Robust portfolio optimization considers uncertainty in market probabilities.
problem Uncertainty in market probabilities in multiperiod portfolio selection.
method Robust mean-variance optimization using Wasserstein ball centered at empirical data.
result Numerical simulations show improved performance compared to other strategies.
Proposes a new framework to optimize portfolios with reduced estimation errors.
problem Estimation errors in multiperiod mean-variance portfolio optimization.
method Reference-regulated multiperiod mean-variance (RRMV) framework.
result Improves portfolio stability and out-of-sample Sharpe ratios.
We provide easily verifiable conditions for the well-posedness of the optimal investment problem for a behavioral investor in an incomplete discrete-time multiperiod financial market model, for the first time in the literature. Under two different sets of assumptions we also establish the existence of optimal strategie…
Optimal transport with scalar martingales defined over multiple periods.
problem Finding optimal transport plans with specific properties over multiple time periods.
method Introducing left-monotone transports and characterizing them through various properties.
result Left-monotone transports are unique under certain conditions and have specific order properties.
The estimate of a Multiperiod probability of default applied to residential mortgages can be obtained using the mean of the observed default, so called the Mean of ratios estimator, or aggregating the default and the issued mortgages and computing the ratio of their sum, that is the Ratio of means. This work studies th…
New metric derived for robust optimization in stochastic control problems.
problem Non-parametric uncertainty in multiperiod stochastic control problems.
method Derived a new metric, adapted (p,∞)--Wasserstein distance, and used dynamic programming principle. result Dynamic programming principle for DRO problems with semi-separable cost functions.
Study examines how slight model changes affect multi-period optimization outcomes.
problem Effect of small probabilistic model changes on multi-period optimization problems.
method Adapted Wasserstein distance for measuring changes, explicit first-order approximations proved.
result Explicit first-order approximations for multi-period stochastic optimization and optimal stopping problems.
Proposes a new investment strategy to optimize portfolio value within a target range.
problem Maximizing portfolio value within a specified range of returns.
method Two-stage least squares Monte Carlo method to handle complex payoffs.
result STRS strategy effectively contains portfolio value within the targeted range, improving risk-return trade-off.
In this paper we provide compelling evidence of cyclical mean reversion and multiperiod stock return predictability over horizons of about 30 years with a half-life of about 15 years. This implies that the US stock market follows a long-term rhythm where a period of above average returns tends to be followed by a perio…
A new ratio, the Hansen ratio, simplifies mean-variance portfolio theory.
problem Simplifying mean-variance portfolio theory.
method Introducing the Hansen ratio and extending mean-variance theory.
result The Hansen ratio provides a parsimonious description of the mean-variance efficient frontier.
Optimizes stock portfolios with a constraint on correlation to reduce risk.
problem Portfolio optimization with a correlation constraint in a stochastic financial market.
method Analytical expressions for constrained subgame perfect and precommitment portfolios.
result CSGP and CPC portfolios yield lower risk than unconstrained portfolios at a small utility cost.
New robust estimators for superhedging prices in financial markets.
problem Lack of robustness in existing statistical estimation methods for superhedging prices.
method Introduced novel estimators using martingale measures with tradeoffs between empirical measures and martingale densities.
result Established consistency and robustness of the new estimators, offering superior performance compared to the plugin estimator.
We discuss the role of integrated chance constraints (ICC) as quantitative risk constraints in asset and liability management (ALM) for pension funds. We define two types of ICC: the one period integrated chance constraint (OICC) and the multiperiod integrated chance constraint (MICC). As their names suggest, the OICC …
Modeling dynamic groundwater markets with price formation and trading strategies.
problem Understanding competitive effects in environmental markets with groundwater banking.
method Stochastic models and game theory with machine learning algorithms.
result Sub-game perfect Nash equilibria characterized by groundwater price processes.
Entropy measure quantifies volatility correlation and risk diversity in asset portfolios.
problem Quantifying volatility correlation and risk diversity in asset portfolios.
method Kullback-Leibler cluster entropy DC[P∥Q] for empirical and model probability distributions of realized volatility. result Portfolio built on diversity indexes derived from Kullback-Leibler entropy measure of realized volatility exhibits better performance.
Hydro storage system optimization is becoming one of the most challenging tasks in Energy Finance. While currently the state-of-the-art of the commercial software in the industry implements mainly linear models, we would like to introduce risk aversion and a generic utility function. At the same time, we aim to develop…
The paper solves multi-period portfolio selection with constraints using a dynamic factor model.
problem Multi-period mean-variance portfolio selection with constraints.
method Dynamic factor model, dynamic programming, piecewise linear feedback policy.
result Optimal portfolio policies determined by two stochastic processes.
The paper tackles uncertainties in corporate default risk predictions.
problem Evaluating uncertainties associated with corporate default risk predictions.
method Developed a procedure to quantify uncertainties by disentangling multiple contributing sources.
result Substantial uncertainties exist in default risk assessments.