README: linked file directory, placebos and data format sections

- Replace the Files table with a nested list of the 2026.10 files; each file links
to its hub page, each folder to its tree view, and firm-level files note omitted signals
- Add a Placebos section: what they are, why they are included (nesting Hou, Xue,
and Zhang), why they may still be useful, and how to build BidAskTAQ
- Add a Data Format section: firm-level columns and timing, portfolio columns,
return timing and signing
- Link release notes via /blob/ so they render; fix size (12 KB)
- Link Quick download to the file directory; drop the redundant exclusions paragraph

README.md

@@ -42,21 +42,20 @@ use them, please cite [Chen and Zimmermann (2022)](#citation).
 
 ## Quick download (latest release, 2026.10)
 
-### Predictor Portfolios
+### Core predictor portfolios and documentation
 
-Click a link to download, or pass it to any parquet reader. No account or token is needed.
+Click a link to download.
 
 | Data                                                                         | File                                                                                                                                                                                           | Size    |
 | ---------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------- |
 | Signal documentation                                                         | [SignalDoc.csv](https://huggingface.co/datasets/OpenSourceAP/CrossSection/resolve/Data-Release-2026.10/SignalDoc.csv)                                                                          | 0.2 MB  |
 | Long-short returns, original papers' construction (wide)                     | [PredictorLSretWide.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/resolve/Data-Release-2026.10/Portfolios/Full%20Sets%20OP/PredictorLSretWide.parquet)                    | 1.4 MB  |
 | All portfolio returns, original papers' construction (long)                  | [PredictorPortsFull.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/resolve/Data-Release-2026.10/Portfolios/Full%20Sets%20OP/PredictorPortsFull.parquet)                    | 18.7 MB |
-| Placebo portfolio returns (long)                                             | [PlaceboPortsFull.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/resolve/Data-Release-2026.10/Portfolios/Full%20Sets%20OP/PlaceboPortsFull.parquet)                        | 7.9 MB  |
 | Value-weighted decile portfolio returns (long)                               | [PredictorAltPorts_DecilesVW.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/resolve/Data-Release-2026.10/Portfolios/Full%20Sets%20Alt/PredictorAltPorts_DecilesVW.parquet) | 25.7 MB |
 | Daily value-weighted portfolio returns, original papers' construction (long) | [PredictorVW.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/resolve/Data-Release-2026.10/DailyPortfolios/PredictorVW.parquet)                                              | 252 MB  |
-| Release notes                                                                | [Release Notes 2026.10.md](https://huggingface.co/datasets/OpenSourceAP/CrossSection/resolve/Data-Release-2026.10/Release%20Notes%202026.10.md)                                                | 17 KB   |
+| Release notes                                                                | [Release Notes 2026.10.md](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Release%20Notes%202026.10.md)                                                   | 12 KB   |
 
-For example, in Python:
+Or use a parquet reader, e.g.:
 
 ```python
 import pandas as pd
@@ -66,6 +65,8 @@ ports = pd.read_parquet(
 )
 ```
 
+We offer many other portfolio implementations too. See the [File Directory](#file-directory-202610).
+
 ### Accessing Specific Predictor Signals (Firm Level Characteristics)
 
 For most predictors, you can quickly download them via the `columns` argument in `pd.read_parquet()`.
@@ -117,55 +118,132 @@ Package documentation:
 - Python: [openassetpricing](https://github.com/mk0417/open-asset-pricing-download)
 - R: [OpenSourceAP.DownloadR](https://github.com/tomz23/OpenSourceAP.DownloadR)
 
-## Files (2025.10 and later)
-
-| Path                                                           | Contents                                                                                                                                     |
-| -------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------- |
-| `SignalDoc.parquet`, `SignalDoc.csv`                           | One row per signal: category, original paper, sign, portfolio construction settings                                                          |
-| `Firm Level Characteristics/Predictors.parquet`                | Wide panel: `permno`, `yyyymm`, one column per predictor (209 predictors)                                                                    |
-| `Firm Level Characteristics/signed_predictors_dl_wide.parquet` | Same, with each predictor multiplied by its `Sign`, so that higher means higher expected return                                              |
-| `Firm Level Characteristics/Placebos.parquet`                  | Wide panel of placebos (113 "not predictors" and "indirect evidence" signals)                                                                |
-| `Portfolios/Full Sets OP/PredictorPortsFull.parquet`           | Monthly portfolio returns using the original papers' construction. Long: `signalname`, `port`, `date`, `ret`, `signallag`, `Nlong`, `Nshort` |
-| `Portfolios/Full Sets OP/PredictorLSretWide.parquet`           | Long-short returns, wide: `date`, one column per predictor                                                                                   |
-| `Portfolios/Full Sets OP/PlaceboPortsFull.parquet`             | Same as `PredictorPortsFull`, for placebos                                                                                                   |
-| `Portfolios/Full Sets OP/*Summary.xlsx`                        | Summary statistics by signal                                                                                                                 |
-| `Portfolios/Full Sets Alt/*.parquet`                           | Alternative implementations: deciles, quintiles, EW/VW, holding periods, liquidity screens, FF93 style                                       |
-| `DailyPortfolios/*.parquet`                                    | Daily portfolio returns. Long: `signalname`, `port`, `date`, `ret`                                                                           |
-| `Results/`                                                     | Figures and tables from the paper                                                                                                            |
-
-For firm-level signals, `yyyymm` identifies the month-end when the signal is available
-and valid. Use signals from month-end $t$ to predict returns in month $t+1$.
-For monthly portfolio returns, `date` identifies the return month: the return runs
-from the last trading day's closing price in the preceding month to the last trading
-day's closing price in that month. Returns are in percent.
-`port` is text: `"01"`–`"10"` for quantiles, `"LS"` for long-short.
-
-Firm-level signals exclude Price, Size and STreversal (CRSP-only), and BidAskTAQ (TAQ),
-which cannot be redistributed. The R and Python packages above retrieve the three
-CRSP signals using your WRDS account. To construct BidAskTAQ, use the required TAQ
-data with the
-[CrossSection code](https://github.com/OpenSourceAP/CrossSection).
+### Placebos
+
+Placebos are 114 signals whose original papers did not show clear, statistically significant
+predictability in long-short portfolios. This includes 14 "not-predictors," which were clearly 
+insignificant, and 100 "indirect signals," which had only suggestive evidence or were modifications of 
+another signal. Most come from [Hou, Xue, and Zhang (2020)](https://doi.org/10.1093/rfs/hhy131), 
+who count them among their 452 "anomalies." Chen and Zimmermann (2022) include them so that 
+the dataset nests Hou, Xue, and Zhang, and helps reconcile the disparate replication rates
+(Hou, Xue, and Zhang's "failed replications" are mostly tests that were never shown to be
+predictive previously). 
+
+
+The placebos may still be useful. Many of them seem to have predictive power and true 
+statistical predictability is plentiful, historically ([Chen (2026, JF Insights)](https://arxiv.org/abs/2206.15365);
+[Chen and Dim (2023)](https://arxiv.org/abs/2311.10685)). 
+
+Firm-level placebo signals are in [Placebos.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Firm%20Level%20Characteristics/Placebos.parquet),
+and their portfolio returns are in
+[PlaceboPortsFull.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Portfolios/Full%20Sets%20OP/PlaceboPortsFull.parquet).
+
+`BidAskTAQ` is not included. To build it with your own TAQ, ISSM and CRSP data, run the
+[TAQ prep scripts](https://github.com/OpenSourceAP/CrossSection/tree/master/Signals/pyCode/PrepScripts/taq-chen-velikov)
+and then [BidAskTAQ.py](https://github.com/OpenSourceAP/CrossSection/blob/master/Signals/pyCode/Placebos/BidAskTAQ.py)
+from the CrossSection repo.
+
+## File Directory (2026.10)
+
+Click a file or folder to open its page on the hub. Then click "Download" to download.
+
+- [SignalDoc.csv](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/SignalDoc.csv) (0.2 MB) — one row per signal: category, original paper, sign, portfolio settings
+- [SignalDoc.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/SignalDoc.parquet) (64 KB) — same, as parquet
+- [Release Notes 2026.10.md](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Release%20Notes%202026.10.md) (12 KB)
+- **[Firm Level Characteristics/](https://huggingface.co/datasets/OpenSourceAP/CrossSection/tree/Data-Release-2026.10/Firm%20Level%20Characteristics)** — monthly panels: `permno`, `yyyymm`, one column per signal
+  - [Predictors.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Firm%20Level%20Characteristics/Predictors.parquet) (1.9 GB) — 209 predictors; omits `Price`, `Size` and `STreversal` ([how to get them](#the-full-panel-of-firm-level-predictors-signals))
+  - [signed_predictors_dl_wide.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Firm%20Level%20Characteristics/signed_predictors_dl_wide.parquet) (1.9 GB) — same, each multiplied by its `Sign` so that higher signal means higher in-sample mean return; omits `Price`, `Size` and `STreversal` ([how to get them](#the-full-panel-of-firm-level-predictors-signals))
+  - [Placebos.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Firm%20Level%20Characteristics/Placebos.parquet) (1.0 GB) — 113 placebos (not-predictors and indirect signals); omits `BidAskTAQ` ([how to get it](#placebos))
+- **[Portfolios/](https://huggingface.co/datasets/OpenSourceAP/CrossSection/tree/Data-Release-2026.10/Portfolios)**
+  - **[Full Sets OP/](https://huggingface.co/datasets/OpenSourceAP/CrossSection/tree/Data-Release-2026.10/Portfolios/Full%20Sets%20OP)** — monthly returns, original papers' construction
+    - [PredictorLSretWide.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Portfolios/Full%20Sets%20OP/PredictorLSretWide.parquet) (1.4 MB) — long-short returns, one column per predictor
+    - [PredictorPortsFull.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Portfolios/Full%20Sets%20OP/PredictorPortsFull.parquet) (18.7 MB) — all portfolios, long format
+    - [PlaceboPortsFull.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Portfolios/Full%20Sets%20OP/PlaceboPortsFull.parquet) (7.9 MB) — same, for placebos
+    - [PredictorSummary.xlsx](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Portfolios/Full%20Sets%20OP/PredictorSummary.xlsx) (1.1 MB) — summary statistics by predictor
+    - [PlaceboSummary.xlsx](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Portfolios/Full%20Sets%20OP/PlaceboSummary.xlsx) (0.4 MB) — summary statistics by placebo
+  - **[Full Sets Alt/](https://huggingface.co/datasets/OpenSourceAP/CrossSection/tree/Data-Release-2026.10/Portfolios/Full%20Sets%20Alt)** — monthly returns, alternative constructions
+    - [PredictorAltPorts_Deciles.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Portfolios/Full%20Sets%20Alt/PredictorAltPorts_Deciles.parquet) (25.1 MB)
+    - [PredictorAltPorts_DecilesEW.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Portfolios/Full%20Sets%20Alt/PredictorAltPorts_DecilesEW.parquet) (25.1 MB)
+    - [PredictorAltPorts_DecilesVW.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Portfolios/Full%20Sets%20Alt/PredictorAltPorts_DecilesVW.parquet) (25.7 MB)
+    - [PredictorAltPorts_Quintiles.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Portfolios/Full%20Sets%20Alt/PredictorAltPorts_Quintiles.parquet) (13.7 MB)
+    - [PredictorAltPorts_QuintilesEW.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Portfolios/Full%20Sets%20Alt/PredictorAltPorts_QuintilesEW.parquet) (13.7 MB)
+    - [PredictorAltPorts_QuintilesVW.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Portfolios/Full%20Sets%20Alt/PredictorAltPorts_QuintilesVW.parquet) (13.9 MB)
+    - [PredictorAltPorts_HoldPer_1.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Portfolios/Full%20Sets%20Alt/PredictorAltPorts_HoldPer_1.parquet) (18.8 MB)
+    - [PredictorAltPorts_HoldPer_3.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Portfolios/Full%20Sets%20Alt/PredictorAltPorts_HoldPer_3.parquet) (19.0 MB)
+    - [PredictorAltPorts_HoldPer_6.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Portfolios/Full%20Sets%20Alt/PredictorAltPorts_HoldPer_6.parquet) (18.9 MB)
+    - [PredictorAltPorts_HoldPer_12.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Portfolios/Full%20Sets%20Alt/PredictorAltPorts_HoldPer_12.parquet) (18.8 MB)
+    - [PredictorAltPorts_LiqScreen_ME_gt_NYSE20pct.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Portfolios/Full%20Sets%20Alt/PredictorAltPorts_LiqScreen_ME_gt_NYSE20pct.parquet) (18.8 MB)
+    - [PredictorAltPorts_LiqScreen_NYSEonly.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Portfolios/Full%20Sets%20Alt/PredictorAltPorts_LiqScreen_NYSEonly.parquet) (18.2 MB)
+    - [PredictorAltPorts_LiqScreen_Price_gt_5.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Portfolios/Full%20Sets%20Alt/PredictorAltPorts_LiqScreen_Price_gt_5.parquet) (18.9 MB)
+    - [PredictorAltPorts_LiqScreen_VWforce.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Portfolios/Full%20Sets%20Alt/PredictorAltPorts_LiqScreen_VWforce.parquet) (19.0 MB)
+    - [PredictorAltPorts_FF93style.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Portfolios/Full%20Sets%20Alt/PredictorAltPorts_FF93style.parquet) (16.2 MB)
+    - [PlaceboPortsFull.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/Portfolios/Full%20Sets%20Alt/PlaceboPortsFull.parquet) (7.9 MB)
+- **[DailyPortfolios/](https://huggingface.co/datasets/OpenSourceAP/CrossSection/tree/Data-Release-2026.10/DailyPortfolios)** — daily returns, long format
+  - [Predictor.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/DailyPortfolios/Predictor.parquet) (252 MB)
+  - [PredictorVW.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/DailyPortfolios/PredictorVW.parquet) (252 MB)
+  - [CtsPredictorDecile.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/DailyPortfolios/CtsPredictorDecile.parquet) (324 MB)
+  - [CtsPredictorDecileVW.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/DailyPortfolios/CtsPredictorDecileVW.parquet) (324 MB)
+  - [CtsPredictorQuintile.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/DailyPortfolios/CtsPredictorQuintile.parquet) (182 MB)
+  - [CtsPredictorQuintileVW.parquet](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/DailyPortfolios/CtsPredictorQuintileVW.parquet) (182 MB)
+  - [DailyPortSummary.xlsx](https://huggingface.co/datasets/OpenSourceAP/CrossSection/blob/Data-Release-2026.10/DailyPortfolios/DailyPortSummary.xlsx) (8 KB)
+- **[Results/](https://huggingface.co/datasets/OpenSourceAP/CrossSection/tree/Data-Release-2026.10/Results)** — figures and tables from the paper
 
 Older releases may have slightly different file structure.
 
+## Data Format
+
+**Firm-level signals** (`Firm Level Characteristics/`)
+
+- One row per stock-month. `permno` is the CRSP stock identifier, `yyyymm` is the month as an
+  integer (e.g. `198601`), and every other column is one signal, named by its acronym in
+  `SignalDoc.csv`.
+- Timing: signals are available and relevant for trading (based on the original paper) at the
+  end of the month `yyyymm`. Use signals with `yyyymm = 202511` to predict the return between
+  end of November 2025 and some future date (e.g. end of December 2025).
+- Note: Many of the original papers imply that signals are valid long after the fiscal year end.
+  For example, Fama-French 1992 assume that book equity is available 6 months after the fiscal
+  year end, and is relevant for trading for another 12 months after that.
+
+**Monthly portfolio returns** (`Portfolios/`)
+
+- Long format (`PredictorPortsFull`, `PlaceboPortsFull` and the `Full Sets Alt` files): one row
+  per signal, portfolio and month, with columns
+  - `signalname`: the signal's acronym, as in `SignalDoc.csv`
+  - `port`: text, `"01"`–`"10"` for quantile portfolios and `"LS"` for long-short
+  - `date`: the return month, dated the last trading day of the month
+  - `ret`: return, in percent
+  - `signallag`: the average lagged signal of the stocks in the portfolio
+  - `Nlong`, `Nshort`: the number of stocks in the long and short legs (for quantile
+    portfolios, `Nlong` is the number of stocks and `Nshort` is 0)
+- Wide format (`PredictorLSretWide`): long-short returns only, one row per month, with `date`
+  and one column per predictor.
+- The return for `date` runs from the closing price on the last trading day of the preceding
+  month to the closing price on the last trading day of that month.
+- Long-short portfolios are signed using the original papers' results, so the long leg is
+  the one the original paper found to have higher returns.
+
+**Daily portfolio returns** (`DailyPortfolios/`)
+
+- Long format with `signalname`, `port`, `date` (the trading day) and `ret` (in percent).
+
 ## Releases
 
 For another release, replace `Data-Release-2026.10` in the link with that release's branch
 from the table below. 
 
-| Release | Branch (`revision=`)     | Notes |
-| ------- | ------------------------ | ----- |
-| 2026.10 | `"Data-Release-2026.10"` | 212 predictors, 114 placebos; data through 2025-12; CRSP v2 (CIZ); parquet only. See `Release Notes 2026.10.md` |
-| 2025.10 | `"2025.10"`              | 212 predictors, 114 placebos; data through 2024-12; code translated from Stata to Python (v2.0.0) |
-| 2024.10 | `"2024.10"`              | 212 predictors, 114 placebos; patch of 2024.08 fixing look-ahead bias in AnnouncementReturn |
-| 2024.08 | `"2024.08"`              | 212 predictors, 114 placebos; data through 2023-12; OptionMetrics signals end 2022-12 |
-| 2023.08 | `"2023.08"`              | 212 predictors, 114 placebos; data through 2022-12; 5 new predictors; BM follows Stattman (1980) |
-| 2022.04 | `"2022.04"`              | 207 predictors, 114 placebos; SignalDoc corrections; no daily portfolios or `Results/` |
-| 2022.03 | `"2022.03"`              | 207 predictors, 114 placebos; data through 2021-12; `SignalDoc.csv` replaces the xlsx; FF93-style portfolios added |
-| 2021.04 | `"2021.04"`              | 205 predictors, 114 placebos; adds value-weighted and daily portfolios; docs in `SignalDocumentation.xlsx` |
+| Release | Branch (`revision=`)     | Notes                                                                                                                                                                                  |
+| ------- | ------------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| 2026.10 | `"Data-Release-2026.10"` | 212 predictors, 114 placebos; data through 2025-12; CRSP v2 (CIZ); parquet only. See `Release Notes 2026.10.md`                                                                        |
+| 2025.10 | `"2025.10"`              | 212 predictors, 114 placebos; data through 2024-12; code translated from Stata to Python (v2.0.0)                                                                                      |
+| 2024.10 | `"2024.10"`              | 212 predictors, 114 placebos; patch of 2024.08 fixing look-ahead bias in AnnouncementReturn                                                                                            |
+| 2024.08 | `"2024.08"`              | 212 predictors, 114 placebos; data through 2023-12; OptionMetrics signals end 2022-12                                                                                                  |
+| 2023.08 | `"2023.08"`              | 212 predictors, 114 placebos; data through 2022-12; 5 new predictors; BM follows Stattman (1980)                                                                                       |
+| 2022.04 | `"2022.04"`              | 207 predictors, 114 placebos; SignalDoc corrections; no daily portfolios or `Results/`                                                                                                 |
+| 2022.03 | `"2022.03"`              | 207 predictors, 114 placebos; data through 2021-12; `SignalDoc.csv` replaces the xlsx; FF93-style portfolios added                                                                     |
+| 2021.04 | `"2021.04"`              | 205 predictors, 114 placebos; adds value-weighted and daily portfolios; docs in `SignalDocumentation.xlsx`                                                                             |
 | 2021.03 | `"2021.03"`              | 205 predictors, 114 placebos; **code v1.0.0, matches the CFR publication**; portfolios in `Full_Sets_Main/` and `Full_Sets_Extended/`; `signed_predictors_dl_wide` lacks KZ and ZScore |
-| 2020.07 | `"2020.07"`              | 210 base and 104 additional signals; adds trading-cost portfolios (`PortCosts/`); original layout |
-| 2020.05 | `"2020.05"`              | 210 base and 104 additional signals; first release; original layout (`signalbase`, `portbase`, ...) |
+| 2020.07 | `"2020.07"`              | 210 base and 104 additional signals; adds trading-cost portfolios (`PortCosts/`); original layout                                                                                      |
+| 2020.05 | `"2020.05"`              | 210 base and 104 additional signals; first release; original layout (`signalbase`, `portbase`, ...)                                                                                    |
 
 Counts include Price, Size, STreversal and BidAskTAQ, which are not in the firm-level files.