This document discusses extracting and using information from XBRL instance documents. It notes that extracting specific pieces of data is straightforward with XBRL, as it was designed for reuse of financial information. However, properly interpreting and validating the extracted data requires understanding concepts, contexts, taxonomies, and XBRL rules. The document provides a basic example using VBA macros to extract a fact value from an XBRL document into an Excel spreadsheet, but cautions that reliably using XBRL data for analysis requires considering many additional complexities.
Mis2013 chapter 12 business intelligence and knowledge managementAndi Iswoyo
The document discusses data warehousing and business intelligence systems. It notes that a large amount of new data is being created daily due to factors like Moore's Law, but much of this data is not useful for analysis due to issues like inconsistencies, missing values, and incorrect formats. Data warehouses address these problems by cleaning, integrating, and reformatting data from various sources into a single database optimized for analysis using business intelligence tools. The cleaned and integrated data stored in a data warehouse is then used for reporting, online analytical processing, and data mining to help organizations make better business decisions.
IRJET- Development and Design of Recommendation System for User Interest Shop...IRJET Journal
This document presents a machine learning based recommendation system for recommending products to users based on their interests. It proposes a technique called Fidoop DP that uses Voronoi diagrams to partition user data across nodes in a Hadoop cluster in order to reduce network overhead. The system tracks users' social media activities to identify brands and products they like. These are used to rank and recommend products to users on a shopping site. It was found to significantly reduce loads on Hadoop cluster nodes. The authors believe this approach could be enhanced further using real machine learning algorithms and big data from actual social media and shopping applications.
During the summer of 2014, I worked with The CloudMiner Ltd., a startup based in Hong Kong that provides cloud based mining solutions for mining and investment professionals. I worked with the VP of Engineering and the development team with data analytics and product development.
This document provides an overview of common ABAP interview questions and answers. It discusses topics such as the ABAP data dictionary, domains and data elements, foreign key relationships, data classes, indexes, transparent vs pooled tables, ABAP/4 queries, BDC programming, internal tables, ITS, DynPros, screen and menu painters, SAP script components, ALV programming, ABAP events, CTS, logical databases, batch input sessions, CATT data uploading, Smart Forms, dependent vs independent data, and the differences between macros and subroutines.
This document introduces DataZoa, a data dissemination platform created by Leading Market Technologies for airports and the airline industry. DataZoa allows users to easily publish and share data, access over 200 million public time series, and keep costs low as it requires no hardware or software purchases. It highlights how DataZoa can help airports achieve missions like collecting and reporting metrics, maximizing usability of data, and staying at the leading edge of technology. Rudy Parker provides contact information to discuss further how DataZoa can deliver value for customers.
Quick Viewer is a report generating tool in SAP that allows users to create simple reports without any ABAP coding knowledge. It generates basic list reports by connecting database tables, selecting fields, and setting filters. The document provides step-by-step instructions on how to use Quick Viewer, including selecting data sources, joining tables, choosing fields, setting filters and sorts, and various output options. It also compares Quick Viewer to SAP Query and discusses converting QuickViews to SAP Queries and transporting QuickViews between systems.
The Financial Management Module incorporates Financial Accounting, Accounts Receivable, Accounts
Payable and Management Reporting.
Salient Features
Integrated General Ledger, Accounts Receivable, Accounts Payable and MIS Reporting. l
Multi Company and Multi Departmental Accounting and consolidation at company level. l
Trial Balance, Balance Sheet, Profit & Loss Account at unit level as well as company level. l
Analysis reports by Department. l
Multi currency system enables maintenance of Accounts in foreign currency. l
Post-Dated Cheques Management. l
User-definable summary and detailed formats for Balance Sheet and Profit & Loss Statements. l
Flexible Chart of Account Coding Structure. l
Balance sheet and Profit & Loss Account
classifications are independent of the Account
Codes. This facilitates the shifting of Balance Sheet
or Profit & Loss account heads from one group to
another, without re-coding the main accounts, and
losing the General Ledger history of that account.
Allows for user defined accounting periods. l
l Generalized transaction entry screens to simplify
data entry procedures.
Option of batch posting of transactions. l
VAT and Sales Tax handling. l
Un-posted statistics. l
l Ledger Interface for Purchase & Sales
transactions.
Ratio Analysis. l
Bank Reconciliation statement
This document discusses extracting and using information from XBRL instance documents. It notes that extracting specific pieces of data is straightforward with XBRL, as it was designed for reuse of financial information. However, properly interpreting and validating the extracted data requires understanding concepts, contexts, taxonomies, and XBRL rules. The document provides a basic example using VBA macros to extract a fact value from an XBRL document into an Excel spreadsheet, but cautions that reliably using XBRL data for analysis requires considering many additional complexities.
Mis2013 chapter 12 business intelligence and knowledge managementAndi Iswoyo
The document discusses data warehousing and business intelligence systems. It notes that a large amount of new data is being created daily due to factors like Moore's Law, but much of this data is not useful for analysis due to issues like inconsistencies, missing values, and incorrect formats. Data warehouses address these problems by cleaning, integrating, and reformatting data from various sources into a single database optimized for analysis using business intelligence tools. The cleaned and integrated data stored in a data warehouse is then used for reporting, online analytical processing, and data mining to help organizations make better business decisions.
IRJET- Development and Design of Recommendation System for User Interest Shop...IRJET Journal
This document presents a machine learning based recommendation system for recommending products to users based on their interests. It proposes a technique called Fidoop DP that uses Voronoi diagrams to partition user data across nodes in a Hadoop cluster in order to reduce network overhead. The system tracks users' social media activities to identify brands and products they like. These are used to rank and recommend products to users on a shopping site. It was found to significantly reduce loads on Hadoop cluster nodes. The authors believe this approach could be enhanced further using real machine learning algorithms and big data from actual social media and shopping applications.
During the summer of 2014, I worked with The CloudMiner Ltd., a startup based in Hong Kong that provides cloud based mining solutions for mining and investment professionals. I worked with the VP of Engineering and the development team with data analytics and product development.
This document provides an overview of common ABAP interview questions and answers. It discusses topics such as the ABAP data dictionary, domains and data elements, foreign key relationships, data classes, indexes, transparent vs pooled tables, ABAP/4 queries, BDC programming, internal tables, ITS, DynPros, screen and menu painters, SAP script components, ALV programming, ABAP events, CTS, logical databases, batch input sessions, CATT data uploading, Smart Forms, dependent vs independent data, and the differences between macros and subroutines.
This document introduces DataZoa, a data dissemination platform created by Leading Market Technologies for airports and the airline industry. DataZoa allows users to easily publish and share data, access over 200 million public time series, and keep costs low as it requires no hardware or software purchases. It highlights how DataZoa can help airports achieve missions like collecting and reporting metrics, maximizing usability of data, and staying at the leading edge of technology. Rudy Parker provides contact information to discuss further how DataZoa can deliver value for customers.
Quick Viewer is a report generating tool in SAP that allows users to create simple reports without any ABAP coding knowledge. It generates basic list reports by connecting database tables, selecting fields, and setting filters. The document provides step-by-step instructions on how to use Quick Viewer, including selecting data sources, joining tables, choosing fields, setting filters and sorts, and various output options. It also compares Quick Viewer to SAP Query and discusses converting QuickViews to SAP Queries and transporting QuickViews between systems.
The Financial Management Module incorporates Financial Accounting, Accounts Receivable, Accounts
Payable and Management Reporting.
Salient Features
Integrated General Ledger, Accounts Receivable, Accounts Payable and MIS Reporting. l
Multi Company and Multi Departmental Accounting and consolidation at company level. l
Trial Balance, Balance Sheet, Profit & Loss Account at unit level as well as company level. l
Analysis reports by Department. l
Multi currency system enables maintenance of Accounts in foreign currency. l
Post-Dated Cheques Management. l
User-definable summary and detailed formats for Balance Sheet and Profit & Loss Statements. l
Flexible Chart of Account Coding Structure. l
Balance sheet and Profit & Loss Account
classifications are independent of the Account
Codes. This facilitates the shifting of Balance Sheet
or Profit & Loss account heads from one group to
another, without re-coding the main accounts, and
losing the General Ledger history of that account.
Allows for user defined accounting periods. l
l Generalized transaction entry screens to simplify
data entry procedures.
Option of batch posting of transactions. l
VAT and Sales Tax handling. l
Un-posted statistics. l
l Ledger Interface for Purchase & Sales
transactions.
Ratio Analysis. l
Bank Reconciliation statement
IRJET- Achieving Data Truthfulness and Privacy Preservation in Data MarketsIRJET Journal
This document discusses achieving data truthfulness and privacy preservation in data markets. It proposes a system called TPDM that aims to ensure data honesty and privacy preservation simultaneously. TPDM allows data contributors to honestly submit their own data without impersonating others, and requires the service provider to honestly collect and process data. It also protects both the personally identifiable information and sensitive data of contributors. The document describes how TPDM could be implemented for profile matching and data distribution services, and evaluates its performance on real-world datasets. Ensuring both data honesty and privacy is challenging but important for the healthy development of data markets.
BUSINESS FINANCE BBUS350Stock Portfolio ProjectObjectiveTh.docxfelicidaddinwoodie
BUSINESS FINANCE BBUS350
Stock Portfolio Project
Objective
The framework for financial decision-making always requires a risk and return tradeoff. The levelof risk that an investor is willing to take on should be rewarded with an acceptable level of
return. Conversely, a required rate of return is accompanied with a certain degree of risk that
limits unreasonable returns. This project seeks to demonstrate that the world of stock investing
exhibits equilibrium pricing and well-defined risk and return tradeoff for all participants.
Goals
Completion of this project should provide participants with an understanding of how equityinvesting is affected by stock selection, therelative risks of each stock choice, and how riskis defined and controlled through portfoliocreations. Upon completion of the project,participants are expected to be familiar withconcepts of rates of return along varioustemporal dimensions, stand-alone risk, portfoliorisk, and where to locate stock performanceinformation leading to a cursory ability to conductequity research.
Solution
A cross section of publicly traded companies isselected by each participant as their research assignment. Individual securities are analyzed fortheir respective historical risk-return tradeoff performance. In Part 2 of this project, analystsare grouped together to construct a well-diversified portfolio of equity securities and are taskedto find an optimal portfolio construction.
Project Outline
The final set of deliverables for this analysis is a multi-page executive summary along with
appendices supporting your assessments as securities analysts. The project consists of finding
financial information on selected equity securities. Information about securities must be gleaned from various University of Washington subscription databases and other free internet sources.
All collected information is analyzed using a business-accepted electronic spreadsheet for ease
of estimation and communication. The results of the analyses are reported, presented, and
discussed.
EQUITY PORTFOLIO ANALYSIS I— INDIVIDUAL
DIRECTIONS
1. Stock selections
Select ten (10) different stocks from the universe of NYSE and NASDAQ stocks. The stocks
selected must meet all of the following criteria:
o Actively traded on either the New York Stock Exchange or NASDAQ
o Continuously active for the past 3 years. (Must have a beta measure)
o A company profile on Mergent Online
o Two (2) stocks must be in the same industry (2-digit SIC code matched)
o Four (4) different industries must be represented among the stocks (2-digit SIC code)
There are numerous stock exchanges in the United States and many more world-wide.
However, for purposes of this project, the analysis is limited to stocks traded on the largest two
domestic equity exchanges.
2.Sources of Information
You must have an active UWNetId account inorder to access certain databases of requiredcompany information. Other information may besourced from various onlin.
BUSINESS FINANCE BBUS350Stock Portfolio ProjectObjectiveTh.docxjasoninnes20
BUSINESS FINANCE BBUS350
Stock Portfolio Project
Objective
The framework for financial decision-making always requires a risk and return tradeoff. The levelof risk that an investor is willing to take on should be rewarded with an acceptable level of
return. Conversely, a required rate of return is accompanied with a certain degree of risk that
limits unreasonable returns. This project seeks to demonstrate that the world of stock investing
exhibits equilibrium pricing and well-defined risk and return tradeoff for all participants.
Goals
Completion of this project should provide participants with an understanding of how equityinvesting is affected by stock selection, therelative risks of each stock choice, and how riskis defined and controlled through portfoliocreations. Upon completion of the project,participants are expected to be familiar withconcepts of rates of return along varioustemporal dimensions, stand-alone risk, portfoliorisk, and where to locate stock performanceinformation leading to a cursory ability to conductequity research.
Solution
A cross section of publicly traded companies isselected by each participant as their research assignment. Individual securities are analyzed fortheir respective historical risk-return tradeoff performance. In Part 2 of this project, analystsare grouped together to construct a well-diversified portfolio of equity securities and are taskedto find an optimal portfolio construction.
Project Outline
The final set of deliverables for this analysis is a multi-page executive summary along with
appendices supporting your assessments as securities analysts. The project consists of finding
financial information on selected equity securities. Information about securities must be gleaned from various University of Washington subscription databases and other free internet sources.
All collected information is analyzed using a business-accepted electronic spreadsheet for ease
of estimation and communication. The results of the analyses are reported, presented, and
discussed.
EQUITY PORTFOLIO ANALYSIS I— INDIVIDUAL
DIRECTIONS
1. Stock selections
Select ten (10) different stocks from the universe of NYSE and NASDAQ stocks. The stocks
selected must meet all of the following criteria:
o Actively traded on either the New York Stock Exchange or NASDAQ
o Continuously active for the past 3 years. (Must have a beta measure)
o A company profile on Mergent Online
o Two (2) stocks must be in the same industry (2-digit SIC code matched)
o Four (4) different industries must be represented among the stocks (2-digit SIC code)
There are numerous stock exchanges in the United States and many more world-wide.
However, for purposes of this project, the analysis is limited to stocks traded on the largest two
domestic equity exchanges.
2.Sources of Information
You must have an active UWNetId account inorder to access certain databases of requiredcompany information. Other information may besourced from various onlin ...
IRJET- Towards Efficient Framework for Semantic Query Search Engine in Large-...IRJET Journal
The document proposes a new framework for efficient semantic search in large datasets. It aims to improve understanding of short texts by enriching them with concepts and related terms from a probabilistic knowledge base. A deep learning model using stacked autoencoders is designed to learn features from the enriched short texts and encode them into binary codes, allowing similarity searches. Experiments show the new approach captures semantics better than existing methods and enables applications like short text retrieval and classification.
AJAY _ Synopsis-1(1).pdf for project report for bcachauhanajay68136
The document outlines a proposed Farming Assistance Web Service that aims to empower farmers through a digital platform. The project would provide farmers comprehensive support including enabling informed decision making, mitigating risks, facilitating financial planning, and optimizing resource usage. Key aspects of the project covered include objectives, data models, data flow diagrams, report generation capabilities, software testing approaches, and the overall scope.
IRJET- Analysis of Boston’s Crime Data using Apache PigIRJET Journal
This document discusses analyzing crime data from Boston using Apache Pig. It begins with an introduction to big data and Apache Pig. Pig is presented as a tool that reduces the complexity of writing MapReduce programs by allowing users to write scripts in Pig Latin, an SQL-like language. The document then outlines the methodology used, which involves collecting Boston crime data, loading it into HDFS, processing it with MapReduce, and analyzing it using Pig. Several example Pig Latin queries are provided that analyze the crime data to find things like the top reporting areas, safest streets, busiest crime hours, and crimes by day of week and offense type. The document concludes by discussing how Pig can help analyze large crime datasets.
The document discusses SAP's Business Warehouse (BW) system. It describes BW's information model, including data sources, info sources, ODS objects, info cubes, info providers, and multi-providers. It also discusses BW's analytical view, multi-tier architecture, extraction and loading processes, and role of storage services. Key challenges for BW include maintaining accurate and up-to-date data across its complex database objects. BW 3.0 introduced new navigation facilities through an OLAP BAPI interface to improve third-party access to info cubes.
The document discusses Hyperion's product suite which includes tools for business intelligence, planning, performance management, and data management. It provides an overview of Essbase, a multidimensional database that allows users to analyze business data from multiple perspectives and levels. Key concepts covered include multidimensional data modeling, OLAP operations for analyzing data (e.g. drill-down, drill-up, slice and dice), and comparing multi-dimensional and relational database approaches.
Tutorial 22 mastering olap reporting drilling through using mdxSubandi Wahyudi
This document discusses using drillthrough functionality in SQL Server Reporting Services to view underlying transaction details from aggregated OLAP data. It begins with an example business scenario where a report user wants to drill into product sales data to see the individual transactions. It then covers preparing the reporting environment, cloning an existing sample report, enabling drillthrough in the OLAP cube, and creating a target report with an MDX DRILLTHROUGH statement to retrieve the transaction details and link it to the primary report for drillthrough functionality. The document provides details on configuring both reports to meet the example requirements.
This document proposes three analytics projects for a client:
1. A retail lending dashboard to provide insights into loan portfolio performance, risks, and opportunities through interactive visualizations.
2. A channel sales analysis to identify preferred sales channels for different customer segments and products in order to introduce new channels or incentives.
3. A cross-sell analysis to determine current and achievable cross-selling ratios, recommend optimal cross-sell sequences, and quantify potential lifetime customer values to increase revenue.
This document discusses using machine learning techniques like supervised learning to predict market trends in finance using both fast and slow structured data from sources like news, social media, prices, and reports. It presents an example project that focuses on predicting closing prices of major country indexes using features like daily changes and moving averages. Several machine learning algorithms like linear models, random forests, and support vector machines are compared using cross validation to evaluate their ability to predict a $100,000 investment in the S&P 500. While the example is an oversimplification, the document notes the challenges of predicting shifting market correlations and avoiding overfitting.
Reporting data in alternate unit of measure in bi 7.0Ashwin Kumar
This document discusses how to report data in alternate units of measure in SAP Business Intelligence 7.0. It covers creating a quantity conversion type using transaction RSUOM, specifying the conversion type in a query definition, and creating a variable for the target unit of measure to provide flexibility in unit selection. When the query is executed, the user will be prompted to select a unit, and results will be displayed in the selected unit due to conversion calculations performed using the conversion factor from the reference InfoObject.
MicroStrategy abstracted the SAP HANA data schema, along with other data warehouses and multi-dimensional sources, into one unified system of record, hiding the underlying complexity from end users.
This document presents a study on finding profitable and preferable itemsets from transactional datasets. It proposes algorithms to find the top-k profitable and popular product itemsets within given utility and support threshold constraints. The paper describes the system structure, which includes modules for preprocessing product and user datasets, identifying frequent itemsets, finding smaller frequent sets, price correlation analysis, and determining the top-k popular products. An example is provided to illustrate the frequent itemset mining process. An experimental comparative study on real and synthetic datasets demonstrates the effectiveness and efficiency of the proposed algorithms.
INTELLIGENT ALGORYTHM FOR IMMEDIATE FINANCIAL STRATEGY FOR SMESijscai
This document summarizes an intelligent algorithm developed to predict financial risk for small and medium enterprises (SMEs). The algorithm uses a support vector machine (SVM) model trained on SME financial data to predict the risk of credit default. A RapidMiner workflow was created to automatically load data, train the SVM model, optimize model parameters, apply the model to predict risks, and analyze results. The SVM model analyzed financial attributes of SMEs and predicted risks with 95.64% accuracy based on the confusion matrix and ROC curve results. The workflow provides a methodology for using machine learning to analyze SME financial data and predict risks to help inform immediate financial strategies.
In this work is discussed a scientific methodology concerning an intelligent algorithm oriented on financial
strategy for SMEs. The paper follows the research guidelines of ‘Frascati’ manual about knowledge gain
by innovative algorithms. Specifically has been applied a Support Vector Machine (SVM) algorithms
predicting financial score of Small and Medium Enterprises –SMEs-. For the output results has been
executed a Rapid Miner workflow. The used approach represents a methodology to follow in order to
improve a research project about financial technologies
INTELLIGENT ALGORYTHM FOR IMMEDIATE FINANCIAL STRATEGY FOR SMESijscai
In this work is discussed a scientific methodology concerning an intelligent algorithm oriented on financial
strategy for SMEs. The paper follows the research guidelines of ‘Frascati’ manual about knowledge gain
by innovative algorithms. Specifically has been applied a Support Vector Machine (SVM) algorithms
predicting financial score of Small and Medium Enterprises –SMEs-. For the output results has been
executed a Rapid Miner workflow. The used approach represents a methodology to follow in order to
improve a research project about financial technologies.
Kumaravel Sugumar has over 1.7 years of experience as an SAP ABAP technical consultant. He has worked on projects for clients like Onninen and MaheshValue Group, developing reports, forms, conversions between legacy and SAP systems, and notification programs. He is proficient in ABAP, SQL, and various SAP modules like SD, MM, and FICO. Kumaravel holds an M.E. in VLSI Design and a B.E. in Electronics and Communication.
Zephyr is developing a web-based financial analysis platform called Zephyrnet that will aggregate real-time global financial data and analytical tools into a customizable interface. Zephyrnet will target retail and professional investors by offering the platform through a monthly subscription that is significantly cheaper than competitors' offerings. The platform will leverage XBRL data standards and partnerships with data providers to provide users comprehensive fundamental analysis capabilities.
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
IRJET- Achieving Data Truthfulness and Privacy Preservation in Data MarketsIRJET Journal
This document discusses achieving data truthfulness and privacy preservation in data markets. It proposes a system called TPDM that aims to ensure data honesty and privacy preservation simultaneously. TPDM allows data contributors to honestly submit their own data without impersonating others, and requires the service provider to honestly collect and process data. It also protects both the personally identifiable information and sensitive data of contributors. The document describes how TPDM could be implemented for profile matching and data distribution services, and evaluates its performance on real-world datasets. Ensuring both data honesty and privacy is challenging but important for the healthy development of data markets.
BUSINESS FINANCE BBUS350Stock Portfolio ProjectObjectiveTh.docxfelicidaddinwoodie
BUSINESS FINANCE BBUS350
Stock Portfolio Project
Objective
The framework for financial decision-making always requires a risk and return tradeoff. The levelof risk that an investor is willing to take on should be rewarded with an acceptable level of
return. Conversely, a required rate of return is accompanied with a certain degree of risk that
limits unreasonable returns. This project seeks to demonstrate that the world of stock investing
exhibits equilibrium pricing and well-defined risk and return tradeoff for all participants.
Goals
Completion of this project should provide participants with an understanding of how equityinvesting is affected by stock selection, therelative risks of each stock choice, and how riskis defined and controlled through portfoliocreations. Upon completion of the project,participants are expected to be familiar withconcepts of rates of return along varioustemporal dimensions, stand-alone risk, portfoliorisk, and where to locate stock performanceinformation leading to a cursory ability to conductequity research.
Solution
A cross section of publicly traded companies isselected by each participant as their research assignment. Individual securities are analyzed fortheir respective historical risk-return tradeoff performance. In Part 2 of this project, analystsare grouped together to construct a well-diversified portfolio of equity securities and are taskedto find an optimal portfolio construction.
Project Outline
The final set of deliverables for this analysis is a multi-page executive summary along with
appendices supporting your assessments as securities analysts. The project consists of finding
financial information on selected equity securities. Information about securities must be gleaned from various University of Washington subscription databases and other free internet sources.
All collected information is analyzed using a business-accepted electronic spreadsheet for ease
of estimation and communication. The results of the analyses are reported, presented, and
discussed.
EQUITY PORTFOLIO ANALYSIS I— INDIVIDUAL
DIRECTIONS
1. Stock selections
Select ten (10) different stocks from the universe of NYSE and NASDAQ stocks. The stocks
selected must meet all of the following criteria:
o Actively traded on either the New York Stock Exchange or NASDAQ
o Continuously active for the past 3 years. (Must have a beta measure)
o A company profile on Mergent Online
o Two (2) stocks must be in the same industry (2-digit SIC code matched)
o Four (4) different industries must be represented among the stocks (2-digit SIC code)
There are numerous stock exchanges in the United States and many more world-wide.
However, for purposes of this project, the analysis is limited to stocks traded on the largest two
domestic equity exchanges.
2.Sources of Information
You must have an active UWNetId account inorder to access certain databases of requiredcompany information. Other information may besourced from various onlin.
BUSINESS FINANCE BBUS350Stock Portfolio ProjectObjectiveTh.docxjasoninnes20
BUSINESS FINANCE BBUS350
Stock Portfolio Project
Objective
The framework for financial decision-making always requires a risk and return tradeoff. The levelof risk that an investor is willing to take on should be rewarded with an acceptable level of
return. Conversely, a required rate of return is accompanied with a certain degree of risk that
limits unreasonable returns. This project seeks to demonstrate that the world of stock investing
exhibits equilibrium pricing and well-defined risk and return tradeoff for all participants.
Goals
Completion of this project should provide participants with an understanding of how equityinvesting is affected by stock selection, therelative risks of each stock choice, and how riskis defined and controlled through portfoliocreations. Upon completion of the project,participants are expected to be familiar withconcepts of rates of return along varioustemporal dimensions, stand-alone risk, portfoliorisk, and where to locate stock performanceinformation leading to a cursory ability to conductequity research.
Solution
A cross section of publicly traded companies isselected by each participant as their research assignment. Individual securities are analyzed fortheir respective historical risk-return tradeoff performance. In Part 2 of this project, analystsare grouped together to construct a well-diversified portfolio of equity securities and are taskedto find an optimal portfolio construction.
Project Outline
The final set of deliverables for this analysis is a multi-page executive summary along with
appendices supporting your assessments as securities analysts. The project consists of finding
financial information on selected equity securities. Information about securities must be gleaned from various University of Washington subscription databases and other free internet sources.
All collected information is analyzed using a business-accepted electronic spreadsheet for ease
of estimation and communication. The results of the analyses are reported, presented, and
discussed.
EQUITY PORTFOLIO ANALYSIS I— INDIVIDUAL
DIRECTIONS
1. Stock selections
Select ten (10) different stocks from the universe of NYSE and NASDAQ stocks. The stocks
selected must meet all of the following criteria:
o Actively traded on either the New York Stock Exchange or NASDAQ
o Continuously active for the past 3 years. (Must have a beta measure)
o A company profile on Mergent Online
o Two (2) stocks must be in the same industry (2-digit SIC code matched)
o Four (4) different industries must be represented among the stocks (2-digit SIC code)
There are numerous stock exchanges in the United States and many more world-wide.
However, for purposes of this project, the analysis is limited to stocks traded on the largest two
domestic equity exchanges.
2.Sources of Information
You must have an active UWNetId account inorder to access certain databases of requiredcompany information. Other information may besourced from various onlin ...
IRJET- Towards Efficient Framework for Semantic Query Search Engine in Large-...IRJET Journal
The document proposes a new framework for efficient semantic search in large datasets. It aims to improve understanding of short texts by enriching them with concepts and related terms from a probabilistic knowledge base. A deep learning model using stacked autoencoders is designed to learn features from the enriched short texts and encode them into binary codes, allowing similarity searches. Experiments show the new approach captures semantics better than existing methods and enables applications like short text retrieval and classification.
AJAY _ Synopsis-1(1).pdf for project report for bcachauhanajay68136
The document outlines a proposed Farming Assistance Web Service that aims to empower farmers through a digital platform. The project would provide farmers comprehensive support including enabling informed decision making, mitigating risks, facilitating financial planning, and optimizing resource usage. Key aspects of the project covered include objectives, data models, data flow diagrams, report generation capabilities, software testing approaches, and the overall scope.
IRJET- Analysis of Boston’s Crime Data using Apache PigIRJET Journal
This document discusses analyzing crime data from Boston using Apache Pig. It begins with an introduction to big data and Apache Pig. Pig is presented as a tool that reduces the complexity of writing MapReduce programs by allowing users to write scripts in Pig Latin, an SQL-like language. The document then outlines the methodology used, which involves collecting Boston crime data, loading it into HDFS, processing it with MapReduce, and analyzing it using Pig. Several example Pig Latin queries are provided that analyze the crime data to find things like the top reporting areas, safest streets, busiest crime hours, and crimes by day of week and offense type. The document concludes by discussing how Pig can help analyze large crime datasets.
The document discusses SAP's Business Warehouse (BW) system. It describes BW's information model, including data sources, info sources, ODS objects, info cubes, info providers, and multi-providers. It also discusses BW's analytical view, multi-tier architecture, extraction and loading processes, and role of storage services. Key challenges for BW include maintaining accurate and up-to-date data across its complex database objects. BW 3.0 introduced new navigation facilities through an OLAP BAPI interface to improve third-party access to info cubes.
The document discusses Hyperion's product suite which includes tools for business intelligence, planning, performance management, and data management. It provides an overview of Essbase, a multidimensional database that allows users to analyze business data from multiple perspectives and levels. Key concepts covered include multidimensional data modeling, OLAP operations for analyzing data (e.g. drill-down, drill-up, slice and dice), and comparing multi-dimensional and relational database approaches.
Tutorial 22 mastering olap reporting drilling through using mdxSubandi Wahyudi
This document discusses using drillthrough functionality in SQL Server Reporting Services to view underlying transaction details from aggregated OLAP data. It begins with an example business scenario where a report user wants to drill into product sales data to see the individual transactions. It then covers preparing the reporting environment, cloning an existing sample report, enabling drillthrough in the OLAP cube, and creating a target report with an MDX DRILLTHROUGH statement to retrieve the transaction details and link it to the primary report for drillthrough functionality. The document provides details on configuring both reports to meet the example requirements.
This document proposes three analytics projects for a client:
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2. A channel sales analysis to identify preferred sales channels for different customer segments and products in order to introduce new channels or incentives.
3. A cross-sell analysis to determine current and achievable cross-selling ratios, recommend optimal cross-sell sequences, and quantify potential lifetime customer values to increase revenue.
This document discusses using machine learning techniques like supervised learning to predict market trends in finance using both fast and slow structured data from sources like news, social media, prices, and reports. It presents an example project that focuses on predicting closing prices of major country indexes using features like daily changes and moving averages. Several machine learning algorithms like linear models, random forests, and support vector machines are compared using cross validation to evaluate their ability to predict a $100,000 investment in the S&P 500. While the example is an oversimplification, the document notes the challenges of predicting shifting market correlations and avoiding overfitting.
Reporting data in alternate unit of measure in bi 7.0Ashwin Kumar
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MicroStrategy abstracted the SAP HANA data schema, along with other data warehouses and multi-dimensional sources, into one unified system of record, hiding the underlying complexity from end users.
This document presents a study on finding profitable and preferable itemsets from transactional datasets. It proposes algorithms to find the top-k profitable and popular product itemsets within given utility and support threshold constraints. The paper describes the system structure, which includes modules for preprocessing product and user datasets, identifying frequent itemsets, finding smaller frequent sets, price correlation analysis, and determining the top-k popular products. An example is provided to illustrate the frequent itemset mining process. An experimental comparative study on real and synthetic datasets demonstrates the effectiveness and efficiency of the proposed algorithms.
INTELLIGENT ALGORYTHM FOR IMMEDIATE FINANCIAL STRATEGY FOR SMESijscai
This document summarizes an intelligent algorithm developed to predict financial risk for small and medium enterprises (SMEs). The algorithm uses a support vector machine (SVM) model trained on SME financial data to predict the risk of credit default. A RapidMiner workflow was created to automatically load data, train the SVM model, optimize model parameters, apply the model to predict risks, and analyze results. The SVM model analyzed financial attributes of SMEs and predicted risks with 95.64% accuracy based on the confusion matrix and ROC curve results. The workflow provides a methodology for using machine learning to analyze SME financial data and predict risks to help inform immediate financial strategies.
In this work is discussed a scientific methodology concerning an intelligent algorithm oriented on financial
strategy for SMEs. The paper follows the research guidelines of ‘Frascati’ manual about knowledge gain
by innovative algorithms. Specifically has been applied a Support Vector Machine (SVM) algorithms
predicting financial score of Small and Medium Enterprises –SMEs-. For the output results has been
executed a Rapid Miner workflow. The used approach represents a methodology to follow in order to
improve a research project about financial technologies
INTELLIGENT ALGORYTHM FOR IMMEDIATE FINANCIAL STRATEGY FOR SMESijscai
In this work is discussed a scientific methodology concerning an intelligent algorithm oriented on financial
strategy for SMEs. The paper follows the research guidelines of ‘Frascati’ manual about knowledge gain
by innovative algorithms. Specifically has been applied a Support Vector Machine (SVM) algorithms
predicting financial score of Small and Medium Enterprises –SMEs-. For the output results has been
executed a Rapid Miner workflow. The used approach represents a methodology to follow in order to
improve a research project about financial technologies.
Kumaravel Sugumar has over 1.7 years of experience as an SAP ABAP technical consultant. He has worked on projects for clients like Onninen and MaheshValue Group, developing reports, forms, conversions between legacy and SAP systems, and notification programs. He is proficient in ABAP, SQL, and various SAP modules like SD, MM, and FICO. Kumaravel holds an M.E. in VLSI Design and a B.E. in Electronics and Communication.
Zephyr is developing a web-based financial analysis platform called Zephyrnet that will aggregate real-time global financial data and analytical tools into a customizable interface. Zephyrnet will target retail and professional investors by offering the platform through a monthly subscription that is significantly cheaper than competitors' offerings. The platform will leverage XBRL data standards and partnerships with data providers to provide users comprehensive fundamental analysis capabilities.
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
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significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
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Gender and Mental Health - Counselling and Family Therapy Applications and In...PsychoTech Services
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A wound is a break in the integrity of the skin or tissues, which may be associated with disruption of the structure and function.
Healing is the body’s response to injury in an attempt to restore normal structure and functions.
Healing can occur in two ways: Regeneration and Repair
There are 4 phases of wound healing: hemostasis, inflammation, proliferation, and remodeling. This document also describes the mechanism of wound healing. Factors that affect healing include infection, uncontrolled diabetes, poor nutrition, age, anemia, the presence of foreign bodies, etc.
Complications of wound healing like infection, hyperpigmentation of scar, contractures, and keloid formation.
How to Make a Field Mandatory in Odoo 17Celine George
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Temple of Asclepius in Thrace. Excavation resultsKrassimira Luka
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বাংলাদেশের অর্থনৈতিক সমীক্ষা ২০২৪ [Bangladesh Economic Review 2024 Bangla.pdf] কম্পিউটার , ট্যাব ও স্মার্ট ফোন ভার্সন সহ সম্পূর্ণ বাংলা ই-বুক বা pdf বই " সুচিপত্র ...বুকমার্ক মেনু 🔖 ও হাইপার লিংক মেনু 📝👆 যুক্ত ..
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Chapter wise All Notes of First year Basic Civil Engineering.pptxDenish Jangid
Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
1. 1
SUBMITTED TO:-
PROF. S.K BABOO
BI REPORT ANALYSIS
SUBMITTED BY:-
NAME: NIBEDITA SINGH
ROLL NO. : 16DM044
2. 2
PIVOT TABLE
A pivot table is a program tool that allows you to reorganize and summarize
selected columns and rows of data in a spreadsheetor database table to obtain a
desired report.
REPORT-1
Objective- To know the total value of loans of different categories given by
different banks.
The database selected here is “Bank Data”.
Different categories of loan are agricultural, car, educational, home and personal
loan. Personalloan has the maximum loan values as compared to other categories
of loan.
3. 3
REPORT-2
Objective- Objectiveis to know the share of different banks in different categories
of loan as percentage of grand total.
From the above report we can conclude that the share of CUB bank is maximum
for the loans given out of the total loans provided by all the banks.
SSRS(SQL SERVER REPORTING SERVICE)
CHART-
chart data regions to help readers of your Reporting Services paginated reports
understand large volumes of aggregated data at a glance.
REPORT-3
Objective- The database taken here is “Online data”. The objective is to find out
total Pname, rname and units by using column chart.
5. 5
SELECT dtransaction.units,dnregion.rname,dnproduct.pname
FROM dnproductINNERJOIN
dtransactionON dnproduct.pkey=dtransaction.PKEYINNERJOIN
dnregionON dtransaction.RKEY=dnregion.rkey
DRILL DOWN REPORT- Drilldown reports initially hide complexity and enable the
user to toggle conditionally hidden report items to control how much detail data
they want to see. Drilldown reports must retrieve all possible data that can be
shown in the report.
REPORT-4
Objective- The database taken here is “Online data”. The objective is to find out
total pay no total sales made according to respective CNO.
The database selected here is “Online Data”.
6. 6
SELECT SALES,RNO,CNO,PAYNO
FROM ORDERS1
INTERACTIVEREPORTING-Interactivesortprovides ability to allow the user to sort
the data in thereportbasedon their requirement in ascendingordescending order.
REPORT-5
Objective- To know the least last price and the highest Opening price of different
mutual fund products provided by mutual fund companies.
The database selected here is “Data Analysis”.
8. 8
(Sorting of o price in Descending order)
Looking at the report we can say that “Tata Pure Equity Fund” has the highest
Oprice (opening price)
CASCADING REPORT
Cascading parameters provide a way of managing large amounts of report data.
With cascading parameters, the list of values for one parameter depends on the
value chosen in preceding parameter.
REPORT-6
Objective- To know the total sales by taking into consideration CNO and RNO.
The database selected here is “Online Data”.
1. SELECT CNO,RNO,SALES
FROM ORDERS1
WHERE (CNOIN (@CNO))
AND(RNOIN (@RNO))
10. 10
PARAMATERIZED REPORT
A parameterized report uses input values to complete report or data processing. With
a parameterized report, you can vary the output of a report based on values that are
set when the report runs.
REPORT-7
Objective- To know the lprice (Last price) according to the product key specified
15. 15
DATASET-2
STEP-1
REPORT-8
SSAS
It manages multidimensional cubes of data and provides access to heaps of
information including aggregationof data. Onecan createdata mining modelsfrom
data sources and use it for Business Intelligence also including reporting features.
The database used here is “Bank Data”.
Objective-
To know the total interest and total amount of transactions for different
types of loan for the given banks
16. 16
To know the bank namewhich is collecting moreinterest on total amount of
loans that it has given.
17. 17
Thus,we can knowwith the help of the abovereportthat “CUB” bank hascollected
moreinterest on thetotal loan amountas comparedto others.Interestcomponent
of this bank is around 28% of the total amount of its loan transactions.
REPORT-9
Objective- The objective of the report is to know the region wise total units sold
with respective product name.
The database selected here is “New data analysis”.