A Fast Literature Search Engine based on top-quality journals, by Dr. Mingze Gao.
- Topic classification is ongoing.
- Please kindly let me know [mingze.gao@mq.edu.au] in case of any errors.
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Results 379 resources
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This paper develops a closed-form option valuation formula for a spot asset whose variance follows a GARCH(p, q) process that can be correlated with the returns of the spot asset. It provides the first readily computed option formula for a random volatility model that can be estimated and implemented solely on the basis of observables. The single lag version of this model contains Heston's (1993) stochastic volatility model as a continuous-time limit. Empirical analysis on S&P500 index options shows that the out-of-sample valuation errors from the single lag version of the GARCH model are substantially lower than the ad hoc Black-Scholes model of Dumas, Fleming and Whaley (1998) that uses a separate implied volatility for each option to fit to the smirk/smile in implied volatilities. The GARCH model remains superior even though the parameters of the GARCH model are held constant and volatility is filtered from the history of asset prices while the ad hoc Black-Scholes model is updated every period. The improvement is largely due to the ability of the GARCH model to simultaneously capture the correlation of volatility, with spot returns and the path dependence in volatility.
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This paper develops an equilibrium model of a competitive futures market in which investors trade to hedge positions and to speculate on their private information. Equilibrium return and trading patterns are examined. (1) In markets where the information asymmetry among investors is small, the return volatility of a futures contract decreases with time‐to‐maturity (i.e., the Samuelson effect holds). (2) However, in markets where the information asymmetry among investors is large, the Samuelson effect need not hold. (3) Additionally, the model generates rich time‐to‐maturity patterns in open interest and spot price volatility that are consistent with empirical findings.
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This paper challenges the current belief that income inequality has a negative relationship with economic growth. It uses an improved data set on income inequality, which not only reduces measurement error, but also allows estimation via a panel technique. Panel estimation makes it possible to control for time-invariant country-specific effects, therefore eliminating a potential source of omitted-variable bias. Results suggest that in the short and medium term, an increase in a country's level of income inequality has a significant positive relationship with subsequent economic growth. This relationship is highly robust across samples, variable definitions, and model specifications.
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This paper introduces various sources of consumer heterogeneity in one-sector representative consumer (RC) growth models and develops tools to study the evolution of the distribution of consumptions, assets, and incomes. These tools are applied to the Ramsey-Cass-Koopmans model of optimal savings and the Arrow-Romer model of productive spillovers. The RC property per se places very few restrictions on the nature of observed distributions, and a wide range of distributive dynamics and income mobility patterns can arise as the equilibrium outcome. An example illustrates how to use these tools to generate quantitative predictions and compare them to the data.
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