Author: Som Naik, James Glimm, Ryan Kaufman, August 11, 2022 Inflation Uncertainty: ETF Risk Model, Structural Change, and Breakeven Inflation Abstract We present a predictive risk model for a popular Treasury In ation Protected Securities (TIPS) ETF. The model is based on ARMA-GARCH and a heavy-tailed volatility model. Read More
Author: Eesh Naika,b, James Glimma,b, August 3, 2022 TIPS ETF: An Explanatory Model using CPI This paper investigates the relationship between ETFs composed of Treasury Inflation Protected Securities (TIPS) and inflation as indicated by the CPI. Read More
Author: Yuhao Liu , Petar M. Djuric ́, Young Shin Kim , Svetlozar T. Rachev and James Glimm , July 14, 2021 Systemic Risk Modeling with Lévy Copulas 1. Introduction Value-at-risk (VaR) quantifies the level of financial risk of investments over a specific time frame, and it is the most common tool in risk management. Read More
Author: Yuan Hu, Abootaleb Shirvani , W. Brent Lindquist , Frank J. Fabozzi and Svetlozar T. Rachev 1, February 2, 2021 Option Pricing Incorporating Factor Dynamics in Complete Markets Abstract: Using the Donsker–Prokhorov invariance principle, we extend the Kim–Stoyanov–Rachev –Fabozzi option pricing model to allow for variably-spaced trading instances, an important consideration for short-sellers of options. Read More
Author: Abootaleb Shirvani, Stoyan V. Stoyanovy, Frank J. Fabozziz, Svetlozar T. Rachevx, December 19, 2020 Equity Premium Puzzle or Faulty Economic Modelling? In this paper we revisit the equity premium puzzle reported in 1985 by Mehra and Prescott. We show that the large equity premium that they report can be explained by choosing a more appropriate distribution for the return data. Read More
Author: Abootaleb Shirvania, Stoyan V. Stoyanovb, Svetlozar T. Rachevc, and Frank J. Fabozzid, November 30, 2020 A New Set of Financial Instruments Abstract In complete markets there are risky assets and a riskless asset. It is as- sumed that the riskless asset and the risky asset are traded continuously in time and that the market is frictionless. Read More
Author: Young Shin Kim, November 9, 2020 Cryptocurrency Portfolio Optimization We study portfolio optimization of four major cryptocurrencies. Our time series model is a generalized autoregressive conditional heteroscedasticity (GARCH) model with multivariate normal tempered stable (MNTS) distributed residuals used to cap- ture the non-Gaussian cryptocurrency return dynamics. Read More
Author: Young Shin Kim, August 13, 2020 Portfolio Optimization the Dispersion Risk and the Asymmetric Tail Risk In this paper, we propose a market model with returns assumed to follow a multivariate normal tempered stable distribution defined by a mixture of the multivariate normal distribution and the tempered stable subordinator. Read More
Author: Abigail Hsu, Ryan Kaufman, Hyunkyung Lim and James Glimm, August 10, 2020 Glimm Analytics Overnight Risk Model: A Unique Capability We present a novel risk measurement model capable of capturing overnight risk i.e. the risk encountered between the closing time of the previous day and the opening time of the next day. Read More