Is there a right data for financial modeling, we will explore the difference between exogenous and endogenous factors and learn about the different types of financial data that are used to create quantitative models of asset prices. Once you have a good understanding of how financial data is used in trading and investing, you will use the power of BigQuery ML, to create a model to predict the performance of data processing machines from competing manufacturers. This is an example of modeling exogenous or fundamental data, that you can use to decide which manufacturer stock you want to buy and which want to sell short. First, we'll identify the different types of features or factors that can be modeled using financial data, then we'll explore how they can be used to create models of asset price behavior and make trading and investment decisions. Trading models try to predict relatively short-term changes in the price of an asset. Investing models have a longer time horizon and focus on estimating the fair value of assets relative to their current price. Both types of model require lots of data from a variety of sources to identify features or factors that are useful in predicting price changes. In trading and investing model input factors are categorized as either endogenous or exogenous. You can think of endogenous factors as anything related to the price or volume traded of an asset. Endogenous factors are also called technical factors. Endogenous models also assume that all available fundamental data is already incorporated into the assets current market price and so is irrelevant. Trading volume is a secondary technical factor that reflects market conviction and helps distinguish trading price invoice for more durable changes in price. Here's an example of an endogenous or technical model for AAPL, where we use historical stock prices, order book information, and trading volume to predict changes in AAPL share price. Exogenous factors are external information that can be expected to impact in assets' current price, and the long-term value. They are based on fundamental or real data and also macroeconomic data. Fundamental and macro data are usually but not always, released on a scheduled date at a particular time. Traders create models to compare analyst expectations to the actual numbers released. This helps them to predict both the direction and size of changes in share prices after announcements. These event-driven models can be used as an add-on to technical models, but in most often uses stand-alone by traders who specialize in profiting from market reactions to the release of new data. Here we show a different model for AAPL based on exogenous factors like earnings releases and supplier in customer shops. The key takeaway here is that, exogenous variables affects share price but are not dependent on share price. So who uses endogenous or technical models? Technical models are used by high-frequency trading groups such as Renaissance Technologies. They can be statistical models of ultra short term behavior based on volume, bid-ask spread, and volatility or a longer-term models or price trends that seek to identify momentum patterns and reversals. Generally, fundamental or macro data have already been released, are ignored by technical traders. However, in order to protect themselves against large losses when fundamental or macro data is released, many technical traders avoid trading immediately before and after these events. Now it's your turn, which of these factors would you include in your technical model? Which of these factors are endogenous? So how did you do? For technical factors we got trading volume mesh with price to track volume weighted average price, quarterly earnings announcements, and transit stock prices measured by momentum. This means that the other factors are event-driven or exogenous. Event-driven models take the current market prices that are given and try to anticipate the market short-term reaction to the release of fundamental data, on the company itself, its suppliers and customers, and also the release of macroeconomic data that can affect the company's share price and performance. This data is released in frequently, usually quarterly or monthly, but can trigger very large moves and share prices, and so can be more profitable to trade in technical factors alone. Remember that all of the factors shown here have an impact on share price. Depending on whether you are a technical trader or an event-driven trader, you will specialize in using endogenous or exogenous data to drive your trading strategy. The distinction between endogenous and exogenous factors is unique to quantitative trading. Economists and statisticians draw a different distinction. Endogenous factors or variables are determined by the model itself. Exogenous factors and variables are determined outside the model and are taken as given by the model.