Modelling
Solving the FRTB puzzle
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A structural model for estimating losses associated with the mis-selling of retail banking products
In this paper, a structural model is presented for estimating losses associated with the mis-selling of retail banking products. It is the first paper to consider factor-based modeling for this operational/conduct risk scenario.
Banks seek to pry open CCP black boxes
Clarity on model inputs may have averted Brexit chaos, FCMs claim
Energy firms assess costs of cyber attacks
Analytics are considered key to cyber risk management
Operational risk modelling – finally?
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Further investigation of parametric loss given default modeling
The authors conduct a comprehensive study of some parametric models that are designed to fit the unusual bounded and bimodal distribution of loss given default (LGD).
Impact of nonstationarity on estimating and modeling empirical copulas of daily stock returns
This paper investigates the extent to which the nonstationarity of financial time series affects both the estimation and the modeling of empirical copulas.
Multifactor risk models and heterotic CAPM
The authors of this paper give a complete algorithm and source code for constructing general multifactor risk models via any combination of style factors, principal components and/or industry factors.
FRTB standard rules cause worries about duplication
Sensitivity-based approach means “we have to do everything twice”, complains one head of trading
Model firms vie to pinpoint ‘X factor’ in private equity, property
Difficulties gathering data plague efforts to determine correlation between private and publicly traded assets
Relative performance persistence of financial forecasting models and its economic implications
This paper addresses the issue of model selection risk by examining whether a model’s past performance in forecasting expected returns provides an indication of its future forecasting performance.
Even for me, AMA models are too complicated
The AMA doesn’t make any sense – but the idea of a single, simple equation does, writes Ruben Cohen
Banks told to seize moment to devise new op risk charge
Banks should “get clever and develop their own model” in response to SMA, says UK bank risk manager
US model risk rules put lions back in their cages
Impact of Federal Reserve and OCC model risk guidance is being felt well beyond US banks
Energy trading firms race to improve analytics capabilities
Surging availability of data lets firms with best market insight gain an edge
Research uncovers new sources of financial model risk
Past performance of financial models is no guarantee of future success, two forthcoming papers suggest
Priips performance scenario rules under fire
New rules needlessly confusing, say distributors
Stress tests at risk of becoming too complex, say bank heads
Regulator demands could lead to "tick-the-box" exercise, hear delegates at Quant Summit Europe
Top quant Peter Carr leaves Morgan Stanley
Global head of market modelling is no longer with the bank, say industry sources
Network theory takes root in post-crisis financial markets
Developments since 2008 open up exciting possibilities, says Kimmo Soramäki
Discarding the AMA could become a source of op risk
Basel Committee’s “tantrum-like reaction” is not supported by evidence, say practitioners
B-spline techniques for volatility modeling
In this paper the use of B-splines is advocated for volatility modeling within the calibration of stochastic local volatility (SLV) models and for the parameterization of an arbitrage-free implied volatility surface calibrated to sparse option data.
AERB: developing AIRB PIT–TTC PD models using external ratings
In this paper, the authors show how one can use a certain class of models for modeling portfolios such as large corporates, banks and insurance companies.
Insurers wary of capital 'uncertainty' in multi-asset funds
Firms concerned about modelling future portfolio changes