Portfolio Optimization
37 papers with code • 0 benchmarks • 0 datasets
Portfolio management is the task of obtaining higher excess returns through the flexible allocation of asset weights. In reality, common examples are stock selection and the Enhanced Index Fund (EIF). The general solution of portfolio management is to score the potential of assets, buy assets with upside potential and increase their weighting, and sell assets that are likely to fall or are relatively weak. A large number of strategies have been proposed for portfolio management.
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Latest papers with no code
Portfolio Optimization under Transaction Costs with Recursive Preferences
The Merton investment-consumption problem is fundamental, both in the field of finance, and in stochastic control.
Beyond Expectations: Learning with Stochastic Dominance Made Practical
Stochastic dominance models risk-averse preferences for decision making with uncertain outcomes, which naturally captures the intrinsic structure of the underlying uncertainty, in contrast to simply resorting to the expectations.
FDR-Controlled Portfolio Optimization for Sparse Financial Index Tracking
In high-dimensional data analysis, such as financial index tracking or biomedical applications, it is crucial to select the few relevant variables while maintaining control over the false discovery rate (FDR).
Large (and Deep) Factor Models
We open up the black box behind Deep Learning for portfolio optimization and prove that a sufficiently wide and arbitrarily deep neural network (DNN) trained to maximize the Sharpe ratio of the Stochastic Discount Factor (SDF) is equivalent to a large factor model (LFM): A linear factor pricing model that uses many non-linear characteristics.
Constrained Max Drawdown: a Fast and Robust Portfolio Optimization Approach
We propose an alternative linearization to the classical Markowitz quadratic portfolio optimization model, based on maximum drawdown.
Optimization of portfolios with cryptocurrencies: Markowitz and GARCH-Copula model approach
The growing interest in cryptocurrencies has drawn the attention of the financial world to this innovative medium of exchange.
Randomized Signature Methods in Optimal Portfolio Selection
We present convincing empirical results on the application of Randomized Signature Methods for non-linear, non-parametric drift estimation for a multi-variate financial market.
Time-inconsistent mean field and n-agent games under relative performance criteria
In this paper we study a time-inconsistent portfolio optimization problem for competitive agents with CARA utilities and non-exponential discounting.
Factor Risk Budgeting and Beyond
From this perspective, one question arises: is it possible to allocate risk at the factor level using the Risk Budgeting approach?
TaskMet: Task-Driven Metric Learning for Model Learning
We propose take the task loss signal one level deeper than the parameters of the model and use it to learn the parameters of the loss function the model is trained on, which can be done by learning a metric in the prediction space.
