Strategic Risk Adoption in Real Options under Multi-Horizon Regime Switching and Uncertainty

This project's first object and second object is illustrated before updating. Here is articles' information updating: Until July, 2021, totally 13 articles can be related to this project with acknowledgement to the funding of the project. The formation of the acknowledgement is: XXX gratefully acknowledges funding from the Finance Market Fund, Norwegian Research Council (Project number 274569). Those 13 articles including 2 conference papers, 8 journal publications and 3 papers working on progress. Three project members (Lars Hegnes Sendstad, Michail Chronopoulos; Yushu Li) have been working on the topics to extend traditional real options models to account not only for attitudes towards risk but also for the regime-switching behavior of economic indicators when the probability of switching between different regimes is both fixed and stochastic. There are two conferences paper in those topics: 1. Chronopoulos, M (2018), "The Value of Modular Design and Project Scale for Alternative Green Investment," in the 41st IAEE International Conference, 10-13 June, Groningen. 2. Sendstad, Lars Hegnes; Chronopoulos, Michail; Li, Yushu. The Value of Turning-Point Detection for Optimal Investment. The 23rd Annual International Real Options Conference; Dublin, Ireland; 2019-06-27 - 2019-06-29 and 3 publications: 1. Sendstad, Lars Hegnes; Chronopoulos, Michail (2021), Strategic technology switching under risk aversion and uncertainty, Journal of Economic Dynamics & Control, Vol.126. 2. Sendstad, Lars Hegnes; Chronopoulos, Michail and Verena Hagspiel (2021), Optimal Risk Adoption and Capacity Investment in Technological Innovations,IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT 3. Sendstad, Lars Hegnes; Chronopoulos, Michail, (2020) Sequential investment in renewable energy technologies under policy uncertainty, Energy Policy, Vol 137. As planned, this project also develops modern time-series methodologies with can deal with non-stationary data such as dataset with long memory, structural break (a type of regime switch), as well as the implementation in finance and economics. The topic of uncertainty forecasting (eg density forecasting) as well as evaluation are also included in the project. We have already publications: 1. Yushu Li and Fredrik N.G. Andersson (2020) A simple wavelet-based test for serial correlation in panel data models, (Online 22. Feb.), Empirical Economics 2. Fredrik N.G. Andersson and Yushu Li (2019) Are Central Bankers Inflation Nutters? A MCMC Estimator of the Long-Memory Parameter in a State Space Model, (Online 19 June 2019), Computational economics 3. Yushu Li and Jonas Andersson (2019): A Likelihood Ratio and Markov Chain Based Method to Evaluate Density Forecasting, (published on line 17 May 2019), Jounnal of forecasting 4. Hyunjoo Kim Karlsoon, Yushu Li and Ghazi Shukur (2018): The Causal Nexus between Oil Prices, Interest Rates, and Unemployment in Norway Using Wavelet Methods", Sustainability 2018, 10(8), 2792; https://doi.org/10.3390/su10082792 5. Talha Omer, Pär Sjölander, Kristofer Månsson, B. M. Golam Kibria (2021), Improved estimators for the Zero-inflated Poisson regression model in the presence of multicollinearity: Simulation and application of maternal death data (2021), accepted, Communications in Statistics ? Case Studies and Data Analysis The project members also have three papers working on progress: 1. Fredrik N.G. Andersson and Yushu Li (2021) Are real effective exchange rates real mean-reverting? Long memory and structural breaks (is prepared for being sent to journals for consideration of publication). 2. Bjørn Gunnar Hansen and Yushu Li (2021) Mean reverting properties of milk prices in EU countries ----Problem of misidentification under structural break (has already been sent out for consideration of publication) 3. Pär Henrik Sjölander, Yushu Li and Peter S Karlsson (2021) A simple panel causality test in the presence of cross-section dependence (working on progress). Based on the above output of the project, we can say that the beneficiaries of project are decision theorists and financial mathematicians, macro-economist, econometricians and empirical statisticians.

We have 8 journal publications ,2 working papers with conference presentations (conference paper), and 2 working on the process (working paper). More detailed information of topics/links related to the journal publication/conference papers can be found in the attached Results Report at next side

This project is a cooperation among the statistics group from the Department of Mathematics at Universty of Bergen, the Department of Computing, Engineering and Mathematics at the University of Brighton, the Department of Economics at Simon Fraser University in Canada, the Department of Economics at Lund University, and eventually Norwegian School of Economics. The research result from this project will provide a framework for evaluating the interaction of scenarios, decisions, options to delay, and investment choice. This type of framework can be used to model several features of investment in infrastructure projects and alternative energy technologies. This project will also develop a new statistical model, which is Hidden Markov models combined with wavelet methodology. This model will be especially effective to handle the different regime switching dynamic in economical, political, social and environmental issues. The immediate beneficiaries of our work will be decision theorists and financial mathematicians. The result of this project will also benefit researchers in the field of public policy and behavioral economics.