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Lakshmi Krishnamurthy edited this page Dec 14, 2024 · 293 revisions

DROP

v6.51 14 December 2024

DROP implements libraries targeting analytics/risk, transaction cost analytics, asset liability analytics, capital, exposure, and margin analytics, valuation adjustment analytics, and portfolio construction analytics within and across fixed income, credit, commodity, equity, FX, and structured products. It also includes auxiliary libraries for graph algorithms, numerical analysis, numerical optimization, spline builder, model validation, statistical learning, and computational support

DROP is composed of three modules.

  • Product Core Module => Fixed Income Product Analytics, Loan Analytics, and Transaction Cost Analytics.
  • Portfolio Core Module => Portfolio Contruction and Asset Liability, along with Exposure, Margin, XVA, and Capital Analytics.
  • Computation Core Module => Algorithm/Computation Support, Function Analysis, Model Validation, Numerical Analysis, Numerical Optimizer, Spline Builder, Graph Algorithms, and Statistical Learning.

Pointers

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Join the chat at https://gitter.im/lakshmiDRIPDROP

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Repo Structure

Module, Library, and Project Layout

Project Home Issues Library Module
alm README Git Asset Liability Analytics Portfolio
analytics README Git Fixed Income Analytics Product
capital README Git Capital Analytics Portfolio
dynamics README Git Fixed Income Analytics Product
execution README Git Transaction Cost Analytics Product
exposure README Git Exposure Analytics Portfolio
feed README Git Computation Support Computational
function README Git Numerical Analysis Computational
graph README Git Numerical Analysis Computational
historical README Git Computation Support Computational
json README Git Computation Support Computational
learning README Git Statistical Learning Computational
loan README Git Loan Analytics Product
market README Git Fixed Income Analytics Product
measure README Git Numerical Analysis Computational
numerical README Git Numerical Analysis Computational
optimization README Git Numerical Optimizer Computational
param README Git Fixed Income Analytics Product
portfolio construction README Git Asset Allocation Analytics Portfolio
pricer README Git Fixed Income Analytics Product
product README Git Fixed Income Analytics Product
regression README Git Computation Support Computational
sequence README Git Statistical Learning Computational
service README Git Computation Support Computational
simm README Git Margin Analytics Portfolio
spaces README Git Statistical Learning Computational
special function README Git Function Analysis Computational
spline README Git Spline Builder Computational
state README Git Fixed Income Analytics Product
template README Git Fixed Income Analytics Product
validation README Git Model Validation Computational
xva README Git XVA Analytics Portfolio

Installation

Installation is as simple as building a jar and dropping into the classpath. There are no other dependencies.

Samples

Java Samples | Excel Samples | Test Data

Documentation

Javadoc API | DROP Specifications | Release Notes | User guide is a work in progress!

Misc

JUnit Tests | Jacoco Coverage | Jacoco Session | Credit Attributions | Version Specifications

Contact

lakshmidrip7977@gmail.com

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DROP Project | Library | Module Layout

Product Core Module

  • Fixed Income Analytics Library => Valuation and Risk Functionality of the Principal Asset Classes, i.e., Equity, Rates, Credit, FX, Commodity, and their Hybrids.
    • Analytics => Date, Cash Flow, and Cash Flow Period Measure Generation Utilities.
    • Dynamics => HJM, Hull-White, LMM, and SABR Dynamic Evolution Models.
    • Market => Static Market Fields - the Definitions, the OTC/Exchange Traded Products, and the Treasury Settings.
    • Param => Core Suite of Parameters - Product Cash Flow, Valuation, Market, Pricing, and Quoting Parameters.
    • Pricer => Custom Pricing Algorithms and the Derivative Fokker Planck Trajectory Generators.
    • Product => Product Components/Baskets for Credit, FRA, FX, Govvie, Rates, and Option Asset Classes.
    • State => Latent State Inference and Creation Utilities.
    • Template => Pricing/Risk Templates for Fixed Income Products.
  • Loan Analytics => Valuation and Risk Functionality for Asset Backed and Mortgage Backed Securities.
    • Loan => Asset Backed Borrower and Loan Level Characteristics.
  • Transaction Cost Analytics => Functionality to estimate single Trade/Portfolio Execution Cost, and corresponding Optimal Trajectories.
    • Execution => Optimal Impact/Capture Based Trading Trajectories - Deterministic, Stochastic, Static, and Dynamic.

Portfolio Core Module

  • Asset Allocation Analytics => Optimal Portfolio Construction and Asset Allocation Functionality.
    • Portfolio Construction => Optimal and Constrained Portfolio Construction Functionality.
  • Asset Liability Analytics => Asset Liability Analytics Functionality.
    • ALM => Asset Liability Analytics Functionality.
  • Capital Analytics => Economic Risk Capital and Basel Operational Capital Analytics.
    • Capital => Basel Market Risk and Operational Capital Analytics.
  • Exposure Analytics => Scenario Exposures at the specified Trade Group Granularity.
    • Exposure => Exposure Group Level Collateralized/Uncollateralized Exposure.
  • Margin Analytics => Initial and Variation Margin Analytics.
    • SIMM => Initial Margin Analytics based on ISDA SIMM and its Variants.
  • XVA Analytics => Valuation Adjustments (Collateral VA/CVA/DVA/FBA/FCA/FVA/MVA/XVA).
    • XVA => Valuation Adjustments that account for Collateral, CC Credit/Debt and Funding Overhead.

Computational Core Module

  • Function Analysis => Special Function and their Analysis.
    • Special Function => Special Function and their Analysis.
  • Graph Algorithm => Graph Representation and Path Traversal.
    • Graph => Graph Representation and Path Traversal.
  • Model Validation Library => Functionality for Statistical Hypotheses Validation and Testing.
    • Validation => Statistical Hypotheses Evidence Processing and Testing.
  • Numerical Analysis => Functionality for Numerical Methods - including Rx Solvers, Linear Algebra, and Statistical Measure Distributions.
    • Function => Implementation and Solvers for a Suite of Rx To R1 Functions.
    • Measure => Continuous and Discrete Measure Distributions and Variate Evolutions.
    • Numerical => Suite of DROP Numerical Analysis Utilities.
  • Numerical Optimizer Library => Functionality for Numerical Optimization - including Constrained and Mixed Integer Non-Linear Optimizers.
    • Optimization => Necessary, Sufficient, and Regularity Checks for Gradient Descent in a Constrained Optimization Setup.
  • Spline Builder Library => Functionality for constructing Spline Based Curves and Surfaces.
    • Spline => Basis Splines and Linear Compounders across a Broad Family of Spline Basis Functions.
  • Statistical Learning Library => Statistical Learning Analyzers and Machine Learning Schemes.
    • Learning => Agnostic Learning Bounds under Empirical Loss Minimization Schemes.
    • Sequence => Bounds Metrics for Random, Custom, and Functional Sequences.
    • Spaces => R1 and Rd Vector/Tensor Spaces (Validated and/or Normed), and Function Classes off of them.
  • Computation Support Library
    • Feed => Functionality to load, transform, and compute target metrics across feeds.
    • Historical => Historical State Processing Utilities.
    • JSON => Implementation of the RFC-4627 Compliant JSON Encoder/Decoder (Parser).
    • Regression => Regression Test Runs for Fixed Income, Numerical Analysis, and Spline Libraries.
    • Service => Environment, Product/Definition Containers, and hosts the Scenario/State Manipulation APIs.
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