docs: remove more --dmmp docs

docs/hyperopt.md

@@ -917,7 +917,7 @@ After you run Hyperopt for the desired amount of epochs, you can later list all
 
 Once the optimized strategy has been implemented into your strategy, you should backtest this strategy to make sure everything is working as expected.
 
-To achieve same the results (number of trades, their durations, profit, etc.) as during Hyperopt, please use the same configuration and parameters (timerange, timeframe, ...) used for hyperopt `--dmmp`/`--disable-max-market-positions` and `--eps`/`--enable-position-stacking` for Backtesting.
+To achieve same the results (number of trades, their durations, profit, etc.) as during Hyperopt, please use the same configuration and parameters (timerange, timeframe, ...) used for hyperopt for Backtesting.
 
 ### Why do my backtest results not match my hyperopt results?
 Should results not match, check the following factors:

docs/strategy_analysis_example.md

@@ -215,7 +215,7 @@ trades.groupby("pair")["exit_reason"].value_counts()
 ```
 
 ## Analyze the loaded trades for trade parallelism
-This can be useful to find the best `max_open_trades` parameter, when used with backtesting in conjunction with `--disable-max-market-positions`.
+This can be useful to find the best `max_open_trades` parameter, when used with backtesting in conjunction with a very high `max_open_trades` setting.
 
 `analyze_trade_parallelism()` returns a timeseries dataframe with an "open_trades" column, specifying the number of open trades for each candle.
 

freqtrade/templates/strategy_analysis_example.ipynb

@@ -305,7 +305,7 @@
    "metadata": {},
    "source": [
     "## Analyze the loaded trades for trade parallelism\n",
-    "This can be useful to find the best `max_open_trades` parameter, when used with backtesting in conjunction with `--disable-max-market-positions`.\n",
+    "This can be useful to find the best `max_open_trades` parameter, when used with backtesting in conjunction with a very high `max_open_trades` setting.\n",
     "\n",
     "`analyze_trade_parallelism()` returns a timeseries dataframe with an \"open_trades\" column, specifying the number of open trades for each candle."
    ]