diff --git a/openbb_terminal/miscellaneous/integration_tests_scripts/portfolio/test_portfolio.openbb b/openbb_terminal/miscellaneous/integration_tests_scripts/portfolio/test_portfolio.openbb
index 231ff5618666..46f17097e517 100644
--- a/openbb_terminal/miscellaneous/integration_tests_scripts/portfolio/test_portfolio.openbb
+++ b/openbb_terminal/miscellaneous/integration_tests_scripts/portfolio/test_portfolio.openbb
@@ -2,6 +2,13 @@ portfolio
 load --example
 show
 bench QQQ
+bench FAKE_BENCH
+bench TSLA
+alloc assets -t -l 4
+alloc sectors -t -l 4
+alloc countries -t -l 4
+alloc regions -t -l 4
+bench SPY
 alloc assets -t -l 4
 alloc sectors -t -l 4
 alloc countries -t -l 4
diff --git a/openbb_terminal/portfolio/allocation_model.py b/openbb_terminal/portfolio/allocation_model.py
index 9cdf7b933cf1..606f06fdef30 100644
--- a/openbb_terminal/portfolio/allocation_model.py
+++ b/openbb_terminal/portfolio/allocation_model.py
@@ -72,11 +72,16 @@ def get_assets_allocation(
     pd.DataFrame
         DataFrame with the portfolio's asset allocations
     """
-    benchmark_assets_allocation = pd.DataFrame(benchmark_info["holdings"])
-    benchmark_assets_allocation.rename(
-        columns={"symbol": "Symbol", "holdingPercent": "Benchmark"}, inplace=True
-    )
-    benchmark_assets_allocation.drop(columns=["holdingName"], inplace=True)
+    if "holdings" in benchmark_info:
+        benchmark_assets_allocation = pd.DataFrame(benchmark_info["holdings"])
+        benchmark_assets_allocation.rename(
+            columns={"symbol": "Symbol", "holdingPercent": "Benchmark"}, inplace=True
+        )
+        benchmark_assets_allocation.drop(columns=["holdingName"], inplace=True)
+    else:
+        benchmark_assets_allocation = pd.DataFrame(
+            columns=["Symbol", "Benchmark", "Sector", "Country"]
+        )
 
     portfolio_assets_allocation = (
         portfolio_trades[portfolio_trades["Type"] != "CASH"]
@@ -109,34 +114,37 @@ def get_sectors_allocation(
     Returns
     -------
     pd.DataFrame
-        DataFrame with regional allocations.
+        DataFrame with benchmark allocations.
     pd.DataFrame
-        DataFrame with country allocations
+        DataFrame with portfolio allocations
     """
 
-    benchmark_sectors_allocation = (
-        pd.DataFrame.from_dict(
-            data={
-                sector_name: allocation
-                for sector in benchmark_info["sectorWeightings"]
-                for sector_name, allocation in sector.items()
-            },
-            orient="index",
+    if "sectorWeightings" in benchmark_info:
+        benchmark_sectors_allocation = (
+            pd.DataFrame.from_dict(
+                data={
+                    sector_name: allocation
+                    for sector in benchmark_info["sectorWeightings"]
+                    for sector_name, allocation in sector.items()
+                },
+                orient="index",
+            )
+            .squeeze()
+            .sort_values(ascending=False)
         )
-        .squeeze()
-        .sort_values(ascending=False)
-    )
 
-    # Prettify sector allocations of benchmark to align with Portfolio Excel
-    prettified = [
-        sector.replace("_", " ").title()
-        for sector in benchmark_sectors_allocation.index
-    ]
+        # Prettify sector allocations of benchmark to align with Portfolio Excel
+        prettified = [
+            sector.replace("_", " ").title()
+            for sector in benchmark_sectors_allocation.index
+        ]
 
-    benchmark_sectors_allocation.index = prettified
-    benchmark_sectors_allocation = pd.DataFrame(benchmark_sectors_allocation)
-    benchmark_sectors_allocation.reset_index(inplace=True)
-    benchmark_sectors_allocation.columns = ["Sector", "Benchmark"]
+        benchmark_sectors_allocation.index = prettified
+        benchmark_sectors_allocation = pd.DataFrame(benchmark_sectors_allocation)
+        benchmark_sectors_allocation.reset_index(inplace=True)
+        benchmark_sectors_allocation.columns = ["Sector", "Benchmark"]
+    else:
+        benchmark_sectors_allocation = pd.DataFrame(columns=["Sector", "Benchmark"])
 
     # Define portfolio sector allocation
     # Aggregate sector value for stocks and crypto
@@ -243,9 +251,9 @@ def get_countries_allocation(
     Returns
     -------
     pd.DataFrame
-        DataFrame with regional allocations.
+        DataFrame with benchmark allocations.
     pd.DataFrame
-        DataFrame with country allocations
+        DataFrame with portfolio allocations
     """
 
     benchmark_allocation = get_symbol_allocation(
@@ -305,7 +313,7 @@ def get_symbol_allocation(
     Returns
     -------
     pd.DataFrame
-        Dictionary with country allocations
+        Dictionary with category allocations
     """
 
     if category == "Region":
@@ -332,7 +340,10 @@ def get_symbol_allocation(
     # Collect data from Fidelity about the portfolio composition of the benchmark
     URL = f"https://screener.fidelity.com/ftgw/etf/goto/snapshot/portfolioComposition.jhtml?symbols={symbol}"
     html = request(URL).content
-    df_list = pd.read_html(html)
+    try:
+        df_list = pd.read_html(html)
+    except ValueError:
+        return pd.DataFrame(columns=[category, col_name])
 
     # Find the ones that contain regions and countries
     for index, item in enumerate(df_list):
diff --git a/openbb_terminal/portfolio/attribution_model.py b/openbb_terminal/portfolio/attribution_model.py
index 795a29d2d55f..1e517ae556cc 100644
--- a/openbb_terminal/portfolio/attribution_model.py
+++ b/openbb_terminal/portfolio/attribution_model.py
@@ -9,6 +9,7 @@
 import yfinance as yf
 
 from openbb_terminal.decorators import log_start_end
+from openbb_terminal.rich_config import console
 
 logger = logging.getLogger(__name__)
 
@@ -68,7 +69,11 @@ def get_spy_sector_contributions(
 
     # Load in info
     sp500_tickers_data = get_daily_sector_prices(start_date, end_date)
-    weight_data = yf.Ticker(sectors_ticker).info["sectorWeightings"]
+    try:
+        weight_data = yf.Ticker(sectors_ticker).info["sectorWeightings"]
+    except Exception as _:  # noqa
+        console.print("[red]Could not get info for S&P 500.")
+        return pd.DataFrame()
 
     # reformat Data
     weights: Dict[str, dict] = {"SPY": {}}
diff --git a/openbb_terminal/portfolio/portfolio_controller.py b/openbb_terminal/portfolio/portfolio_controller.py
index 66fc00e1ec8c..ae29a5e7df2a 100644
--- a/openbb_terminal/portfolio/portfolio_controller.py
+++ b/openbb_terminal/portfolio/portfolio_controller.py
@@ -141,6 +141,7 @@ def __init__(self, queue: List[str] = None):
         self.portfolio_name: str = ""
         self.benchmark_name: str = ""
         self.original_benchmark_ticker = ""
+        self.recalculate_alloc = False
         self.risk_free_rate = 0
         self.portlist: List[str] = os.listdir(self.DEFAULT_HOLDINGS_PATH)
         self.portfolio = None
@@ -149,6 +150,10 @@ def __init__(self, queue: List[str] = None):
             self.update_choices()
             choices: dict = self.choices_default
             self.choices = choices
+            self.choices["bench"] = {
+                "--benchmark": {c: None for c in statics.BENCHMARK_CHOICES},
+                "-b": "--benchmark",
+            }
             self.completer = NestedCompleter.from_nested_dict(choices)
 
     def update_choices(self):
@@ -416,7 +421,6 @@ def call_bench(self, other_args: List[str]):
             dest="benchmark",
             required="-h" not in other_args,
             help="Set the benchmark for the portfolio. By default, this is SPDR S&P 500 ETF Trust (SPY).",
-            choices={c: {} for c in statics.BENCHMARK_CHOICES},
             metavar="BENCHMARK",
         )
         parser.add_argument(
@@ -437,9 +441,14 @@ def call_bench(self, other_args: List[str]):
                     "[red]Please first load transactions file using 'load'[/red]"
                 )
             else:
-                self.benchmark_name = statics.BENCHMARK_CHOICES.get(ns_parser.benchmark)
-                self.original_benchmark_ticker = ns_parser.benchmark
-                self.portfolio.set_benchmark(ns_parser.benchmark, ns_parser.full_shares)
+                if self.portfolio.set_benchmark(
+                    ns_parser.benchmark, ns_parser.full_shares
+                ):
+                    self.benchmark_name = statics.BENCHMARK_CHOICES.get(
+                        ns_parser.benchmark, ns_parser.benchmark
+                    )
+                    self.original_benchmark_ticker = ns_parser.benchmark
+                    self.recalculate_alloc = True
 
     @log_start_end(log=logger)
     def call_alloc(self, other_args: List[str]):
@@ -481,27 +490,31 @@ def call_alloc(self, other_args: List[str]):
             ):
                 if ns_parser.agg == "assets":
                     portfolio_view.display_assets_allocation(
-                        self.portfolio,
-                        ns_parser.limit,
-                        ns_parser.tables,
+                        portfolio_engine=self.portfolio,
+                        limit=ns_parser.limit,
+                        tables=ns_parser.tables,
+                        recalculate=self.recalculate_alloc,
                     )
                 elif ns_parser.agg == "sectors":
                     portfolio_view.display_sectors_allocation(
-                        self.portfolio,
-                        ns_parser.limit,
-                        ns_parser.tables,
+                        portfolio_engine=self.portfolio,
+                        limit=ns_parser.limit,
+                        tables=ns_parser.tables,
+                        recalculate=self.recalculate_alloc,
                     )
                 elif ns_parser.agg == "countries":
                     portfolio_view.display_countries_allocation(
-                        self.portfolio,
-                        ns_parser.limit,
-                        ns_parser.tables,
+                        portfolio_engine=self.portfolio,
+                        limit=ns_parser.limit,
+                        tables=ns_parser.tables,
+                        recalculate=self.recalculate_alloc,
                     )
                 elif ns_parser.agg == "regions":
                     portfolio_view.display_regions_allocation(
-                        self.portfolio,
-                        ns_parser.limit,
-                        ns_parser.tables,
+                        portfolio_engine=self.portfolio,
+                        limit=ns_parser.limit,
+                        tables=ns_parser.tables,
+                        recalculate=self.recalculate_alloc,
                     )
                 else:
                     console.print(
@@ -576,9 +589,13 @@ def call_attrib(self, other_args: List[str]):
                 bench_result = attribution_model.get_spy_sector_contributions(
                     start_date, end_date
                 )
+                if bench_result.empty:
+                    return
                 portfolio_result = attribution_model.get_portfolio_sector_contributions(
                     start_date, self.portfolio.portfolio_trades
                 )
+                if portfolio_result.empty:
+                    return
 
                 # relative results - the proportions of return attribution
                 if ns_parser.type == "relative":
@@ -951,6 +968,23 @@ def call_mret(self, other_args: List[str]):
             help="Period to select start end of the year returns",
             metavar="PERIOD",
         )
+        parser.add_argument(
+            "-i",
+            "--instrument",
+            type=str,
+            dest="instrument",
+            default="both",
+            choices=["both", "portfolio", "benchmark"],
+            help="Whether to show portfolio or benchmark monthly returns. By default both are shown in one table.",
+        )
+        parser.add_argument(
+            "-g",
+            "--graph",
+            action="store_true",
+            default=False,
+            dest="graph",
+            help="Plot the monthly returns on a heatmap",
+        )
         parser.add_argument(
             "-s",
             "--show",
@@ -965,7 +999,7 @@ def call_mret(self, other_args: List[str]):
             parser,
             other_args,
             raw=True,
-            export_allowed=EXPORT_ONLY_FIGURES_ALLOWED,
+            export_allowed=EXPORT_ONLY_RAW_DATA_ALLOWED,
         )
 
         if ns_parser and self.portfolio is not None:
@@ -975,10 +1009,13 @@ def call_mret(self, other_args: List[str]):
                 portfolio_view.display_monthly_returns(
                     self.portfolio,
                     ns_parser.period,
-                    ns_parser.raw,
+                    ns_parser.instrument,
+                    ns_parser.graph,
                     ns_parser.show_vals,
                     ns_parser.export,
-                    ns_parser.sheet_name,
+                    sheet_name=" ".join(ns_parser.sheet_name)
+                    if ns_parser.sheet_name
+                    else None,
                 )
 
     @log_start_end(log=logger)
@@ -1020,7 +1057,9 @@ def call_dret(self, other_args: List[str]):
                     ns_parser.raw,
                     ns_parser.limit,
                     ns_parser.export,
-                    ns_parser.sheet_name,
+                    sheet_name=" ".join(ns_parser.sheet_name)
+                    if ns_parser.sheet_name
+                    else None,
                 )
 
     @log_start_end(log=logger)
@@ -1042,9 +1081,6 @@ def call_maxdd(self, other_args: List[str]):
                 portfolio_view.display_maximum_drawdown(
                     self.portfolio,
                     export=ns_parser.export,
-                    sheet_name=" ".join(ns_parser.sheet_name)
-                    if ns_parser.sheet_name
-                    else None,
                 )
 
     @log_start_end(log=logger)
@@ -1278,18 +1314,26 @@ def call_metric(self, other_args: List[str]):
                         self.portfolio,
                         ns_parser.risk_free_rate / 100,
                         ns_parser.export,
-                        ns_parser.sheet_name,
+                        sheet_name=" ".join(ns_parser.sheet_name)
+                        if ns_parser.sheet_name
+                        else None,
                     )
                 elif ns_parser.metric == "sortino":
                     portfolio_view.display_sortino_ratio(
                         self.portfolio,
                         ns_parser.risk_free_rate / 100,
                         ns_parser.export,
-                        ns_parser.sheet_name,
+                        sheet_name=" ".join(ns_parser.sheet_name)
+                        if ns_parser.sheet_name
+                        else None,
                     )
                 elif ns_parser.metric == "maxdrawdown":
                     portfolio_view.display_maximum_drawdown_ratio(
-                        self.portfolio, ns_parser.export, ns_parser.sheet_name
+                        self.portfolio,
+                        ns_parser.export,
+                        sheet_name=" ".join(ns_parser.sheet_name)
+                        if ns_parser.sheet_name
+                        else None,
                     )
                 elif ns_parser.metric == "rsquare":
                     portfolio_view.display_rsquare(
@@ -1301,15 +1345,27 @@ def call_metric(self, other_args: List[str]):
                     )
                 elif ns_parser.metric == "gaintopain":
                     portfolio_view.display_gaintopain_ratio(
-                        self.portfolio, ns_parser.export, ns_parser.sheet_name
+                        self.portfolio,
+                        ns_parser.export,
+                        sheet_name=" ".join(ns_parser.sheet_name)
+                        if ns_parser.sheet_name
+                        else None,
                     )
                 elif ns_parser.metric == "trackerr":
                     portfolio_view.display_tracking_error(
-                        self.portfolio, ns_parser.export, ns_parser.sheet_name
+                        self.portfolio,
+                        ns_parser.export,
+                        sheet_name=" ".join(ns_parser.sheet_name)
+                        if ns_parser.sheet_name
+                        else None,
                     )
                 elif ns_parser.metric == "information":
                     portfolio_view.display_information_ratio(
-                        self.portfolio, ns_parser.export, ns_parser.sheet_name
+                        self.portfolio,
+                        ns_parser.export,
+                        sheet_name=" ".join(ns_parser.sheet_name)
+                        if ns_parser.sheet_name
+                        else None,
                     )
                 elif ns_parser.metric == "tail":
                     portfolio_view.display_tail_ratio(
@@ -1321,30 +1377,52 @@ def call_metric(self, other_args: List[str]):
                     )
                 elif ns_parser.metric == "commonsense":
                     portfolio_view.display_common_sense_ratio(
-                        self.portfolio, ns_parser.export, ns_parser.sheet_name
+                        self.portfolio,
+                        ns_parser.export,
+                        sheet_name=" ".join(ns_parser.sheet_name)
+                        if ns_parser.sheet_name
+                        else None,
                     )
                 elif ns_parser.metric == "jensens":
                     portfolio_view.display_jensens_alpha(
                         self.portfolio,
                         ns_parser.risk_free_rate / 100,
                         ns_parser.export,
-                        ns_parser.sheet_name,
+                        sheet_name=" ".join(ns_parser.sheet_name)
+                        if ns_parser.sheet_name
+                        else None,
                     )
                 elif ns_parser.metric == "calmar":
                     portfolio_view.display_calmar_ratio(
-                        self.portfolio, ns_parser.export, ns_parser.sheet_name
+                        self.portfolio,
+                        ns_parser.export,
+                        sheet_name=" ".join(ns_parser.sheet_name)
+                        if ns_parser.sheet_name
+                        else None,
                     )
                 elif ns_parser.metric == "kelly":
                     portfolio_view.display_kelly_criterion(
-                        self.portfolio, ns_parser.export, ns_parser.sheet_name
+                        self.portfolio,
+                        ns_parser.export,
+                        sheet_name=" ".join(ns_parser.sheet_name)
+                        if ns_parser.sheet_name
+                        else None,
                     )
                 elif ns_parser.metric == "payoff" and self.portfolio is not None:
                     portfolio_view.display_payoff_ratio(
-                        self.portfolio, ns_parser.export, ns_parser.sheet_name
+                        self.portfolio,
+                        ns_parser.export,
+                        sheet_name=" ".join(ns_parser.sheet_name)
+                        if ns_parser.sheet_name
+                        else None,
                     )
                 elif ns_parser.metric == "profitfactor" and self.portfolio is not None:
                     portfolio_view.display_profit_factor(
-                        self.portfolio, ns_parser.export, ns_parser.sheet_name
+                        self.portfolio,
+                        ns_parser.export,
+                        sheet_name=" ".join(ns_parser.sheet_name)
+                        if ns_parser.sheet_name
+                        else None,
                     )
 
     @log_start_end(log=logger)
@@ -1384,7 +1462,9 @@ def call_distr(self, other_args: List[str]):
                     ns_parser.period,
                     ns_parser.raw,
                     ns_parser.export,
-                    ns_parser.sheet_name,
+                    sheet_name=" ".join(ns_parser.sheet_name)
+                    if ns_parser.sheet_name
+                    else None,
                 )
 
     @log_start_end(log=logger)
@@ -1431,7 +1511,9 @@ def call_summary(self, other_args: List[str]):
                     ns_parser.period,
                     ns_parser.risk_free_rate / 100,
                     ns_parser.export,
-                    ns_parser.sheet_name,
+                    sheet_name=" ".join(ns_parser.sheet_name)
+                    if ns_parser.sheet_name
+                    else None,
                 )
 
 
diff --git a/openbb_terminal/portfolio/portfolio_engine.py b/openbb_terminal/portfolio/portfolio_engine.py
index bdad5ef64f5f..1086fc0c57f3 100644
--- a/openbb_terminal/portfolio/portfolio_engine.py
+++ b/openbb_terminal/portfolio/portfolio_engine.py
@@ -22,7 +22,8 @@
 from openbb_terminal.terminal_helper import suppress_stdout
 
 # pylint: disable=E1136,W0201,R0902,C0302
-# pylint: disable=unsupported-assignment-operation,redefined-outer-name,too-many-public-methods, consider-using-f-string
+# pylint: disable=unsupported-assignment-operation,redefined-outer-name
+# pylint: too-many-public-methods, consider-using-f-string,disable=raise-missing-from
 
 logger = logging.getLogger(__name__)
 
@@ -117,7 +118,7 @@ def __init__(self, transactions: pd.DataFrame = pd.DataFrame()):
         self.tickers_list = None
         self.tickers: Dict[Any, Any] = {}
         self.benchmark_ticker: str = ""
-        self.benchmark_info = None
+        self.benchmark_info: Dict[Any, Any] = {}
         self.historical_trade_data = pd.DataFrame()
 
         # Portfolio
@@ -226,7 +227,7 @@ def __preprocess_transactions(self):
             13. Populate fields Sector, Industry and Country
         """
 
-        p_bar = tqdm(range(14), desc="Preprocessing transactions")
+        p_bar = tqdm(range(14), desc="Preprocessing transactions", leave=False)
 
         try:
             # 0. If optional fields not in the transactions add missing
@@ -495,7 +496,7 @@ def __load_company_data(self):
                         ] = info_list
 
     @log_start_end(log=logger)
-    def set_benchmark(self, symbol: str = "SPY", full_shares: bool = False):
+    def set_benchmark(self, symbol: str = "SPY", full_shares: bool = False) -> bool:
         """Load benchmark into portfolio.
 
         Parameters
@@ -505,11 +506,14 @@ def set_benchmark(self, symbol: str = "SPY", full_shares: bool = False):
         full_shares: bool
             Whether to mimic the portfolio trades exactly (partial shares) or round down the
             quantity to the nearest number
+
+        Returns
+        -------
+        bool
+            True if successful, False otherwise
         """
 
-        p_bar = tqdm(range(4), desc="         Loading benchmark")
-
-        self.benchmark_ticker = symbol
+        p_bar = tqdm(range(4), desc="         Loading benchmark", leave=False)
 
         self.benchmark_historical_prices = yf.download(
             symbol,
@@ -519,6 +523,15 @@ def set_benchmark(self, symbol: str = "SPY", full_shares: bool = False):
             ignore_tz=True,
         )["Adj Close"]
 
+        if self.benchmark_historical_prices.empty:
+            console.print(
+                f"\n[red]Could not download benchmark data for {symbol}."
+                " Choose another symbol.\n[/red]"
+            )
+            return False
+
+        self.benchmark_ticker = symbol
+
         p_bar.n += 1
         p_bar.refresh()
 
@@ -538,11 +551,6 @@ def set_benchmark(self, symbol: str = "SPY", full_shares: bool = False):
         p_bar.refresh()
 
         self.benchmark_returns = self.benchmark_historical_prices.pct_change().dropna()
-        self.benchmark_info = yf.Ticker(symbol).info
-
-        p_bar.n += 1
-        p_bar.refresh()
-
         (
             self.portfolio_returns,
             self.benchmark_returns,
@@ -551,6 +559,21 @@ def set_benchmark(self, symbol: str = "SPY", full_shares: bool = False):
         p_bar.n += 1
         p_bar.refresh()
 
+        try:
+            self.benchmark_info = dict(yf.Ticker(symbol).info)
+            self.benchmark_info["symbol"] = symbol
+        except Exception as _:  # noqa
+            console.print(
+                f"[red]\n\nCould not get info for {symbol}."
+                " This affects 'alloc' command.[/red]\n"
+            )
+            return False
+
+        p_bar.n += 1
+        p_bar.refresh()
+
+        return True
+
     @log_start_end(log=logger)
     def __mimic_trades_for_benchmark(self, full_shares: bool = False):
         """Mimic trades from the transactions based on chosen benchmark assuming partial shares
@@ -650,7 +673,9 @@ def __load_portfolio_historical_prices(self, use_close: bool = False):
             whether to use close or adjusted close prices
         """
 
-        p_bar = tqdm(range(len(self.tickers)), desc="        Loading price data")
+        p_bar = tqdm(
+            range(len(self.tickers)), desc="        Loading price data", leave=False
+        )
 
         for ticker_type, data in self.tickers.items():
             price_data = yf.download(
@@ -781,7 +806,7 @@ def __calculate_portfolio_returns(self):
                 from any sales during the period [Cash Inflow(t)].
         """
 
-        p_bar = tqdm(range(1), desc="       Calculating returns")
+        p_bar = tqdm(range(1), desc="       Calculating returns", leave=False)
 
         trade_data = self.historical_trade_data
 
@@ -906,6 +931,12 @@ def calculate_allocation(self, category: str, recalculate: bool = False):
             Flag to force recalculate allocation if already exists
         """
 
+        if not self.benchmark_info:
+            return
+
+        if self.portfolio_trades.empty:
+            return
+
         if category == "Asset":
             if (
                 self.benchmark_assets_allocation.empty
diff --git a/openbb_terminal/portfolio/portfolio_model.py b/openbb_terminal/portfolio/portfolio_model.py
index f6703b0ec6c3..030cf692095d 100644
--- a/openbb_terminal/portfolio/portfolio_model.py
+++ b/openbb_terminal/portfolio/portfolio_model.py
@@ -58,8 +58,8 @@ def generate_portfolio(
     transactions = PortfolioEngine.read_transactions(transactions_file_path)
     portfolio_engine = PortfolioEngine(transactions)
     portfolio_engine.generate_portfolio_data()
-    portfolio_engine.set_benchmark(symbol=benchmark_symbol, full_shares=full_shares)
     portfolio_engine.set_risk_free_rate(risk_free_rate)
+    portfolio_engine.set_benchmark(symbol=benchmark_symbol, full_shares=full_shares)
 
     return portfolio_engine
 
@@ -92,7 +92,7 @@ def get_transactions(portfolio_engine: PortfolioEngine) -> pd.DataFrame:
 @log_start_end(log=logger)
 def set_benchmark(
     portfolio_engine: PortfolioEngine, symbol: str, full_shares: bool = False
-):
+) -> bool:
     """Load benchmark into portfolio
 
     Parameters
@@ -106,6 +106,11 @@ def set_benchmark(
         Whether to mimic the portfolio trades exactly (partial shares) or round down the
         quantity to the nearest number
 
+    Returns
+    -------
+    bool
+        True if successful, False otherwise
+
     Examples
     --------
     >>> from openbb_terminal.sdk import openbb
@@ -113,7 +118,7 @@ def set_benchmark(
     >>> output = openbb.portfolio.bench(p, symbol="SPY")
     """
 
-    portfolio_engine.set_benchmark(symbol=symbol, full_shares=full_shares)
+    return portfolio_engine.set_benchmark(symbol=symbol, full_shares=full_shares)
 
 
 @log_start_end(log=logger)
@@ -366,7 +371,36 @@ def get_monthly_returns(
         ],
     )
 
-    return monthly_returns, bench_monthly_returns
+    years = [
+        (year, instrument)
+        for year in monthly_returns.index
+        for instrument in ["Portfolio", "Benchmark", "Alpha"]
+    ]
+    total_monthly_returns = pd.DataFrame(
+        np.nan,
+        columns=monthly_returns.columns,
+        index=pd.MultiIndex.from_tuples(years, names=["Year", "Instrument"]),
+    )
+
+    for year in monthly_returns.index:
+        for instrument in ["Portfolio", "Benchmark", "Alpha"]:
+            if instrument == "Portfolio":
+                total_monthly_returns.loc[
+                    (year, instrument), monthly_returns.columns
+                ] = monthly_returns.loc[year].values
+            elif instrument == "Benchmark":
+                total_monthly_returns.loc[
+                    (year, instrument), monthly_returns.columns
+                ] = bench_monthly_returns.loc[year].values
+            elif instrument == "Alpha":
+                total_monthly_returns.loc[
+                    (year, instrument), monthly_returns.columns
+                ] = (
+                    monthly_returns.loc[year].values
+                    - bench_monthly_returns.loc[year].values
+                )
+
+    return monthly_returns, bench_monthly_returns, total_monthly_returns
 
 
 @log_start_end(log=logger)
@@ -430,6 +464,13 @@ def join_allocation(
     pd.DataFrame
         DataFrame with portfolio and benchmark allocations
     """
+
+    if portfolio.empty:
+        portfolio = pd.DataFrame(columns=[column, "Portfolio"])
+
+    if benchmark.empty:
+        benchmark = pd.DataFrame(columns=[column, "Benchmark"])
+
     combined = pd.merge(portfolio, benchmark, on=column, how="left")
     combined["Difference"] = combined["Portfolio"] - combined["Benchmark"]
     combined = combined.replace(np.nan, "-")
diff --git a/openbb_terminal/portfolio/portfolio_view.py b/openbb_terminal/portfolio/portfolio_view.py
index e5734881216d..ad93590837c2 100644
--- a/openbb_terminal/portfolio/portfolio_view.py
+++ b/openbb_terminal/portfolio/portfolio_view.py
@@ -145,6 +145,7 @@ def display_assets_allocation(
     portfolio_engine: PortfolioEngine,
     limit: int = 10,
     tables: bool = False,
+    recalculate: bool = False,
 ):
     """Display portfolio asset allocation compared to the benchmark
 
@@ -152,16 +153,19 @@ def display_assets_allocation(
     ----------
     portfolio_engine: PortfolioEngine
         Instance of PortfolioEngine class
-    tables: bool
-        Whether to include separate asset allocation tables
     limit: int
         The amount of assets you wish to show, by default this is set to 10
+    tables: bool
+        Whether to include separate asset allocation tables
+    recalculate: bool
+        Whether to recalculate the allocation
     """
 
     combined, portfolio_allocation, benchmark_allocation = get_assets_allocation(
         portfolio_engine=portfolio_engine,
         limit=limit,
         tables=True,
+        recalculate=recalculate,
     )
 
     display_category(
@@ -179,6 +183,7 @@ def display_sectors_allocation(
     portfolio_engine: PortfolioEngine,
     limit: int = 10,
     tables: bool = False,
+    recalculate: bool = False,
 ):
     """Display portfolio sector allocation compared to the benchmark
 
@@ -190,12 +195,15 @@ def display_sectors_allocation(
         The amount of assets you wish to show, by default this is set to 10
     tables: bool
         Whether to include separate asset allocation tables
+    recalculate: bool
+        Whether to recalculate the allocation
     """
 
     combined, portfolio_allocation, benchmark_allocation = get_sectors_allocation(
         portfolio_engine=portfolio_engine,
         limit=limit,
         tables=True,
+        recalculate=recalculate,
     )
 
     display_category(
@@ -213,6 +221,7 @@ def display_countries_allocation(
     portfolio_engine: PortfolioEngine,
     limit: int = 10,
     tables: bool = False,
+    recalculate: bool = False,
 ):
     """Display portfolio country allocation compared to the benchmark
 
@@ -224,12 +233,15 @@ def display_countries_allocation(
         The amount of assets you wish to show, by default this is set to 10
     tables: bool
         Whether to include separate asset allocation tables
+    recalculate: bool
+        Whether to recalculate the allocation
     """
 
     combined, portfolio_allocation, benchmark_allocation = get_countries_allocation(
         portfolio_engine=portfolio_engine,
         limit=limit,
         tables=True,
+        recalculate=recalculate,
     )
 
     display_category(
@@ -247,6 +259,7 @@ def display_regions_allocation(
     portfolio_engine: PortfolioEngine,
     limit: int = 10,
     tables: bool = False,
+    recalculate: bool = False,
 ):
     """Display portfolio region allocation compared to the benchmark
 
@@ -258,12 +271,15 @@ def display_regions_allocation(
         The amount of assets you wish to show, by default this is set to 10
     tables: bool
         Whether to include separate asset allocation tables
+    recalculate: bool
+        Whether to recalculate the allocation
     """
 
     combined, portfolio_allocation, benchmark_allocation = get_regions_allocation(
         portfolio_engine=portfolio_engine,
         limit=limit,
         tables=True,
+        recalculate=recalculate,
     )
 
     display_category(
@@ -459,7 +475,8 @@ def display_yearly_returns(
 def display_monthly_returns(
     portfolio_engine: PortfolioEngine,
     window: str = "all",
-    raw: bool = False,
+    instrument: str = "both",
+    graph: bool = False,
     show_vals: bool = False,
     export: str = "",
     sheet_name: str = None,
@@ -474,27 +491,38 @@ def display_monthly_returns(
         Use `portfolio.load` to create a PortfolioEngine.
     window : str
         interval to compare cumulative returns and benchmark
-    raw : False
-        Display raw data from cumulative return
+    instrument : str
+        Display raw data from cumulative return, default is showing both the portfolio and benchmark in one table
     show_vals : False
         Show values on heatmap
     export : str
         Export certain type of data
+    sheet_name : str
+        Whether to export to a specific sheet name in an Excel file
     external_axes: plt.Axes
         Optional axes to display plot on
     """
 
-    portfolio_returns, benchmark_returns = get_monthly_returns(portfolio_engine, window)
+    portfolio_returns, benchmark_returns, total_monthly_returns = get_monthly_returns(
+        portfolio_engine, window
+    )
 
-    if raw:
+    if instrument == "portfolio":
         print_rich_table(
             portfolio_returns,
             title="Monthly returns - portfolio [%]",
             headers=portfolio_returns.columns,
             show_index=True,
         )
-        console.print("\n")
 
+        export_data(
+            export,
+            os.path.dirname(os.path.abspath(__file__)),
+            "mret_portfolio",
+            portfolio_returns,
+            sheet_name,
+        )
+    elif instrument == "benchmark":
         print_rich_table(
             benchmark_returns,
             title="Monthly returns - benchmark [%]",
@@ -502,7 +530,49 @@ def display_monthly_returns(
             show_index=True,
         )
 
-    else:
+        export_data(
+            export,
+            os.path.dirname(os.path.abspath(__file__)),
+            "mret_benchmark",
+            benchmark_returns,
+            sheet_name,
+        )
+    elif instrument == "both":
+        # Converts multi-index into readable rich table while keeping the multi-index intact for export
+        total_monthly_returns_rich = total_monthly_returns.copy()
+        total_monthly_returns_rich.insert(
+            0, "Instruments", total_monthly_returns_rich.index.get_level_values(1)
+        )
+        total_monthly_returns_rich.insert(
+            0,
+            "Year",
+            sum(
+                [
+                    [year, "", ""]
+                    for year in total_monthly_returns_rich.index.get_level_values(
+                        0
+                    ).unique()
+                ],
+                [],
+            ),
+        )
+
+        print_rich_table(
+            total_monthly_returns_rich,
+            title="Total Monthly returns [%]",
+            headers=total_monthly_returns_rich.columns,
+            show_index=False,
+        )
+
+        export_data(
+            export,
+            os.path.dirname(os.path.abspath(__file__)),
+            "mret_total",
+            total_monthly_returns,
+            sheet_name,
+        )
+
+    if graph or show_vals:
         if external_axes is None:
             _, ax = plt.subplots(
                 2,
@@ -548,14 +618,6 @@ def display_monthly_returns(
         if external_axes is None:
             theme.visualize_output()
 
-    export_data(
-        export,
-        os.path.dirname(os.path.abspath(__file__)),
-        "mret",
-        portfolio_returns,
-        sheet_name,
-    )
-
 
 @log_start_end(log=logger)
 def display_daily_returns(