Forecasting Models and Probabilistic Sensitivity Analysis: An Application to Bank’s Risk Appetite Thresholds Within the Risk Appetite Framework

Maurizio Polato (), Josanco Floreani, Giuseppe Giannelli and Nicola Novielli
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Maurizio Polato: University of Udine
Josanco Floreani: University of Udine
Giuseppe Giannelli: University of Udine
Nicola Novielli: University of Udine

Chapter Chapter 6 in Financial Markets, SME Financing and Emerging Economies, 2017, pp 95-119 from Palgrave Macmillan

Abstract: Abstract Bank’s financial planningFinancial planning requires forecasting modelsForecasting models that allow to forecast and measure the effects of possible future scenarios. Both environmental changes and regulatory innovations even more stimulate, especially under stress scenarios, the development of simulation-based forecasting modelsForecasting models specifically devoted to assess bank’s financial soundness and capital adequacy, along with the persistency of equilibria. The rationale of employing sophisticated quantitative methods in bank’s decision-making should be rooted in the compelling need to adequately manage uncertainty concerning the most relevant exogenous and policy variables for bank’s management. The very promising implications of implementing the Risk Appetite Framework Risk Appetite Framework are to be traced in a rapidly changing approach to bank’s management where the system of risks is a fundamental part of financial planningFinancial planning , rather than just being a by-product of it. Indeed, the RAF approach while becoming a fundamental tool for strategic control, allowing to represent mission and strategies by means of quantitative variables, enables the management to link risk targets to bank’s operations. In that, it is an important tool for risk management. Within this framework, the present work is aimed at investigating the implications of a probabilistic forecasting model for determining risk tolerance thresholds under an RAF environment.

Keywords: Risk Appetite (RA); Appetite Framework; Probabilistic Forecasting Model; Risk Tolerance; Risk Capacity (RC) (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/978-3-319-54891-3_6

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