This study investigates determinants of financial behavior (FB) of university students at a university in South Africa. It examines whether financial behavior, confidence, time preferences, risk preferences and financial literacy perceptions of university students differ by financial literacy level. Data were gathered via a questionnaire that included personal information, FB, financial perceptions and financial knowledge responses as well as a multiple price list (MPL) risk preferences and time preferences experiment tasks. A convenient total sample of 191 students (females = 53%) participated in the study. A t-test analysis showed that FB, risk preferences, confidence levels, time preferences and financial literacy perceptions of university students significantly differed by financial literacy level. Our results show that university students with low financial literacy levels are more overconfident, risk loving and impatient; such FB is synonymous with major causes of financial crises across the world. An OLS regression model analysis showed that the risk preferences index, financial literacy perception index and confidence significantly influenced the FB of categorized university students. The risk preference index significantly influenced debt FB of categorized university students. In order to

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In this study, we examine the dynamic comovements between housing and oil market returns in the United States over the period 1859-2013, while controlling for real gross domestic product growth, inflation, interest rates, and real stock, gold and silver returns that are known to affect both these markets. As such, we provide a bird's-eye view on the interdependencies between these two markets from a historical perspective. The results of our empirical analysis reveal that comovements between housing and oil market returns are consistently negative over time, apart from several recessions the U.S. economy experienced in the 19th century, wherein correlations were positive.

This paper investigates asymmetry in US housing price cycles at the state and metropolitan statistical area (MSA) level, using the Triples test (Randles, Flinger, Policello, & Wolfe, 1980) and the Entropy test of Racine and Maasoumi (2007). Several reasons may account for asymmetry in housing prices, including non-linearity in their determinants and in behavioural responses, in particular linked to equity constraints and loss aversion. However, few studies have formally tested the symmetry of housing price cycles. We find that housing prices are asymmetric in the vast majority of cases. Taking into account the results of the two tests, deepness asymmetry, which represents differences in the magnitude of upswings and downturns, is found in 39 out of the 51 states (including the District of Columbia) and 238 out of the 381 MSAs. Steepness asymmetry, which measures differences in the speed of price changes during upswings and downturns, is found in 40 states and 257 MSAs. These results imply that linear models are in most cases insufficient to capture housing price dynamics.