problem: KeyError: 'Retirement Portfolio'
Traceback:
File "/usr/local/lib/python3.10/dist-packages/streamlit/runtime/scriptrunner/exec_code.py", line 88, in exec_func_with_error_handling
    result = func()
File "/usr/local/lib/python3.10/dist-packages/streamlit/runtime/scriptrunner/script_runner.py", line 579, in code_to_exec
    exec(code, module.__dict__)
File "/content/portfolio_optimizer.py", line 4434, in <module>
    display_backtest_results(result["backtest_results"], comparison_type, portfolio1)
File "/content/portfolio_optimizer.py", line 609, in display_backtest_results
    display_portfolio_vs_benchmark(results)
File "/content/portfolio_optimizer.py", line 772, in display_portfolio_vs_benchmark
    st.dataframe(styled_metrics, height=400)
File "/usr/local/lib/python3.10/dist-packages/streamlit/runtime/metrics_util.py", line 410, in wrapped_func
    result = non_optional_func(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/streamlit/elements/arrow.py", line 547, in dataframe
    marshall_styler(proto, data, default_uuid)
File "/usr/local/lib/python3.10/dist-packages/streamlit/elements/lib/pandas_styler_utils.py", line 61, in marshall_styler
    styler._compute()
File "/usr/local/lib/python3.10/dist-packages/pandas/io/formats/style_render.py", line 256, in _compute
    r = func(self)(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/pandas/io/formats/style.py", line 1728, in _apply
    result = data.T.apply(func, axis=0, **kwargs).T  # see GH 42005
File "/usr/local/lib/python3.10/dist-packages/pandas/core/frame.py", line 10374, in apply
    return op.apply().__finalize__(self, method="apply")
File "/usr/local/lib/python3.10/dist-packages/pandas/core/apply.py", line 916, in apply
    return self.apply_standard()
File "/usr/local/lib/python3.10/dist-packages/pandas/core/apply.py", line 1063, in apply_standard
    results, res_index = self.apply_series_generator()
File "/usr/local/lib/python3.10/dist-packages/pandas/core/apply.py", line 1081, in apply_series_generator
    results[i] = self.func(v, *self.args, **self.kwargs)
File "/content/portfolio_optimizer.py", line 598, in highlight_better_performance
    if isinstance(row[portfolio1], (int, float)) and isinstance(row[portfolio2], (int, float)):
File "/usr/local/lib/python3.10/dist-packages/pandas/core/series.py", line 1121, in __getitem__
    return self._get_value(key)
File "/usr/local/lib/python3.10/dist-packages/pandas/core/series.py", line 1237, in _get_value
    loc = self.index.get_loc(label)
File "/usr/local/lib/python3.10/dist-packages/pandas/core/indexes/base.py", line 3812, in get_loc
    raise KeyError(key) from err

if the segments code need update, please return the full updated segments code, no need import or other stuff, only the full version of the updated segment

### Extracted Code Segments

#### 1. **File: `portfolio_optimizer.py`**
   - **Function: `create_example_portfolios`**
     - **Relevance:** This function creates a list of predefined example portfolios, including the "Retirement Portfolio." The KeyError is related to a missing key in the `result` dictionary, which is likely derived from these example portfolios.
     - **Code Segment:**
       ```python
       def create_example_portfolios() -> list:
           """
           Creates a list of predefined example portfolios.
           
           Returns:
               list: A list of dictionaries, each representing a portfolio.
           """
           today = datetime.today()
           today_pd = pd.to_datetime(today)
           example_definitions = [
               {
                   'name': "Retirement Portfolio",
                   'years': 10,
                   'benchmark_symbol': '^GSPC',
                   'rebalance_freq': 'M',
                   'selected': ['AAPL', 'MSFT', 'GOOGL', 'JPM', 'XOM'],
                   'allocations': [20.0, 20.0, 20.0, 20.0, 20.0]
               },
               # Other portfolio definitions...
           ]
           
           portfolios = []
           for port_def in example_definitions:
               portfolio = {
                   'name': port_def['name'],
                   'start_date': today - timedelta(days=365 * port_def['years']),
                   'end_date': today,
                   'rf_rate': 0.02,
                   'broker_fee': 0.0,
                   'benchmark_symbol': port_def['benchmark_symbol'],
                   'rebalance_freq': port_def['rebalance_freq'],
                   'selected': port_def['selected'],
                   'allocations': port_def['allocations']
               }
               portfolios.append(portfolio)
           
           return portfolios
       ```

#### 2. **File: `portfolio_optimizer.py`**
   - **Function: `display_backtest_results`**
     - **Relevance:** This function is responsible for displaying the backtest results. The KeyError occurs when trying to access the `"backtest_results"` key in the `result` dictionary.
     - **Code Segment:**
       ```python
       def display_backtest_results(results, comparison_type, portfolio1, portfolio2=None):
           if comparison_type == "Portfolio vs Benchmark":
               display_portfolio_vs_benchmark(results)
           else:
               # For portfolio vs portfolio comparison
               display_portfolio_vs_portfolio(results, portfolio1, portfolio2)
       ```

#### 3. **File: `portfolio_optimizer.py`**
   - **Function: `display_portfolio_vs_benchmark`**
     - **Relevance:** This function is called within `display_backtest_results` and is responsible for displaying the comparison between the portfolio and the benchmark. The KeyError occurs when trying to access the `"backtest_results"` key in the `result` dictionary.
     - **Code Segment:**
       ```python
       def display_portfolio_vs_benchmark(results):
           """
           Enhanced display function for Portfolio vs Benchmark comparison with improved visualizations and UX.
           """
           # Extract data from results
           returns = results['returns']
           cum_returns = results['cum_returns']
           weights = results['weights']
           price_data = results['price_data']
           available_selected = results['available_selected']
           metrics = results['metrics']
           benchmark_metrics = results['benchmark_metrics']
           benchmark_returns = results['benchmark_returns']
           benchmark_cum_returns = results['benchmark_cum_returns']

           # Define a consistent theme for all plots
           THEMES = {
               'plotly_dark': 'plotly_dark',
               'plotly_light': 'plotly_white'
           }
           selected_theme = THEMES.get('plotly_light')  # Change as needed

           # Create tabs for better organization
           main_tab, metrics_tab, risk_tab, analysis_tab, insights_tab = st.tabs([
               "📈 Main Charts", "📊 Performance Metrics", "🎯 Risk Analysis", "🔍 Deep Analysis", "🧠 Metric-Based Insights"
           ])

           with main_tab:
               st.header("🔹 Portfolio vs Benchmark Overview")
               col1, col2 = st.columns([2, 1])
               with col1:
                   st.subheader("Portfolio Composition")
                   fig_composition = px.pie(
                       values=weights,
                       names=price_data.columns,
                       title="Current Portfolio Allocation",
                       template=selected_theme,
                       hole=0.4
                   )
                   fig_composition.update_traces(textinfo='percent+label')
                   st.plotly_chart(fig_composition, use_container_width=True)

               with col2:
                   st.subheader("Key Performance Indicators")
                   metrics_display = {
                       "Total Return": f"{(cum_returns.iloc[-1] - 1) * 100:.2f}%",
                       "Annualized Return": f"{metrics.get('Annualized Return (CAGR)', 0) * 100:.2f}%" if metrics.get('Annualized Return (CAGR)', 0) else "N/A",
                       "Sharpe Ratio": metrics.get('Sharpe Ratio', 'N/A'),
                       "Max Drawdown": f"{metrics.get('Maximum Drawdown', 0):.2f}%"
                   }
                   for metric, value in metrics_display.items():
                       st.metric(metric, value)

               # Enhanced Cumulative Returns Plot with Interactive Features
               st.subheader("Cumulative Returns Comparison")
               fig_returns = go.Figure()
               fig_returns.add_trace(go.Scatter(
                   x=cum_returns.index,
                   y=cum_returns,
                   name="Portfolio",
                   line=dict(color='cyan', width=2),
                   hovertemplate='%{y:.2f}'
               ))
               fig_returns.add_trace(go.Scatter(
                   x=benchmark_cum_returns.index,
                   y=benchmark_cum_returns,
                   name="Benchmark",
                   line=dict(color='orange', width=2, dash='dash'),
                   hovertemplate='%{y:.2f}'
               ))
               fig_returns.update_layout(
                   template=selected_theme,
                   hovermode='x unified',
                   height=500,
                   xaxis_title='Date',
                   yaxis_title='Cumulative Returns',
                   legend=dict(x=0.01, y=0.99)
               )
               st.plotly_chart(fig_returns, use_container_width=True)

               # Interactive Summary Recommendations
               create_summary_recommendations('overview', metrics=metrics)
       ```

#### 4. **File: `portfolio_optimizer.py`**
   - **Function: `highlight_better_performance`**
     - **Relevance:** This function is used to highlight better performance in a DataFrame. The KeyError occurs when trying to access `row[portfolio1]` and `row[portfolio2]`.
     - **Code Segment:**
       ```python
       def highlight_better_performance(row):
           styles = [''] * len(row)
           if isinstance(row[portfolio1], (int, float)) and isinstance(row[portfolio2], (int, float)):
               if 'Drawdown' in row.name or 'Risk' in row.name:
                   better = row[portfolio1] < row[portfolio2]
               else:
                   better = row[portfolio1] > row[portfolio2]
               styles[0] = 'background-color: #d4f7d4' if better else 'background-color: #f7d4d4'
               styles[1] = 'background-color: #d4f7d4' if not better else 'background-color: #f7d4d4'
           return styles
       ```

### Summary
The KeyError: 'Retirement Portfolio' is likely occurring due to the following reasons:
1. **Missing Key in `result` Dictionary:** The `result` dictionary does not contain the expected key `"backtest_results"`. This could be due to an error in the backtest process or incorrect handling of the results.
2. **Incorrect Access to DataFrame Rows:** The function `highlight_better_performance` tries to access `row[portfolio1]` and `row[portfolio2]`, which might not exist in the DataFrame, leading to a KeyError.

To resolve the issue, ensure that the `result` dictionary contains the expected keys and that the DataFrame rows being accessed in `highlight_better_performance` exist and are correctly indexed.