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 such as executing large orders, market making, targeting VWAP and other schedules, trading pairs or collection of assets, and executing in dark pools. These models are grounded on how the exchanges work, whether the algorithm is trading with better informed traders (adverse selection), and the type of information available to market participants at both ultra-high and low frequency. Algorithmic and High-Frequency Trading is the first book that combines sophisticated mathematical modelling, empirical facts and financial economics, taking the reader from basic ideas to cutting-edge research and practice. If you need to understand how modern electronic markets operate, what information provides a trading edge, and how other market participants may affect the profitability of the algorithms, then this is the book for you.
Financial Modeling with Crystal Ball and Excel, + Website
- Spreadsheet Sensitivity Analysis with Crystal Ball
- Monte Carlo Simulation – NPV example
- Basic Monte Carlo Simulation of a Stock Portfolio in Excel
- Excel – Simple Revenue Forecast (and dealing with outliers)
- Excel Charts – Creating a Revenue Forecast
- No Crystal Ball Required – Predictive Analytics for Business
- GoForecast – Web Model for Financial Forecasting
- Tornado Chart Final
- Excel Sensitivity Analysis
- How an Investment Simulation Can Be Used to Help Build Your Portfolio – Monte Carlo Simulation
Updated look at financial modeling and Monte Carlo simulation with software by Oracle Crystal Ball
This revised and updated edition of the bestselling book on financial modeling provides the tools and techniques needed to perform spreadsheet simulation. It answers the essential question of why risk analysis is vital to the decision-making process, for any problem posed in finance and investment. This reliable resource reviews the basics and covers how to define and refine probability distributions in financial modeling, and explores the concepts driving the simulation modeling process. It also discusses simulation controls and analysis of simulation results.
© 2018 Stephen Collie Enterprises