The study aims at simulating and forecasting a company's stock returns and prices by a fundamentalist analysis process based on a Vector Error Correction with Exogenous Variables (VECX) econometric model. To achieve this, we selected relevant fundamentalist indicators and specified a model...

Three models are presented: AR (autoregressive), MA (moving average) and ARMA (autoregressive moving average) are common models used in time series forecasting. These three models are the various definition of each element of the General Linear Model: Y = a + b + c. For the study of linear...

This paper presents a short survey on limit theorems for certain functionals of semimartingales, which are observed at high frequency. Our aim is to explain the main ideas of the theory to a broader audience. We introduce the concept of stable convergence, which is crucial for our purpose. We...

This paper estimates the stock market and its price dynamics in terms of the multifractional Brownian motion. In our analysis, we use the financial dataset of the Dow Jones Industrial Average (DJI) time series from March 2009 to June 2015. First, we briefly introduce the definitions and...

In high dimensional data, relevant interactions can be difficult to identify due to the extremely large number of possible interactions among variables. Conventional methods use a screening stage to vastly reduce the dimension of the variable space before examining the interaction effect....

We develop a network-based vector autoregressive approach to uncover the interactions amongfinancial assets by integrating multiple realized measures based on high-frequency data. Undera restricted parameter structure, our approach allows the capture of cross-sectional and time ependencies...

This paper considers issues related to identification, inference, and computation in linearized dynamic stochastic general equilibrium (DSGE) models. We first provide a necessary and sufficient condition for the local identification of the structural parameters based on the (first and) second...

It is well-known that outliers exist in the type of multivariate data used by financial practitioners for portfolio construction and risk management. Typically, outliers are addressed prior to model fitting by applying some combination of trimming and/or Winsorization to each individual...

This paper extends the existing literature on linear quadratic adjustment cost (LQAC) models under rational expectations to the inferential issues arising when: (i) agents optimise with respect to a vector of endogenous variables; (ii) the behavioural equations stemming from the agent's...

This article surveys estimation in stationary time series models using the approach of optimal instrumentation. We review tools that allow construction and implementation of optimal instrumental variables estimators in various circumstances - in single- and multi-period models, in the absence...