY average 0.51%, 28 (48.2%) down, 30 (51.72%) up. Down days with average of -4.1%, and up days with average of 4.82%.

• 10 Days later: SPY average 0.42%, 26 (44.83%) down, 32 (55.17%) up. Down days with average of -5.5% and up days with average of 5.23%.

From this simple test, it is very clear that farther weakness is not likely to follow extreme weakness even when stretched out to 10 day move. The observation holds true even in the drop lasted from 6/6/2008 to 4/20/2009. The day after extreme drop has average gain of 0.5% in the period, only when zooming out to 5 days or more the down trend is clear.

What Happen To SPY After Extreme Strong Day

從學習交易以來，我一直把 Dr. Steenbarger 當成是模仿的對象，再來這一系列的文章是以 Dr. Steenbarger <Consecutive Narrow Days: What Comes Nex> 這種文章為範本，來探討 SPY ETF 的特性。

利用 1/2/2002 到 12/18/2009 每日歷史資料 N=2007，我們來看看當 S&P 上漲超過 2.28% 後，再來 1, 3, 5, 10 天的表現。會選擇 2.28% 是因為它剛好是 2 standard deviations from absolute value of daily move，在過去七年來這種情形發生了 50 次：

• Next Day: SPY average -0.01%，20 (40%) down, 29 (58%) up，1 (2%) flat. Down day with average of -1.67, and up day with average of 1.14%.

• 3 Days later: SPY average 0.46%, 21 (42%) down, 29 (58%) up. Down days with average of -3.31%, and up days with average of 3.19%.

• 5 Days later: SPY average -0.4%, 27 (54%) down, 23 (46%) up. Down days with average of -4.2%, and up days with average of 4.06%.

• 10 Days later: SPY average 0.29%, 21 (42%) down, 29 (58%) up. Down days with average of -5.68% and up days with average of 4.27%.

From the first glance, strength seems to have follow through in the immediate three days after the big move, peters out after stretched out to five days, and gaining back strength after ten days.

Cumulative TICK 的研究

NYSE 指標當中有一個叫做 TICK 的東西，它是 NYSE 股票交易在 uptick 和 downtick 的差別，一搬來講它的值在 1000 到 -1000 中，而 cumulative TICK 則是把一分鐘內 TICK 的高、低、收三個值的平均值加起來的總合。

我採用的資料是 4/30/2007 到 11/20/2009 647 天的一分鐘 TICK 。而這個研究的目的是要看是否能用前十五分鐘 cumulative TICK 來判斷今天是否會成為 trend day。

首先我先算 median，standard deviation (stdev)；

• median = 143, mean = 106
• stdev = 2882
• 1 stdev up = 3025, 1 stdev down = -2739

以這個數據我假設說假如 8:45 分 cumulative TICK 在 1 stdev 以上 SPY 收盤的價錢也應該是同樣的方向。

首先我們先來看 TICK 為正數的天數，以下這個 table 可以看的出來 TICK 在過去兩年內，市場是比較偏向於 mean reversion，當 cumulative TICK 超過 1 stdev 但是沒有超過 4000，市場當天上漲的機會比下跌的機會多，但是下跌的幅度比較大。 TICK 必須超過 4000 才勉強算是有 small edge，不過發生的機率實在太低了。

	Close Higher	Close Lower	Winning %	Average % Change	Positive Average % Change	Negative Average % Change
Less Than 4000	29	26	52.73%	-0.12%	0.95%	-1.28%
4000 ~ 5000	13	8	61.9%	0.16%	1.01%	-1.34%
5000 ~ 6000	12	7	63.16%	0.47%	1.29%	-0.92%
6000 ~ 7000	7	1	87.5%	1.49%	1.73%	-0.22%
7000 ~ 8000	1	0	100%	1.10%	1.10%	0

在來我們看看假如 cumulative TICK 是 1 stdev 往負數的結果。在以下這個表裡，我們可以再次看到市場 reversion to means 的傾向，市場在 cumulative TICK 沒有達到 -4000 的情況下，當天不但上漲的機率較高，上漲的百分比也較多。

	Close Higher	Close Lower	Winning %	Average Change %	Positive Average % Change	Negative Average % Change
Greater Than -3000	8	4	33.33%	1.11%	1.96%	-0.59%
Neg. 4000 ~ 5000	8	13	61.90%	-0.42%	1.20%	-1.41%
Neg. 5000 ~ 6000	5	15	75%	-1.17%	2.43%	-2.37%
Neg. 6000 ~ 7000	1	6	85.71%	-1.04%	0.9%	-1.37%
Neg. 7000 ~ 8000	0	4	100%	-2.29%	0	-2.64%

依照這次的數據，於是我又發展了兩個簡單的交易規則：

• Cumulative TICK 在 8:45 AM 之前達到 -4000 或 4000，除非當天有新聞公佈，continuation 可能性較高。
• Cumulative TICK 若未在 8:45 AM 達到 -4000 或 4000，除非當天有新聞公佈，reversion 可能性較高。

Advance Decline Line 的一些研究

Advance Decline Line 來判斷是否當天真的會有趨勢。$ADD 基本上告訴你今天上漲股票與下跌股票支的差，假如是 1500 表示今天上漲的股票比下跌的多 1500 支。 詳細的解釋可以在<財金商業科技辭典>找到。

這個週末回顧時看到 Dr. Steenbarger 部落格這篇 <The NYSE Advance-Decline Line: Identifying Trending and Range Environment>，他說的一些數據我覺得還滿值得研究的；

By the end of the first half hour of trade, again going back to October, 2008, we find that the median value for $ADD has been -346, with a whopping standard deviation of 1378. That tells us that, within the first 30 minutes of trading, much of the issue of whether or not we're in a trending environment has been sorted out. (My next post will explore this issue more specifically). If we're seeing $ADD between -1000 and +1000 by the end of the first half hour of trade, we're much less likely to be in a trending environment than if we have readings of +1500 or more or -1500 or less.

Will a break above or below a range lead to a directional, trending move? It's likely that the participation of the NYSE advance-decline line will provide some clues. If, for instance, a break above a market's opening range (say, its range for the first 15 minutes of trade) occurs with $ADD well below +1000 and with mixed sector strength, we might be much less likely to go with that move than if the breakout vaults $ADD above +1500 with strong sector participation and leadership.

也就是說 $ADD 在開盤後半小時幾乎已經成了定局，而判斷是否有突破為真正的突破則可以參考 $ADD 是否超過 1500。我用 2007 年 12/13 到 2009 年 11/13 的數字，出來的數在和史丁巴格博士得數據稍有不同，不過大致上還滿類似的。在我找到的數據裡，開盤時的 median 是 66，standard deviation 是 762，十五分鐘後 median 為 -69，standard deviation 為 1235，半小時後，median 為 -97，standard deviation 為 1217，收盤時 median 為 -3，standard deviation 為 1341。開盤十五分鐘後大局以定。開盤時 ADD 與收盤時 ADD 的 correlation 為 0.53，開盤後十五分鐘 ADD 與收盤時 ADD 的 correlation 為 0.62，

由此可見假如開盤後十五分鐘假如 ADD 超過 1200 或者小於 -1300，表示這一天趨勢還滿強的，必須要注意今天成為 trend day 的可能信還滿高的。從 2007 年十二月到今天只有 37% 的天數是從一開盤就有可能成為 trend day，所以在還未確認前假設今天是 range day，是個正確的假設。

另一個還滿有趣的數據，有 197 天一開盤的 $ADD 是在 1 個 standard deviation 之外 (>882 或者 <-697)。三十分鐘後，還能為在 882 之上或者是 -697 之下的有 82%，但是過了十一點之後只剩 62% 還在這個範圍之外。這樣表示就算一開盤的氣勢很強，但是能維持的只有六成左右，再一次確認假設為 range day 是正確的。最後，一整天都能維持在之前提到的範圍內是所有天數的 25%。 由這個 counting excercise，可以發展出兩個簡單的交易規則：

• 所有的天數有趨勢的日子不到四分之一，因為我用的趨勢定義已經很低了。
• 當 $ADD 在開盤後十五分鐘，假如超過 1200 或小於 -1314，今天發展成為趨勢日的機率有四成，比平常高。Fade the market 時要非常小心。

2X IBH 不同的獲利目標與三點停損

2X IBH 不同的獲利目標與三點停損

Instrument	Performance	Target	Total Net Profit	Max. Drawdown	Sharpe Ratio	Percent Profitable	# of Winning Trades	# of Losing Trades
ES 12-10	2.25	76	3450	-12	0.92	0.4722	17	19
ES 12-10	2.22	72	3375	-12	0.93	0.4722	17	19
ES 12-10	2.17	68	3225	-12	0.93	0.4722	17	19
ES 12-10	2.14	84	3162.5	-12	0.9	0.4722	17	19
ES 12-10	2.14	88	3137.5	-12	0.91	0.4722	17	19
ES 12-10	2.14	52	3137.5	-12	0.84	0.4722	17	19
ES 12-10	2.14	92	3137.5	-12	0.91	0.4722	17	19
ES 12-10	2.14	100	3137.5	-12	0.91	0.4722	17	19
ES 12-10	2.14	96	3137.5	-12	0.91	0.4722	17	19
ES 12-10	2.13	80	3112.5	-12	0.91	0.4722	17	19
ES 12-10	2.11	64	3075	-12	0.93	0.4722	17	19
ES 12-10	2.1	56	3037.5	-12	0.86	0.4722	17	19
ES 12-10	2.06	60	2925	-12	0.92	0.4722	17	19
ES 12-10	2.05	48	2887.5	-12	0.83	0.4722	17	19
ES 12-10	1.97	44	2687.5	-12	0.83	0.4722	17	19
ES 12-10	1.86	40	2387.5	-12	0.8	0.4722	17	19
ES 12-10	1.76	36	2087.5	-12	0.74	0.4722	17	19
ES 12-10	1.65	32	1787.5	-12	0.67	0.4722	17	19
ES 12-10	1.59	24	1537.5	-9	0.66	0.5	18	18
ES 12-10	1.54	28	1500	-12	0.58	0.4722	17	19
ES 12-10	1.58	12	1137.5	-9	0.42	0.6389	23	13
ES 12-10	1.37	20	962.5	-9	0.45	0.5	18	18
ES 12-10	1.27	16	662.5	-9	0.24	0.5278	19	17
ES 12-10	1.22	8	387.5	-12	0.15	0.6667	24	12

這張表則是今年一月到十月二十七號在 IB x2 的地方放空的結果。從這一張圖再次看到 scale-out 的重要性。獲利的多寡與 scale-out 的比率到15 S&P 點幾乎是成正比 (15 點為 60 ticks)，15 點之後則是有點看運氣了。

2X IBL 不同的獲利目標與三點停損

2X IBL 不同的獲利目標與三點停損

Instrument	Performance	Target	Total Net Profit	Max. Drawdown	Sharpe Ratio	Percent Profitable	# of Winning Trades	# of Losing Trades
ES 12-10	1.31	148	837.5	-24.25	0.1	0.3571	10	18
ES 12-10	1.3	24	675	-12	0.24	0.4643	13	15
ES 12-10	1.29	172	775	-24.25	0.1	0.3571	10	18
ES 12-10	1.29	184	775	-24.25	0.1	0.3571	10	18
ES 12-10	1.29	196	775	-24.25	0.1	0.3571	10	18
ES 12-10	1.29	160	775	-24.25	0.1	0.3571	10	18
ES 12-10	1.27	12	487.5	-9	0.27	0.5714	16	12
ES 12-10	0.85	8	-262.5	-13	-0.13	0.5714	16	12
ES 12-10	0.85	48	-412.5	-24.25	-0.12	0.3571	10	18
ES 12-10	0.83	44	-462.5	-24.25	-0.13	0.3571	10	18
ES 12-10	0.82	4	-212.5	-11.25	-0.12	0.7143	20	8
ES 12-10	0.81	40	-525	-24.5	-0.15	0.3571	10	18
ES 12-10	0.77	36	-625	-25.5	-0.19	0.3571	10	18
ES 12-10	0.73	32	-725	-26.5	-0.22	0.3571	10	18

這是在 2x IBL 做多用今年的歷史資料回測的結果，在這個回測中我固定用三點作為停損，來看那一個獲利點的損益最好。從結果中看的到滿有趣的一點，trade manage 在損益上可以造成很到的影響。效益第二好的與最差唯一不同的地方在於獲利點兩點的差別，但是這 S&P 兩點卻造成了將近一口一千六百美金的獲利差別。這個表中也可以看到 scale-out 重要的地方。效益最好的前幾名，分除了 24 這個獲利點外，其他皆是採用超大獲利點為出口。仔細看了一下交易明細，發現造成這個現象的原因是在一月二十一號有一比三十多點的交易。由此可見放長線釣大魚重要的地方。