More Like this

1. Leveraged Exchange-Traded Funds with Market Closure and Frictions

   https://doi.org/10.1287/mnsc.2022.4407  

   Dai, Min ; Kou, Steven ; Soner, H Mete ; Yang, Chen ( April 2023 , Management Science)

   Although leveraged exchange-traded funds (ETFs) are popular products for retail investors, how to hedge them poses a great challenge to financial institutions. We develop an optimal rebalancing (hedging) model for leveraged ETFs in a comprehensive setting, including overnight market closure and market frictions. The model allows for an analytical optimal rebalancing strategy. The result extends the principle of “aiming in front of target” introduced by Gârleanu and Pedersen (2013) from a constant weight between current and future positions to a time-varying weight because the rebalancing performance is monitored only at discrete time points, but the rebalancing takes place continuously. Empirical findings and implications for the weekend effect and the intraday trading volume are also presented.

   This paper was accepted by Agostino Capponi, finance.

   Funding: M. Dai acknowledges support from the National Natural Science Foundation of China [Grant 12071333], the Hong Kong Polytechnic University [Grant P0039114], and the Singapore Ministry of Education [Grants R-146-000-243/306/311-114 and R-703-000-032-112]. H. M. Soner acknowledges partial support from the National Science Foundation [Grant DMS 2106462]. C. Yang acknowledges support from the Chinese University of Hong Kong [Grant 4055132 and a University Startup Grant].

   Supplemental Material: Data and the online supplement are available at https://doi.org/10.1287/mnsc.2022.4407 .

    

   more » « less
2. A Riemannian Smoothing Steepest Descent Method for Non-Lipschitz Optimization on Embedded Submanifolds of Rn

   https://doi.org/10.1287/moor.2022.0286  

   Zhang, Chao ; Chen, Xiaojun ; Ma, Shiqian ( August 2023 , Mathematics of Operations Research)

   In this paper, we study the generalized subdifferentials and the Riemannian gradient subconsistency that are the basis for non-Lipschitz optimization on embedded submanifolds of [Formula: see text]. We then propose a Riemannian smoothing steepest descent method for non-Lipschitz optimization on complete embedded submanifolds of [Formula: see text]. We prove that any accumulation point of the sequence generated by the Riemannian smoothing steepest descent method is a stationary point associated with the smoothing function employed in the method, which is necessary for the local optimality of the original non-Lipschitz problem. We also prove that any accumulation point of the sequence generated by our method that satisfies the Riemannian gradient subconsistency is a limiting stationary point of the original non-Lipschitz problem. Numerical experiments are conducted to demonstrate the advantages of Riemannian [Formula: see text] [Formula: see text] optimization over Riemannian [Formula: see text] optimization for finding sparse solutions and the effectiveness of the proposed method.

   Funding: C. Zhang was supported in part by the National Natural Science Foundation of China [Grant 12171027] and the Natural Science Foundation of Beijing [Grant 1202021]. X. Chen was supported in part by the Hong Kong Research Council [Grant PolyU15300219]. S. Ma was supported in part by the National Science Foundation [Grants DMS-2243650 and CCF-2308597], the UC Davis Center for Data Science and Artificial Intelligence Research Innovative Data Science Seed Funding Program, and a startup fund from Rice University.

    

   more » « less
3. Carol Upadhya and Sachinkumar Rathod, Caste at the City’s Edge: Land Struggles in Peri-urban Bangalore. 26: 1-28.

   Upadhya, Carol ; Rathod, Sachinkumar ( April 2021 , South Asia multidisciplinary academic journal)

   null (Ed.)

   This paper draws on fieldwork carried out between 2017 and 2020 as part of the project “Speculative Urbanism: Land, Livelihoods, and Finance Capital,” in collaboration with the University of Minnesota, funded by the National Science Foundation [grant number BCS-1636437]. We thank our colleagues Vinay Gidwani, Michael Goldman, Hemangini Gupta, Eric Sheppard, Helga Leitner, and other members of the research team for many discussions and debates. Earlier versions of the paper were presented at the Third Annual Research Conference of the Indian Institute for Human Settlements, Bengaluru, January 10–12, 2019; in the panel on The Peri-urban Question: Renewing Concepts and Categories at RC21@Delhi, September 18–20, 2019; and at the French Institute of Pondicherry, February 13, 2020. We are grateful to the organizers and participants of those conferences for their valuable feedback, as well as to the anonymous referees for their constructive comments. All photos are by Pierre Hauser, who we sincerely thank for allowing us to use his work. 

   more » « less
4. Estimating and Mitigating the Congestion Effect of Curbside Pick-ups and Drop-Offs: A Causal Inference Approach

   https://doi.org/10.1287/trsc.2022.0195  

   Liu, Xiaohui ; Qian, Sean ; Teo, Hock-Hai ; Ma, Wei ( December 2023 , Transportation Science)

   Curb space is one of the busiest areas in urban road networks. Especially in recent years, the rapid increase of ride-hailing trips and commercial deliveries has induced massive pick-ups/drop-offs (PUDOs), which occupy the limited curb space that was designed and built decades ago. These PUDOs could jam curbside utilization and disturb the mainline traffic flow, evidently leading to significant negative societal externalities. However, there is a lack of an analytical framework that rigorously quantifies and mitigates the congestion effect of PUDOs in the system view, particularly with little data support and involvement of confounding effects. To bridge this research gap, this paper develops a rigorous causal inference approach to estimate the congestion effect of PUDOs on general regional networks. A causal graph is set to represent the spatiotemporal relationship between PUDOs and traffic speed, and a double and separated machine learning (DSML) method is proposed to quantify how PUDOs affect traffic congestion. Additionally, a rerouting formulation is developed and solved to encourage passenger walking and traffic flow rerouting to achieve system optimization. Numerical experiments are conducted using real-world data in the Manhattan area. On average, 100 additional units of PUDOs in a region could reduce the traffic speed by 3.70 and 4.54 miles/hour (mph) on weekdays and weekends, respectively. Rerouting trips with PUDOs on curb space could respectively reduce the system-wide total travel time (TTT) by 2.44% and 2.12% in Midtown and Central Park on weekdays. A sensitivity analysis is also conducted to demonstrate the effectiveness and robustness of the proposed framework.

   Funding: The work described in this paper was supported by the National Natural Science Foundation of China [Grant 52102385], grants from the Research Grants Council of the Hong Kong Special Administrative Region, China [Grants PolyU/25209221 and PolyU/15206322], a grant from the Otto Poon Charitable Foundation Smart Cities Research Institute (SCRI) at the Hong Kong Polytechnic University [Grant P0043552], and a grant from Hong Kong Polytechnic University [Grant P0033933]. S. Qian was supported by a National Science Foundation Grant [Grant CMMI-1931827].

   Supplemental Material: The e-companion is available at https://doi.org/10.1287/trsc.2022.0195 .

    

   more » « less
5. Elucidating the Magma Plumbing System of Ol Doinyo Lengai (Natron Rift, Tanzania) Using Satellite Geodesy and Numerical Modeling: Supplementary Model Files

   https://doi.org/10.5281/zenodo.7897255  

   Daud, Ntambila ; Stamps, D. Sarah ; Battaglia, Maurizio ; Huang, Mong-Han ; Saria, Elifuraha ; Ji, Kang-Hyeun ( January 2023 , Zenodo)

   Supplementary code and model files for the manuscript entitled "Elucidating the Magma Plumbing System of Ol Doinyo Lengai (Natron Rift, Tanzania) Using Satellite Geodesy and Numerical Modeling". OlDoinyoLengai_code_and_models.zip contains all necessary Matlab code, functions, input and output files for the GNSS, InSAR, and joint inversions presented in our manuscript necessary to reproduce the results. dMODELS is an open source code developed by the United States Geological Survey. The originally published program is available here: https://pubs.usgs.gov/tm/13/b1/ and the revised software archived here will also be available through the USGS website code.usgs.gov/vsc/publications/OlDoinyoLengai or by contacting Maurizio Battaglia. With this manuscript we are providing an update to dMODELS that includes improved graphics and joint inversion capabilities for both InSAR and GNSS data. 

   This work was funded by the National Science Foundation (NSF) grant number EAR-1943681, Virginia Tech, Korean Institute of Geosciences and Minerals (KIGAM), and Ardhi University. Funding for this work also came from USAID via the Volcano Disaster Assistance Program and from the U.S. Geological Survey (USGS) Volcano Hazards Program.This material is based on services provided by the GAGE Facility, operated by UNAVCO, Inc., with support from the National Science Foundation, the National Aeronautics and Space Administration, and the U.S. Geological Survey under NSF Cooperative Agreement EAR-1724794. We acknowledge and thank Alaska Satellite Facility for making InSAR data freely available and TZVOLCANO GNSS data sets available through the UNAVCO data archive. 

   more » « less