Skip to main content
Have a personal or library account? Click to login
AI-Assisted Forecasts in Discounted Cash Flow Valuation: Valuation Date, Information Set, and Audit Trail Cover

AI-Assisted Forecasts in Discounted Cash Flow Valuation: Valuation Date, Information Set, and Audit Trail

By:  and    
Open Access
|Jul 2026

References

  1. Abbasli, T., Toyoda, K., Wang, Y., Witt, L., Ali, M. A., Miao, Y., Li, D., & Wei, Q. (2025). Comparing uncertainty measurement and mitigation methods for large language models: A systematic review. https://arxiv.org/abs/2504.18346.
  2. Albelali, S., & Ahmed, M. (2025). Hidden leaks in time series forecasting: How data leakage affects LSTM evaluation across configurations and validation strategies. https://arxiv.org/abs/2512.06932.
  3. Cheung, K. S. (2023). Real estate insights: Unleashing the potential of ChatGPT in property valuation reports: The “Red Book” compliance chain-of-thought (CoT) prompt engineering. Journal of Property Investment & Finance, 42(2), 200–206. https://doi.org/10.1108/JPIF-06-2023-0053.
  4. Cheung, K. S. (2024). Real estate insights: Establishing transparency—Setting AI standards in property valuation. Journal of Property Investment & Finance, 42(4), 406–408. https://doi.org/10.1108/JPIF-04-2024-0050.
  5. Eurostat. (2026). Harmonised index of consumer prices (HICP) – ECOICOP ver. 2 – indices and rates of change, annual data [Data set]. https://ec.europa.eu/eurostat/databrowser/view/prc_hicp_ainr/default/table?lang=en.
  6. Hwang, Y., Lee, D., Kang, T., Lee, M., & Jung, K. (2026). When wording steers the evaluation: Framing bias in LLM. https://arxiv.org/abs/2601.13537.
  7. International Valuation Standards Council. (2024). International Valuation Standards (effective 31 January 2025). https://ivsc.org/standards/.
  8. Ji, Z., Lee, N., Frieske, R., Yu, T., Su, D., Xu, Y., Ishii, E., Bang, Y. J., Madotto, A., & Fung, P. (2023). Survey of hallucination in natural language generation. ACM Computing Surveys, 55(12), Article 248, 1–38. https://doi.org/10.1145/3571730.
  9. Lewis, P., Perez, E., Piktus, A., Petroni, F., Karpukhin, V., Goyal, N., Küttler, H., Lewis, M., Yih, W.-t., Rocktäschel, T., Riedel, S., & Kiela, D. (2020). Retrieval-augmented generation for knowledge-intensive NLP tasks. In Advances in Neural Information Processing Systems (Vol. 33). https://proceedings.neurips.cc/paper/2020/hash/6b493230205f780e1bc26945df7481e5-Abstract.html.
  10. Liu, L., Pan, Y., Li, X., & Chen, G. (2024). Uncertainty estimation and quantification for LLMs: A simple supervised approach. https://arxiv.org/abs/2404.15993.
  11. Sriramanan, G., Bharti, S., Sadasivan, V. S., Saha, S., Kattakinda, P., & Feizi, S. (2024). LLM-Check: Investigating detection of hallucinations in large language models. In Advances in Neural Information Processing Systems (Vol. 37). https://proceedings.neurips.cc/paper_files/paper/2024/hash/3c1e1fdf305195cd620c118aaa9717ad-Abstract-Conference.html.
  12. Yang, X., Zang, S., Ren, Y., Peng, D., & Wen, Z. (2024). Evaluating large language models on financial report summarization: An empirical study. https://arxiv.org/abs/2411.06852.
  13. Zhang, Z., Chen, R., & Stadie, B. C. (2026). All leaks count, some count more: Interpretable temporal contamination detection in LLM backtesting. https://arxiv.org/abs/2602.17234.
Language: English
Page range: 574 - 583
Published on: Jul 16, 2026
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2026 Romana CIZINSKA, Pavel NESET, published by Bucharest University of Economic Studies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.