Details about Rutger-Jan Lange

Access statistics for papers by Rutger-Jan Lange.

Last updated 2024-09-07. Update your information in the RePEc Author Service.

Short-id: pla919

Working Papers

2024

1. Dynamic determinants of optimal global climate policy
   Tinbergen Institute Discussion Papers, Tinbergen Institute
   See also Journal Article Dynamic determinants of optimal global climate policy, Structural Change and Economic Dynamics, Elsevier (2024) (2024)
2. Implicit score-driven filters for time-varying parameter models
   Tinbergen Institute Discussion Papers, Tinbergen Institute View citations (2)
3. Kullback-Leibler-based characterizations of score-driven updates
   Papers, arXiv.org
   Also in Tinbergen Institute Discussion Papers, Tinbergen Institute (2024)

2022

4. This article establishes the Poisson optional stopping times (POST) method by Lange et al. (2020) as a near-universal method for solving liquidity-constrained American options, or, equivalently, penalised optimal-stopping problems. In this setup, the decision maker is permitted to “stopâ€, i.e. exercise the option, only at a set of Poisson arrival times; this can be viewed as a liquidity constraint or “penalty†that limits access to optionality. We use monotonicity arguments in function space to establish that the POST algorithm either (i) finds the solution or (ii) demonstrates that no solution exists. The monotonicity of POST carries over to the discretised setting, where we additionally show geometric convergence and provide convergence bounds. For jump-diffusion processes, dense matrix factorisation may be avoided by using a suitable operator-splitting method for which we prove convergence. We also highlight a connection with linear complementarity problems (LCPs). We use the POST algorithm to value American options and compute early-exercise boundaries for Kou’s jump-diffusion model and Heston’s stochastic volatility model, illustrating the breadth of application and numerical reliability of the method
   Tinbergen Institute Discussion Papers, Tinbergen Institute

2021

5. Bellman filtering for state-space models
   Tinbergen Institute Discussion Papers, Tinbergen Institute
6. The option value of vacant land: Don't build when demand for housing is booming
   CEPR Discussion Papers, C.E.P.R. Discussion Papers
   Also in Tinbergen Institute Discussion Papers, Tinbergen Institute (2021)

2018

7. Systems Innovation, Inertia and Pliability: A mathematical exploration with implications for climate change abatement
   Working Papers, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge View citations (1)
8. The option value of vacant land and the optimal timing of city extensions
   Tinbergen Institute Discussion Papers, Tinbergen Institute View citations (7)
   Also in CEPR Discussion Papers, C.E.P.R. Discussion Papers (2018) View citations (7)

2016

9. Score-Driven Systemic Risk Signaling for European Sovereign Bond Yields and CDS Spreads
   Tinbergen Institute Discussion Papers, Tinbergen Institute View citations (6)

2015

10. Modeling the Interactions between Volatility and Returns
    Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge View citations (4)
11. Volatility Modeling with a Generalized t-distribution
    Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge View citations (17)

Undated

12. Can Google Search Data Help Predict Macroeconomic Series?
    Tinbergen Institute Discussion Papers, Tinbergen Institute
    See also Journal Article Can Google search data help predict macroeconomic series?, International Journal of Forecasting, Elsevier (2020) View citations (21) (2020)

Journal Articles

2024

1. Bellman filtering and smoothing for state–space models
   Journal of Econometrics, 2024, 238, (2)
2. Dynamic determinants of optimal global climate policy
   Structural Change and Economic Dynamics, 2024, 71, (C), 490-508
   See also Working Paper Dynamic determinants of optimal global climate policy, Tinbergen Institute Discussion Papers (2024) (2024)
3. Irreversible investment under predictable growth: Why land stays vacant when housing demand is booming
   Journal of Economic Theory, 2024, 215, (C)

2020

4. Can Google search data help predict macroeconomic series?
   International Journal of Forecasting, 2020, 36, (3), 1163-1172 View citations (21)
   See also Working Paper Can Google Search Data Help Predict Macroeconomic Series?, Tinbergen Institute Discussion Papers
5. Real-Option Valuation in Multiple Dimensions Using Poisson Optional Stopping Times
   Journal of Financial and Quantitative Analysis, 2020, 55, (2), 653-677 View citations (12)

2018

6. Modeling the Interactions between Volatility and Returns using EGARCH‐M
   Journal of Time Series Analysis, 2018, 39, (6), 909-919 View citations (13)

2016

7. When Is Information Sufficient for Action? Search with Unreliable yet Informative Intelligence
   Operations Research, 2016, 64, (2), 315-328 View citations (2)