Forecasting spot prices of agricultural commodities in India: Application of deep-learning models

Food price fluctuations can impact both producers and consumers. Forecasting the prices of the agricultural commodities is of prime concern not only to the government but also to farmers and agribusiness firms. In developing countries like India, management of food security needs competent and efficient forecasting of food prices. With the availability of data, recent innovation in deep-learning models provides a feasible solution to accurately forecast the prices. In this study, we examine the superiority of these models using the daily spot prices of five major commodities traded on the National Commodity and Derivatives Exchange: cotton seed, castor seed, rape mustard seed, soybean seed, and guar seed. The results were obtained from the application of the traditional univariate autoregressive integrated moving average model and deep-learning techniques like the time-delay neural network (TDNN) and long short-term memory (LSTM) network. The empirical results indicate that the LSTM model is indeed suitable for the financial domain and captures the directional movement of the spot price changes with high accuracy compared with the TDNN and other linear models. Accuracy of the performance of these models has been compared using out-of-sample performance measure. The overall objective of this paper is to demonstrate the utility of spot price forecasting for farmers and traders in offering them the best predictions of the price movements. Our results provide a possibility of developing pricing models that can help in fairly regulating agricultural commodity prices.     

Soft commodities and the global financial crisis: Implications for the economy,resources and institutions

Over the past decade, soft commodities have been subjected to increasing speculative price fluctuations. Following the 2008 financial crisis, most studies have highlighted causal relationships between price volatility, derivative and future markets for underlying financial assets as well as agricultural and mineral commodities. This article investigates the multifaceted effects of unrestrained financialization of the resources and goods markets and its implications for agricultural markets and soft commodities for purposes other than direct human consumption. We place a particular emphasis on the process of commodification of food and non-food crops and their use as green source of liquid fuels (i.e. soy, sugar cane, palm oil, jatropha, and canola). It is argued that speculation in financial markets has led to spillover effects across commodity and resource markets. More importantly, speculation and price volatility in the commodity markets has had a direct bearing on the resource markets and organization and appropriation of common-pool resources. The article sheds further light on the causal relationship between derivative markets, hedging techniques, financial yields and price volatility and spillover effects in the market for food and soft commodities.     

近十年中国通货膨胀成因的实证分析

近年来,如何防范和治理通货膨胀已成为中国宏观经济领域亟需解决的一项重大课题,而治理通胀的关键在于对其形成原因的科学把握。本文选取CPI和PPI作为通货膨胀的衡量指标,以产出缺口、货币供应量、国际大宗商品价格、超额工资水平、资产价格、汇率水平六大因素作为解释变量,运用向量自回归(VAR)、脉冲响应和方差分解的方法,对2000-2011年中国通货膨胀的形成原因进行实证分析,得到了各项因素的作用大小、作用时滞和传导链条的顺序,最后提出了相应的政策建议。     

Do commodities add value in multi-asset portfolios? An out-of-sample analysis for different investment strategies

An essential motive for investing in commodities is to enhance the performance of portfolios traditionally including only stocks and bonds. We analyze the in-sample and out-of-sample portfolio effects resulting from adding commodities to a stock-bond portfolio for commonly implemented asset allocation strategies such as equally- and strategically-weighted portfolios, risk-parity, minimum-variance as well as reward-to-risk timing, mean-variance and Black–Litterman. We analyze different commodity groups such as agricultural and livestock commodities that currently are critically discussed. The out-of-sample portfolio analysis indicates that the attainable benefits of commodities are much smaller than suggested by previous in-sample studies. Hence, in-sample analyses, such as spanning tests, might exaggerate the advantages of commodities. Moreover, the portfolio gains greatly vary between different types of commodities and sub-periods. While aggregate commodity indices, industrial and precious metals as well as energy improve the performance of a stock-bond portfolio for most asset allocation strategies, we hardly find positive portfolio effects for agriculture and livestock. Consequently, investments in food commodities are not essential for efficient asset allocation.     

The role of speculation in international futures markets on commodity prices

The role of futures contracts on spot prices has been one of the key focus areas of research since the recent surge in commodity prices and increase in the volatility of commodity returns. However, no consensus arises from this literature, and hence it is difficult to link the use of futures contracts in agricultural commodities by non-hedgers and the growing food insecurity within developing countries. The purpose of this paper is to highlight causal relationships from futures contracts to spot prices of underlying assets, namely agricultural commodities. As research that focus on exchange-traded funds do not provide any clear conclusions, we focus on the imbalance between short- and long-open positions, this imbalance being caused by the exchange traded funds’ participation in futures markets. In this paper, we estimate relationships between financial variables including indicators for speculation in futures markets and the returns of cocoa, corn, soybean, wheat, coffee, rice, and sugar on a weekly basis from 1998 to 2013. Significant results lead to Granger-causality tests that in turn validate the hypothesis of a positive impact of speculation in futures markets to returns on the underlying commodities.     

经济租金和物价上涨与通胀的治理

在刚性需求条件下,缺乏供给弹性的商品存在着可观的经济租金,而过量流动性为金融资本竞相追逐经济租金提供了货币基础,这是此轮物价结构性上涨的根源所在。若相关商品供求弹性没有得到有效改善,物价结构性上涨在中长期内将是一种常态,此时单纯的回收流动性等总量调控措施只具有短期性的效果。今后,宏观政策的着眼点应当由以需求管理为主转向以供给管理和需求管理并重,只有通过双管齐下,才能从根本上缓解结构性通胀对宏观经济运行的不利影响。     

Nominal uncertainty,real uncertainty and macroeconomic performance in a time-varying asymmetric framework: Implications for monetary policy

This study examines the dynamic causal links and volatility spillovers of inflation, output growth and their uncertainties in four South Asian countries, namely, Pakistan, India, Bangladesh and Sri Lanka by utilizing asymmetric GARCH family models. Our empirical evidence supports a number of important conclusions. There is an overwhelming support for Friedman-Ball hypothesis of positive inflation-uncertainty trade-off for all countries excluding India and Sri Lanka. The Cukierman-Meltzer’s idea that inflation uncertainty generates inflation, hold for Bangladesh and Sri Lanka only and the Holland’s hypothesis of negative influence of inflation uncertainty on level inflation is supported by India only. The positive influence of output uncertainty on inflation (Devereux (1989) hypothesis) is supported by all countries excluding Bangladesh while nominal uncertainty (real uncertainty) has negative (positive) effect on output growth in Pakistan (Bangladesh). Output growth is reducing real uncertainty in all countries excluding Sri Lanka and nominal uncertainty in Pakistan only. There is significant negative relationship between inflation and output growth for Pakistan only while real uncertainty is positively (negatively) related with nominal uncertainty in India (Bangladesh). The estimated results are almost robust with the simultaneous estimation procedure for testing the main hypotheses. In general, there is asymmetric effect and persistence of the GARCH parameters for all countries. The study suggests that the concerned central banks should pay more attention to the effects of macroeconomic uncertainty and should focus their monetary policy strategy on stabilizing both output growth and inflation.     

Quantifying the cyclically adjusted fiscal stance for India

Taking cue from recent debate in the literature, we attempt to disentangle cyclically adjusted fiscal balance (CAB) for India broadly using the methodology recommended by the IMF, an indigenous revenue elasticity for India and a range of potential output estimates. Our results indicate that after initial success in containing CAB, it increased considerably during the crisis period. Notwithstanding a positive output gap in the post-crisis period (2009–11) and subsequent increase in inflation, the CAB continued to be expansionary, with limited withdrawal of expansionary stance, albeit a reduction in fiscal impulse. This calls for further reforms and binding framework that can withstand business cycles.     

Financialization and de-financialization of commodity futures: A quantile regression approach

This study employs a quantile regression approach to examine the financialization of commodity futures. We confirm a strong degree of dependence in energy commodities from 2004 to 2013, with moderate effects in metals and lesser magnitudes in agriculture. Our findings show a strengthening in the financialization of energy commodities during the 2008–2009 global financial crisis, while there were weaker effects in agriculture and a decoupling or de-financialization in metal markets. The findings reveal the de-financialization of metals and agricultural markets from 2014 to 2017, after the 2013 closure of commodity trading units on Wall Street. Overall, our findings cast doubt on the diversification benefits of energy-dominated commodity indices after 2013. We argue the impact of financialization on commodity futures markets is more permanent than previously thought.     

How world uncertainties and global pandemics destabilized food,energy and stock markets? Fresh evidence from quantile on quantile regressions

In this study, we analyse the impact of world uncertainty, global pandemics, including the recent COVID-19, and geopolitical risk on global food, energy commodities, and stock markets from a global perspective. The study uses quantile on quantile regression (QQR) and a quantile causality test using quarterly data from 1996Q1 to 2020Q1. Overall, the study results indicate heterogeneity in the influence of the world uncertainty index, global pandemic index, and geopolitical risk on the global food, energy, and stock markets. However, our findings predominantly show a negative impact of world uncertainty, and global pandemic on global food, energy commodities, and stock markets with substantial variations across markets (food, energy, and stock) and quantiles within each market. For robustness, this study applied the geopolitical risk and found the similar impact on food, energy and stock markets. Additionally, the quantile causality test confirms unidirectional causality running from world uncertainty, global pandemic uncertainty, and geopolitical risk to world food, energy, and stock markets. Our findings give a clear guideline to policymakers and investors managing food, energy, and equity markets during uncertainty and pandemic periods.     

Liquidity commonality in commodities

We examine liquidity commonality in commodity futures markets. Using data from 16 agricultural, energy, industrial metal, precious metal, and livestock commodities, we show there is a strong systematic liquidity factor in commodities. Liquidity commonality was present in 1997–2003 when commodity prices were relatively stable and during the recent boom. There is some support for both “supply-side” and “demand-side” explanations for this commonality. We find no evidence of a consistent link between stock and commodity liquidity in general. Energy commodities appear to provide a better hedge against equity market liquidity risk than the other commodity families.     

Commodity prices and inflation: Testing in the frequency domain

We provide evidence for a long term, positive relation between commodity prices and inflation. However, this is only detected when frequency dependency in the regression is statistically accounted for, suggesting nonlinear dynamics between the variables. We also test whether commodity prices can be used to forecast inflation. Again relying on frequency domain methods, we indeed find support for long term causality from commodities to inflation. Moreover, the information content of commodity futures prices is robust to the effects of several financial and economic variables.     

Monetary Policy Reaction Functions of the TICKs: A Quantile Regression Approach

This study investigates how Taiwan, India, China, and Korea (TICKs) set interest rates in the context of policy reaction functions using a quantile-based approach. Our results indicate the tendency of a milder response to inflation at low interest rates and greater response at higher quantiles of interest rates, where inflation is presumably higher than desired for China and South Korea. While the response to inflation over the quantiles is significant for India, yet the Taylor principle is less likely to hold. For Taiwan, the results imply that another instrument is employed to deal with its official managed floating currency.     

Have cryptocurrencies become an inflation hedge after the reopening of the U.S. economy?

In this paper, we study how the comovement between cryptocurrencies and the U.S. inflation expectation rates has changed during the post-reopening of the U.S. economy after the Covid-19 crisis. To do so, we develop a new concept of “exceedance co-kurtosis” which allows us to quantify asymmetry in strong comovement between each cryptocurrency and the inflation expectation rate. The key findings are as follows. First, we show the change in the co-kurtosis asymmetry for major cryptocurrencies: the downside co-kurtosis was higher than the upside co-kurtosis but it decreased after the reopening of the economy. Although the unconditional correlations between cryptocurrencies and the inflation expectation rates remain very low, our results indicate that the major cryptocurrencies become a slightly better inflation hedge after the reopening. Second and more interestingly, the results do not depend on whether a cryptocurrency has a cap on maximum supply or not. Therefore, treating the major cryptocurrencies as digital commodities could be misleading from the viewpoint of portfolio optimization.     

Dynamics of inflation in India: does the new inflation bias hypothesis provide an explanation?

In this paper we estimate the Reserve Bank of India's (RBI) policy response to supply shocks. In particular, we exploit an important strand of the recent literature (the new inflation bias hypothesis) to understand why the two frequently cited measures of inflation in India have persistently diverged in recent years. Specifically, it is argued that the difference in coverage and weighting pattern between the indices interacting with policies pursued by the RBI to control its preferred inflation measure WPI turned out to be inappropriate with respect to stabilizing expected CPI-IW inflation. This in turn provides an explanation for the persistent divergence between the two measures of inflation.     

Financialization in commodity markets: A passing trend or the new normal?

In this paper, we show that large inflows into commodity investments, a recent phenomenon known as financialization, has changed the behavior and dependence structure between commodities and the general stock market. The common perception is that the increase in comovements is the result of distressed investors selling both assets during the 2007–2009 financial crisis. We show that financial distress alone cannot explain the size and persistence of comovements. Instead, we argue that commodities have become an investment style for institutional investors. Given that institutional investors continue to target funds into commodities, we predict spillovers between commodities and the stock market to remain high in the future.     

Optimal inflation persistence: Ramsey taxation with capital and habits

Ramsey models of fiscal and monetary policy featuring time-separable preferences and a fixed supply of capital predict highly volatile inflation with no serial correlation. In this paper, we show that an otherwise-standard Ramsey model that incorporates capital accumulation and habit persistence predicts highly persistent inflation. The result depends on increases in either the ability to smooth consumption or the preference for doing so. The effect operates through the Fisher relationship: a smoother profile of consumption implies a more persistent real interest rate, which in turn implies persistent optimal inflation. Our work complements a recent strand of the Ramsey literature based on models with nominal rigidities. In these latter models, inflation volatility is lower than in the baseline model but continues to exhibit little persistence. We quantify the effects of habit and capital on inflation persistence and also relate our findings to recent work on optimal fiscal policy with incomplete markets.     

The Passthrough of Labor Costs to Price Inflation

We use a time‐varying parameter/stochastic volatility VAR framework to assess how the passthrough of labor costs to price inflation has evolved over time in U.S. data. We find little evidence that independent movements in labor costs have had a material effect on price inflation in recent years, even for compensation measures where some degree of passthrough to prices still appears to be present. Our results cast doubt on explanations of recent inflation behavior that appeal to such mechanisms as downward nominal wage rigidity or a differential contribution of long‐term and short‐term unemployed workers to wage and price pressures.     

货币供给、通货膨胀和粮食价格波动互动关系研究

在VAR模型和方差分解基础上,利用1997年以来的月度数据,分析货币供应量、通货膨胀和粮食价格之间的关系。结果显示：通货膨胀对粮食价格有显著影响,存在货币供应量、通货膨胀到粮食价格变动这一传导途径,同时发现通货膨胀有较强的自身惯性,通过抑制粮食价格来控制通货膨胀是无效的。     

Asset management in an inflationary environment—Are commodities a useful hedge?

The 2008 German investment act now allows insurers to buy commodities. Taking the perspective of a German investor and using techniques of cointegration analysis this paper aims to investigate whether commodity investments can be a useful hedge against inflation. A financial asset can only be considered to be a hedge against inflation if its price is cointegrated with the general price level. The results of the study seem to imply that commodity investments may be considered as a hedge against inflation for German insurers, but only to a limited extend.