Quantitative Asset Management
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computer code for Quantitative asset management by michael robbins

email info@quantitativeassetmanagement.com for passwords

under construction

FEATURED COMPUTER CODE

BACKTESTING TAX-LOSS HARVESTING STRATEGIES ANALYZING TRANSACTION DATA FROM 101 OF THE LARGEST ROBOADVISORS (300MB) QUANTAMENTAL GLOBAL TACTICAL ASSET ALLOCATION (1GB) HIGH-FREQUENCY TRANSACTION COST PREDICTION AND ANALYSIS (100GB) OPPORTUNISTIC REBALANCING
Excerpt from the book Missing and Minority Data. Most financial time series have a great deal of uninteresting data, such as small price changes, and little important data, such as large rallies and routs. As rare as this minority data is, the rarest and most valuable data are the minority data that look like majority data—the small price movements that warn of large ones to come. Oversampling, undersampling, and combinations of both are common ways to manage imbalanced data. Oversampling may include random oversampling, SVM, Synthetic Minority Oversampling Technique (SMOTE), “borderline” methods that use only misclassified minority data, and Adaptive Synthetic Sampling (ADASYN), which uses a density metric.

chapter 1: introduction chapter 2: choosing your product chapter 3: the investment process chapter 4: leadership and governance

CHAPTER 5: Financial data

case study: managing low-frequency and archival (point-in-time) data
case study: managing multi-asset transaction data from 101 of the largest roboadvisors
Case study: managing 100gb of high frequency equity transaction data
case study: gibbs sampler

chapter 7: features

case study: missing and minority data (borderline Smote)
case study: synthetic data generation (time-GANN)

chapter 13: execution models

chapter 16: backtesting

on-line backtesting (event driven)
  latest backtesting code (live matlab script)
transaction cost analysis
tax-loss harvesting
case study: performance of the largest 101 roboadvisors

Heading

Case Study: Vector Error Correcting (VEC) Vs Dynamic Stochastic General Equilibrium Model (DSGE)
Case STUDY: Fee engineering
case study: gates, lockups, and settlement periods
case study: contagion
case study: economic surprise
case study: quantemental gtaa
case study: ESG TAA
case study: south african taa
case study: lazy (opportunistic) rebalancing

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