Related papers: Investigating Wheat Price with a Multi-Agent Model
We study the effect of globalization of world economy between 1980 and 2010 by using network analysis technics on trade and GDP data of 71 countries in the world. We draw results distinguishing relatively developing and relatively developed…
Emerging geopolitical risks have begun to threaten global supply chains, including those that produce life-saving drugs. Export bans may prevent a company from shipping products internationally, and it is unclear how these new dynamics may…
Traditional competitive markets do not account for negative externalities; indirect costs that some participants impose on others, such as the cost of over-appropriating a common-pool resource (which diminishes future stock, and thus…
The intention of this research is to study and design an automated agriculture commodity price prediction system with novel machine learning techniques. Due to the increasing large amounts historical data of agricultural commodity prices…
According to Eurostat estimates, the overall number of farms in Europe declined of about 3 million units between 2010 and 2020. Parallel, the agricultural standard output increased from 304 billion to nearly 360 billion over the same…
Wild oat (Avena fatua L.) is widely recognized as one of the most detrimental grassy weeds in winter wheat production systems globally. While chemical control remains the dominant strategy, the reliance on herbicides without considering…
There are several approaches to modeling and forecasting time series as applied to prices of commodities and financial assets. One of the approaches is to model the price as a non-stationary time series process with heteroscedastic…
We propose a multivariate elastic net regression forecast model for German quarter-hourly electricity spot markets. While the literature is diverse on day-ahead prediction approaches, both the intraday continuous and intraday call-auction…
In this paper, we analyze the long-term distributive impact of climate change through rising food prices. We use a standard incomplete markets model and account for non-linear Engel curves for food consumption. For the calibration of our…
We apply the recently developed reduced Google matrix algorithm for the analysis of the OECD-WTO world network of economic activities. This approach allows to determine interdependences and interactions of economy sectors of several…
We present a new model for commodity pricing that enhances accuracy by integrating four distinct risk factors: spot price, stochastic volatility, convenience yield, and stochastic interest rates. While the influence of these four variables…
This paper addresses the problem of testing for persistence in the effects of the shocks affecting the prices of renewable commodities, which have potential implications on stabilization policies and economic forecasting, among other areas.…
Global oil price is an important factor in determining many economic variables in the world's economy. It is generally modeled as a stochastic process and have been studied through different techniques by comparing the historic time series…
A crop can be viewed as a complex system with outputs (e.g. yield) that are affected by inputs of genetic, physiology, pedo-climatic and management information. Application of numerical methods for model exploration assist in evaluating the…
We propose a mathematical procedure for finding informed traders in ultra-high frequency trading. We wrote it as Vector ARMA and found condition of its stationarity. For the price exposure complied with ARMA(1,2) we proved that underlying…
In this study, we apply functional regression analysis to identify the specific within-season periods during which temperature and precipitation anomalies most affect crop yields. Using provincial data for Italy from 1952 to 2023, we…
We apply an empirical, data-driven approach for describing crop yield as a function of monthly temperature and precipitation by employing generative probabilistic models with parameters determined through Bayesian inference. Our approach is…
International trade policies have recently garnered attention for limiting cross-border exchange of essential goods (e.g. steel, aluminum, soybeans, and beef). Since trade critically affects employment and wages, predicting future patterns…
Tariff liberalization and its impact on tax revenue is an important consideration for developing countries, because they are increasingly facing the difficult task of implementing and harmonizing regional and international trade…
We carry out a detailed large-scale data analysis of price response functions in the spot foreign exchange market for different years and different time scales. Such response functions provide quantitative information on the deviation from…