Dutch Flower Still Life of 17th Century: Interest and Oblivion through the Centuries

Over three and a half centuries, the genre of flower still life created by Dutch artists experienced ups of interest and oblivion. There were the maximum assessment of society in the form of high fees of the 17th century artists; the criticism of connoisseurs and art theorists; the neglect in the 19th century and the rise of auction prices and close attention of art critics, manifested from the middle of the 20th century to the present day. In the middle of the 17th century, there was already a hierarchy of genres, based on both the subject and the size of the paintings, which was reflected in the price. Still lifes and landscapes were cheaper than allegorical and historical scenes, but there were exceptions, for example, in the works of Jan Brueghel the Elder and Jan Davidsz. de Heem. Art theorists Willem van Hoogstraten and Arnold Houbraken, resting upon academic tastes, downplayed the importance of still-life painting. Meanwhile, the artists themselves, determining the worth of their paintings, sought for maximum naturalism, and such paintings were sold well.In the 20th century, this genre attracted the attention of collectors in Europe and the United States. A revival of interest in Dutch still lifes in general, and in flower ones in particular, began in the 20th century, the paintings rose in price at auctions, and collecting them became almost a fashion. Art societies and art dealers of the Netherlands and Belgium organized several small exhibitions of still lifes. The course for studying symbolic messages in still lifes, presented by Ingvar Bergström, is continued by Eddie de Jong, who emphasizes the diverse nature of symbolism in Dutch painting of the 17th century. Svetlana Alpers, on the contrary, criticizes the iconological method and presents the Dutch painting of that period as an example of visual culture. Norman Bryson’s view of Dutch still lifes is formed against the background of the development of a consumer society, economic prosperity and abundance. Finally, there has been an increasing interest in the natural science aspects of flower still-life painting in the researches of the last twenty years. Curiosity, skill, and admiration for nature are the impulses that can still be felt in the images of bouquets and fruits.

An Empirical Study on Forecasting Production and Price of Tea in India

Tea is a very indispensable beverage for Indian population as we rank the world’s largest consumer of black tea. Indian tea industry had been facing many downfalls for the past few years in terms of low price, excess supply, losing flavour and all this as a whole had affected the performance of the tea industry in India. With India being the second largest producer of tea globally, the production of tea in India can be subdivided into North India and South India. The current study focuses on the comparative analysis between North India, South India and India in terms of their trends in area, production, yield, export quantity, export price, auction price and auction quantity of tea. Compounded Annual growth rate (CAGR) was the tool used to find the trends of various variables. This study also focuses on the forecasting the production and auction prices of tea in India till 2023using Autoregressive Integrated Moving Average (ARIMA) model. The results of the present study areindicating that all the variables like area, production, yield, export quantity, export price, auction price and auction quantity of tea had shown a positive trend annually, except for that of North India’s export quantity. Production and auction prices were forecasted till 2023 using different ARIMA models amongst which ARIMA (1,1,0) proved to be the best fit model for study period.

What Type of Title Would You Put on Your Paintings?: The Impact on the Price of Artwork According to Its Title

This paper investigated the impact of the type of title on the price of the artwork effects using the hammer price of the paintings auctioned in Korea during a two-year period from December 2017 to November 2019. The results of the analysis showed that a descriptive title had a negative effect on the prices fetched, whereas a more elaborate title had a positive effect on auction prices. Also, it was found that elaborate titles for abstract paintings had a significant positive impact on the hammer price. In the case of unknown artists, a descriptive title had a negative effect on the auction price, while the absence of a title had a positive impact. The findings of this study suggest that artists must make careful decisions when titling their work because the title of the work affects the purchase decisions of art collectors.

Intraday Electricity Pricing of Night Contracts

This paper investigates the intraday electricity pricing of 15-min. contracts in night hours. We tailor a recently introduced econometric model with fundamental impacts, which is successful in describing the pricing of day contracts. Our estimation results show that the mean reversion and the positive price impact of neighboring contracts are generic features of the price formation process on the intraday market, independent of the time of day. Intraday auction prices have higher explanatory power for the pricing of night than day contracts, particularly, for the first and last 15-min. contract in a night hour. Intradaily updated forecasts of wind power infeed are the only significant fundamental factors for intraday electricity prices at night. Neither expected conventional capacities nor the slope of the merit order curve contribute to explaining price dynamics. Overall, we conclude that fundamentals lose in importance in night hours and the 15-min. intraday market is rather driven by price information.

Developing a Forecasting Model for Real Estate Auction Prices Using Artificial Intelligence

The real estate auction market has become increasingly important in the financial, economic and investment fields, but few artificial intelligence-based studies have attempted to forecast the auction prices of real estate. The purpose of this study is to develop forecasting models of real estate auction prices using artificial intelligence and statistical methodologies. The forecasting models are developed through a regression model, an artificial neural network and a genetic algorithm. For empirical analysis, we use Seoul apartment auction data from 2013 to 2017 to predict the auction prices and compare the forecasting accuracy of the models. The genetic algorithm model has the best performance, and effective regional segmentation based on the auction appraisal price improves the predictive accuracy.