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Using a high-frequency framework, we show that the Auroba-Diebold-Scotti (ADS) daily business conditions index significantly increases the accuracy of U.S. unemployment nowcasts in real-time. This is of particular relevance in times of recession, such as the Global Financial Crisis and the Covid-19 pandemic, when the unemployment rate is prone to rise steeply. Based on our results, the ADS index presents itself as a better predictor than the financial indicators widely used by the literature and central banks, including both interest and credit spreads and the VXO.

We estimate multivariate quantile models to measure the responses of the six main Latin American (LA) stock markets to a shock in the United States (US) stock index. We compare the regional responses with those of seven developed markets. In general, we document weaker tailcodependences between the US and LA than those between the US and the mature markets. Our results suggest possible diversification strategies that could be exploited by investing in Latin America following a sizable shock to the US market. We also document asymmetrical responses to the shocks depending on the conditioning quantile at which they are calculated.

Treballs Finals del Màster de Ciències Actuarials i Financeres, Facultat d'Economia i Empresa, Universitat de Barcelona, Curs: 2020-2021, Tutor: Helena Chuliá, El trabajo final de master se centra en el análisis de la relación lineal y no lineal entre los precios de commodities, los cuales han ido ganando fuerza e importancia en el mercado financiero internacional en las últimas décadas, y el índice bursátil S&P 500 de los Estados Unidos, siendo los commodities estratégicos escogidos en el análisis, el oro, el cobre, el petróleo crudo, el trigo y el algodón. Para ello, recurriremos desde un enfoque lineal al modelo DCC-GARCH. Mediante este modelo obtendremos las correlaciones condicionales y realizaremos un análisis comparativo de las mismas centrándonos especialmente en la crisis financiera del 2008 y la crisis del COVID-19. Por otro lado, utilizaremos el modelo de regresión cuantílica para medir la relación no lineal entre el S&P 500 y los precios de los commodities. Abstract The final master thesis focuses on the analysis of the linear and non-linear relationship between commodities prices, which have attracted considerable interest in the international financial market in recent decades and the S&P 500 stock index of the United States, being the strategic commodities chosen in the analysis, gold, copper, crude oil, wheat and cotton. For that purpose, we will use the DCC-GARCH model as a linear approach. By using this model, we will obtain the conditional correlations and we will carry out a comparison of them, focusing on the financial crisis of 2008 and the crisis of the COVID-19. On the other hand, we will use the quantile regression to measure the non-linear relationship between the S&P 500 the commodity prices.