[huuan26]

Resolves #119.

Summary

This PR adds support for SSL Channel (Securement Stop Loss Channel) as first-class indicator columns in StockDataFrame.

Features

1. SSL Channel:

   • Implements Erwin Beckers' SSL Channel indicator.
   • Calculates dynamic support and resistance bands using SMA of High and Low prices and tracks the close price relative trend position:
     • sma_high = SMA(high, window)
     • sma_low = SMA(low, window)
     • hlv[i] = 1 if close[i] > sma_high[i] else (-1 if close[i] < sma_low[i] else hlv[i-1])
     • ssl_down = sma_high if hlv < 0 else sma_low
     • ssl_up = sma_low if hlv < 0 else sma_high
   • Exposes df['ssl'] (defaults to ssl_up), df['ssl_up'], df['ssl_down'].
   • Supports default window (10) and custom window (e.g., df['ssl_up_5'], df['ssl_down_5'], df['ssl_14']).
   • Supports crossover detection for buy/sell trading signals (e.g. df['ssl_up_xu_ssl_down'] for bullish crossover, df['ssl_up_xd_ssl_down'] for bearish crossunder).
   • Adds class method StockDataFrame.ssl_channel(high, low, close, window).
   • Handles edge cases cleanly (empty series, single row series, window bounds).

2. Configuration & Handler:

   • Added "ssl": 10, "ssl_up": 10, "ssl_down": 10 to _dft_windows.
   • Registered ("ssl", "ssl_up", "ssl_down"): self._get_ssl in self.handler.

Verification & Documentation

• Added unit tests in test.py:
  • test_ssl_channel: Verified against 30-day stock data benchmark, trend flipping verification (20110117), custom window evaluation (ssl_up_5), and crossunder detection (ssl_up_xd_ssl_down).
  • test_ssl_channel_edge_cases: Verified edge cases (empty series, single-element).
• Updated README.md Summary table, Introduction list, and Trend section with formula and usage examples.
• Code style: flake8 stockstats.py test.py passed with 0 errors.
• Test suite: 137/137 tests passed (96% coverage).