Beyond the Bid-Ask: Strategic Insights into Spread Prediction and the Global Mid-Price Phenomenon
This research extends the conventional concepts of the bid--ask spread (BAS) and mid-price to include the total market order book bid--ask spread (TMOBBAS) and the global mid-price (GMP). Using high-frequency trading data, we investigate these new constructs, finding that they have heavy tails and significant deviations from normality in the distributions of their log returns, which are confirmed by three different methods. We shift from a static to a dynamic analysis, employing the ARMA(1,1)-GARCH(1,1) model to capture the temporal dependencies in the return time-series, with the normal inverse Gaussian distribution used to capture the heavy tails of the returns. We apply an option pricing model to address the risks associated with the low liquidity indicated by the TMOBBAS and GMP. Additionally, we employ the Rachev ratio to evaluate the risk--return performance at various depths of the limit order book and examine tail risk interdependencies across spread levels. This study provides insights into the dynamics of financial markets, offering tools for trading strategies and systemic risk management.
Code (0)
등록된 구현이 없습니다.
Tasks
NavigateNovel ConceptsMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Learning Strategic Network Emergence Games
Real-world networks, especially the ones that emerge due to actions of animate agents (e.g. humans, animals), are the result of underlying strategic mechanisms aimed at maximizing individual or collective benefits. Learn…
Effects of human dynamics on epidemic spreading in C\^{o}te d'Ivoire
Understanding and predicting outbreaks of contagious diseases are crucial to the development of society and public health, especially for underdeveloped countries. However, challenging problems are encountered because of…
Human DynamicsUnityA Dynamic Population Model of Strategic Interaction and Migration under Epidemic Risk
In this paper, we show how a dynamic population game can model the strategic interaction and migration decisions made by a large population of agents in response to epidemic prevalence. Specifically, we consider a modifi…
A Novel Methodology in Credit Spread Prediction Based on Ensemble Learning and Feature Selection
The credit spread is a key indicator in bond investments, offering valuable insights for fixed-income investors to devise effective trading strategies. This study proposes a novel credit spread forecasting model leveragi…
Decision MakingEnsemble Learningfeature selectionStrategic Bidding in 6G Spectrum Auctions with Large Language Models
Efficient and fair spectrum allocation is a central challenge in 6G networks, where massive connectivity and heterogeneous services continuously compete for limited radio resources. We investigate the use of Large Langua…