State-Dependent Computation Using Coupled Recurrent Networks

Although conditional branching between possible behavioral states is a hallmark of intelligent behavior, very little is known about the neuronal mechanisms that support this processing. In a step toward solving this problem, we demonstrate by theoretical analysis and simulation how networks of richly interconnected neurons, such as those observed in the superficial layers of the neocortex, can embed reliable, robust finite state machines. We show how a multistable neuronal network containing a number of states can be created very simply by coupling two recurrent networks whose synaptic weights have been configured for soft winner-take-all (sWTA) performance. These two sWTAs have simple, homogeneous, locally recurrent connectivity except for a small fraction of recurrent cross-connections between them, which are used to embed the required states. This coupling between the maps allows the network to continue to express the current state even after the input that elicited that state iswithdrawn. In addition, a small number of transition neurons implement the necessary input-driven transitions between the embedded states. We provide simple rules to systematically design and construct neuronal state machines of this kind. The significance of our finding is that it offers a method whereby the cortex could construct networks supporting a broad range of sophisticated processing by applying only small specializations to the same generic neuronal circuit

The effect of asymmetries on stock index return value-at-risk estimates

It is widely accepted that equity return volatility increases more following negative shocks rather than positive shocks. However, much of value-at-risk (VaR) analysis relies on the assumption that returns are normally distributed (a symmetric distribution). This article considers the effect of asymmetries on the evaluation and accuracy of VaR by comparing estimates based on various models

The macroeconomics of a financial Dutch disease

We describe the medium-run macroeconomic effects and long-run development consequences of a financial Dutch disease that may take place in a small developing country with abundant natural resources. The first move is in financial markets. An initial surge in foreign direct investment targeting natural resources sets in motion a perverse cycle between exchange rate appreciation and mounting short- and medium-term capital flows. Such a spiral easily leads to exchange rate volatility, capital reversals, and sharp macroeconomic instability. In the long run, macroeconomic instability and overdependence on natural resource exports dampen the development of nontraditional tradable goods sectors and curtail labor productivity dynamics. We advise the introduction of constraints to short- and medium-term capital flows to tame exchange rate/capital flows boom-and-bust cycles. We support the implementation of a developmentalist monetary policy targeting competitive nominal and real exchange rates in order to encourage product and export diversification