StockYard - Revision history

Pat at 01:29, 28 February 2017

2017-02-28T01:29:35Z

Pat at 01:28, 28 February 2017

2017-02-28T01:28:44Z

Pat at 00:15, 13 February 2017

2017-02-13T00:15:08Z

Pat at 00:04, 13 February 2017

2017-02-13T00:04:59Z

Pat at 23:37, 12 February 2017

2017-02-12T23:37:49Z

Pat at 23:16, 12 February 2017

2017-02-12T23:16:34Z

Pat at 00:24, 3 February 2017

2017-02-03T00:24:19Z

Pat at 00:21, 3 February 2017

2017-02-03T00:21:48Z

Pat at 00:17, 3 February 2017

2017-02-03T00:17:01Z

Wangjlgz at 17:53, 1 February 2017

2017-02-01T17:53:37Z

@@ Line 21: / Line 21: @@
     pip install pyhamcrest
-If starting from scratch one of the simplest install methods is to install Anaconda2 which installs python 2.7 and most of the packages with their dependencies.  Then from the Anaconda prompt install seaborn and bintrees as above.
+If starting from scratch one of the simplest install methods is to install Anaconda2 which installs python 2.7 and most of the packages with their dependencies.  Then from the Anaconda prompt install seaborn, bintrees and pyhamcrest as above.
 Also, the repository contains a file requirements.txt that list the various packages required and the entire group can be installed with the following command:

@@ Line 19: / Line 19: @@
     pip install seaborn
     pip install bintrees
 If starting from scratch one of the simplest install methods is to install Anaconda2 which installs python 2.7 and most of the packages with their dependencies.  Then from the Anaconda prompt install seaborn and bintrees as above.

@@ Line 33: / Line 33: @@
 * The trading logic should be present in the "strat" method of <user_name>_agent.py
-Step 2: Add user agent based object in config4.py
+Step 2: Add user agent based object using config4_new.py as an example.
-* Import the agent
+* Import the agent. For example:
-* Create object and add it to the list of agents
+  import traders.vgeorge6.vgeorge6_agent as vg
 Step3 : Run stockyard.py with a command line argument specifying the desired config file

@@ Line 37: / Line 37: @@
 * Create object and add it to the list of agents
-Step3 : Run bootstrap.py
+Step3 : Run stockyard.py with a command line argument specifying the desired config file
-The program executes by running the Bootstrap file.<br>
+The program executes by running the stockyard file.<br>
 Go to the directory where the repository is present and type in the following command.
-   python bootstrap.py
+   python stockyard.py config4_new
 <h2>Sample Output</h2>
 The following is a sample output shown in the terminal:

@@ Line 42: / Line 42: @@
    python bootstrap.py
 <h2>Sample Output</h2>
-The following is a sample output shown in the terminal
+The following is a sample output shown in the terminal:
-  ----------
-  Id: 1
+ ********************
-  Name: NASDAQ
+ Stock Yard
-  Type: exchange
+ Version 0.0.1
-  ----------
+ ********************
-  Id: 1
-  Name: Agent 1
+ Simulation Started:
-  Exchange: NASDAQ
+ Start Date: 2008-03-08
-  Type: trader
+ End Date:  2008-03-08
-  ----------
+ number of days 1
-  Id: 2
+ Excahnge 0 Start of Simulation received
-  Name: Agent 2
+ Agent 99 Start of Simulation received
-  Exchange: NASDAQ
-  Type: trader
+  Exchange Recieved: Start of Day 1
-  ----------
+  Agent 99 Start message for Day 1
-  Kernel Runner started
+ Exchange Open
-  time stamp: 0, awakening all messages
+  Simulation Completed
-  Agent Agent 1 Started, Time Stamp: 0
+ Total time for simulation run = 1 seconds and 718000 micro seconds
-  Agent Agent 2 Started, Time Stamp: 0
-  ----------
+ Process finished with exit code 0
   <h1>How to Configure</h1>

@@ Line 16: / Line 16: @@
 Alternatively, the repository can be downloaded as a zip file and unzipped in a convenient location.
-  several support packages are required beyond the ML4T virtual machine:
+  several support packages are required beyond the ML4T virtual machine if using the  ML4T VM is convenient:
     pip install seaborn
     pip install bintrees
 If starting from scratch one of the simplest install methods is to install Anaconda2 which installs python 2.7 and most of the packages with their dependencies.  Then from the Anaconda prompt install seaborn and bintrees as above.
 <h1>How to Run</h1>

@@ Line 14: / Line 14: @@
 To download the repository type in the following command.<br>
   git clone https://github.gatech.edu/tb34/qsrgsim/
   several support packages are required beyond the ML4T virtual machine:

@@ Line 61: / Line 61: @@
    Agent: Agent 1
    Time Stamp: 3
-   Ping Excahnge and wake up again in 6 minutes
+   Ping Exchange and wake up again in 6 minutes
-   Exchange Recieved Ping Message from agent|  Time Stamp: 3
+   Exchange Received Ping Message from agent|  Time Stamp: 3
-   Agent Recieved Ping Message from exchange Time Stamp: 3
+   Agent Received Ping Message from exchange Time Stamp: 3
    ----------
    Agent: Agent 2
    Time Stamp: 5
-   Ping Excahnge and wake up again in 10 minutes
+   Ping Exchange and wake up again in 10 minutes
-   Exchange Recieved Ping Message from agent|  Time Stamp: 5
+   Exchange Received Ping Message from agent|  Time Stamp: 5
-   Agent Recieved Ping Message from exchange Time Stamp: 5
+   Agent Received Ping Message from exchange Time Stamp: 5
    ----------
    Agent: Agent 1
    Time Stamp: 6
-   Ping Excahnge and wake up again in 9 minutes
+   Ping Exchange and wake up again in 9 minutes
-   Exchange Recieved Ping Message from agent|  Time Stamp: 6
+   Exchange Received Ping Message from agent|  Time Stamp: 6
-   Agent Recieved Ping Message from exchange Time Stamp: 6
+   Agent Received Ping Message from exchange Time Stamp: 6
    ----------
    .......
@@ Line 81: / Line 81: @@
    Agent: Agent 1
    Time Stamp: 21
-   Ping Excahnge and wake up again in 24 minutes
+   Ping Exchange and wake up again in 24 minutes
-   Exchange Recieved Ping Message from agent|  Time Stamp: 21
+   Exchange Received Ping Message from agent|  Time Stamp: 21
-   Agent Recieved Ping Message from exchange Time Stamp: 21
+   Agent Received Ping Message from exchange Time Stamp: 21
    ----------
    Agent: Agent 1
    Time Stamp: 24
-   Ping Excahnge and wake up again in 27 minutes
+   Ping Exchange and wake up again in 27 minutes
-   Exchange Recieved Ping Message from agent|  Time Stamp: 24
+   Exchange Received Ping Message from agent|  Time Stamp: 24
-   Agent Recieved Ping Message from exchange Time Stamp: 24
+   Agent Received Ping Message from exchange Time Stamp: 24
   <h1>How to Configure</h1>
@@ Line 95: / Line 95: @@
 We would be moving it to a properties file(csv/text format) from which the various key-value parameters can be read
 <h2>Configuration Example</h2>
-   Entern Exchange Name: NASDAQ
+   Enter Exchange Name: NASDAQ
    Enter Duration of run: 24
    Enter Number of Trading Agents: 2

@@ Line 3: / Line 3: @@
 <br>
 <h1>Introduction</h1>
-The main idea behind the Market Simulator is to  build a virtual environment where various trading strategies can be tested.
+StockYard is a market simulator. The main idea behind the it is to  build a virtual environment where various trading strategies can be tested.
 The system is implemented using a discrete event simulator and also uses the concept of time wraps.
 The system would mainly consist of multiple agents having different trading strategies incorporated in them and would compete against each other in the stock exchange.