UNDERSTANDING WORLD COMMODITY PRICES Returns, Volatility and Diversification

In recent times, the prices of internationally-traded commodities have reached record highs and there is considerable uncertainty regarding their future. This phenomenon is partially driven by strong demand from a small number of emerging economies, such as China and India. This paper places the recent commodity price boom in historical context, drawing on an investigation of the long-term time-series properties, and presents unique features for 33 individual commodity prices. Using a new methodology for examining cross-sectional variation of commodity returns and its components, we find strong evidence that the prices of world primary commodities are extremely volatile. In addition, prices are roughly 30 percent more volatile under floating than under fixed exchange rate regimes. Finally, using the capital asset pricing model as a loose framework, we find that global macroeconomic risk components have become relatively more important in explaining commodity price volatility.

Volatility term structures in commodity markets

In this study, we comprehensively examine the volatility term structures in commodity markets. We model state‐dependent spillovers in principal components (PCs) of the volatility term structures of different commodities, as well as that of the equity market. We detect strong economic links and a substantial interconnectedness of the volatility term structures of commodities. Accounting for intra‐commodity‐market spillovers significantly improves out‐of‐sample forecasts of the components of the volatility term structure. Spillovers following macroeconomic news announcements account for a large proportion of this forecast power. There thus seems to be substantial information transmission between different commodity markets

A model of financialization of commodities

We analyze how institutional investors entering commodity futures markets, referred to as the financialization of commodities, affect commodity prices. Institutional investors care about their performance relative to a commodity index. We find that all commodity futures prices, volatilities, and correlations go up with financialization, but more so for index futures than for nonindex futures. The equity-commodity correlations also increase. We demonstrate how financial markets transmit shocks not only to futures prices but also to commodity spot prices and inventories. Spot prices go up with financialization, and shocks to any index commodity spill over to all storable commodity prices

How many independent bets are there?

The benefits of portfolio diversification is a central tenet implicit to modern financial theory and practice. Linked to diversification is the notion of breadth. Breadth is correctly thought of as the number of in- dependent bets available to an investor. Conventionally applications us- ing breadth frequently assume only the number of separate bets. There may be a large discrepancy between these two interpretations. We uti- lize a simple singular-value decomposition (SVD) and the Keiser-Gutman stopping criterion to select the integer-valued effective dimensionality of the correlation matrix of returns. In an emerging market such as South African we document an estimated breadth that is considerably lower than anticipated. This lack of diversification may be because of market concentration, exposure to the global commodity cycle and local currency volatility. We discuss some practical extensions to a more statistically correct interpretation of market breadth, and its theoretical implications for both global and domestic investors.Comment: Less technical rewrite. 12 Pages, 6 Figures (.eps

Risk, Growth and Poverty: what do we know, what do we need to know?

This note has three objectives: first, it aims to take stock of the nature of the evidence available and on the links between uninsured risk and shocks on the one hand, and growth and poverty on the other, both at a macro and micro level. Secondly, it makes a number of suggestions of the type of work that could be fruitfully implemented. Finally, it tries to strike a balance between the needs for the policy maker and the requirements for academic scrutiny of evidence, in offering suggestions for priorities in work.

Evaluating the Present State of Japan as An International Financial Center

Japan has various advantages over many other countries in terms of the capacity to further develop the capital, financial, and foreign exchange markets as a more internationally-competitive financial center. The advantages include the 2nd largest economic size (large market size), ample financial assets (large investor base), presence of many internationally-competitive knowledge-intensive manufacturing firms (large issuer base), good infrastructure, the 2nd largest stock market (large market access), role of the Japanese yen as one of key international currencies, etc. Despite these advantages and a series of reforms implemented since 1997 under the slogan of Japanese version of “Financial Big Bang”, Japan has not been able to foster an internationally-competitive international financial center until today. The gaps with the United States and United Kingdom have expanded further over the past decade. This paper gives a detailed analysis over the present state of Japan’s capital, financial, and foreign exchange markets to highlight where Japanese advantages and challenges lie, as compared with the United Kingdom and the United States. It also provides a clear picture of Japan’s position in Asia (Korea, Singapore, Hong Kong, and mainland China). It also reviews recent Government’s vision and actions.Japan, International Financial Center, Financial Big Bang

Boosting the Anatomy of Volatility

Risk and, thus, the volatility of financial asset prices plays a major role in financial decision making and financial regulation. Therefore, understanding and predicting the volatility of financial instruments, asset classes or financial markets in general is of utmost importance for individual and institutional investors as well as for central bankers and financial regulators. In this paper we investigate new strategies for understanding and predicting financial risk. Specifically, we use componentwise, gradient boosting techniques to identify factors that drive financial-market risk and to assess the specific nature with which these factors affect future volatility. Componentwise boosting is a sequential learning method, which has the advantages that it can handle a large number of predictors and that it-in contrast to other machine-learning techniques-preserves interpretation. Adopting an EGARCH framework and employing a wide range of potential risk drivers, we derive monthly volatility predictions for stock, bond, commodity, and foreign exchange markets. Comparisons with alternative benchmark models show that boosting techniques improve out-of-sample volatility forecasts, especially for medium- and long-run horizons. Another finding is that a number of risk drivers affect volatility in a nonlinear fashion