In this paper I examine various extensions of the Nelson and Siegel (1987) model with the purpose of fitting and forecasting the term structure of interest rates. As expected, I find that using more flexible models leads to a better in-sample fit of the term structure. However, I show that the...

The sum of squared intraday returns provides an unbiased and almost error-free measure of ex-post volatility. In this paper we develop a nonlinear Autoregressive Fractionally Integrated Moving Average (ARFIMA) model for realized volatility, which accommodates level shifts, day-of-the-week...

This paper investigates the merits of high-frequency intraday data when forming minimum variance portfolios and minimum tracking error portfolios with daily rebalancing from the individual constituents of the S&P 100 index. We focus on the issue of determining the optimal sampling frequency,...

We examine the importance of incorporating macroeconomic information and, in particular, accounting for model uncertainty when forecasting the term structure of U.S.interest rates. We start off by analyzing and comparing the forecast performance of several individual term structure models. Our...

This paper reviews literature on the empirical relationship between vulnerabilities in the financial system and the macroeconomy, and how monetary policy affects that connection. Financial vulnerabilities build up over time, with both risk appetite and risk taking rising during economic...

New Keynesian models of monetary policy assign no role to monetary aggregates, in the sense that the level of output, prices, and interest rates can be determined without knowledge of the quantity of money. We evaluate the empirical validity of this prediction by studying the effects of shocks...

We show that U.S. banks do not engage in zombie lending to firms of deteriorating profitability, irrespective of capital levels and exposure to such firms. In contrast, unregulated financial intermediaries do, originating more and cheaper loans to these firms. We establish these results using...

We use Zip code-level Statistics of Income data from the Internal Revenue Service to measure the distribution of income within U.S. metropolitan areas from 1998 through 2019. Exploiting geographic variation in income distribution over time, we study how unanticipated changes in the monetary...

This paper proposes a methodology to nowcast and forecast inflation using data with sampling frequency higher than monthly. The nowcasting literature has been focused on GDP, typically using monthly indicators in order to produce an accurate estimate for the current and next quarter. This paper...

The term now-casting is a contraction for now and forecasting and has been used for a long-time in meteorology and recently also in economics. In this paper we survey recent developments in economic now-casting with special focus on those models that formalize key features of how market...