 The financial services industry and in particularly the investment and portfolio management sub-field has a quite a few industry specific terms. As a group, financial professionals tend to think most people who are not in our industry understand many of terms we use so freely - which of course isn't necessarily true. So I've attached a link to a great resource of financial glossary terms provided by YCharts.com. If you are an avid financial reader or DIY investor you might want to book mark this page, and then when you come across a term you aren't sure about, you'll now have a way to bring yourself up to speed. The link is at the very end of this article. From the several hundred definitions provided, here are a couple of examples, taken directly from the financial glossary (Altman Z-Score and Beta) at YCharts.com: ALTMAN Z-SCORE CAUTION: The Altman Z-Score is meant to be applied only to manufacturing firms that are near bankruptcy. It was not based on a sample including non-manufacturing firms (service firms, banks, etc.). Use it at your own risk with those companies, but beware that bankruptcy probabilities may be misstated. The Altman Z-Score helps investors to gauge the probability of a company going bankrupt. Generally, firms with a score above 3.00 have a low probability of bankruptcy, and those with a Z-Score of less than 1.81 have a relatively high probability of bankruptcy. Note that this is a probabilistic model, so it will not classify perfectly. The score was first published in a 1968 paper by Edward Altman titled "Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy." Altman re-tested the model in a 2000 paper titled "Predicting financial distress of companies: Revisiting the Z-score and Zeta models". The paper showed that the model still had utility for looking at manufacturers, though the number of misclassifications did increase over time. FormulaZ = 1.2 x (Working Capital / Total Assets) + 1.4 x (Retained Earnings / Total Assets) + 3.3 x (Earnings Before Interest and Taxes / Total Assets) + 0.6 x (Market Value of Equity / Total Liabilities) + 1.0 x (Sales / Total Assets) Where: Working Capital = Current Assets - Current Liabilities Market Value of Equity = Market Cap + Preferred Stock BETA Beta is a measure of the risk of a stock when it is included in a well-diversified portfolio. In financial theory, the Capital Asset Pricing Model (CAPM) breaks down expected stock returns into two components. The first is the return that would be expected based on covariance with the movements of the market (for most stocks, when the market as a whole goes up, the price of the stock will also go up). This is considered systematic risk. The second part is the increase in the price of a stock that is not explained by the market (nonsystematic risk). The first part - covariance with the market - is what Beta captures. When Beta is positive, the stock price tends to move in the same direction as the market, and the magnitude of Beta tells by how much. If a stock's Beta is greater than 1, that means that when the market index goes up 1%, we expect the stock will go up by more than 1%. On the contrary, if the market goes down by 1%, we expect the stock to go down by more than 1%. Negative betas signify a negative correlation. When the market goes up, a stock with a negative beta would be expected to go down. For readers with a background in regression analysis, Beta is the slope of the linear regression shown in the formula below, where Returns are the return on an individual stock or portfolio, R_f is the risk free rate, R_Market is the return on a market portfolio, and e is an error term. So take a look around and enjoy a great resource from the YChart.com website. Click the link below. -Paul R. Rossi, CFA Financial Glossary (ycharts.com)
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