Deep Calibration of Market Simulations using Neural Density Estimators and Embedding Networks

The ability to construct a realistic simulator of financial exchanges, including reproducing the dynamics of the limit order book, can give insight into many counterfactual scenarios, such as a flash crash, a margin call, or changes in macroeconomic outlook. In recent years, agent-based models have been developed that reproduce many features of an exchange, as summarised by a set of stylised facts and statistics. However, the ability to calibrate simulators to a specific period of trading remains an open challenge. In this work, we develop a novel approach to the calibration of market simulators by leveraging recent advances in deep learning, specifically using neural density estimators and embedding networks. We demonstrate that our approach is able to correctly identify high probability parameter sets, both when applied to synthetic and historical data, and without reliance on manually selected or weighted ensembles of stylised facts.Comment: 4th ACM International Conference on AI in Finance (ICAIF 2023

Analysis of Arsenic Speciation Distribution in Agaric, Shiitake Mushroom, Matsutake and Agrocybe by IC-ICP-MS Method

To analyze the speciation distribution of arsenic in agaric, shiitake mushroom, matsutake and agrocybe, the ion chromatography-inductive coupled plasma mass spectrometer (IC-ICP-MS) was used to determine arsenobetaine, dimethyl arsenic, arsenous acid, arsenic choline, monomethyl arsenic and arsenic acid, and the methodological investigation and content determination were carried out. The results showed that the method could completely separate all six arsenic forms within 5 minutes, and the peak patterns were good. The linear relationship of the method was good (mass concentration of 0.5~20 μg/L, r>0.999). The detection limit and quantification limit of six arsenic species were not more than 0.005 and 0.017 mg/kg respectively. The recovery rate of six arsenic forms in agaric, agrocybe and shiitake mushroom could reach 80%~120% with standard addition. For matsutake, the standard addition recovery rate could also reach 80%~120% when adding right standard amounts (0.05 mg/kg dimethyl arsenic, arsenic choline and arsenic acid; 0.2 mg/kg arsenite and monomethyl arsenic; 5 mg/kg arsenic betaine). Combined with the dehydration rate of dry products, the inorganic arsenic content of the tested samples met the requirements of GB 2762-2022. The content of total arsenic in matsutake was the highest, but the proportion of inorganic arsenic（arsenic choline+arsenic acid） in total arsenic was the lowest 3.6%~6.8%, and the highest proportion was arsenobetaine (75.8%~87.3%). The main form of arsenic in agaric, agrocybe, and shiitake mushroom were inorganic arsenic. The proportion of inorganic arsenic to total arsenic could reach 58.4%~66.1%、60.0%~66.7%、81.2%~91.7%, respectively. There was a risk of food safety when the total arsenic content was high