diff --git a/openbb_terminal/stocks/comparison_analysis/finbrain_model.py b/openbb_terminal/stocks/comparison_analysis/finbrain_model.py
index 293bdd64700..fe5a69ea9f4 100644
--- a/openbb_terminal/stocks/comparison_analysis/finbrain_model.py
+++ b/openbb_terminal/stocks/comparison_analysis/finbrain_model.py
@@ -13,6 +13,36 @@ from openbb_terminal.rich_config import console
 logger = logging.getLogger(__name__)
 
 
+@log_start_end(log=logger)
+def find_smallest_num_data_point(results_list: List[dict]) -> int:
+    """Helper function to find the number for the smallest total number of data points
+    out of all the tickers. This is necessary because if one ticker has more or less
+    data points than another then it will throw an indexing error. The solution is to
+    have each ticker have the same number of data points as to graph and view properly.
+    We chose to set each ticker to the minimum of number data points out of all the
+    tickers
+
+    Parameters
+    ----------
+    results_list : List[json]
+        List of dicts storing ticker data
+
+    Returns
+    -------
+    int
+        Value of smallest total number of sentiment data points
+    """
+    small_list = list()
+    for result_json in results_list:
+        if (
+            "ticker" in result_json
+            and "sentimentAnalysis" in result_json
+            and len(result_json["sentimentAnalysis"].values()) > 0
+        ):
+            small_list.append(len(result_json["sentimentAnalysis"].values()))
+    return min(small_list)
+
+
 @log_start_end(log=logger)
 def get_sentiments(tickers: List[str]) -> pd.DataFrame:
     """Gets Sentiment analysis from several tickers provided by FinBrain's API
@@ -31,26 +61,54 @@ def get_sentiments(tickers: List[str]) -> pd.DataFrame:
     df_sentiment = pd.DataFrame()
     dates_sentiment = []
     tickers_to_remove = list()
+    results_list = list()
     for ticker in tickers:
         result = requests.get(f"https://api.finbrain.tech/v0/sentiments/{ticker}")
+        # Check status code, if its correct then convert to dict using .json()
         if result.status_code == 200:
             result_json = result.json()
-            if "ticker" in result_json and "sentimentAnalysis" in result_json:
-                df_sentiment[ticker] = [
-                    float(val)
-                    for val in list(result_json["sentimentAnalysis"].values())
-                ]
-                dates_sentiment = list(result_json["sentimentAnalysis"].keys())
-            else:
-                console.print(f"Unexpected data format from FinBrain API for {ticker}")
-                tickers_to_remove.append(ticker)
-
+            results_list.append(result_json)
         else:
             console.print(
                 f"Request error in retrieving {ticker} sentiment from FinBrain API"
             )
             tickers_to_remove.append(ticker)
 
+    # Finds the smallest amount of data points from any of the tickers as to not run
+    # into an indexing error when graphing
+    smallest_num_data_point = find_smallest_num_data_point(results_list)
+
+    num = 0
+    for result_json in results_list:
+        ticker = tickers[num]
+        # Checks to see if sentiment data in results_json
+        if (
+            "ticker" in result_json
+            and "sentimentAnalysis" in result_json
+            and len(result_json["sentimentAnalysis"].values()) > 0
+        ):
+            # Storing sentiments and dates in list
+            sentiments = list(result_json["sentimentAnalysis"].values())
+            dates_sentiment = list(result_json["sentimentAnalysis"].keys())
+
+            # If there are more sentiment data points for one ticker compared to the
+            # smallest amount of data points, then remove that data points from that
+            # ticker as to be able to graph properly
+            if len(sentiments) > smallest_num_data_point:
+                sentiments = sentiments[0:smallest_num_data_point]
+                dates_sentiment = dates_sentiment[0:smallest_num_data_point]
+
+            df_sentiment[ticker] = [float(val) for val in sentiments]
+
+        # If sentiment data not in results_json remove it
+        else:
+            console.print(
+                f"Unexpected data format or no data from FinBrain API for {ticker}"
+            )
+            tickers_to_remove.append(ticker)
+
+        num = num + 1
+
     for ticker in tickers_to_remove:
         tickers.remove(ticker)