diff --git a/app/cron_implied_volatility.py b/app/cron_implied_volatility.py
index 9979a0e..ec4f0af 100644
--- a/app/cron_implied_volatility.py
+++ b/app/cron_implied_volatility.py
@@ -34,10 +34,11 @@ def filter_past_six_months(data):
     sorted_data = sorted(filtered_data, key=lambda x: datetime.strptime(x['date'], '%Y-%m-%d'))
     return sorted_data
 
-async def get_data(ticker_list):
-    ticker_str = ','.join(ticker_list)
+async def get_data(ticker):
+    #ticker_str = ','.join(ticker_list)
+    
     async with aiohttp.ClientSession() as session:
-        url = url = f"https://data.nasdaq.com/api/v3/datatables/ORATS/OPT?date={date_str}&ticker={ticker_str}&api_key={api_key}"
+        url = url = f"https://data.nasdaq.com/api/v3/datatables/ORATS/OPT?date={date_str}&ticker={ticker}&api_key={api_key}"
         async with session.get(url) as response:
             if response.status == 200:
                 res = await response.json()
@@ -54,7 +55,7 @@ async def run():
 
     cursor = con.cursor()
     cursor.execute("PRAGMA journal_mode = wal")
-    cursor.execute("SELECT DISTINCT symbol FROM stocks")
+    cursor.execute("SELECT DISTINCT symbol FROM stocks WHERE marketcap >=10E6 AND symbol NOT LIKE '%.%'")
     stocks_symbols = [row[0] for row in cursor.fetchall()]
 
     etf_cursor = etf_con.cursor()
@@ -69,14 +70,21 @@ async def run():
     chunk_size = len(total_symbols) // 70  # Divide the list into N chunks
     chunks = [total_symbols[i:i + chunk_size] for i in range(0, len(total_symbols), chunk_size)]
     
-    for chunk in tqdm(chunks):
-        data, columns = await get_data(chunk)
-        transformed_data = []
+    for ticker in tqdm(total_symbols):
+        data, columns = await get_data(ticker)
+        filtered_data = []
         for element in tqdm(data):
             # Assuming the number of columns matches the length of each element in `data`
-            transformed_data.append({columns[i]["name"]: element[i] for i in range(len(columns))})
+            filtered_data.append({columns[i]["name"]: element[i] for i in range(len(columns))})
 
+        try:
+            sorted_data = sorted(filtered_data, key=lambda x: datetime.strptime(x['date'], '%Y-%m-%d'))
+            if len(sorted_data) > 0:
+                await save_json(ticker, sorted_data)
+        except Exception as e:
+            print(e)
 
+        '''
         for symbol in chunk:
             try:
                 filtered_data = [item for item in transformed_data if symbol == item['ticker']]               
@@ -85,6 +93,7 @@ async def run():
                     await save_json(symbol, sorted_data)
             except Exception as e:
                 print(e)
+        '''
     
     con.close()
     etf_con.close()
diff --git a/app/primary_cron_job.py b/app/primary_cron_job.py
index b47e8de..6788e4c 100755
--- a/app/primary_cron_job.py
+++ b/app/primary_cron_job.py
@@ -447,7 +447,7 @@ schedule.every().day.at("10:30").do(run_threaded, run_sec_filings).tag('sec_fili
 schedule.every().day.at("11:00").do(run_threaded, run_executive).tag('executive_job')
 schedule.every().day.at("03:00").do(run_threaded, run_retail_volume).tag('retail_volume_job')
 schedule.every().day.at("11:45").do(run_threaded, run_clinical_trial).tag('clinical_trial_job')
-schedule.every().day.at("02:00").do(run_threaded, run_implied_volatility).tag('implied_volatility_job')
+schedule.every().day.at("05:00").do(run_threaded, run_implied_volatility).tag('implied_volatility_job')
 
 
 schedule.every().day.at("13:30").do(run_threaded, run_stockdeck).tag('stockdeck_job')