Challenges In Financial Data Engineering | Data & Feature Engineering for Trading

FREE PREVIEW: https://quantra.quantinsti.com/course/financial-data-science-feature-engineering Welcome to this video lesson on challenges in financial data. After completing this video, you will be able to list the most common challenges faced in financial data. The six most common challenges faced in the financial data are shown on screen. These are common challenges that we will discuss in the course in detail. In this video, we will give you an overview of the mentioned challenges. The first challenge is ever-changing company names or tickers. To overcome this problem, some of the data vendors have created a unique identifier for companies. However, different data vendors use different unique identifiers. So it is complicated to merge data from different vendors. The second challenge is in the event of corporate actions such as dividend or stock splits; there is a change in the stock price. Some data vendors smoothen the stock prices to incorporate the impact of the corporate actions, and this is called an adjusted price series. Depending on the strategies, you need to choose adjusted price or unadjusted price series. The third problem is survivorship bias. Often you backtest the strategy on the current stock universe instead of the historical stock universe which causes survivorship bias in the data. Apart from stock databases, the issue of survivorship bias also prevails in many other databases such as futures and forex. Something more insidious than survivorship is look