Multifractal analysis of financial markets: A review
Multifractality is ubiquitously observed in complex natural and socioeconomic systems.
Multifractal analysis provides powerful tools to understand the complex nonlinear nature of …
Multifractal analysis provides powerful tools to understand the complex nonlinear nature of …
Generating synthetic data in finance: opportunities, challenges and pitfalls
Financial services generate a huge volume of data that is extremely complex and varied.
These datasets are often stored in silos within organisations for various reasons, including …
These datasets are often stored in silos within organisations for various reasons, including …
[图书][B] Algorithmic and high-frequency trading
The design of trading algorithms requires sophisticated mathematical models backed up by
reliable data. In this textbook, the authors develop models for algorithmic trading in contexts …
reliable data. In this textbook, the authors develop models for algorithmic trading in contexts …
Get real: Realism metrics for robust limit order book market simulations
Market simulation is an increasingly important method for evaluating and training trading
strategies and testing" what if" scenarios. The extent to which results from these simulations …
strategies and testing" what if" scenarios. The extent to which results from these simulations …
Generating realistic stock market order streams
We propose an approach to generate realistic and high-fidelity stock market data based on
generative adversarial networks (GANs). Our Stock-GAN model employs a conditional …
generative adversarial networks (GANs). Our Stock-GAN model employs a conditional …
[图书][B] Parameter estimation in stochastic volatility models
JPN Bishwal - 2022 - Springer
In this book, we study stochastic volatility models and methods of pricing, hedging, and
estimation. Among models, we will study models with heavy tails and long memory or long …
estimation. Among models, we will study models with heavy tails and long memory or long …
Robust market making via adversarial reinforcement learning
We show that adversarial reinforcement learning (ARL) can be used to produce market
marking agents that are robust to adversarial and adaptively-chosen market conditions. To …
marking agents that are robust to adversarial and adaptively-chosen market conditions. To …
Deep order flow imbalance: Extracting alpha at multiple horizons from the limit order book
We employ deep learning in forecasting high‐frequency returns at multiple horizons for 115
stocks traded on Nasdaq using order book information at the most granular level. While raw …
stocks traded on Nasdaq using order book information at the most granular level. While raw …
Multi-agent reinforcement learning in a realistic limit order book market simulation
Optimal order execution is widely studied by industry practitioners and academic
researchers because it determines the profitability of investment decisions and high-level …
researchers because it determines the profitability of investment decisions and high-level …
State dependent parallel neural Hawkes process for limit order book event stream prediction and simulation
Z Shi, J Cartlidge - Proceedings of the 28th ACM SIGKDD Conference …, 2022 - dl.acm.org
The majority of trading in financial markets is executed through a limit order book (LOB). The
LOB is an event-based continuously-updating system that records contemporaneous …
LOB is an event-based continuously-updating system that records contemporaneous …