Blog

February, 2015

• 6 February

  Architect of Quantitative Trading Systems

  

  Technology, while a powerful modernizing force, cannot be implemented in a vacuum. In financial and commodity markets, as in most other industries, technology becomes valuable only when applied to business issues. Cost pressures, impending regulatory changes, low trading volumes, and regulation  have combined to create a dangerous crisis of confidence. In cooperation with the business side, advances in technology have the power to help the …

September, 2014

• 16 September

  Quantitative Financial Valuation

  

  Forecasting cash flows The initial step in the valuation process. In order to forecast cash flows, it is important to: Precisely define the components of cash flow. Develop statistical tools to aid in forecasting cash flows. Analyze different types of annuities, which are structured series of cash flows. We mathematically derive the cash flow statement as the result of creating and manipulating a …
• 14 September

  Linux Distributions for Quantitative Finance

  

  Choosing a Linux distribution If you’re new to Linux you’ll face a choice between some unfamiliar distributions. In this article we try to de-mystify those choices. So many options When you’re creating a server instance you have to choose what Linux distribution you want to run. Fortunately the distributions all share a lot of common functionality. They mostly differ in …
• 14 September

  Advanced Derivatives Pricing Theory

  

  Pricing theory for derivative securities is a highly technical topic in finance. Its foundations rely on trading practices and its theory relies on advanced methods from stochastic calculus and numerical analysis. Financial assets are subdivided into several classes, some being quite basic while others are structured as complex contracts referring to more other assets. Examples of elementary asset classes include stocks, which are ownership …
• 11 September

  Data Mining and Computational Finance

  

  The set of computing techniques collectively called data mining methods can be applied to stock market analysis, predictions, and other financial applications. In this article we will discuss outline these methods for financial modeling and present a survey of current capabilities of these methods in financial analysis. There  are two main categories:  adaptive linear and non-linear “mining” of financial data.  Example of such methods as: ARIMA, …
• 9 September

  Data Management in Financial Engineering

  

  “Data is the lifeblood of electronic markets” All financial research requires data, and the efficient management and storage of data is crucial to the profitable operation of a trading system.  Industrial-strength relational database management systems, such as Oracle or MS SQL Server, can store terabytes of such things as historical market data and firm wide trade and position information. Often, …
• 9 September

  Machine Learning and Financial Models

  

  The machine-learning approach to financial modeling is an attempt to find financial models automatically, through a process of progressive adaptation. Machine learning is rooted in statistics and artificial intelligence (AI). There are several machine-learning approaches to automatic problem solving that play a role in financial asset management. Machine learning (and AI techniques in general) is one of the many techniques used in specific applications in financial …