Prediction of NFT Sale Price Fluctuations on OpenSea Using Machine Learning Approaches

The rapid expansion of the non-fungible token(NFT)market has attracted many investors.However,studies on the NFT price fluctuations have been relatively limited.To date,the machine learning approach has not been used to demonstrate a specific error in NFT sale price fluctuation prediction.The aim of this study was to develop a prediction model for NFT price fluctuations using the NFT trading information obtained from OpenSea,the world’s largest NFT marketplace.We used Python programs to collect data and summarized them as:NFT information,collection information,and related account information.AdaBoost and Random Forest(RF)algorithms were employed to predict the sale price and price fluctuation of NFTs using regression and classification models,respectively.We found that the NFT related account information,especially the number of favorites and activity status of creators,confer a good predictive power to both the models.AdaBoost in the regression model had more accurate predictions,the root mean square error(RMSE)in predicting NFT sale price was 0.047.In predicting NFT sale price fluctuations,RF performed better,which the area under the curve(AUC)reached 0.956.We suggest that investors should pay more attention to the information of NFT creators.We anticipate that these prediction models will reduce the number of investment failures for the investors.

Study on Vegetable Price Fluctuation and Its Impact in Guangxi

Vegetables,as one of the most important non-staple foods in the daily consumption of Chinese residents,are closely related to the life of urban residents. The fluctuation of regional vegetable prices has a negative effect on producers and consumers. Relevant research on vegetable price fluctuations has been carried out,which provides a corresponding basis for realizing the balance of supply and demand in the agricultural products market within Guangxi,and for government departments to macro-regulate agricultural production and optimize the agricultural industrial structure.

Analysis of Pig Price Fluctuation in Recent Decade Based on the Changes in Breeding Scale

In recent decade, the fluctuation of pig price has become more and more acute with obvious periodicity. Currently, the pig breeding mode dominated by individual households leads to acute fluctuation of pig price to some extent. The scale expansion of recent decade intensified the fluc- tuation of pig price in the short term but will stabilize the price in the long term. Therefore. it is necessary to expand breeding scale for maintaining long-term price stability and the optimal scale should be chosen according to the circumstances to ensure the social benefit maximization.

Pig Price Fluctuations and Forecasting Model Based on Information Platform

Pork is common in people's daily life consumption,and it accounts for more than half of all meats. By collecting data information published by Bureau of Statistics and Bureau of Agriculture,this paper makes a statistical analysis of the influence of price fluctuation in the pork market on China's pork production,and finds that China's pork production shows a general trend of fluctuations due to the impact of price factors.According to the predecessors' studies on the factors influencing pig market price,combined with the actual situation of pig breeding in China,this paper uses the latest website data released by the government's public information platform to establish a forecasting model.

Impact and Policy Implications of Swine Epidemic on Price Fluctuation of Livestock Products in China

The drastic price fluctuation of livestock products caused by frequent swine epidemics has seriously affected the stable and healthy development of the livestock product market.It is important to develop strategies for the stability and development of livestock product market by understanding the impact of swine epidemic on the price of livestock products.Therefore,we systematically analyzed the impact of the swine epidemic on the price of livestock products in China based on monthly data from February 2009 to July 2020 using the factor augmented vector autoregression(FAVAR)model.The results showed that:(i)During the swine epidemic,the price of pork first showed a negative response and then a positive response,while the price of other livestock products showed positive response overall.(ii)The price of pork was the most affected by the swine epidemic,followed by price of chicken.Price fluctuation of beef and mutton was similar,and the price response of eggs and fresh milk was relatively smaller.Based on these results,we put forward policy suggestions for stabilizing the price of livestock products in China during swine epidemic from the aspects of improving the defense system and guiding consumption scientifically.

Theory Analysis of Model for Price Fluctuations in a Single Commodity Market

The price model for a single commodity market is a very important economic model that describes the basic rules for price fluctuations in a single commodity market. In this paper, we investigated the general case for the model, and proved that every positive solution is bounded and we obtained a necessary and sufficient condition for oscillation of every positive solution concerning positive state solution.

Impact of Sharp Fluctuations of Live Pig Prices on Financial Capacity of Pig Breeding Enterprises : An Analysis Based on the Data of Listed Enterprises from 2018 to 2021

Based on the general equilibrium theory of microeconomics,this study first analyzed the causes of sharp fluctuations in live pig prices,and then explored the financial capabilities of enterprises during the sharp fluctuations of live pig prices by using the financial data of 4 typical top listed enterprises from 2018 to 2021.By comparing the changes in the capabilities of enterprises,the impact of price on the financial capability of enterprises and differences were identified.The research results showed that the price of live pigs played a decisive role in enterprise profits,and there were huge differences in the fluctuation period.In the sharp increase period of price,price temptation is easy to cause enterprises to over-invest,resulting in excessive growth of enterprise assets,and increasing the business risk of enterprises.Based on the above conclusions,some policy suggestions were put forward to promote the stable development of industry from the three levels of enterprises,industries and government departments.

Prediction of metal futures price volatility and empirical analysis based on symbolic time series of high-frequency

The metal futures price fluctuation prediction model was constructed based on symbolic high-frequency time series using high-frequency data on the Shanghai Copper Futures Exchange from July 2014 to September 2018,and the sample was divided into 194 histogram time series employing symbolic time series.The next cycle was then predicted using the K-NN algorithm and exponential smoothing,respectively.The results show that the trend of the histogram of the copper futures earnings prediction is gentler than that of the actual histogram,the overall situation of the prediction results is better,and the overall fluctuation of the one-week earnings of the copper futures predicted and the actual volatility are largely the same.This shows that the results predicted by the K-NN algorithm are more accurate than those predicted by the exponential smoothing method.Based on the predicted one-week price fluctuations of copper futures,regulators and investors in China’s copper futures market can timely adjust their regulatory policies and investment strategies to control risks.

药品价格指数的构建与应用

目的基于药品零售价格大数据构建药品价格指数,描述其波动特征,发挥其药品价格宏观监管作用,促进药品价格保持合理水平。方法运用链式拉氏指数构建原理建立药品价格指数模型,运用时间序列模型描述指数波动特征,识别并分析药品价格波动异常状况。结果2015年1月—2020年12月,药品价格总指数小幅上涨,累计涨幅为14.43%,年均涨幅约2.40%,市场化改革成效较为显著。通过基于局部加权回归的季节趋势分解(seasonal-trend decomposition using loess,STL)方法对获得的药品价格总指数时间序列进行分析,指数呈长期平缓上升趋势,不规则波动值为-1.41~2.03,说明药品价格受外因影响较小,周期性特征仍有待进一步研究。2015年1月—2020年12月,根据药品价格指数共监测到价格异常风险32次。结论药品价格指数较全面地反映药品价格走势,对于药品价格异常波动具有一定的预警作用,能够为我国药品价格监管提供有效工具。

Study on the investment value and investment opportunity of renewable energies under the carbon trading system

China has promised to start the national carbon trading system in 2017.In the carbon trading system,the renewable energy projects may obtain additional benefits through the Certified Carbon Emission Reduction(CCER) trade.As the carbon price fluctuates along with the market conditions,such fluctuation enables the renewable power projects to acquire the rights of an option,i.e.it may contain an even higher value due to the uncertainties in the future.While making an investment decision,the renewable power companies may choose to make the investment immediately,or postpone the investment and accumulate more information to increase the return of investment;and for immediate investments,the return must be sufficient to exceed the potential value of a waiting option.To study the investment in renewable power projects subject to the fluctuation of carbon price,this paper adopts the trinomial tree model of real options to estimate the net present value(NPV) and real option value(ROV) of three types of renewable power projects;according to the decision-making rules of real options to defer,all the three types of projects will exercise the option to postpone the investment decision.This thesis also calculates the benchmark prices of the three types of renewable projects at different times,in the two situations of having no government subsidy and having the government subsidy,so as to determine the investment opportunity of a project.The benchmark price decreases gradually along with the increase of government subsidy,indicating that the government subsidy will stimulate the investment in renewable projects.The benchmark price also increases gradually along with the lapse of time,indicating that the uncertainty will increase together with the time span and thus requires an even higher carbon price to determine the investment opportunity.This thesis also analyzes the sensitivity of factors affecting the investment in renewable projects and draws the conclusion that the fluctuation of carbon price is positively related with the benchmark price of renewable power projects,which indicates that the fluctuation of carbon price increases the option value of an investment but postpones the time of investment.As the China's carbon trading system improves gradually,the carbon price will reach a stable status,thus stimulate the power companies to invest in the renewable projects.

Optimal portfolio design of energy storage devices with financial and physical right market

With the continuous development of the spot market,in the multi-stage power market environment with the day-ahead market and right market,the study associated with the portfolio of energy storage devices requires that attention should be paid to transmission congestion and power congestion.To maximize the profit of energy storage and avoid the imbalance of power supply and consumption and the risk of node price fluctuation caused by transmission congestion,this paper presents a portfolio strategy of energy storage devices with financial/physical contracts.First,the concepts of financial/physical transmission rights and financial/physical storage rights are proposed.Then,the portfolio models of financial contract and physical contract are established with the conditional value-at-risk to measure the risks.Finally,the portfolio models are verified through the test data of the Pennsylvania-New Jersey-Maryland(PJM)electric power spot market,and the comparison between the risk aversion of portfolios based on financial/physical contract with the portfolio of the market without rights.The simulation results show that the portfolio models proposed in this paper can effectively avoid the risk of market price fluctuations.