Derivatives are alternative financial instruments which extend traders opportunities to achieve some financial goals. They are risk management instruments that are related to a data in the future, and also they react to uncertain prices. Study on pricing futures can provide useful tools to understand the stochastic behavior of prices to manage the risk of price volatility. Thus, this study eval...

FEWS NET is a USAID-funded activity. The authors' views expressed in this publication do not necessarily reflect the view of the United States Agency for International Development or the United States Government. Anomaly – is a deviation from the norm or average. Arbitrage – is taking advantage of a price differential. The two most common types of arbitrage related to food security are spatial ...

Endogenous variables in structural models of agricultural commodity markets are typically treated as stationary. Yet, tests for unit roots have rather frequently implied that commodity prices are not stationary. This seeming inconsistency is investigated by focusing on alternative specifications of unit root tests. We apply various specifications to Illinois farm prices of corn, soybeans, barro...

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Commodity prices are often thought to have in‡ationary consequences but formal statistical evidence in support of this perception has been far from robust. In this paper, we provide evidence that the two leading principal components in a panel of 23 commodity convenience yields have statistically and quantitatively important predictive power for in‡ation even after controlling for unemployment ...

This paper provides evidence that the two leading principal components in a panel of 23 commodity convenience yields have statistically and quantitatively important predictive power for inflation even after controlling for unemployment gap and oil prices. The results hold up in out-of-sample forecasts, across forecast horizons, and across G7 countries. The convenience yields also explain commod...

A new machine learning approach for price modeling is proposed. The use of neural networks as an advanced signal processing tool may be successfully used to model and forecast energy commodity prices, such as crude oil, coal, natural gas, and electricity prices. Energy commodities have shown explosive growth in the last decade. They have become a new asset class used also for investment purpose...

Open interest in commodity futures, which signals commodity market activity, contains information about future commodity and bond prices. High open-interest growth predicts high commodity-price inflation, a rising short rate, and low bond returns. Open interest is a more powerful predictor of commodity prices than the short rate, the yield spread, basis, and hedging pressure. While highly corre...

Commodity prices are important both as a source of shocks and for the propagation of shocks originating elsewhere in the economy. Many vector autoregression (VAR) studies estimate a gradual response of commodity prices to monetary policy shocks. Exploiting information in high-frequency financial market data, and using the methods of Rigobon and Sack (2004) I find that a 10 basis point surprise ...

Agricultural commodity futures prices play a significant role in the change tendency of these spot prices and the supply–demand relationship of global agricultural product markets. Due to the nonlinear and nonstationary nature of this kind of time series data, it is inevitable for price forecasting research to take this nature into consideration. Therefore, we aim to enrich the existing researc...