Federal Reserve Bank of St. Louis

About: Federal Reserve Bank of St. Louis is a other organization based out in St Louis, Missouri, United States. It is known for research contribution in the topics: Monetary policy & Inflation. The organization has 203 authors who have published 1650 publications receiving 46084 citations.

Lessons from the Evolution of Foreign Exchange Trading Strategies

Abstract: The adaptive markets hypothesis posits that trading strategies evolve as traders adapt their behavior to changing circumstances. This paper studies the evolution of trading strategies for a hypothetical trader who chooses portfolios from forex technical rules in major and emerging markets, the carry trade and U.S. equities. The results show that forex trading alone dramatically outperforms the S&P 500. But there is little gain to coordinating forex and equity strategies, which explains why practitioners consider these tools separately. In addition, a backtesting procedure to choose optimal portfolios does not select carry trade strategies until well into the 1990s, which helps to explain the relatively recent surge in interest in this strategy. Forex trading returns dip significantly in the 1990s but recover by the end of the decade and have greatly outperformed an equity position since 1998. Overall, trading rule returns still exist in forex markets – with substantial stability in the types of rules – though they have migrated to emerging markets to a considerable degree.

Credit Constraints in Education

Abstract: We review studies of the impact of credit constraints on the accumulation of human capital. Evidence suggests that credit constraints are increasingly important for schooling and other aspects of households' behavior. We highlight the importance of early childhood investments, since their response largely determines the impact of credit constraints on the overall lifetime acquisition of human capital. We also review the intergenerational literature and examine the macroeconomic impacts of credit constraints on social mobility and the income distribution.A common limitation across all areas of the human capital literature is the imposition of ad hoc constraints on credit. We propose a more careful treatment of the structure of government student loan programs as well as the incentive problems underlying private credit. We show that endogenizing constraints on credit for human capital helps explain observed borrowing, schooling, and default patterns and offers new insights about the design of government policy.

Conditional Heteroscedasticity in Qualitative Response Models of Time Series: A Gibbs-Sampling Approach to the Bank Prime Rate

Abstract: Previous time series applications of qualitative response models have ignored features of the data, such as conditional heteroscedasticity, that are routinely addressed in time series econometrics of financial data. This article addresses this issue by adding Markov-switching heteroscedasticity to a dynamic ordered probit model of discrete changes in the bank prime lending rate and estimating via the Gibbs sampler. The dynamic ordered probit model of Eichengreen, Watson, and Grossman allows for serial autocorrelation in probit analysis of a time series, and this article demonstrates the relative simplicity of estimating a dynamic ordered probit using the Gibbs sampler instead of the Eichengreen et al. maximum likelihood procedure. In addition, the extension to regime-switching parameters and conditional heteroscedasticity is easy to implement under Gibbs sampling. The article compares tests of goodness of fit between dynamic ordered probit models of the prime rate that have constant variance and condition...

FRED-QD: A Quarterly Database for Macroeconomic Research

Abstract: In this paper we present and describe a large quarterly frequency, macroeconomic database. The data provided are closely modeled to that used in Stock and Watson (2012a). As in our previous work on FRED-MD, our goal is simply to provide a publicly available source of macroeconomic “big data” that is updated in real time using the FRED database. We show that factors extracted from this data set exhibit similar behavior to those extracted from the original Stock and Watson data set. The dominant factors are shown to be insensitive to outliers, but outliers do affect the relative influence of the series as indicated by leverage scores. We then investigate the role unit root tests play in the choice of transformation codes with an emphasis on identifying instances in which the unit root-based codes differ from those already used in the literature. Finally, we show that factors extracted from our data set are useful for forecasting a range of macroeconomic series and that the choice of transformation codes can contribute substantially to the accuracy of these forecasts.