Category: Bonds

Beginning VB.NET Quant Developer – Fixed Rate Bond

By Toyin Akin,

Beginning VB.Net Quant Developer – Fixed Rate Bond-750_422

Quant Developer, we look at constructing, pricing and reporting on Fixed Rate Bond securities in VB.NET using opengamma strata.

We, at poc-d, have taken opengamma‘s strata library (which has been developed in java) and extended it for online learning of capital market products for C#, VB.Net, C++, Python, Java and Scala developers as well an Microsoft Excel addin for financial analysts.

The learning is hands on, which means you will be provided a copy of the library to follow along.

 

Course Curriculum

  • Module #1 : Fixed Rate Bond Structure
    • xxx
    • xxx
    • xxx
  • Module #2 : Fixed Rate Bond Pricing
    • xxx
    • xxx
    • xxx
  • Module #3 : Fixed Rate Bond Risks
    • xxx
    • xxx
    • xxx
  • Provided (for hands on)
    • Microsoft Excel Addin which exposes required opengamma strata financial functions within Excel
    • .NET assembly in which to write capital market code against
  • Required
    • Minimum Microsoft Windows 7
    • 4GB of RAM (8GB preferred)
    • Visual Studio 2010 onwards for .NET Development (You can install the free version of Visual studio 2015 community)
    • Optional : Microsoft Excel 2007 onwards

 

Course Access

This course is broken down into modules (as seen in the graphic above).

You can access all the Capital Market courses based on C#, VB.Net, C++, Python, Java, Scala and Microsoft Excel for one low monthly fee. Currently the membership site houses courses that covers Fixed Rate Bonds, Swaps, Inverse Floaters, Swaptions and Cap/Floors.

Or each module can be purchased individually from

 

Fixed Rate Bond Securities

In finance, a fixed rate bond is a type of debt instrument bond with a fixed coupon (interest) rate, as opposed to a floating rate note. A fixed rate bond is a long term debt paper that carries a predetermined interest rate. The interest rate is known as coupon rate and interest is payable at specified dates before bond maturity. The fixed-rate bond, although a conservative investment, is highly susceptible to a loss in value due to inflation. The fixed-rate bond’s long maturity schedule and predetermined coupon rate offers an investor a solidified return, while leaving the individual exposed to a rise in the consumer price index and overall decrease in their purchasing power.

The coupon rate attached to the fixed-rate bond is payable at specified dates before the bond reaches maturity; the coupon rate and the fixed-payments are delivered periodically to the investor at a percentage rate of the bond’s face value. Due to a fixed-rate bond’s lengthy maturity date, these payments are typically small and are not tied into interest rates.

Purchasing a fixed rate bond is knowing, from the very start, what to expect out of the investment. As such, beginners in the investment world, as well as more experienced but conservative ones see this as a good and stable option. Those who are not very well-versed in investments could benefit, because it would no longer becomes necessary to monitor each change in the economy that might have a detrimental effect to the expected return of the bond.

Regardless of how the official Bank interest rate moves over the term of the bond its interest rate stays fixed until the bond expires.

The text below is an edited version taken from the strata web site : http://strata.opengamma.io/introduction/

Introduction to Strata for the Quant Developer

What is Strata?

Strata is the award-winning open source analytics and market risk library from OpenGamma.

Strata allows quant developers to build or enhance existing applications with standardized, off-the-shelf market risk components. It includes:

  • Pricing, financial analytics and curve calibration
  • Reporting
  • Scenario evaluation
  • Trade modelling
  • Market data representation
  • Financial foundations – currencies, indices, holidays, date adjustments, schedules, time-series

Strata has been built from the ground up to be lightweight and flexible. It does not impose any database, server or middleware requirements; these would be built on top of Strata. It provides a high-quality, open source Java toolkit that is designed to be used both in its entirety, as well as for its individual components.

Who is Strata for?

Firms have long employed expensive resources – quants and quant developers – to build and maintain market risk functionality that  offers no real competitive advantage. Where possible, they wish to leverage existing investments in systems and other in-house technologies, while looking externally for just the components required to fill their solution gaps.

Is there an alternative?

One alternative to building in-house is to look towards out-of-the-box offerings provided by financial software vendors. While these vendors offer solutions to industry business issues, the downside is that many firms have been burned by opaque, closed source vendor models, including vendor lock-in to make or support any changes, and “sledgehammer to crack a nut” software footprints.

Solution

Strata delivers the best of both worlds – industry standard market risk functionality, distributed as open source java software to eliminate vendor dependency and return control back to in-house development teams. With open access to standard market risk components and java source code, firms can accelerate the time-to-market of their solutions.

Developers

Strata is aimed at quant or systems developers tasked with delivering analytic solutions into trading, risk, clearing or prime servicing, or collateral businesses. Strata empowers developers with vetted open source java components that deliver standard market risk functionality, allowing them to focus on the unique aspects of solutions delivery to their business stakeholders.

Beginning C# Quant Developer – Fixed Rate Bond

By Toyin Akin,

Beginning C# Quant Developer – Fixed Rate Bond-750_422

Quant Developer, we look at constructing, pricing and reporting on Fixed Rate Bond securities in C# using opengamma strata.

We, at poc-d, have taken opengamma‘s strata library (which has been developed in java) and extended it for online learning of capital market products for C#, VB.Net, C++, Python, Java and Scala developers as well an Microsoft Excel addin for financial analysts.

The learning is hands on, which means you will be provided a copy of the library to follow along.

 

Course Curriculum

  • Module #1 : Fixed Rate Bond Structure
    • xxx
    • xxx
    • xxx
  • Module #2 : Fixed Rate Bond Pricing
    • xxx
    • xxx
    • xxx
  • Module #3 : Fixed Rate Bond Risks
    • xxx
    • xxx
    • xxx
  • Provided (for hands on)
    • Microsoft Excel Addin which exposes required opengamma strata financial functions within Excel
    • .NET assembly in which to write capital market code against
  • Required
    • Minimum Microsoft Windows 7
    • 4GB of RAM (8GB preferred)
    • Visual Studio 2010 onwards for .NET Development (You can install the free version of Visual studio 2015 community)
    • Optional : Microsoft Excel 2007 onwards

 

Course Access

This course is broken down into modules (as seen in the graphic above).

You can access all the Capital Market courses based on C#, VB.Net, C++, Python, Java, Scala and Microsoft Excel for one low monthly fee. Currently the membership site houses courses that covers Fixed Rate Bonds, Swaps, Inverse Floaters, Swaptions and Cap/Floors.

Or each module can be purchased individually from

 

Fixed Rate Bond Securities

In finance, a fixed rate bond is a type of debt instrument bond with a fixed coupon (interest) rate, as opposed to a floating rate note. A fixed rate bond is a long term debt paper that carries a predetermined interest rate. The interest rate is known as coupon rate and interest is payable at specified dates before bond maturity. The fixed-rate bond, although a conservative investment, is highly susceptible to a loss in value due to inflation. The fixed-rate bond’s long maturity schedule and predetermined coupon rate offers an investor a solidified return, while leaving the individual exposed to a rise in the consumer price index and overall decrease in their purchasing power.

The coupon rate attached to the fixed-rate bond is payable at specified dates before the bond reaches maturity; the coupon rate and the fixed-payments are delivered periodically to the investor at a percentage rate of the bond’s face value. Due to a fixed-rate bond’s lengthy maturity date, these payments are typically small and are not tied into interest rates.

Purchasing a fixed rate bond is knowing, from the very start, what to expect out of the investment. As such, beginners in the investment world, as well as more experienced but conservative ones see this as a good and stable option. Those who are not very well-versed in investments could benefit, because it would no longer becomes necessary to monitor each change in the economy that might have a detrimental effect to the expected return of the bond.

Regardless of how the official Bank interest rate moves over the term of the bond its interest rate stays fixed until the bond expires.

The text below is an edited version taken from the strata web site : http://strata.opengamma.io/introduction/

Introduction to Strata for the Quant Developer

What is Strata?

Strata is the award-winning open source analytics and market risk library from OpenGamma.

Strata allows quant developers to build or enhance existing applications with standardized, off-the-shelf market risk components. It includes:

  • Pricing, financial analytics and curve calibration
  • Reporting
  • Scenario evaluation
  • Trade modelling
  • Market data representation
  • Financial foundations – currencies, indices, holidays, date adjustments, schedules, time-series

Strata has been built from the ground up to be lightweight and flexible. It does not impose any database, server or middleware requirements; these would be built on top of Strata. It provides a high-quality, open source Java toolkit that is designed to be used both in its entirety, as well as for its individual components.

Who is Strata for?

Firms have long employed expensive resources – quants and quant developers – to build and maintain market risk functionality that  offers no real competitive advantage. Where possible, they wish to leverage existing investments in systems and other in-house technologies, while looking externally for just the components required to fill their solution gaps.

Is there an alternative?

One alternative to building in-house is to look towards out-of-the-box offerings provided by financial software vendors. While these vendors offer solutions to industry business issues, the downside is that many firms have been burned by opaque, closed source vendor models, including vendor lock-in to make or support any changes, and “sledgehammer to crack a nut” software footprints.

Solution

Strata delivers the best of both worlds – industry standard market risk functionality, distributed as open source java software to eliminate vendor dependency and return control back to in-house development teams. With open access to standard market risk components and java source code, firms can accelerate the time-to-market of their solutions.

Developers

Strata is aimed at quant or systems developers tasked with delivering analytic solutions into trading, risk, clearing or prime servicing, or collateral businesses. Strata empowers developers with vetted open source java components that deliver standard market risk functionality, allowing them to focus on the unique aspects of solutions delivery to their business stakeholders.

Real World Excel Quant Analyst – Bond Risks / Reporting

By Toyin Akin,

Real World Excel Quant Analyst - Bond Risks - Reporting

Note : This course is built on top of the “Real World Spark 2 – Jupyter Python Spark Core – Toyin Akin” course

Jupyter Notebook is a system similar to Mathematica that allows you to create “executable documents”. Notebooks integrate formatted text (Markdown), executable code (Python), mathematical formulas (LaTeX), and graphics and visualizations (matplotlib) into a single document that captures the flow of an exploration and can be exported as a formatted report or an executable script.,

The Jupyter Notebook is a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, machine learning and much more.

Big data integration

Leverage big data tools, such as Apache Spark, from Python

The Jupyter Notebook is based on a set of open standards for interactive computing. Think HTML and CSS for interactive computing on the web. These open standards can be leveraged by third party developers to build customized applications with embedded interactive computing.

Spark Monitoring and Instrumentation

While creating RDDs, performing transformations and executing actions, you will be working heavily within the monitoring view of the Web UI.

Every SparkContext launches a web UI, by default on port 4040, that displays useful information about the application. This includes:

A list of scheduler stages and tasks A summary of RDD sizes and memory usage Environmental information. Information about the running executors

Why Apache Spark …

Apache Spark run programs up to 100x faster than Hadoop MapReduce in memory, or 10x faster on disk. Apache Spark has an advanced DAG execution engine that supports cyclic data flow and in-memory computing. Apache Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python and R shells. Apache Spark can combine SQL, streaming, and complex analytics.

Apache Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application.

Real World Excel Quant Analyst – Bond Pricing

By Toyin Akin,

Real World Excel Quant Analyst - Bond Pricing

Note : This course is built on top of the “Real World Spark 2 – Interactive Python pyspark Core – Toyin Akin” course

Spark’s python shell provides a simple way to learn the API, as well as a powerful tool to analyze data interactively. It is available in Python. Start it by running the following anywhere within a bash terminal within the built Virtual Machine

pyspark

Spark’s primary abstraction is a distributed collection of items called a Resilient Distributed Dataset (RDD). RDDs can be created from collections, Hadoop InputFormats (such as HDFS files) or by transforming other RDDs

Spark Monitoring and Instrumentation

While creating RDDs, performing transformations and executing actions, you will be working heavily within the monitoring view of the Web UI.

Every SparkContext launches a web UI, by default on port 4040, that displays useful information about the application. This includes:

A list of scheduler stages and tasks A summary of RDD sizes and memory usage Environmental information. Information about the running executors

Why Apache Spark …

Apache Spark run programs up to 100x faster than Hadoop MapReduce in memory, or 10x faster on disk. Apache Spark has an advanced DAG execution engine that supports cyclic data flow and in-memory computing. Apache Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python and R shells. Apache Spark can combine SQL, streaming, and complex analytics.

Apache Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application.

Real World Excel Quant Analyst – Bond Product

By Toyin Akin,

Real World Excel Quant Analyst - Bond Product

Note : This course is built on top of the “Real World Spark 2 – Interactive Scala spark-shell Core – Toyin Akin” course

Spark’s shell provides a simple way to learn the API, as well as a powerful tool to analyze data interactively. It is available in Scala (which runs on the Java VM and is thus a good way to use existing Java libraries). Start it by running the following anywhere within a bash terminal within the built Virtual Machine

spark-shell

Spark’s primary abstraction is a distributed collection of items called a Resilient Distributed Dataset (RDD). RDDs can be created from collections, Hadoop InputFormats (such as HDFS files) or by transforming other RDDs

Spark Monitoring and Instrumentation

While creating RDDs, performing transformations and executing actions, you will be working heavily within the monitoring view of the Web UI.

Every SparkContext launches a web UI, by default on port 4040, that displays useful information about the application. This includes:

A list of scheduler stages and tasks A summary of RDD sizes and memory usage Environmental information. Information about the running executors

Why Apache Spark …

Apache Spark run programs up to 100x faster than Hadoop MapReduce in memory, or 10x faster on disk. Apache Spark has an advanced DAG execution engine that supports cyclic data flow and in-memory computing. Apache Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python and R shells. Apache Spark can combine SQL, streaming, and complex analytics.

Apache Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application.