Fast & furious: Do psychological and legal factors affect commodity price volatility?

Abstract

Funding informationBundesministerium für Wirtschaftliche Zusammenarbeit und ; Entwicklung K E Y W O R D Scommodities, economic policy uncertainty, regulatory regimes | INTRODUCTIONFollowing the dot.com crash in 2001 and fuelled by the high diversification opportunities, low correlations with stocks and bonds, and the 'safe haven' characteristics they offered (Ali, Bouri, Czudaj,

Message in a bottle: Forecasting wine prices

“…Models based on Michigan consumer surveys, order inventories, interest rates, and exchange rates data deliver the best performances, especially for horizons above 1 year. Some of these results corroborate a strand of the literature that suggests the importance of psychological and sentiment aspects in influencing commodity markets and price forecasts (e.g., Algieri, 2021;Andreasson et al, 2016;Shiller, 2003). Other results are in line with intuitions.…”

Can commodity prices predict stock market returns? The case of dry bulk shipping companies

“…Moreover, while Angelopoulos et al (2019), provide evidence on the mixed signs between lead and lag times between commodity prices and freight rates, one must bear in mind that since the financialization of commodities (Basak and Pavlova 2016;Bruno et al 2017;Henderson et al 2015) the latter are not only affected by the supply and demand of the product itself but also from the market sentiment for each commodity. As studies have shown, both psychological factors and the de-regulation of the markets have increased the volatility of the markets (Algieri 2021). This de-regulation has helped academics construct commodity market sentiment indices that rely on both statistical and financial variables (such as skewness and IPO's) to capture the phenomenon (Baker and Wurgler 2007;Gao and Süss 2015).…”

Financial Speculation Impact on Agricultural and Other Commodity Return Volatility: Implications for Sustainable Development and Food Security

“…Long-run speculation is described by the number of noncommercial positions held, whereas short-run speculation is described by trading activity. Two economic theories that investigate the impact of speculation on financial market prices are effective market hypotheses [44][45][46][47] and behavioral theories [48][49][50]. On the one hand, speculators provide new information to commodity markets; on the other hand, they have different motivations than conventional corporate users who hedge against price risk, and their behavior patterns may lead to commodity prices varying from their underlying fundamental value.…”

“…Various methodological frameworks have been used to investigate the interplay between the financial markets, speculation in derivatives, and the agricultural commodities markets. This includes methods used for time-series analysis: the Johansen cointegration test [63], the Granger non-causality test [63,64], vector autoregression (VAR) models [65], nonparametric regression tests [65], the autoregressive distributed lag (ARDL) model [66], the generalized autoregressive conditional heteroskedasticity (GARCH) model [19,50], panel Granger non-causality analysis [22], the vector error correction model (VECM) [63,67], the dynamic conditional correlation (DCC) GARCH model [68,69], the stochastic volatility (SV) model [70,71], the standard heterogeneous autoregressive (HAR) model [72,73], the structural vector autoregressive (SVAR) model [1,34], the continuous Granger non-causality test [74], and quantile regression models [75,76].…”