Implementation of Monte-Carlo Method in Curriculum Efficiency, Cost Forecasting and Price Path Prediction
- DOI
- 10.2991/978-94-6463-408-2_40How to use a DOI?
- Keywords
- Monte-Carlo method; computer science; statistics; finance
- Abstract
As a matter of fact, Monte-Carlo method has been widely implemented in various fields including distribution issues and stochastic process in recent years. With this in mind, this study mainly focuses the utilization of Monte-Carlo simulation onto some real-life scenarios. In retrospect, the Monte-Carlo simulation is a program-based algorithm which compute the possible outcome when the analysts input the samples. In general, it is used to give a portrait of the future for risk management in many fields. According to the analysis, the mechanics of using Monte-Carlo in some different cases is explained, analyzed and compared to judge the efficiency of using different distributions for an estimation. Moreover, some limits of using those are suggested and appealed for solutions to modify and improve the algorithm tool for future research. Overall, these results shed light on guiding further exploration of applications for Monte-Carlo simulation based on state-of-art techniques as well as broadening the implementation situations.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Qixuan Hu PY - 2024 DA - 2024/05/07 TI - Implementation of Monte-Carlo Method in Curriculum Efficiency, Cost Forecasting and Price Path Prediction BT - Proceedings of the 9th International Conference on Financial Innovation and Economic Development (ICFIED 2024) PB - Atlantis Press SP - 352 EP - 358 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-408-2_40 DO - 10.2991/978-94-6463-408-2_40 ID - Hu2024 ER -