Related Articles

Power price stability and the insurance value of renewable technologies

To understand if renewables stabilize or destabilize electricity prices, we simulate European power markets as projected by the National Energy and Climate Plans for 2030 but replicating the historical variability in electricity demand, the prices of fossil fuels and weather. We propose a β-sensitivity metric, defined as the projected increase in the average annual price of electricity when the price of natural gas increases by 1 euro. We show that annual power prices spikes would be more moderate because the β-sensitivity would fall from 1.4 euros to 1 euro. Deployment of solar photovoltaic and wind technologies exceeding 30% of the 2030 target would lower it further, below 0.5 euros. Our framework shows that this stabilization of prices would produce social welfare gains, that is, we find an insurance value of renewables. Because market mechanisms do not internalize this value, we argue that it should be explicitly considered in energy policy decisions.

Unequal roles of cities in the intercity healthcare system

Cities are increasingly interdependent regarding healthcare provision and demand. However, the intercity healthcare system (IHS) behind the nationwide patient mobility remains insufficiently understood. Here, leveraging human mobility big data, we reveal cities’ roles in providing and demanding quality healthcare within the IHS of China. We find that 8% of Chinese cities are national and regional hubs that address the healthcare shortage of cities deprived of quality healthcare, while 63% of the cities that are unnoticed compensate for migrant workers being denied healthcare rights in megacities. The IHS generates new structural inequalities in healthcare access exhibiting a Matthew effect. The few cities (12%) that are already rich in healthcare resources benefit more and can strengthen their advantages in providing healthcare to local populations (32% of China’s total population). The many cities (35%), while facing healthcare shortages, are further disadvantaged in ensuring adequate healthcare for their local populations (26% of China’s total population).

An artificial market model for the forex market

As financial markets have transitioned toward electronic trading, there has been a corresponding increase in the number of algorithmic strategies and degree of transaction frequency. This move to high-frequency trading at the millisecond level, propelled by algorithmic strategies, has brought to the forefront short-term market reactions, like market impact, which were previously negligible in low-frequency trading scenarios. Such evolution necessitates a new framework for analyzing and developing algorithmic strategies in these rapidly evolving markets. Employing artificial markets stands out as a solution to this problem. This study aims to construct an artificial foreign exchange market referencing market microstructure theory, without relying on the assumption of information or technical traders. Furthermore, it endeavors to validate the model by replicating stylized facts, such as fat tails, which exhibit a higher degree of kurtosis in the return distribution than that predicted by normal distribution models. The validated artificial market model will be used to simulate market dynamics and algorithm strategies; its generated rates could also be applied to pricing and risk management for currency options and other foreign exchange derivatives. Moreover, this work explores the importance of order flow and the underlying factors of stylized facts within the artificial market model.

Responses

Your email address will not be published. Required fields are marked *