Detecting pump-and-dump schemes involving cryptoassets with high-frequency data is challenging due to imbalanced datasets and the early occurrence of unusual trading volumes. To address these issues, we propose constructing synthetic balanced datasets using resampling methods and flagging a...

This pdf contains a do file that shows how to estimate a latent class discrete choice panel data model in Stata via Maximum Likelihood and an EM algorithm.

Let U be an unobserved random variable with compact support and let e_t be unobserved i.i.d. random errors also with compact support. Observe the random variables V_t, X_t, and Y_t = 1{U +d X_t+e_t V_t}, t = T, where d is an unknown parameter. This type of model is relevant for many stated...

In many stated choice experiments researchers observe the random variables V_t , X_t , and Y_t = 1{U +δ X_t +e_t V_t }, t ≤ T , where δ is an unknown parameter and U and e_t are unobservable random variables. We show that under weak assumptions the distributions of U and e_t and also the...

We consider two popular classes of volatility models, the generalized autoregressive conditional heteroscedastic (GARCH) model and the stochastic volatility (SV) model. We compare these two models with two classes of intensity models, the integer-valued GARCH (INGARCH) model and the...

Interaction terms are often misinterpreted in the empirical economics literature by assuming that the coefficient of interest represents unconditional marginal changes. I present the correct way to estimate conditional marginal changes in a series of non-linear models including (ordered)...

We propose a broad class of count time series models, the mixed Poisson integer-valued stochastic intensity models. The proposed specification encompasses a wide range of conditional distributions of counts. We study its probabilistic structure and design Markov chain Monte Carlo algorithms for...

Peek and Rosengren (2005) suggested the mechanism of ``unnatural selection,'' where Japanese banks with impaired capital increase credit to low-quality firms because of their motivation to pursue balance sheet cosmetics. In this study, we reexamine this mechanism in terms of the interaction...

We propose a multiplicative autoregressive conditional proportion (ARCP) model for (0,1)-valued time series, in the spirit of GARCH (generalized autoregressive conditional heteroscedastic) and ACD (autoregressive conditional duration) models. In particular, our underlying process is defined as...

The paper presents the results of an econometric assessment of probabilistic default models on a sample of medium-sized manufacturing companies in Russia for the period from 2012 to 2020. Characteristics of the macroeconomic environment were included in the models. The inclusion of the real...