1. Stock Analysis using Hadoop
Framework
Presented by:
Sudhanshu Ranjan
Vaibhav Jain
Santosh Koppada
Sumit Sahay
Madhumita Ghosh

2. AGENDA
• OBJECTIVE
• TECHNICAL ARCHITECTURE
• BASIC STRUCTURE & CODES USED
• FINAL RESULTS
• BUSINESS IMPLICATIONS

3. OBJECTIVE
• To obtain the companies adjusted closed share price after
dividend distribution.
• To review the past trends of dividend payout & formulate
future group strategy.
• Brand establishment
increasing dividends.
across
the
industry
by
paying

4. TECHNICAL ARCHITECTURE
MapReduce
Program
Using Hive
Mapper -1
Table Creation
Reducer -1
Loading Data
Final Output
Inner Join
Final Output

5. BASIC STRUCTURE & CODES USED(Using Hive)
•
FOR REMOVING THE HEADER: ON UNIX
–
•
Tail -n +2 {FILE_NAME_WITH_HEADER} > {FILE_NAME_WITHOUT_HEADER}
CREATING NYSE TABLE: ON HIVE
–
hive> CREATE TABLE NYSE
(exchange STRING, stock_symbol STRING, T_date STRING,
SP_open FLOAT, stock_price_high FLOAT, stock_price_low FLOAT,
stock_price_close FLOAT, stock_volume INT, stock_price_adj_close FLOAT)
ROW FORMAT DELIMITED FIELDS TERMINATED BY ',';
•
LOADING THE DATA INTO NYSE TABLE:
–
hive>Load data local inpath '/home/ec2-user/MS_Praxis/
NYSE_daily_prices_AT_W.csv'
Overwrite into table NYSE;
•
To SELECT ADJUSTED CLOSING PRICE FOR EACH DAY THAT A STOCK REPORTED A DIVIDEND
–
hive> select n.stock_symbol,n.t_date,stock_price_adj_close
FROM nyse n
JOIN
dividend d
ON
n.stock_symbol=d.stock_symbol and n.t_date=d.t_date;

6. BASIC STRUCTURE & CODES USED(Using
MapReduce) : Mapper
Import java and hadoop packages
Public class stockers
{
Public static class stockanalysismapper extends mapreducebase implements mapper
<longwritable, text, text, text>
{
// Declared the mapkey and mapvalue
@Override
Public void map(longwritable key, text value,outputcollector<text, text> output, reporter reporter)
throws ioexception
{
// declaration of given variables
// Used for loop switch case to parse the input lines and store the data
// Check for null values in the key
// Check the header and send the key value to output collector
}
}

7. Contd…Reducer
public static class StockAnalysisReducer extends MapReduceBase
implements Reducer<Text, Text, Text, Text>
{
//Declaration of required variables
@Override
public void reduce(Text key, Iterator<Text> values,OutputCollector<Text, Text> output, Reporter
reporter) throws IOException
{
//Declaration of sum and flag variables
while (values.hasNext())
{
// Parse the inputs which are count, stock adjusted closing price and check
// Store them as required after parsing
//check for null values of stock adjusted closing price
//Increment the sum
}
// write to output if sum is 2 and flag is 0
}
}
}

8. Contd…
• Implementation of MapReduce on Hadoop:
– Copy the data from UNIX directory to HDFS
• hadoop fs -put *.csv eproj/input/
– Run ‘JAR’ code on hadoop
• hadoop jar Hadoop_matching.jar Stockers eproj/input
mproj/output108
– To view the output
• hadoop fs -cat mproj/output108/part-00000

9. RESULT
• We have found the adjusted stock closing prices of
companies on dates when they offered dividends.

10. BUSINESS IMPLICATIONS
• Examining historical adjusted closing price trends as it give
accurate representation of the company equity value beyond
simple market price.
• Basis the findings, it will encourage new investors will invest in
the company.
• It shows that the company is performing efficiently & meeting
shareholder’s expectations.
• Incase, there is no adjustment and the stock’s price is same after
a dividend distribution, then any investor will get free money by
buying the stock the day before the ex-date & later selling the
stock after dividend distribution. Clearly no such arbitrage
situation exists.

11. THANK YOU