QuantMastery.com Quantitative Finance Newsletter
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“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, historical market data is simply the opening, high, low, and closing prices or other time- incremented data such as implied volatilities, but it could also be more qualitative, economic, or fundamental data such as earnings report data, stock splits, or Fed actions. Whatever the case, analysis of data requires not only the knowledge of quantitative methods, but also the programming tools to implement that analysis in a real- life environment.
Top financial engineers estimate that only a fraction of financial engineering actually deals with mathematics. The lion’s share of time applies to the actual construction and analysis of models and forecasts and technology development. The majority of a financial engineer’s time engaged in construction, though, is not simply spent coding. Rather, the entire development process requires this amount of effort; actual time spent coding should be just a part of it. As you grow in your understanding of programming and trading and/or risk management system development, you will become increasingly aware that comprehensive blueprints, or plans, or development methodologies, of a project must be laid out before any nails are hammered or computer keys pressed. The value of a development project methodology cannot be underestimated.