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Top 10 U.S. Hedge Funds Of 2024 YouTube Views Stats

1Two Sigma

More than 1,400 people who believe the scientific method is the best way to approach investment management, insurance, and related fields. Ideas backed up with information. And improved by iteration. That’s Two Sigma. Learn more at twosigma.com.

2 Citadel

Citadel is a leading alternative investment management firm. For more than three decades, we’ve captured undiscovered market opportunities in markets around the world by empowering extraordinary people to pursue their best and boldest ideas. Our investors at Citadel include many of the world's preeminent public and private institutions. Each day, we reimagine and refine our investment strategies, models and technology in pursuit of market-leading investment returns.

3The D. E. Shaw Group

The D. E. Shaw group is a global investment and technology development firm with offices in North America, Europe, and Asia.

4 Bridgewater Associates

Bridgewater Associates is a premier asset management firm, focused on delivering unique insight and partnership for the most sophisticated global institutional investors.

5 AQR Capital Management

AQR is a global investment management firm built at the intersection of financial theory and practical application. We invest over $143 billion* on behalf of our clients − from pension funds, insurance companies, endowments and foundations to sovereign wealth funds and financial advisors. Our commitment to them is to strive to deliver superior, long-term results. We do this by filtering out market noise to identify and isolate what matters most, and by implementing ideas that stand up to rigorous testing.

# lets import libraries
from googleapiclient.discovery import build
import pandas as pd
import seaborn as sn

1Two Sigma

api_key = 'AIzaSyB24Kop04L1GlTgRCm1XtQ4KB2a4gaBOwA'
Two_Sigma_channel_id = ['UCOylzLjxDbZHFzDbHJiJhgw' # Two Sigma
     
              ]
youtube = build('youtube','v3',developerKey = api_key)

from googleapiclient.errors import HttpError

def get_channel_stats(youtube, Two_Sigma_channel_id):
    all_data = []
    try:
        request = youtube.channels().list(
            part='snippet,contentDetails,statistics',
            id=','.join(Two_Sigma_channel_id)
        )
        response = request.execute()

        for item in response.get('items', []):
            snippet = item.get('snippet', {})
            statistics = item.get('statistics', {})

            data = {
                'Channel_name': snippet.get('title', ''),
                'Subscribers': statistics.get('subscriberCount', ''),
                'Views': statistics.get('viewCount', ''),
                'Total_videos': statistics.get('videoCount', '')
            }

            all_data.append(data)

    except HttpError as e:
        print(f"HTTP error occurred: {e}")
        print(f"Request URL: {e.resp.request.url}")
        print(f"Request body: {e.resp.request.body}")

    return all_data

get_channel_stats(youtube,Two_Sigma_channel_id)

[{'Channel_name': 'Two Sigma',
  'Subscribers': '4600',
  'Views': '155594',
  'Total_videos': '20'}]

channel_statistics = get_channel_stats(youtube, Two_Sigma_channel_id)

Two_Sigma_channel_data =pd.DataFrame(channel_statistics) 

Two_Sigma_channel_data

	Channel_name	Subscribers	Views	Total_videos
0	Two Sigma	4600	155594	20

2 Citadel

# Function to get channel statistics
api_key = 'AIzaSyB24Kop04L1GlTgRCm1XtQ4KB2a4gaBOwA'
Citadel_channel_id = ['UCXuLgCefm8zvvQwSx7A71aQ' # Citadel
     
              ]
youtube = build('youtube','v3',developerKey = api_key)

from googleapiclient.errors import HttpError

def get_channel_stats(youtube, Citadel_channel_id):
    all_data = []
    try:
        request = youtube.channels().list(
            part='snippet,contentDetails,statistics',
            id=','.join(Citadel_channel_id)
        )
        response = request.execute()

        for item in response.get('items', []):
            snippet = item.get('snippet', {})
            statistics = item.get('statistics', {})

            data = {
                'Channel_name': snippet.get('title', ''),
                'Subscribers': statistics.get('subscriberCount', ''),
                'Views': statistics.get('viewCount', ''),
                'Total_videos': statistics.get('videoCount', '')
            }

            all_data.append(data)

    except HttpError as e:
        print(f"HTTP error occurred: {e}")
        print(f"Request URL: {e.resp.request.url}")
        print(f"Request body: {e.resp.request.body}")

    return all_data

get_channel_stats(youtube, Citadel_channel_id)

[{'Channel_name': 'Citadel',
  'Subscribers': '10800',
  'Views': '1753072',
  'Total_videos': '78'}]

channel_statistics = get_channel_stats(youtube, Citadel_channel_id)

Citadel_channel_data =pd.DataFrame(channel_statistics) 

Citadel_channel_data

	Channel_name	Subscribers	Views	Total_videos
0	Citadel	10800	1753072	78

3The D. E. Shaw Group

# Function to get channel statistics
api_key = 'AIzaSyB24Kop04L1GlTgRCm1XtQ4KB2a4gaBOwA'
The_D_E_Shaw_Group_channel_id = ['UCTapQuEwzIFwGNAphDrWjew' # The D. E. Shaw Group
     
              ]
youtube = build('youtube','v3',developerKey = api_key)

from googleapiclient.errors import HttpError

def get_channel_stats(youtube,The_D_E_Shaw_Group_channel_id):
    all_data = []
    try:
        request = youtube.channels().list(
            part='snippet,contentDetails,statistics',
            id=','.join(The_D_E_Shaw_Group_channel_id)
        )
        response = request.execute()

        for item in response.get('items', []):
            snippet = item.get('snippet', {})
            statistics = item.get('statistics', {})

            data = {
                'Channel_name': snippet.get('title', ''),
                'Subscribers': statistics.get('subscriberCount', ''),
                'Views': statistics.get('viewCount', ''),
                'Total_videos': statistics.get('videoCount', '')
            }

            all_data.append(data)

    except HttpError as e:
        print(f"HTTP error occurred: {e}")
        print(f"Request URL: {e.resp.request.url}")
        print(f"Request body: {e.resp.request.body}")

    return all_data

get_channel_stats(youtube,The_D_E_Shaw_Group_channel_id)

[{'Channel_name': 'The D. E. Shaw Group',
  'Subscribers': '1550',
  'Views': '100520',
  'Total_videos': '36'}]

channel_statistics = get_channel_stats(youtube, The_D_E_Shaw_Group_channel_id)

The_D_E_Shaw_Group_channel_data =pd.DataFrame(channel_statistics) 

The_D_E_Shaw_Group_channel_data

	Channel_name	Subscribers	Views	Total_videos
0	The D. E. Shaw Group	1550	100520	36

4 Bridgewater Associates

# Function to get channel statistics
api_key = 'AIzaSyB24Kop04L1GlTgRCm1XtQ4KB2a4gaBOwA'
Bridgewater_Associates_channel_id = ['UC-hKNOj4P-Y8hR9QEHpZPig' # Bridgewater Associates
     
              ]
youtube = build('youtube','v3',developerKey = api_key)

from googleapiclient.errors import HttpError

def get_channel_stats(youtube, Bridgewater_Associates_channel_id):
    all_data = []
    try:
        request = youtube.channels().list(
            part='snippet,contentDetails,statistics',
            id=','.join(Bridgewater_Associates_channel_id)
        )
        response = request.execute()

        for item in response.get('items', []):
            snippet = item.get('snippet', {})
            statistics = item.get('statistics', {})

            data = {
                'Channel_name': snippet.get('title', ''),
                'Subscribers': statistics.get('subscriberCount', ''),
                'Views': statistics.get('viewCount', ''),
                'Total_videos': statistics.get('videoCount', '')
            }

            all_data.append(data)

    except HttpError as e:
        print(f"HTTP error occurred: {e}")
        print(f"Request URL: {e.resp.request.url}")
        print(f"Request body: {e.resp.request.body}")

    return all_data

get_channel_stats(youtube,Bridgewater_Associates_channel_id)

[{'Channel_name': 'Bridgewater Associates',
  'Subscribers': '111000',
  'Views': '4437710',
  'Total_videos': '90'}]

channel_statistics = get_channel_stats(youtube, Bridgewater_Associates_channel_id)

Bridgewater_Associates_channel_data =pd.DataFrame(channel_statistics) 

Bridgewater_Associates_channel_data

	Channel_name	Subscribers	Views	Total_videos
0	Bridgewater Associates	111000	4437710	90

5 AQR Capital Management

# Function to get channel statistics
api_key = 'AIzaSyB24Kop04L1GlTgRCm1XtQ4KB2a4gaBOwA'
AQR_Capital_Management_channel_id = ['UCb2C6udgxl9z_tWf0IFYK7g' # AQR Capital Management
     
              ]
youtube = build('youtube','v3',developerKey = api_key)

from googleapiclient.errors import HttpError

def get_channel_stats(youtube, AQR_Capital_Management_channel_id ):
    all_data = []
    try:
        request = youtube.channels().list(
            part='snippet,contentDetails,statistics',
            id=','.join(AQR_Capital_Management_channel_id )
        )
        response = request.execute()

        for item in response.get('items', []):
            snippet = item.get('snippet', {})
            statistics = item.get('statistics', {})

            data = {
                'Channel_name': snippet.get('title', ''),
                'Subscribers': statistics.get('subscriberCount', ''),
                'Views': statistics.get('viewCount', ''),
                'Total_videos': statistics.get('videoCount', '')
            }

            all_data.append(data)

    except HttpError as e:
        print(f"HTTP error occurred: {e}")
        print(f"Request URL: {e.resp.request.url}")
        print(f"Request body: {e.resp.request.body}")

    return all_data

get_channel_stats(youtube,AQR_Capital_Management_channel_id)

[{'Channel_name': 'AQR Capital Management',
  'Subscribers': '978',
  'Views': '40724',
  'Total_videos': '10'}]

channel_statistics = get_channel_stats(youtube, AQR_Capital_Management_channel_id)

AQR_Capital_Management_channel_data =pd.DataFrame(channel_statistics)

AQR_Capital_Management_channel_data

	Channel_name	Subscribers	Views	Total_videos
0	AQR Capital Management	978	40724	10

# Lets combine the data frames
# Combine DataFrames using concat
combined_hedge_funds_channels_df = pd.concat([Two_Sigma_channel_data ,
                                      Citadel_channel_data , 
                                      The_D_E_Shaw_Group_channel_data ,
                                       Bridgewater_Associates_channel_data,
                                   AQR_Capital_Management_channel_data ,
                                    
                                                                                ], ignore_index=True)

# Display the result
print(combined_hedge_funds_channels_df)

             Channel_name Subscribers    Views Total_videos
0               Two Sigma        4600   155594           20
1                 Citadel       10800  1753072           78
2    The D. E. Shaw Group        1550   100520           36
3  Bridgewater Associates      111000  4437710           90
4  AQR Capital Management         978    40724           10

# # lets have  a look at the datatypes
combined_hedge_funds_channels_df.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 5 entries, 0 to 4
Data columns (total 4 columns):
 #   Column        Non-Null Count  Dtype 
---  ------        --------------  ----- 
 0   Channel_name  5 non-null      object
 1   Subscribers   5 non-null      object
 2   Views         5 non-null      object
 3   Total_videos  5 non-null      object
dtypes: object(4)
memory usage: 292.0+ bytes

# lets change the datatypes to perform  visualisations
combined_hedge_funds_channels_df['Subscribers'] = pd.to_numeric(combined_hedge_funds_channels_df['Subscribers'])
combined_hedge_funds_channels_df['Views'] = pd.to_numeric(combined_hedge_funds_channels_df['Views'])
combined_hedge_funds_channels_df['Total_videos'] = pd.to_numeric(combined_hedge_funds_channels_df['Total_videos'])
# letsconirm if the datatypes has changed
combined_hedge_funds_channels_df.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 5 entries, 0 to 4
Data columns (total 4 columns):
 #   Column        Non-Null Count  Dtype 
---  ------        --------------  ----- 
 0   Channel_name  5 non-null      object
 1   Subscribers   5 non-null      int64 
 2   Views         5 non-null      int64 
 3   Total_videos  5 non-null      int64 
dtypes: int64(3), object(1)
memory usage: 292.0+ bytes

combined_hedge_funds_channels_df

	Channel_name	Subscribers	Views	Total_videos
0	Two Sigma	4600	155594	20
1	Citadel	10800	1753072	78
2	The D. E. Shaw Group	1550	100520	36
3	Bridgewater Associates	111000	4437710	90
4	AQR Capital Management	978	40724	10

import pandas as pd
import matplotlib.pyplot as plt

# Sort the DataFrame by 'Subscribers' in descending order
combined_hedge_funds_channels_df_subscribers_sorted = combined_hedge_funds_channels_df.sort_values(by='Subscribers', ascending=False)

# Shorten channel names
combined_hedge_funds_channels_df_subscribers_sorted['Channel_name'] = combined_hedge_funds_channels_df_subscribers_sorted['Channel_name'].apply(lambda x: x[:15])

# Plotting Subscribers in descending order
fig, axes = plt.subplots(nrows=3, ncols=1, figsize=(10, 15))

axes[0].bar(combined_hedge_funds_channels_df_subscribers_sorted['Channel_name'], combined_hedge_funds_channels_df_subscribers_sorted['Subscribers'], color='blue')
axes[0].set_title('Subscribers')

# Sort the DataFrame by 'Views' in descending order
combined_hedge_funds_channels_df_views_sorted = combined_hedge_funds_channels_df.sort_values(by='Views', ascending=False)

# Shorten channel names
combined_hedge_funds_channels_df_views_sorted['Channel_name'] = combined_hedge_funds_channels_df_views_sorted['Channel_name'].apply(lambda x: x[:15])

# Plotting Views in descending order
axes[1].bar(combined_hedge_funds_channels_df_views_sorted['Channel_name'],combined_hedge_funds_channels_df_views_sorted['Views'], color='brown')
axes[1].set_title('Views')

# Sort the DataFrame by 'Total_videos' in descending order
combined_hedge_funds_channels_df_total_videos_sorted =combined_hedge_funds_channels_df.sort_values(by='Total_videos', ascending=False)

# Shorten channel names
combined_hedge_funds_channels_df_total_videos_sorted['Channel_name'] = combined_hedge_funds_channels_df_total_videos_sorted['Channel_name'].apply(lambda x: x[:15])

# Plotting Total Videos in descending order
axes[2].bar(combined_hedge_funds_channels_df_total_videos_sorted['Channel_name'], combined_hedge_funds_channels_df_total_videos_sorted['Total_videos'], color='orange')
axes[2].set_title('Total Videos')

# Adjust layout for better visibility
plt.tight_layout()

# Show the plot
plt.show()