Celso Brunetti

Speculators, Prices and Market Volatility

We employ data over 2005-2009 which uniquely identify categories of traders to test whether speculators like hedge funds and swap dealers cause price changes or volatility. We find little evidence that speculators destabilize financial markets. To the contrary, speculative trading activity largely reacts to market conditions and reduces volatility levels, consistent with the hypothesis that speculators provide valuable liquidity to the market. These results hold across a variety of products and suggest that hedge funds (with approximately constant risk tolerance as in Deuskar and Johnson [2010]) improve overall market quality.

Return-based and Range-Based (Co)Variance Estimation - With an Application to Foreign Exchange Markets

This paper analyzes and compares range-based and return-based variance/covariance estimates. We provide new results on the relative efficiency of the range. We show that the use of the range is compatible with time varying volatilities and we extend the range to a multivariate setup. A new estimator for the covariance, termed co-range, which is based on high and low prices, is proposed. The main properties of the new estimator are derived. Empirically, we find that range-based measures of variance, standard deviation, co-variance and correlation possess a much higher degree of persistence compared to conventional measures based on open/close prices.

Do OPEC Members Know Something the Market Doesn’t? ‘Fair Price’ Pronouncements and the Market Price of Crude Oil

OPEC producers, individually or collectively, often make statements regarding the “fair price” of crude oil. In some cases, the officials commenting are merely affirming the price prevailing in the crude oil market at the time. In many cases, however, we document that they explicitly disagree with the contemporaneous futures price. A natural question is whether these “fair price” pronouncements contain information not already reflected in market prices. To find the answer, we collect “fair price” statements made between 2000 and 2009 by officials from OPEC or OPEC member countries. Visually, the “fair price” series looks like a sampling discretely drawn (with a lag) from the daily futures market price series. Formally, we use several methodologies to establish that “fair price” pronouncements have little influence on the market price of crude oil and that they supply little or no new news to oil futures market participants.

OPEC 'Fair Price' Pronouncements and the Market Price of Crude Oil

OPEC producers, individually or collectively, often make statements regarding the “fair price” of crude oil. In some cases, the officials commenting are merely affirming the market price prevailing at the time. In many cases, however, we document that they explicitly disagree with contemporaneous oil futures prices. A natural question is whether these “fair price” pronouncements contain information not already reflected in the market price of crude oil. To find the answer, we collect “fair price” statements made from 2000 through 2010 by officials from OPEC or OPEC member countries. Visually, the “fair price” series looks like a sampling discretely drawn (with a lag) from the daily futures market price series. Formally, we use two primary methodologies to establish that “fair price” pronouncements have little influence on the market price of crude oil and supply little or no new news to oil futures market participants.

Trading networks: Trading networks

In this paper, we analyse the time series of 12,000+ networks of traders in the E‐mini S&P 500 stock index futures contract and we empirically link network variables with financial variables more commonly used to describe market conditions. We show that network variables lead trading volume, intertrade duration, effective spreads, trade imbalances and other market liquidity measures. Network variables reflect information, information asymmetry and market liquidity and significantly presage future market conditions prior to volume or liquidity measures. We also find two‐way Granger‐causality between network variables and both returns and volatility, highlighting strong feedback between market conditions and trading behaviour.

Visual Analytics for Network-Based Market Surveillance

Time series of graphs are increasingly prevalent in modern economic and financial data and pose unique challenges to visual exploration and pattern extraction. This paper describes the application of matrix factorizations that enhance existing visualization techniques for exploration and pattern detection in graph time-series. The combination of matrix factorization and visualizations allows the user to home in on and display interesting, underlying structure and its evolution over time. The methods are scalable to data sets with a large number of time points or nodes, and can accommodate sudden changes to graph topology. The tools are used to summarize how dynamics in the interbank and equity markets changed during the sub-prime crisis for banks in the Eurozone area.

Economic Volatility and Financial Markets: The Case of Mortgage-Backed Securities

The volatility of aggregate economic activity in the United States decreased markedly in the mid eighties. The decrease involved several components of GDP and has been linked to a more stable economic environment, identified by smaller shocks and more effective policy, and a diverse set of innovations related to inventory management as well as financial markets. We document a negative relation between the volatility of GDP and some of its components and one such financial development: the emergence of mortgage-backed securities. We also document that this relationship changed sign, from negative to positive, in the early 2000s.

Do Institutional Traders Predict Bull and Bear Markets

We analyze the role of hedge fund, swap dealer and arbitrageur activity in a Markov regime-switching model between high volatility bear markets and low volatility bull markets for crude oil, corn and Mini-SP 2003). Conditioning on hedge fund activity and arbitrageur activity significantly improves our probability estimates, demonstrating that institutional positions can be useful in determining whether price trends resembling bubble patterns will continue or reverse.

Balance Sheet Driven Probability Factorization for Inferring Bank Holdings: Extended Abstract

 Assistant Professor of Operations, Technology and Information Management, Samuel Curtis Johnson Graduate School of Management, Cornell University, 2015 – Present o Graduate Field Member in Statistics, 2017 – Present  Assistant Professor of Business Analytics, Robert H. Smith School of Business, University of Maryland, 2013 – 2015 o Affiliate Faculty of Applied Mathematics and Scientific Computation, University of Maryland, 2014 – 2015  Federal Contractor, the U.S. Commodity Futures Trading Commission, 2009 – 2013  Dissertation Intern, Federal Reserve Board of Governors, Summer 2012

Mortgage Rates and Credit Risk: Evidence from Mortgage Pools

We study interest rates on mortgages using the segmentation adopted in the process of securitization: Mortgages securitized by government-sponsored enterprises; mortgages securitized by private institutions, in turn divided in prime and subprime mortgage pools; and, finally, mortgages held by intermediaries on their balance sheet. We find that, over the period that goes from the mid nineties to present, all mortgage classes were priced equally with the exception of subprime loans. Subprime loans were priced in function of the credit worthiness of the borrower. This process however, was not uniform over time. The crucial aspect of the pricing process is that credit risk becomes increasingly important from (at least) the mid-90s to the crisis of 2008. Moreover, through cointegration analysis we find that the dynamics of delinquencies and, to a lesser extent, housing price are reflected in the dynamics of subprime mortgage rates, and not in other mortgage categories. The evidence documents the importance of the subprime mortgage securitization process and indicates that the willingness of financial markets to support a higher level of credit risk is quantitatively important and dates back at least ten or fifteen years before the crisis.