This paper introduces formal monitoring procedures as a risk-management tool. Continuously monitoring risk forecasts allows practitioners to swiftly review and update their forecasting procedures as soon as forecasts turn inadequate. Similarly, regulators may take timely action in case reported risk forecasts become poor. Extant (one-shot) backtests require, however, that all data are available prior to testing and are not informative of when inadequacies might have occurred. To monitor value-at-risk and expected shortfall forecasts ???online??????that is, as new observations become available???we construct sequential testing procedures. We derive the exact finite-sample distributions of the proposed procedures and discuss the suitability of asymptotic approximations. Simulations demonstrate good behavior of our exact procedures in finite samples. An empirical application to major stock indices during the COVID-19 pandemic illustrates the economic benefits of our monitoring approach.
机构:
Michigan State Univ, Coll Law, 648 North Shaw Lane, E Lansing, MI 48824 USA
Univ Zagreb, Sch Econ & Business, Ekon Fak, JF Kennedyja Trg 6, Zagreb 10000, CroatiaMichigan State Univ, Coll Law, 648 North Shaw Lane, E Lansing, MI 48824 USA
机构:
FGV, Sao Paulo Sch Econ, Sao Paulo, SP, Brazil
Ctr Appl Res Econometr Finance & Stat, Campinas, SP, BrazilFGV, Sao Paulo Sch Econ, Sao Paulo, SP, Brazil
Trucios, Carlos
Tiwari, Aviral K.
论文数: 0引用数: 0
h-index: 0
机构:
Rajagiri Business Sch, Rajagiri Valley Campus, Kochi, Kerala, IndiaFGV, Sao Paulo Sch Econ, Sao Paulo, SP, Brazil
Tiwari, Aviral K.
Alqahtani, Faisal
论文数: 0引用数: 0
h-index: 0
机构:
Minist Finance, Macro & Fiscal Policies Unit, The Hague, Saudi ArabiaFGV, Sao Paulo Sch Econ, Sao Paulo, SP, Brazil