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I recently finished my first attempt at replicating the BCC signals using my own methods rather than using the now defunct GTR1. I decided to compare my results with those of GTR1 starting with the most recent signal (20251128) from GTR1. While I was at it I also compared the BearCatcher signals that zeelotes has recently shared with us. I had his signals starting in 20250103 and going to that 20251128 date. The attached data shows the results of that comparison. (If it is too large to attach, I'll link you to my spreadsheet.)

To make a long story short, zeelotes signals match exactly with GTR1. My signals may be close but do not match GTR1. I suspect most of my problems are involved with calculation of the NewHigh-NewLow (NHNL) signal. In the spreadsheet, the first 7 columns of data are from downloaded GTR1 data where column 7 is the BCC signal. The next 5 columns of data are the signals from zeelotes where the second column is the signal. His data only shows the date and signals for the times when the signal makes a change so I had to align this dates with the GTR1 dates and filled in the signals between.

The remaining 15 columns are the results of all my calculations with the last of those being the BCC signal. I started by downloading dates and daily closing prices for the NASDAQ Composite Index (NASDAQCOM) from FRED. I only chose to download starting in 1990 even though the GTR1 data can go back much further. I wanted enough data to show some signals and figured that 1990 would do. As it is I still have more than 9100 records.

The signal itself is a decimal expression of the three previous columns SMA, NHNL and DBE. Each of those three columns can only be a 1 or a 0 and represents a binary digit where the actual signal is 1*SMA+2*NHNL+4*DBE.

Of the three signals that make up the final signal, the SMA and CBE are the easiest to calculate. The SMA200 is the Simple Moving Average of the previous 200 closing prices. (Add the 200 previous closing prices and divide by 200.) The SMAdiff column is simply the difference between the closing price and the SMA200 value. When that difference is negative put a 0 in the SMA column else put a 1 in the SMA column.

The DBE (Dying Bullish Euphoria) column is determined by looking at the previous 99 DBE values. If any of those have a value of 1 them, 1 is assigned to that date. If all 99 are 0 then you assign a 0 to that date.

The NHNL signal is the tricky one. This is how Robbie (GTR1) expresses it:
Create [PcntNHC252]: [100*[[Sum [[[Closing g-price; quote_lag=0 days]/[Highest closing g-price over 251 days; lag=1 days]] > 1 ? 1 : 0] at step4]/[StockCount]]]
Create [PcntNHC252WMA9]: [[Weighted Sum of [PcntNHC252] over 9 days (daily weights=9,8,7,6,5,4,3,2,1); lag=0 days]/[Weighted Sum of [1] over 9 days (daily weights=9,8,7,6,5,4,3,2,1); lag=0 days]]
Create [PcntNLC252]: [100*[[Sum [[[Closing g-price; quote_lag=0 days]/[Lowest closing g-price over 251 days; lag=1 days]] < 1 ? 1 : 0] at step4]/[StockCount]]]
Create [PcntNLC252WMA9]: [[Weighted Sum of [PcntNLC252] over 9 days (daily weights=9,8,7,6,5,4,3,2,1); lag=0 days]/[Weighted Sum of [1] over 9 days (daily weights=9,8,7,6,5,4,3,2,1); lag=0 days]]
Create [NHNLDiff]: [1*[PcntNHC252WMA9] - 1*[PcntNLC252WMA9]]

This is my interpretation of that. I causes me to add several new columns of data and requires multiple passes through the data to accomplish. The NH252flag is a 0 or a 1 depending on whether that current closing price is greater then the maximum of the previous 251 closing prices. If it is greater than all of them then put a value of 1 the NH251flag column for that date else put a 0 there. The NL251flag is similarly calculated. When the current closing price is less than the minimum closing price of the previous 251 prices the give it a 1 else give it a zero.

To get the number that goes into the NHpcnt column I first add the previous 251 NH251flags which are zeroes and ones to get a number which I divide by 251 and express as a percent (multiply it by 100). That number is placed in the NHpcnt column. Similarly, I sum the previous 251 NL251 flags, divide by 251 and then multiply by 100. The number goes into the NLpcnt column. For each of those percent numbers I calculate the weighted Moving Average over 9 days and fill in the NHWMA9 and NLWMA9 columns. I then find the difference in the NHWMA9 and NLWMA9 columns and put that number in the NHNLdiff column. Finally, depending on whether NHNLdiff is positive or negative, I put a 1 or a 0 in the NHNL column. This gives me everything I need to calculate the BCC signal.

Judging from the fact that many of my computed signals appear as a 7 when GTR1 shows a 5 would indicate to me that my NHNL signal is off since it contributes 2*NHNL to the final result. I would greatly appreciate any help that anyone might suggest.

Larry

The spreadsheet containing my data can be found here: https://www.dropbox.com/scl/fi/18g3jj866abo7jetbpg...

Larry wrote: I would greatly appreciate any help that anyone might suggest.

What you need to provide is the raw underlying data. That is:

1. The COUNT of New Highs in the Nasdaq Exchange
2. The COUNT of the New Lows in the Nasdaq Exchange

Daily.

With this it is relatively easy to do the rest. Your values are so far off that you are most likely not obtaining the underlying data correctly.

Let me illustrate from a point last year near to the peak. See how quickly the number of New Lows overwhelmed New Highs?

           ND                  OCO       
Date       NH   NL    NH-NL    NH   NL   NH-NL
1/27/2025  97   100   39.56    46   68   -6.38
1/28/2025  115  129   32.07    60   92   -9.73
1/29/2025  112  115   25.2     51   82   -13.96
1/30/2025  158  106   29.24    80   74   -10.69
1/31/2025  138  84    32.36    62   56   -8.4
2/3/2025   46   200   -6.67    24   149  -32.47
2/4/2025   105  105   -9.42    63   75   -30.49
2/5/2025   161  88    4.24     90   64   -20.51
2/6/2025   171  81    20.18    98   62   -9.49
2/7/2025   149  141   19.67    77   111  -13
2/10/2025  144  168   12.51    70   130  -21.44
2/11/2025  90   198   -11.22   51   159  -38.87
2/12/2025  99   196   -30.42   52   158  -54.18
2/13/2025  192  96    -7.71    94   72   -41.4
2/14/2025  233  72    27.07    88   50   -25.78
2/18/2025  226  96    48.64    92   67   -16.38
2/19/2025  155  106   51.13    77   81   -13.6
2/20/2025  109  131   39.96    46   96   -19.36
2/21/2025  121  136   32.67    57   110  -23.8
2/24/2025  57   220   -3.71    24   173  -47.02
2/25/2025  83   287   -45.2    33   221  -76.07
2/26/2025  89   189   -63.76   30   141  -87.93
2/27/2025  77   265   -99.84   32   198  -110.69
2/28/2025  86   340   -142.82  30   252  -140.47
3/3/2025   109  427   -189.38  42   336  -178.87
3/4/2025   79   575   -261.58  25   442  -234.78
3/5/2025   77   150   -237.07  27   120  -216.71
3/6/2025   50   143   -215.42  15   110  -198.09
3/7/2025   51   151   -193.44  12   124  -181.93
3/10/2025  51   275   -197.67  20   199  -180
3/11/2025  45   344   -216.44  12   268  -193.67
3/12/2025  28   198   -205     10   171  -185.11
3/13/2025  33   314   -216.16  10   251  -192.67
3/14/2025  44   158   -193.31  14   117  -172.2
3/17/2025  80   99    -156     22   69   -144.78
3/18/2025  54   135   -141.69  18   105  -133.58
3/19/2025  70   104   -117.8   20   80   -117.11
3/20/2025  58   98    -96.42   17   74   -100.82
3/21/2025  51   164   -90.98   15   134  -98.16
3/24/2025  47   84    -72.8    24   63   -80.82
3/25/2025  42   149   -74.44   23   113  -78.51
3/26/2025  43   197   -86.89   23   143  -83.78
3/27/2025  49   192   -99.96   20   137  -91.13
3/28/2025  65   344   -139.58  15   246  -120.98
3/31/2025  70   568   -217.22  23   413  -178.53
4/1/2025   63   411   -255.6   18   312  -210.16
4/2/2025   49   289   -265.4   18   221  -218.38
4/3/2025   87   669   -339.16  23   493  -276.76
4/4/2025   72   1156  -502.89  10   766  -384.53
4/7/2025   24   1249  -671.56  1    742  -473.38
4/8/2025   20   637   -693.78  7    395  -477.16

For what its worth, simply using a 300 to 350 day SMA rule using SPY beat the 3-part one used here and its components.
Try that in your examples.

zeelotes wrote: What you need to provide is the raw underlying data. That is:

1. The COUNT of New Highs in the Nasdaq Exchange
2. The COUNT of the New Lows in the Nasdaq Exchange

Daily.

With this it is relatively easy to do the rest. Your values are so far off that you are most likely not obtaining the underlying data correctly.

I agree with what you say here but where do I go to get that underlying data? If it has not been systematically collected over time then you can't do what you suggest. I find it hard to believe that Robbie had that data and his formulas make it look like he calculated NewHighs and NewLows on the fly based on the current closing price as it related to the 251 previous closing prices. Is that not what he does here?

Create [PcntNHC252]: [100*[[Sum [[[Closing g-price; quote_lag=0 days]/[Highest closing g-price over 251 days; lag=1 days]] > 1 ? 1 : 0] at step4]/[StockCount]]]
Create [PcntNHC252WMA9]: [[Weighted Sum of [PcntNHC252] over 9 days (daily weights=9,8,7,6,5,4,3,2,1); lag=0 days]/[Weighted Sum of [1] over 9 days (daily weights=9,8,7,6,5,4,3,2,1); lag=0 days]]
Create [PcntNLC252]: [100*[[Sum [[[Closing g-price; quote_lag=0 days]/[Lowest closing g-price over 251 days; lag=1 days]] < 1 ? 1 : 0] at step4]/[StockCount]]]
Create [PcntNLC252WMA9]: [[Weighted Sum of [PcntNLC252] over 9 days (daily weights=9,8,7,6,5,4,3,2,1); lag=0 days]/[Weighted Sum of [1] over 9 days (daily weights=9,8,7,6,5,4,3,2,1); lag=0 days]]
Create [NHNLDiff]: [1*[PcntNHC252WMA9] - 1*[PcntNLC252WMA9]]

If you have any idea where I can get those raw NewHigh NewLow I would sure like to know?

Larry

Larry wrote: I find it hard to believe that Robbie had that data and his formulas make it look like he calculated NewHighs and NewLows on the fly based on the current closing price as it related to the 251 previous closing prices. Is that not what he does here?

I can 100% assure you that this is exactly what he is doing!

If you have any idea where I can get those raw NewHigh NewLow I would sure like to know?

I've posted previously multiple sources for this data. It is true you cannot obtain the history back to 1926, but you can obtain the values every day.

Here is an example of where the data can be obtained:

https://www.barrons.com/market-data/market-lab?mod...

Nasdaq
Daily	2/16/2026	2/17/2026	2/18/2026	2/19/2026	2/20/2026
Issues Traded	...	4,981	4,946	4,936	4,929
Advances	...	2,333	2,765	2,327	2,503
Declines	...	2,481	1,976	2,381	2,210
Unchanged	...	167	205	228	216
New Highs	...	144	171	91	183
New Lows	...	284	153	173	176
Blocks - primary	...	39,489	48,686	39,610	46,904
Total (000)	...	7,654,303	7,705,591	6,984,788	8,063,071

Thanks for the link zee. I have been able to use this link https://www.barchart.com/stocks/momentum to get the daily number of new highs and new lows and your link looks like it wlll give me the today's numbers as well as the 4 previous days. My problem is that I would like to have the previous forty years worth. You wouldn't care to share would you?

Larry

Larry asked: You wouldn't care to share would you?

I'd love to, but that would be breaking agreements.

You can easily purchase this data from Pinnacle.

https://pinnacledata2.com/

I think this has been discussed before, but it would seem difficult to match Robbie's New High, New Low measures using public or purchased data sources. Here's the NHNL portion of the link lohill had in his weekly posts of GTR1's BCC results:

https://gtr1.net/2013/?lf-1lp-1h1::iflt%28linear%2...

When I click on "Signal Values", run a backtest and download the file, I see a "StockCount" of 2,199 on 11/28/25. (New highs = 90, New lows = 18, for a difference of 72; See columns E, F and M at the very bottom). This total count is much lower than other "NASDAQ" sources, which makes sense since the backtest code and Robbie's past descriptions say he does not include all "stocks" in NASDAQ (e.g., no ETFs, etc., only "styp.a = 10!11!18!48").

The Barron's data source mentioned here shows total "Issues Traded" of 4,961 on 2/27/26, much higher than Robbie's would be if updated. (NH = 197, NL = 157)

The BarCharts link lohill provided recently in this thread shows a "NASDAQ Total Components" of 3,044 (NH = 69, NL = 102). Again, a much higher total count, and the net difference is negative rather than positive.

The Wall Street Journal has a market diary page, https://www.wsj.com/market-data/stocks/marketsdiar..., which shows mostly the same data as Barrons, with "Issues Traded" and "New lows" matching, but oddly shows "New highs" = 217, versus Barrons' 197. Seems like these two would match.

I think StockCharts measure of $NAHL was discussed for this in the past also - I see 2/27 net difference shown as 60, with the prior day difference of 87. These match the net difference shown by the Wall Street Journal market diary, but not the others.

Given the inconsistencies of approach and actual counts (total, NH, NL), I'm not sure how to match Robbie's results without his data sources.

Ebbtide wrote: I'm not sure how to match Robbie's results without his data sources.

Both Robbie and I calculate the NH-NL using the Nasdaq Exchange components, as well as Operating Companies Only which is explained here:

https://www.cfraresearch.com/insights/faq/what-is-...

And yes, it is rather complex:

https://www.mcoscillator.com/learning_center/kb/ma...

This is from my software laying the two side by side.

            NASDAQ                    OCO NASDAQ           
Date        Total   NH   NL   NH-NL   Total       NH  NL   NH-NL
12/31/2024  4097    57   60   -38.69  2434        27  38   -40.44
1/2/2025    4096    76   34   -15.42  2432        35  27   -25.29
1/3/2025    4101    82   29   5.44    2431        38  22   -11.64
1/6/2025    4103    123  34   27.38   2431        71  26   3.44
1/7/2025    4099    71   53   29.67   2428        32  38   4.42
1/8/2025    4099    52   111  14.49   2426        24  82   -6.44
1/10/2025   4099    54   198  -17.09  2426        19  145  -30.56
1/13/2025   4099    36   236  -56.2   2426        11  171  -58.62
1/14/2025   4101    43   128  -67.58  2427        16  96   -67.27
1/15/2025   4103    81   88   -62.56  2426        35  62   -64.4
1/16/2025   4106    88   96   -57.64  2426        35  73   -63.38
1/17/2025   4106    92   62   -44.02  2423        42  43   -53.93
1/21/2025   4106    162  70   -17.49  2423        84  54   -37.91
1/22/2025   4104    171  89   6.98    2423        65  59   -26.36
1/23/2025   4104    122  100  18.02   2423        51  68   -19.67
1/24/2025   4107    150  62   40.47   2423        57  45   -8.09
1/27/2025   4108    97   100  39.56   2423        46  68   -6.38
1/28/2025   4108    115  129  32.07   2422        60  92   -9.73
1/29/2025   4107    112  115  25.2    2422        51  82   -13.96
1/30/2025   4107    158  106  29.24   2422        80  74   -10.69
1/31/2025   4110    138  84   32.36   2424        62  56   -8.4

One of the ways I use this research is to combine multiple universes together to create a composite signal. Let me illustrate with last year.

The Nasdaq 100 peaked on 2/19/2025. The Extremely Bearish composite signal fired three market days later on 2/24/2025. Notice that the OCO_Nasdaq was already warning of trouble ahead - in fact, it began firing mid-December of 2024. But the signal from the composite came later.

https://www.zeelotes.org/Composite_NH-NL_Signals.P...

The Nasdaq 100 reached a trough on 4/7/2025. This indicator turned to Extremely Bullish on 4/14/2025 - five market days after the bottom. The bull signal came on 4/10/2025 - three market days later.

So what if you followed these signals trading SOXL during BULL periods and SOXS during BEAR periods.

                   SOXL
Date       Signal  SOXS
1/2/2025   BULL    -3.29%
2/24/2025  BEAR    26.11%
4/10/2025  BULL    404.47%
11/3/2025  BEAR    

AI advice:
Free sources:

• StockCharts ($NYHGH, $NYLOW)
• WSJ market breadth pages
• Barchart
• TradingView
• MarketInOut
• Nasdaq official stats

Simpler alternative:

Use NYSE New Highs/New Lows.
It works similarly.

Many professional systems use:

$NYHL or $HILO
CountOfHighs and CountOfLows (as simple counts of “new high today” / “new low today”)

The backtester counts stocks making 52-wk highs/lows. If you have the market breadth series directly (New Highs, New Lows), you can use them without per-stock counting.

To mimic your weighted 9-day ratio with Excel:

K = Weighted highs (9-day weights 9..1)
L = Weighted lows (9-day weights 9..1)

In K10:

=9*C10+8*C9+7*C8+6*C7+5*C6+4*C5+3*C4+2*C3+1*C2

In L10:

=9*D10+8*D9+7*D8+6*D7+5*D6+4*D5+3*D4+2*D3+1*D2

NHNLRatio M10:

=IF(L10=0,9999,K10/L10)

NHNL signal N10 (1 if ratio > 1 else 0):

=IF(M10>1,1,0)

Zee,

Just curious about where do you source your Nasdaq NH and NL numbers from? I'm assuming that "ND" and "OCO" are two different sources for that data?

I get NH/NL numbers from https://www.wsj.com/market-data/stocks/marketsdiar... That source also aligns with the bulk data you can get from Pinnacle (https://www.pinnacledata2.com)

But they're slightly different values to those you've posted above. Same underlying trends and relative movements, just different values. For example on 27-Jan-2025 WSJ had 91 NH and 135 NL vs your 97 NH and 100 NL.

Virtualmark asked: Just curious about where do you source your Nasdaq NH and NL numbers from? I'm assuming that "ND" and "OCO" are two different sources for that data?

My software tracks all exchange stocks daily, and identifies which exchange they are a part of, and then calculates the New Highs and New Lows and Unchanged daily. I purchase the daily stock information from one of the major suppliers.

As to OCO I suggest you read what this means to understand it better.

https://www.cfraresearch.com/insights/faq/what-is-...

So "ND" consists of ALL stocks on the Nasdaq Stock Exchange. The "OCO" begins with this same lists and then does removals to limit the list to a much smaller number.

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