Methods and apparatus employing hierarchical conditional variance to minimize downside risk of a multi-asset class portfolio and improved graphical user interface

Abstract

The traditional Markowitz mean-variance-optimization (MVO) framework that uses the standard deviation of the possible portfolio returns as a measure of risk does not accurately measure the risk of multi-asset class portfolios whose return distributions are non-Gaussian and asymmetric. A scenario-based conditional value-at-risk (CVaR) approach for minimizing the downside risk of a multi-asset class portfolio is addressed that uses Monte-Carlo simulations to generate the asset return scenarios. These return scenarios are incorporated into a modified Rockafellar-Uryasev based convex programming formulation to generate an optimized hedge. One example addresses hedging in an equity portfolio with options. Testing shows that a hierarchical CVaR approach generates portfolios with better predicted worst case loss, downside risk, standard deviation, and skew.

Description

[0001]The present application claims the benefit of U.S. Provisional Application Ser. No. 62 / 333,563 filed May 9, 2016 which is incorporated by reference in its entirety.RELATED APPLICATIONS[0002]The present invention may advantageously be used in conjunction with one or more of the following applications and patents: U.S. patent application Ser. No. 11 / 668,294 filed Jan. 29, 2007 which issued as U.S. Pat. No. 7,698,202; U.S. patent application Ser. No. 12 / 958,778 filed Dec. 2, 2010 which issued as U.S. Pat. No. 8,533,089; U.S. patent application Ser. No. 12 / 711,554 filed Feb. 24, 2010 which issued as U.S. Pat. No. 8,315,936; U.S. patent application Ser. No. 12 / 827,358 filed Jun. 30, 2010; U.S. patent application Ser. No. 13 / 503,696 filed Apr. 24, 2012 which issued as U.S. Pat. No. 8,533,107; U.S. patent application Ser. No. 13 / 503,698 filed Apr. 24, 2012 which issued as U.S. Pat. No. 8,700,516; U.S. patent application Ser. No. 13 / 892,644 filed May 13, 2013; U.S. patent application ...

AI Technical Summary

Benefits of technology

[0048]One goal of the present invention, then, is to provide a methodology that enables a portfolio manager to effectively construct a portfolio with superior downside risk properties. In particular, the portfolio is constructed so that the CVaR is minimized for two or more specified confidence levels.

[0049]Another goal is to provide improved tools for displaying and comparing the predicted performance for alternative portfolios.

[0050]Another goal is to provide an improved, interactive tool in a graphical user interface for use by a portfolio manager who wishes to manage and minimize the CVaR of his or her portfolio at several confidence levels.

[0051]Another goal is to provide an improved, interactive tool embedded in an electronic trading system so that a portfolio manager who wishes to manage and minimize the CVaR of his or her portfolio may efficiently and interactively construct a desirable hedge and transmit and trade that hedge on the electronic trading platform.

Problems solved by technology

Market risk is the risk of a change in the value of a portfolio due to changes in the value of its holdings, for example, changes in the market value of an existing portfolio.

Credit risk is the risk of not receiving promised payments due to default of the counterparty in investments such as credit default swaps.

Such underestimation is commonly the case for multi-asset class portfolios, and it is an important limitation of traditional portfolio construction tools.

When portfolios, hedges, and trade lists are constructed for multi-asset class securities, the likelihood of underestimating the risk of the portfolio is high.

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