16 research outputs found

    Prediction of photoperiodic regulators from quantitative gene circuit models

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    Photoperiod sensors allow physiological adaptation to the changing seasons. The external coincidence hypothesis postulates that a light-responsive regulator is modulated by a circadian rhythm. Sufficient data are available to test this quantitatively in plants, though not yet in animals. In Arabidopsis, the clock-regulated genes CONSTANS (CO) and FLAVIN, KELCH, F-BOX (FKF1) and their lightsensitive proteins are thought to form an external coincidence sensor. We use 40 timeseries of molecular data to model the integration of light and timing information by CO, its target gene FLOWERING LOCUS T (FT), and the circadian clock. Among other predictions, the models show that FKF1 activates FT. We demonstrate experimentally that this effect is independent of the known activation of CO by FKF1, thus we locate a major, novel controller of photoperiodism. External coincidence is part of a complex photoperiod sensor: modelling makes this complexity explicit and may thus contribute to crop improvement

    Spurious long memory, uncommon breaks and the implied–realized volatility puzzle

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    One of the puzzles in international finance is the frequent finding that implied volatility is a biased predictor of realized volatility. However, given asset price volatility is often characterized as possessing long memory, the recent literature has shown that allowing for long-range dependence removes this bias. Of course, the appearance of long memory can be generated by the presence of structural breaks. This paper discusses the effect of structural breaks on the implied-realized volatility relation. Simulations show that if significant structural breaks are omitted, testing can spuriously show the typical patterns of fractional cointegration found in the literature. Next, empirical results show that foreign exchange implied and realized volatility contains structural breaks. The breaks in the implied series never closely anticipate or co-occur with those of the realized series, suggesting that the market has no ability to forecast structural change. When breaks are accounted for in the bi-variate framework, the point estimate of the slope parameter falls and the null of unbiasedness can be rejected. Allowing for structural breaks suggests that the implied-realized volatility puzzle might not be solved after all

    CCPs and network stability in OTC derivatives markets

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    Among the reforms to OTC derivative markets since the global financial crisis is a commitment to collateralize counterparty exposures and to clear standardized contracts via central counterparties (CCPs). The reforms aim to reduce interconnectedness and improve counterparty risk management in these important markets. At the same time, however, the reforms necessarily concentrate risk in one or a few nodes in the financial network and also increase institutions’ demand for high-quality assets to meet collateral requirements. This paper looks more closely at the implications of increased CCP clearing for both the topology and stability of the financial network. Building on Heath et al. (2013) and Markose (2012), the analysis supports the view that the concentration of risk in CCPs could generate instability if not appropriately managed. Nevertheless, maintaining CCP prefunded financial resources in accordance with international standards and dispersing any unfunded losses widely through the system can limit the potential for a CCP to transmit stress even in very extreme market conditions. The analysis uses the Bank for International Settlements Macroeconomic Assessment Group on Derivatives (MAGD) data set on the derivatives positions of the 41 largest bank participants in global OTC derivative markets in 2012

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