Hidden Markov model (HMM) is a statistical signal prediction model, which has been widely used to predict economic regimes and stock prices. In this paper, we introduce the application ofHMMin trading stocks (with S&P 500 index being an example) based on the stock price predictions. The...

Future stock prices depend on many internal and external factors that are not easy to evaluate. In this paper, we use the Hidden Markov Model, (HMM), to predict a daily stock price of three active trading stocks: Apple, Google, and Facebook, based on their historical data. We first use the...

This paper constructs a signal-based composite index, namely ESCORE, which captures the context of earnings management. Specifically, ESCORE aggregates 15 individual signals related to earnings management based on prior relevant literature. Empirical results using UK data shows that when ESCORE...

The growth of last-mile delivery in developing countries is featuring the important contribution of crowdshippers. Therefore, exploring the factors affecting the intentions to stay in jobs of the crowdshippers is of great significance to maintain and sustainably develop the last-mile delivery...

The hidden Markov model (HMM) is typically used to predict the hidden regimes of observation data. Therefore, this model finds applications in many different areas, such as speech recognition systems, computational molecular biology and financial market predictions. In this paper, we use HMM for...

This study examines the behavior of sovereign bonds to COVID-19 related news in 24 countries most affected by the COVID-19 pandemic. The study applies a continuous Hidden Markov Model (HMM) to analyze the regime shifting behavior of sovereign bonds to the news. The results show that the COVID-19...

Previous studies show mixed evidence of the role of banking expertise on the board of directors on accounting conservatism. In this paper, we add to this growing literature by providing an innovative way to measure banking expertise based on life-time working history in banks of all individual...

Benford's Law, which is the law of digit distributions, is widely applied to study fraud or bias in a data set. In this paper, we applied Benford's Law to examine the first digits of financial statement items of UK listed companies. The evidence shows that the first digits conform to Benford's...

Cryptocurrencies are currently traded worldwide, with hundreds of different currencies in existence and even more on the way. This study implements some statistical and machine learning approaches for cryptocurrency investments. First, we implement GJR-GARCH over the GARCH model to estimate the...