v2.63 1 March 2017
DRIP Asset Allocation is a collection of model libraries for MPT framework, Black Litterman Strategy Incorporator, Holdings Constraint, and Transaction Costs.
DRIP Asset Allocation is composed of the following main model libraries:
- MPT Framework Model Library
- Black Litterman Model Library
- Holdings Constraint Model Library
- Transaction Cost Model Library
For Installation, Documentation and Samples, and the associated supporting Numerical Libraries please check out DRIP.
- Spline Builder Library
- Numerical Optimization Library
- Statistical Learning Library
- Machine Learning Library
- DRIP GitHub Source
- DRIP API Javadoc
- DRIP Release Notes
- DRIP Technical Specifications
- DRIP External Specifications
- User guide is a work in progress!
- Asset Liability Management
- Asset Allocation Core
- Asset Allocation Excel
- Black Litterman Core
- Efficient Frontier MPT
- He Litterman Intuition
- Idzorek User Confidence
- Asset Allocation Core
- Mean-Variance Execution
- Nonlinear Impact Function
- Market Impact Estimator
- Optimal Numerical Execution
- Liquidity VaR Objective
- Principal Agency Execution
- Bayesian Trend Drift Analysis
- HJB Based Adaptive Trajectories
- Adaptive, Static, and Rolling Horizon Trajectories
- MPT Core Mathematical Model
- CAPM Asset Pricing
- Canonical Black-Litterman Reference Model
- Computing the Equilibrium Returns
- Specifying the Views
- View Distribution in the Asset Space
- Specifying Omega
- Omega Proportional to the Variance of the Prior
- Using Confidence Inteval for Omega
- Omega as the Variance of Residuals from a Factor Model
- Using Idzorek's Method for Omega
- The Estimation Model
- Theil's Mixed Estimation Model
- The PDF Based Approach
- Using Bayes' Theorem for the Estimation Model
- The Alternate Reference Model
- The Impact of Tau
- Calibration of Tau
- Black Litterman Model Implementation Steps
- Extensions to the Black Litterman Model
- Analysis of the Unconstrained Optimal Portfolio
- Impact of an Incremental Projection
- Projection Distribution Dependence on Parameters
- Black Litterman Intuition Numerical Examples
- Estimating the Excess Returns Distribution
- Reverse Optimization of Expected Returns
- The Black Litterman Model
- Building the Inputs
- Fine Tuning the Model
- Method for Incorporating User-Specified Confidence Levels
- Implied Confidence Levels
- The Tilt-Based Intuitive Approach
- Black Litterman Surplus Optimizer Inputs
- Cash Flow Projections and Liability Returns
- Defining a Trading Strategy
- Price Dynamics
- Temporary Market Impact
- Capture and Cost of Trading Trajectories
- Linear Impact Functions
- The Efficient Frontier of Optimal Execution
- The Definition of the Frontier
- Explicit Construction of Optimal Strategies
- The Half-Life of a Trade
- Structure of the Frontier
- The Utility Function
- Value-at-Risk
- The Role of Utility in Execution
- Choice of Parameters
- The Value of Information
- Drift
- Gain due to Drift
- Serial Correlation
- Parameter Shifts
- Numerical Optimal Trajectory Generation
- The Model
- Nonlinear Cost Functions
- Objective Functions
- Almgren (2003) Example
- Trading-Enhanced Risk
- Constant-Enhanced Risk
- Linear-Enhanced Risk
- Almgren (2003) Nonlinear Example Sample
- Data Description and Filtering Rules
- Data Model - Variables
- Trajectory Cost Model
- Permanent Impact
- Temporary Impact
- Choice of the Functional Form
- Cross-Sectional Description
- Model Determination
- Determination of the Coefficients
- Residual Analysis
- Efficient Frontier Pricing of Program Trades
- The Efficient Frontier Including Discount
- Performance Measures
- Annualization
- Definition of the Information Ratio
- Applications of the Information Ratio
- Price Motion Using Bayesian Update
- Bayesian Inference
- Trading and Price Impact
- Optimal Trading Strategies
- Trajectory by Calculus of Variations
- Optimality of the Bayesian Adaptive Strategy
- Stochastic Optimal Control Treatment
- Adaptive Strategies - Trading in Practice
- AIM/PIM, and Prospect Theory
- Market Model and Static Trajectories
- Non-dimensionalization
- Small Portfolio Limit
- Portfolio Comparison
- Single Update - Mean and Variance
- Almgren and Lorenz (2007) Results Replication
- Continuous Response - Numerical Results Comparison
- Limitations of Arrival Price Frameworks
- The Liquidation Problem
- The Cost of Trading
- Constant Coefficients
- Coordinated Variation
- Rolling Time Horizon Approximation Strategy
- Small Impact Approximation
- Dynamic Programming - Fully Co-ordinated Version
- Log-Normal Model and Non-dimensionalization
- Constant Market
- Long Time Asymptote
- Dynamic Programming - Custom Volatility and Liquidity
- Log-normal Volatility/Liquidity
- Coordinated Variation of Volatility and Liquidity
- Long/Short Time Asymptotic Behavior
- HJB Based Numerical Solution
- HJB Grid Time Discretization
- HJB Grid Space Discretization
- Almgren (2009, 2012) Solutions Replication
- Width/Skew/Size Estimation Models
- Market Making System SKU
- Market Making Parameter Types
- Intra-day Pricing Curve Generation Schemes
- Mid-Price Models
- Width Models
- Skew Models
- Size Model
- Heuristic Controls
- Flow Analysis
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