Machine Learning Model Approaches for Price Prediction in Coffee Market using Linear Regression, XGB, and LSTM Techniques

Investors and other business persons have a desire to know about the future market price because, if the investors know about the future price of a certain commodity or stock it will help them to make appropriate business decisions and they can also get profit out of their investment. There are many previous researches that has been done on stock market predictions but there is no related research that has been done on Ethiopia commodity exchange (ECX). Performing future price prediction with better accuracy and performing comparative analysis between the algorithms for two of Ethiopia commodity exchange (ECX) items which are Coffee and Sesame as the research key objectives. Three different types of prediction algorithms to predict the future price, such as Linear Regression (LR), Extreme Gradient Boosting (XGB), Long Short-Term Memory (LSTM) was utilized. There are limited researches worked on price prediction of ECX items specifically, the idea of the price prediction on different Stock markets like New York stock market Exchange and other commodity market items prediction in order to develop our research in ECX was presented. The study apart from predicting the future price, comparative analysis was implemented between the prediction algorithms that we used based on their performance. Two different datasets from ECX: coffee and sesame were used. The reason for the utilization of these datasets is, the commodity items are the largest export items in Ethiopia which makes them very important for Ethiopian economy, and the different datasets helps us to get the advantage of evaluating the algorithms with different number of datasets, since sesame dataset has 7205 instances and coffee dataset has 1540 instances and both of them has 11 attributes. We build an android application in order two implement our algorithms on mobile applications and see if it is possible to implement the prediction algorithms on mobile platforms and make it easy and accessible to users. We call this mobile application Ethiopia Coffee Prices Predictor (ECPP). This application will be used to display the prediction result of Ethiopia Coffee price for short period and it is designed in the way to be user friendly. The programming environment used to implement the prediction algorithms is python, java programming language to design our android application and we used PHP to implement the API, and finally we used MySQL database in order to store information’s online and make them accessible everywhere.

Commodity Exchange in the First Months of Soviet Power with Participation of Consumer Cooperation (January – April, 1918)

The food crisis in Russia arose during the years of the First World War. The tsarist government and the Provisional Government tried to solve this problem, but to no avail. The food crisis, as it was by inheritance, passed to the Soviet regime. All authorities had to solve the food problem in the conditions of constant military and revolutionary upheavals, and this problem, from the socio-economic, passed into the political sphere. Famine predetermined revolutionary upheaval in the country. The article covers the period from January to April, 1918. At this time the Austro-German army advances in southern Russia. The military, political, and socio-economic situation of the new government was extremely difficult. The Soviet government had to support the grain monopoly introduced by the tsarist and confirmed by the Provisional Governments, although it was not officially confirmed and even introduced by the new government. To strengthen its position, the Soviet government took a number of measures to resolve the food problem. The most important, even the main one was the exchange of goods between the city and the village. It was necessary to save the urban population from hunger, to supply the army with food. It should be noted that the initial measures including in the exchange policy of the Soviet government were not of a violent nature. The country had industrial reserves for commodity exchange in the country: manu- factory, high-grade iron, etc. remaining from tsarism. Everything was sent to the village. There is an opinion that the Soviet government gave industrial products to the peasantry for nothing and that was true. But commodity exchange made it possible to alleviate the food crisis in the cities, feed the army, and politically strengthen the Soviet power. For the exchange of goods, it was necessary to attract various regulatory bodies of the country that were engaged in the procurement and distribution of bread. This article highlights the role of consumer cooperation, which was underexplored in the historical literature, in the commodity exchange. Specific examples, facts and figures are given for the bread producing provinces in southern Russia.

Planning and perspective: promoting international companies in the Russian market

The modern market as a sphere of commodity exchange is dynamic, extremely unstable and extremely demanding on companies. The Russian ice cream market is no exception. Due to its maturity and modest growth in consumption, it is on the verge of structural change. Medium-sized manufacturers are more active and strive to take leading positions, niche companies, which promptly respond to the latest trends, are taking increasingly strong positions.

Future–Spot Relationship in Commodity Market: A Comparison Across Commodity Segments in India

This study aims to analyse the future–spot pricing relationship in the context of most actively traded commodities traded on Multi Commodity Exchange of India, which is the leading commodity exchange in the country today. The study intends to compare the pricing relations of three popular commodity segments, that is, bullion and metal, energy and agricultural segments, to explore whether future–spot pricing relationships are similar for all commodity segments or not. The study has applied vector autoregressive (VAR) model on a sample of 13 commodities, categorized as 7 commodities from bullion and metal segment, 2 commodities from energy segment and 4 commodities from agricultural segment. The results of VAR model show that in India, the non-agricultural commodity sector constituting of bullion, metal and energy commodities behave close to each other, but the behaviour of agricultural commodities is quite different from non-agricultural commodities. As regards non-agricultural commodities, the futures market plays a quite dominant and significant role as compared to the spot markets. However, in case of agricultural commodities, the futures market has a comparatively less dominant and strong role, and their spot market also plays an equally strong role. A comparative study of the pricing relationships existing among the three commodity segments will be extremely helpful for farmers, traders, investors as well as the portfolio managers in choosing the most profitable commodity classes for trading, investment and portfolio optimization. Regulators and policymakers can plan and implement an appropriate regulatory framework to strengthen these markets, especially agricultural commodity market, to promote economic growth.

Does Sentiments Impact the Returns of Commodity Derivatives? An Evidence from Multi-commodity Exchange India

The advancements in technology, increased accessibility to various modes and platforms of communication, and increased willingness on the part of participants to share their ideas/opinions has resulted in huge amounts of data on the World Wide Web, hence, easily available to impact decision-making. Furthermore, commodity prices are primarily driven by demand and supply, wherein such news is open to the cognitive thinking of individuals. Thus, using the principles of natural language processing, which combines concepts of linguistics, computer science and artificial intelligence, helps in improving the accuracy of price determination. Therefore, this article aims to examine the relationship between sentiments conveyed through various sources and the performance of India’s largest commodity market, multi-commodity exchange (MCX). The correlation and causation between sentiment scores extracted from such textual content and the daily returns of select commodity derivatives are analysed. The results show varying levels of significance of sentiments on the returns of commodity contracts and imply that there is an increased scope of using such unstructured content in the field of finance.

Viability of Commodity Exchange in Bhutan: Assessing Challenges and Benefits

This paper investigates the viability of commodity exchange in Bhutan and identifies its essential pre-conditions. Challenges and benefits are enumerated using exploratory and qualitative research with open-ended and semi-structured interviews. Bhutan represents an emerging South-Central Asian country successful emergence of which into the global arena in the last fifty years could serve as an example for other small and developing markets. The results of this study put challenges for farmers in two categories, before and after harvest. All post-harvest challenges can be addressed through an established commodity exchange and its three pre-conditions are essential to the development of commodity exchange in Bhutan.