Macroeconomic Factors and Oil Futures Prices: A Data-Rich Model

I study the dynamics of oil futures prices in the NYMEX using a large panel dataset that includes global macroeconomic indicators, financial market indices, quantities and prices of energy products. I extract common factors from these series and estimate a Factor-Augmented Vector Autoregression for the maturity structure of oil futures prices. I find that latent factors generate information that, once combined with that of the yields, improves the forecasting performance for oil prices. Furthermore, I show that a factor correlated to purely financial developments contributes to the model performance, in addition to factors related to energy quantities and prices.Crude Oil; Futures Markets; Factor Models

The Shannon information of filtrations and the additional logarithmic utility of insiders

The background for the general mathematical link between utility and information theory investigated in this paper is a simple financial market model with two kinds of small traders: less informed traders and insiders, whose extra information is represented by an enlargement of the other agents' filtration. The expected logarithmic utility increment, that is, the difference of the insider's and the less informed trader's expected logarithmic utility is described in terms of the information drift, that is, the drift one has to eliminate in order to perceive the price dynamics as a martingale from the insider's perspective. On the one hand, we describe the information drift in a very general setting by natural quantities expressing the probabilistic better informed view of the world. This, on the other hand, allows us to identify the additional utility by entropy related quantities known from information theory. In particular, in a complete market in which the insider has some fixed additional information during the entire trading interval, its utility increment can be represented by the Shannon information of his extra knowledge. For general markets, and in some particular examples, we provide estimates of maximal utility by information inequalities.Comment: Published at http://dx.doi.org/10.1214/009117905000000648 in the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org

The Shannon Information of Filtrations and the Additional Logarithmic Utility of Insiders

The background for the general mathematical link between utility and information theory investigated in this paper is a simple financial market model with two kinds of small traders: less informed traders and insiders, whose extra information is represented by an enlargement of the other agents’ filtration. The expected logarithmic utility increment, i.e. the difference of the insider’s and the less informed trader’s expected logarithmic utility is described in terms of the information drift, i.e. the drift one has to eliminate in order to perceive the price dynamics as a martingale from the insider’s perspective. On the one hand, we describe the information drift in a very general setting by natural quantities expressing the probabilistic better informed view of the world. This on the other hand allows us to identify the additional utility by entropy related quantities known from information theory. In particular, in a complete market in which the insider has some fixed additional information during the entire trading interval, its utility increment can be represented by the Shannon information of his extra knowledge. For general markets, and in some particular examples, we provide estimates of maximal utility by information inequalities.enlargement of filtration, logarithmic utility, utility maximization, heterogeneous information, insider model, Shannon information, information difference, entropy, differential entropy

Market informational inefficiency, risk aversion and quantity grid

In this paper we show that long run market informational inefficiency is perfectly compatible with standard rational sequential trade models. Our inefficiency result is obtained taking into account two features of actual financial markets: tradable quantities belong to a quantity grid and traders and market makers do not have the same degree of risk aversion. The implementation of our model for reasonable values of the parameters suggests that the long term deviations between asset prices and fundamental value are important. We explain the ambiguous role of the quantity grid in exacerbating or mitigating market inefficiency. We show that stock splits can improve the information content of the order flow and consequently increase price volatility.informational efficiency; quantity grid; stock splits

Competition and Intervention in Sovereign Debt Markets

We investigate markets for defaultable sovereign debt in which even though there are many identical lenders and symmetric information (including no hidden actions), perfect competition does not obtain. When a private lender allows a sovereign country to increase its level of indebtedness, that lender implicitly imposes a default externality on others who have lent to that sovereign. That is, in the case where the borrower would be able to pay back the first loan in the absence of a second loan, the borrower may have a strong incentive to take both loans and default on both loans. When a lender has no control over the actions of other lenders, they must anticipate this behavior and devise a lending strategy that is consistent with the strategies not only of the sovereign borrower, but also of other lenders. We develop a model of this strategic lending behavior in the presence of default, and show that even though there are many competing lenders, the perfectly competitive outcome does not necessarily obtain. Moreover, the equilibrium can result in monopoly-like outcomes in prices and quantities. We also study the consequences of intervention in these markets by a seemingly benevolent international financial institution, and find that these interventions, though well-intentioned, can in some cases be welfare reducing for sovereign countries and welfare improving for private lenders.

Systemic risk and spatiotemporal dynamics of the US housing market

Housing markets play a crucial role in economies and the collapse of a real-estate bubble usually destabilizes the financial system and causes economic recessions. We investigate the systemic risk and spatiotemporal dynamics of the US housing market (1975–2011) at the state level based on the Random Matrix Theory (RMT). We identify richer economic information in the largest eigenvalues deviating from RMT predictions for the housing market than for stock markets and find that the component signs of the eigenvectors contain either geographical information or the extent of differences in house price growth rates or both. By looking at the evolution of different quantities such as eigenvalues and eigenvectors, we find that the US housing market experienced six different regimes, which is consistent with the evolution of state clusters identified by the box clustering algorithm and the consensus clustering algorithm on the partial correlation matrices. We find that dramatic increases in the systemic risk are usually accompanied by regime shifts, which provide a means of early detection of housing bubbles.HM, WJX, ZQJ and WXZ received support from the National Natural Science Foundation of China Grant 11075054 and 71131007, the Shanghai (Follow-up) Rising Star Program Grant 11QH1400800, the Shanghai "Chen Guang'' Project Grant 2012CG34, and Fundamental Research Funds for the Central Universities. BP and HES received support from the Defense Threat Reduction Agency (DTRA), the Office of Naval Research (ONR), and the National Science Foundation (NSF) Grant CMMI 1125290. (11075054 - National Natural Science Foundation of China; 71131007 - National Natural Science Foundation of China; 11QH1400800 - Shanghai (Follow-up) Rising Star Program; 2012CG34 - Shanghai "Chen Guang'' Project; Fundamental Research Funds for the Central Universities; Defense Threat Reduction Agency (DTRA); Naval Research (ONR); CMMI 1125290 - National Science Foundation (NSF))Published versio

Linking Farmers to Markets through Modern Information and Communication Technologies in Kenya

This paper highlights a market information and linkage system (MILS) developed and tested by the Kenya Agricultural Commodity Exchange Limited (KACE) that increases the efficiency of agricultural markets to work better for smallholder farmers and other small and medium sized agro-enterprises (SMEs). The MILS involves harnessing modern information and communication technologies (ICTs) to empower farmers with low-cost reliable and timely market information to enhance the bargaining power of the farmer for a better price in the market place, and to link the farmer to markets more efficiently and profitably. The components of the KACE MILS are (www.kacekenya.com): Rural based Market Information Points (MIPs) which are information kiosks located in rural markets, District-level Market Information Centres (MICs), Mobile Phone Short Messaging Service (SMS), Interactive Voice Response (IVR), Internet based database system, rural FM radio and the Central Coordinating Hub in Nairobi. KACE has adopted a business approach to the provision of its services: users pay for the services. For instance it charges: placement fees per initial offer or bid (US$1.5-15), commissions on concluded deals (0.5$ 65 for 6 months or US$125 for 12 months), fees to visiting foreign groups (US$ 2,000-5,000/visit) and revenue sharing agreements with SMS and IVR service providers. When the KACE MILS services are scaled out and widely used by many farmers and SMEs across Kenya, the system will generate sufficient revenue to sustain its services without reliance on development partner funding. To enhance the financial sustainability of the MILS services further, KACE has recently initiated two innovations: franchising MIPs and MICs to local entrepreneurs, and establishing a virtual trading floor to improve the matching of offers and bids through a rural-based FM Radio program. A recent study of the impact of the KACE MILS concluded that the proportion of farmers and traders that say their incomes has increased and their bargaining positions have improved is very high (75% farmers and 60% commodity traders). Furthermore, the study concluded that it was clear that during the years in which the KACE MILS has been operational, market integration improved for two commodities studied (i.e. maize and beans). This study also highlights the challenges faced by the KACE MILS, including poor infrastructure that imposes high transport costs to markets, high costs of mobile phone calls and SMS and small quantities of produce of varying quality offered. Keywords: Information and communication technology, innovations, Kenya,Agribusiness, Agricultural and Food Policy, Consumer/Household Economics, Environmental Economics and Policy, Farm Management, Food Consumption/Nutrition/Food Safety, Food Security and Poverty, Institutional and Behavioral Economics, International Relations/Trade, Land Economics/Use, Marketing, Productivity Analysis, Research and Development/Tech Change/Emerging Technologies, Research Methods/ Statistical Methods,

Application of spectral methods for high-frequency financial data to quantifying states of market participants

Empirical analysis of the foreign exchange market is conducted based on methods to quantify similarities among multi-dimensional time series with spectral distances introduced in [A.-H. Sato, Physica A, 382 (2007) 258--270]. As a result it is found that the similarities among currency pairs fluctuate with the rotation of the earth, and that the similarities among best quotation rates are associated with those among quotation frequencies. Furthermore it is shown that the Jensen-Shannon spectral divergence is proportional to a mean of the Kullback-Leibler spectral distance both empirically and numerically. It is confirmed that these spectral distances are connected with distributions for behavioral parameters of the market participants from numerical simulation. This concludes that spectral distances of representative quantities of financial markets are related into diversification of behavioral parameters of the market participants.Comment: 8 pages, 6 figures, APFA