USING META-MODELS IN SIMULATION-BASED INVESTMENT ANALYSIS � STUDYING THE FINANCING MIX OF METAL MINING INVESTMENTS

2020 ◽  
Vol 25 (01) ◽  
Author(s):  
Jyrki Savolainen ◽  
Mikael Collan
Keyword(s):  
Investment Analysis ◽  
Metal Mining ◽  
Simulation Based

Using a cycle reverting price process in modeling metal mining project profitability

Kybernetes ◽  
2017 ◽  
Vol 46 (1) ◽  
pp. 131-141 ◽  
Author(s):  
Jyrki Savolainen ◽  
Mikael Collan ◽  
Pasi Luukka
Keyword(s):  
Net Present Value ◽  
Market Price ◽  
Investment Analysis ◽  
Cycle Phase ◽  
Analysis Model ◽  
Metal Mining ◽  
Content Type ◽  
Price Process ◽  
Price Trends

Purpose The purpose of this paper is to demonstrate how managerial estimates of long-term market price trends can be included into investment analysis of metal mining. The inclusion of subjective market information with a new cycle reverting price process is proposed. Design/methodology/approach Subjective managerial estimates are included into stochastic metal price modeling by defining separately the following parameters of each price cycle phase: approximated length, approximated long-term price level and volatility. An net present value-based investment analysis model is applied together with Monte Carlo simulation. Findings It is plausible to combine managerial estimates about metal price trends and cycles with stochastic modeling for shorter term and to include the information into investment analysis. The results show that the difference between the proposed process and the commonly used mean reverting process is remarkable in terms of decision-making implications. Originality/value The proposed method allows the inclusion of more relevant information into the metal price modeling used in mining investment analysis. Results suggest that the cyclical nature of metal prices affects project value of metal mining projects, and it should be considered when making irreversible investment decisions. The proposed method can be generalized for any cyclical processes.

Inquiry Learning

2009 ◽  
Vol 23 (2) ◽  
pp. 117-127 ◽  
Author(s):  
Astrid Wichmann ◽  
Detlev Leutner
Keyword(s):  
Scientific Reasoning ◽  
Inquiry Learning ◽  
Instructional Support ◽  
Test Results ◽  
Knowledge Test ◽  
Simulation Based ◽  
Scientific Experiments ◽  
Specific Support ◽  
Science Classes

Seventy-nine students from three science classes conducted simulation-based scientific experiments. They received one of three kinds of instructional support in order to encourage scientific reasoning during inquiry learning: (1) basic inquiry support, (2) advanced inquiry support including explanation prompts, or (3) advanced inquiry support including explanation prompts and regulation prompts. Knowledge test as well as application test results show that students with regulation prompts significantly outperformed students with explanation prompts (knowledge: d = 0.65; application: d = 0.80) and students with basic inquiry support only (knowledge: d = 0.57; application: d = 0.83). The results are in line with a theoretical focus on inquiry learning according to which students need specific support with respect to the regulation of scientific reasoning when developing explanations during experimentation activities.

Employing Human Role-Players in Simulation-Based Training For Asymmetric and Unconventional Warfare

2004 ◽  
Author(s):  
L. L. Kusumoto ◽  
◽  
R. M. Gehorsam ◽  
B. D. Comer ◽  
J. R. Grosse
Keyword(s):  
Unconventional Warfare ◽  
Simulation Based ◽  
Role Players
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