fix(benchmark): compare agents against DJIA total return (DIA baseline)

README.md

@@ -159,7 +159,7 @@ This script trains 5 DRL agents (A2C, DDPG, PPO, TD3, SAC) using Stable Baseline
 python examples/FinRL_StockTrading_2026_3_Backtest.py
 ```
 
-This script loads the trained agents, runs them on the trading data, and compares their performance against two baselines: Mean Variance Optimization (MVO) and the DJIA index. Results are printed to the console and a plot is saved as `backtest_result.png`.
+This script loads the trained agents, runs them on the trading data, and compares their performance against two baselines: Mean Variance Optimization (MVO) and the DJIA index (total return, via the DIA ETF). Results are printed to the console and a plot is saved as `backtest_result.png`.
 
 
 ## File Structure

examples/FinRL_StockTrading_2026_3_Backtest.py

@@ -152,7 +152,12 @@ def StockReturnsComputing(StockPrice, Rows, Columns):
 
 import yfinance as yf
 
-df_dji = yf.download("^DJI", start=TRADE_START_DATE, end=TRADE_END_DATE)
+# DIA is the DJIA-tracking ETF; adjusted prices include dividends, so the
+# baseline uses the same total-return convention as the agent's account
+# value. ^DJI is a price-return index and would understate the baseline.
+df_dji = yf.download(
+    "DIA", start=TRADE_START_DATE, end=TRADE_END_DATE, auto_adjust=True
+)
 df_dji = df_dji[["Close"]].reset_index()
 df_dji.columns = ["date", "close"]
 df_dji["date"] = df_dji["date"].astype(str)

finrl/plot.py

@@ -51,7 +51,7 @@ def backtest_plot(
     account_value,
     baseline_start=config.TRADE_START_DATE,
     baseline_end=config.TRADE_END_DATE,
-    baseline_ticker="^DJI",
+    baseline_ticker="DIA",
     value_col_name="account_value",
 ):
     df = deepcopy(account_value)
@@ -74,6 +74,9 @@ def backtest_plot(
 
 
 def get_baseline(ticker, start, end):
+    # DIA (a DJIA-tracking ETF) is the default baseline because the
+    # downloader adjusts close prices for dividends, matching the
+    # total-return basis of the agent's account value.
     return YahooDownloader(
         start_date=start, end_date=end, ticker_list=[ticker]
     ).fetch_data()