MGPraxis6,400 papers identified by name

Can Advanced Portfolio Optimization Beat Equal Weighting? Evidence from Indian Large-Cap Walk-Forward Backtests

Himanshu Dabi, Hitesh Dabi·2026

A 2026 paper by Dabi and Dabi on portfolio optimization in equities: the abstract mentions a Sharpe ratio, an information ratio, excess returns, drawdowns, a benchmark, an out-of-sample test and transaction costs and leaves out multiple testing and the size of the universe.

“The study is motivated by a practical research question: do shrinkage covariance and risk-based portfolio construction methods improve historical risk-adjusted performance relative to a simple equal-weight benchmark in Nifty 50-style portfolios?”

AssetEquitiesindices
StrategyPortfolio optimizationlow-volatility anomaly
GeographyIndia
ClaimSharpe ratioinformation ratio

Also stated: Price and volume, benchmark, out-of-sample test, costs

Missing from abstract: multiple testing, universe

Institutional-grade audit of this strategy.
£5 — Request the audit
  • Audit of the paper claims accounting for costs, luck, crises, originality, geography, etc.
  • Reproduction code integratable into Bloomberg, IBKR, etc.
  • Bias-free datasets for backtesting included
  • Delivered in 2 working days
The paper's neighbourhoodPortfolio optimization by year
■ equities■ multi-asset■ currencies■ volatility and options■ other assets20002005201092015202071214This paper2026■ equities■ multi-asset■ currencies■ volatility and options■ other assets20002005201092015202014This paper2026
The family is counted across the whole universe. Asset, method and authors are counted inside the family.
Similar paperscitationsame methodsame assetsame authors
An Automated Black-Litterman Framework for Global Fixed Income by Carver et al.2026
On the Limits of Low-Frequency OHLCV Signals in Machine Learning-Driven Portfolio Optimization A Cost-Aware, Leak-Free Benchmark on Large-Cap US Equities by Pardo2026
A Two-Stage Decision Support System for Sustainability-Aware Long Short Portfolio Optimization by di Tollo et al.2026
Comparative Evaluation of Modern Deep Learning Methodologies for Portfolio Optimization by Ozechi et al.2026
Machine Learning Enhanced Multi-Factor Quantitative Trading: A Cross-Sectional Portfolio Optimization Approach with Bias Correction by Du2026
Not yet audited by MarketGraphs Praxis. Tags from the abstract. Counts from the universe.
RSS · Contacts