Modeling stylized facts for financial time series

Can a Zero-Intelligence Plus Model Explain the Stylized Facts of Financial Time Series Data?

Many agent-based models of financial markets have been able to reproduce certain stylized facts that are observed in actual empirical time series data by using “zero-intelligence” agents whose behaviour is largely random in order to ascertain whether certain phenomena arise from market microstructure as opposed to strategic behaviour. Although these models have been highly successful, it is not...

Can a zero-intelligence plus model explain the stylized facts of financial time series data?

Many agent-based models of financial markets have been able to reproduce certain stylized facts that are observed in actual empirical time series data by using “zero-intelligence” agents whose behaviour is largely random in order to ascertain whether certain phenomena arise from market microstructure as opposed to strategic behaviour. Although these models have been highly successful, it is not...

A Minimal Model of Financial Stylized Facts

Financial System Performance and Inflation in Iran: Some Stylized Facts

The mutual relationship between financial development, as a multilateral concept, and inflation, as a key indicator of macro-economy is crucial. In this paper, inflation regimes are identified using Markov-Switching approach, and then the finance-inflation mutual relationship is investigated in post-revolution cabinets in Iran (1982-2017). Our findings suggest that there are mutual co-movements...

Agent-based Financial Markets: Matching Stylized Facts With Style

Empirical facts from financial data pose some of the most difficult puzzles for equilibrium macroeconomic modeling. Features such as volatility, excess kurtosis, and conditional heteroscedasticity are not easily replicated by any single representative agent model. Most agent-based financial markets are able to match a good subset of these features quite easily. This paper will summarize some of...