Art Prices As Business Cycle Indicator

Master's Thesis from the year 2015 in the subject Economics - Macro-economics, general, grade: 1,0, University of Hamburg, language: English, abstract: “When bankers get together for dinner, they discuss Art. When artists get together for dinner they discuss money.” (Oscar Wilde) Works of art are unique and highly heterogeneous but if they are traded, they share the common purpose of creating income. However, not only artists will discuss money at dinner, also bankers while they discuss art, are likely to talk about financial gains through investments in art. In economics a small group of researchers has examined whether this kind of investment is profitable or not. Although findings are not consistent, some authors conclude that art, compared to equity or bonds, does perform relatively well and offers diversification benefits in investment portfolios. Despite the inconsistency of findings, this research has led to a growing interest in art investment. Promoters of art investment like art investment funds work on a transformation of art into a new and widely accepted asset class, which they hope will prospectively be included in investment portfolios in the same way as real estate (Picinati di Torcello (2012): 15). Investment in art is determined by the expected price appreciation of art works in the future (Stein (1977): 1021). The quantity of original artworks, at least by deceased artists, cannot be augmented and the elasticity of supply is zero (Baumol (1986): 10). The future prices of art works as investment goods will thus depend on demand as well as on wealth of individuals and institutions at the sales date (Goetzmann (1993): 1371). The greater the purchasing power of prospective buyers, the more art is being bought and the higher art prices will be (Goetzmann et al. (2009): 2). Consequently art prices are expected to react to changes in economic prosperity and to fluctuate in the course of the business cycle. Business cycle research is a vital branch of macroeconomics and many theories and studies exist which examine the boom and bust periods of the economy as different phases of business cycles. Contrary there is little research which looks at “the link between the art market and the broader economy” (ibid: 4).This master thesis aims at contributing insights on this link by analysing the behavior of art prices under different macroeconomic conditions. Precisely, the objective is to assess the characteristics of art prices as business cycle indicator for the U.S. economy. [...]

This study presents a Business Intelligence (BI) approach to forecast daily changes in 27 stocks’ prices from 8 industries. The BI approach uses a financial data mining technique specifically Neural Network to assess the feasibility of financial forecasting compared to regression model using ordinary least squares estimation method. We used eight indicators such as macroeconomic indicators, microeconomic indicators, political indicators, market indicators, market sentiment indicators, institutional investor, business cycles, and calendar anomaly to predict changes in stocks’ prices. The results shows NN model better predicts stock prices with up to 92% of forecasting accuracy.

An overview of the macroeconomic forecasting industry in the United States that explains and evaluates the forecasting techniques used to make predictions about various aspects of the national economy.

Widening the focus from the usual business forecasts, explains the techniques for predicting macroeconomic factors such as economic growth, interest rates, and employment. Reviews the concepts of business cycles and long waves, then describes techniques using economic indicators, time series, econometric models, and consensus. Also considers the evaluation of forecasts. Readers with a solid background in mathematics and statistics should learn now to make forecasts; others should get an intuitive understanding that will improve their interpretation of forecasts by others. Paper edition (unseen), $29.95. Annotation copyright by Book News, Inc., Portland, OR

The inability of forecasters to predict accurately the 1990-1991 recession emphasizes the need for better ways for charting the course of the economy. In this volume, leading economists examine forecasting techniques developed over the past ten years, compare their performance to traditional econometric models, and discuss new methods for forecasting and time series analysis.