Current Work

 
  • “A Theory of Debt Accumulation and Deficit Cycles.”

This paper introduces a tractable model of sovereign debt in which governments face intertemporal tradeoffs between (i) preferring more primary deficits to less and (ii) avoiding costly defaults. Governments run deficits when debt and, then, the marginal costs of increasing debt are low. After an extended period of debt accumulation, the probability of default increases, and so do the marginal costs of running debt. Eventually, debt reaches a critical level relative to the size of the economy, a fiscal tipping point, after which debt accumulation stops, with governments cycling between deficits and surpluses, until perhaps a time of default. The main conclusions are that (i) fiscal tipping points typically occur at about 85-90% from default; (ii) the probability of default increases with governments’ myopia, macroeconomic uncertainty, the ease at which defaulted governments re-gain access to capital markets (leading to serial defaulting), or debt markets illiquidity; (iii) fiscal austerity may arrive too late: debt intolerance arises around the fiscal tipping point.

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  • BOOK: Cent’anni di economia e politica italiana (in Italian).

Deals with the delicate linkages among political, institutional and economic developments in Italy mostly since World War II  whilst studying them in the context of global monetary history and major geopolitical occurrences.

  • “Trading Disclosure Requirements and Market Quality Tradeoffs.” With Francesco Sangiorgi (Frankfurt School of Finance & Management).

We analyze the effects of trading disclosure requirements in markets with insider traders and professional investors. The insiders garble their trading throughout a mixed strategy. A number of differentially informed professional investors acquire information and contribute to increased market efficiency. A reform introducing post-trade transparency leads these professional investors to acquire less information and, then, to trade less, contributing to less price discovery. This information crowding-out may be so strong to neutralize the generally positive effects related to public disclosure or to harm market quality, resulting in diminished liquidity and informationally less efficient markets.

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  • “Correlation Risk, Strings and Asset Prices.” With Walter Distaso (Imperial College Business School) and Grigory Vilkov (Frankfurt School of Finance & Management).

Standard asset pricing theories treat return volatility and correlations as two intimately related quantities, which hinders achieving a neat definition of correlation premium. We introduce a model with a continuum of securities that are driven by a string. This model leads to new arbitrage pricing restrictions, according to which, holding any asset requires compensation for the exposure of this asset returns to fluctuations of all other asset returns. We estimate the model and find that this correlation premium is both statistically and economically significant and considerably fluctuates according to global market developments. The model explains both the cross-section of expected returns and the time-series behavior of correlation risk premiums without any reference to common factor.

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  • “The Term Structure of Government Debt Uncertainty.” With Yoshiki Obayashi (Applied Academics LLC) and Shihao Yang (Applied Academics LLC and Harvard University).

How valuable would it be to mitigate uncertainty on government bond volatility? This paper introduces a model that accounts for the complex structure of government bond volatility and provides predictions for the fair value of government bond variance swaps and derivatives referenced upon. Our calibrated model predicts that expected volatilities frequently oscillate between episodes of backwardation and contango, a feature in stark contrast with dynamics known in equity markets. We use the model in risk management experiments and evaluate scenarios such as the reaction of the U.S. Treasury volatility curve to shocks such as unanticipated FED decisions or global economic imbalances. Unlike equity volatility dynamics, which may be specified exogenously without violating no-arbitrage conditions, government bond volatility must be consistent with the dynamics of the whole yield curve. The paper provides quasi-closed form solutions that can be readily implemented despite the high-dimensional no-arbitrage restrictions that underlie the model dynamics.

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  • “Simple Approximate Maximum-Likelihood Estimation of Multivariate Jump-Diffusion Models,” with Dennis Kristensen (University College London) and Young Jun Lee (University College London).

This paper develops new closed-form approximations of the transition densities for a general class of jump-diffusion processes. The approximation relies on a series expansion of the unknown density of interest around an auxiliary transition density which is known on closed form. We employ the approximate transition densities in the development of simple approximate maximum-likelihood estimators (MLE’s) of model parameters. Under regularity conditions, the approximate transition densities converge towards the true, unknown densities as the number number of terms in the series expansion grows. Thus, the corresponding approximate MLE converges towards the exact MLE as well. A number of numerical examples demonstrate that our method is accurate and requires only modest computation time.

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  • “Volatility Begets Ambiguity: Volatility-Uncertainty Spirals in Asset Markets.” With Francesco Sangiorgi (Frankfurt School of Finance & Management).

We consider a market for a long-term security traded throughout overlapping generations. Agents are unsure about whether the future realization of the asset payoff is subject to sudden bouts of severe uncertainty. In equilibrium, agents use private signals as well as past equilibrium volatility to infer the likelihood of future states with Knightian uncertainty. Market volatility is generated both by noise and by the equilibrium implications of uncertainty-averse investors’ portfolio choices. This volatility is a signal of Knightian uncertainty to future generations, and leads to spirals: not only uncertainty leads to thin markets and, hence, high volatility; a period of sustained volatility leads agents to behave as uncertainty-averse agents, thereby raising future volatility. Work in progress.

  • “Uncertainty and Volatility in Financial Markets.” With Francesco Sangiorgi (Frankfurt School of Finance & Management).

This paper is a survey of work on financial market volatility, Knightian uncertainty, and their interlinks. We deal with both theoretical and empirical models and attempt at explaining how these models link to market adoptions of instruments that allow to trade developments in volatility. Work in progress.