Investment Models
Investment Models are a set of mathematical calculations based on data to help analyze investments. These models can be built to help analyze the past, present, or future. In general they provide estimates of investment returns and prices; however, they can also help estimate trade volume, economic growth, sales, and etc. Below is a brief overview of different types and aspects of investment models.
Macro versus Micro Focus
Macro models provide estimates on the economy, industry, currencies, or a universe/group of similar investments. Micro models provide estimates on particular companies, specific projects, or a single asset.
Technical versus Fundamental Data
Without data a model cannot be created. Technical data involves looking at historical trend price trends and market activity. Fundamental data on the other hand uses economic or company specific data such as retail sales for a retailer, oil prices for an oil driller, and population within a 5 miles radius for a shopping mall.
Statistical versus Financial Statement Built
Models are typically built using statistical methods or financial statements (cash flow, income, balance sheet). A statistical model uses relationships between different observations like size of the company to project another variable such as next year's sales growth. In finance, larger companies exhibit slower sales growth. Financial Statements meaning that an analyst would project out items on the financial statement, typically future sales and the model will calculate other financial statement items like cash flow, net income, gross margin, net present value, internal rate of return, and etc. An analyst can also project many other parts of the financial statement and the model will calculate the effects on other financial statement items.
Macro versus Micro Focus
Macro models provide estimates on the economy, industry, currencies, or a universe/group of similar investments. Micro models provide estimates on particular companies, specific projects, or a single asset.
Technical versus Fundamental Data
Without data a model cannot be created. Technical data involves looking at historical trend price trends and market activity. Fundamental data on the other hand uses economic or company specific data such as retail sales for a retailer, oil prices for an oil driller, and population within a 5 miles radius for a shopping mall.
Statistical versus Financial Statement Built
Models are typically built using statistical methods or financial statements (cash flow, income, balance sheet). A statistical model uses relationships between different observations like size of the company to project another variable such as next year's sales growth. In finance, larger companies exhibit slower sales growth. Financial Statements meaning that an analyst would project out items on the financial statement, typically future sales and the model will calculate other financial statement items like cash flow, net income, gross margin, net present value, internal rate of return, and etc. An analyst can also project many other parts of the financial statement and the model will calculate the effects on other financial statement items.