This paper analyzes the ability of unconventional monetary policies to reduce the spread between the credit and the short-term policy interest rates. We provide a theoretical framework based on the bank-lending channel that incorporates an interbank money market. The proposed model shows that...

We propose an optimal architecture for deep neural networks of given size. The optimal architecture obtains from maximizing the minimum number of linear regions approximated by a deep neural network with a ReLu activation function. The accuracy of the approximation function relies on the neural...

This paper proposes a network regression model to account for peer contextual effects on the outcome variable. In contrast to the literature, we estimate the interaction matrix that defines the network structure. Spill-over effects are modelled as a functional coefficient that is approximated...

This paper proposes a novel methodology to construct optimal portfolios that incorporates the occurrence of systemic events. Investors maximize a modified Sharpe ratio conditional on a systemic event. We solve the portfolio allocation problem analytically under the absence of short-selling...

This paper proposes a novel methodology to detect Granger causality in mean in vector autoregressive settings using feedforward neural networks. The approach accommodates unknown dependence structures between the elements of highly-dimensional multivariate time series with weak and strong...

One of the implications of the creation of Basel Committee on Banking Supervision wasthe implementation of Value-at-Risk (VaR) as the standard tool for measuring market risk.Since then, the capital requirements of commercial banks with trading activities are basedon VaR estimates. Therefore,...

We investigate empirically the dependence of the size effect on the top performing stocks in a cross-section of risky assets separated by industry. We propose a test for a lottery-style factor payoff based on a stochastic utility model for an under-diversified investor. The associated...

We define the extreme values of any random sample of size n from a distribution function F as the observations exceeding a threshold and following a type of generalized Pareto distribution (GPD) involving the tail index of F. The threshold is the order statistic that minimizes a...

This paper proposes an empirical model for analyzing the dynamics of Bitcoin prices. To do this, we consider a vector error correction model over two overlapping periods: 2010-2017 and 2010-2019. Price discovery is achieved through the Gonzalo-Granger permanent-transitory decomposition. The...

This paper proposes an empirical asset pricing test based on the homogeneity of the factor risk premia across risky assets. Factor loadings are considered to be dynamic and estimated from data at higher frequencies. The factor risk premia are obtained as estimates from time series regressions...