Higher-order exposures

Traditional exposure measures focus on direct exposures to evaluate the losses an institution is exposed to upon the default of a counterparty. Since the Global Financial Crisis of 2007-2008, the importance of indirect exposures via common asset holdings is increasingly recognized. Yet direct and indirect exposures do not to capture the losses that result from shock propagation and amplification following the counterparty's default. In this paper, we introduce the concept of \higher-order exposures" to refer to these spill-over losses and propose a way to formalize and quantify these.

Mitsotakis prepares for autumn gamble after testing summer

A few days before Greece emerges from the political lull of August, the Thessaloniki International Fair (TIF) is rapidly becoming the focal point of a high-stakes autumn. Prime Minister Kyriakos Mitsotakis is due to unveil a sweeping relief package aimed at easing the cost-of-living crisis, which has proved a source of concern and frustration for voters throughout the last few years.

FEDS Paper: Linear and nonlinear econometric models against machine learning models: realized volatility prediction

Rehim KilicThis paper fills an important gap in the volatility forecasting literature by comparing a broad suite of machine learning (ML) methods with both linear and nonlinear econometric models using high-frequency realized volatility (RV) data for the S&P 500. We evaluate ARFIMA, HAR, regime-switching HAR models (THAR, STHAR, MSHAR), and ML methods including Extreme Gradient Boosting, deep feed-forward neural networks, and recurrent networks (BRNN, LSTM, LSTM-A, GRU).

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