Behind its principals, GlimmAnalytics is supported by a team of approximately one dozen scientists

Author: Som Naik, James Glimm, Ryan Kaufman, August 11, 2022

Inflation Uncertainty: ETF Risk Model, Structural Change, and Breakeven Inflation


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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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