Risk minimization through portfolio replication
نویسندگان
چکیده
منابع مشابه
Doubly Regularized Portfolio with Risk Minimization
Due to recent empirical success, machine learning algorithms have drawn sufficient attention and are becoming important analysis tools in financial industry. In particular, as the core engine of many financial services such as private wealth and pension fund management, portfolio management calls for the application of those novel algorithms. Most of portfolio allocation strategies do not accou...
متن کاملPortfolio Optimization Based on Cross Efficiencies By Linear Model of Conditional Value at Risk Minimization
Markowitz model is the first modern formulation of portfolio optimization problem. Relyingon historical return of stocks as basic information and using variance as a risk measure aretow drawbacks of this model. Since Markowitz model has been presented, many effortshave been done to remove theses drawbacks. On one hand several better risk measures havebeen introduced and proper models have been ...
متن کاملBatch learning from logged bandit feedback through counterfactual risk minimization
We develop a learning principle and an efficient algorithm for batch learning from logged bandit feedback. This learning setting is ubiquitous in online systems (e.g., ad placement, web search, recommendation), where an algorithm makes a prediction (e.g., ad ranking) for a given input (e.g., query) and observes bandit feedback (e.g., user clicks on presented ads). We first address the counterfa...
متن کاملQuadratic Risk Minimization in a Regime-Switching Model with Portfolio Constraints
We study a problem of stochastic control in mathematical finance, for which the asset prices are modeled by Itô processes. The market parameters exhibit “regime-switching” in the sense of being adapted to the joint filtration of the Brownian motion in the asset price models and a given finite-state Markov chain which models “regimes” of the market. The goal is to minimize a general quadratic lo...
متن کاملKeyCredit risk, Portfolio credit risk model, Portfolio optimisation, Genetic
This paper proposes a new combination of quantitative models and Genetic Algorithms for the task of optimising credit portfolios. Currently, quantitative portfolio credit risk models are used to calculate portfolio risk figures, e. g. expected losses, unexpected losses and risk contributions. Usually, this information is used for optimising the risk-return profile of the portfolio. We show that...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The European Physical Journal B
سال: 2007
ISSN: 1434-6028,1434-6036
DOI: 10.1140/epjb/e2007-00130-7