MACD stands for moving average convergence divergence. This is a momentum indicator that track trends and is one of the most widely used and trusted. The standard MACD settings are 12-26-9 meaning, a fast exponential moving average of 12, a slow exponential moving average of 26 and a signal simple moving average of 9. The MACD makes use of two moving averages where it subtracts the longer period moving average from the shorter period moving average. The MACD moves above and below the zero line as shown in the example below. Unlike the Stochastic indicator, this indicator is not bounded, thus it does not signal overbought and/or oversold conditions. The blue line shown below is the MACD line which makes use of a 12 day exponential moving average, given standard MACD settings. The red line shown below is the signal line and makes use of a 9 day moving average. The green bars shown is the MACD histogram. The MACD is a very powerful indicator due to the fact that copious amounts of information can be read from this one indicator.
The crossover method is the most common method use for the MACD. It applies similar principles that create and operate moving averages and stochastic moving averages. Using the example shown below, this principle will be explained. The crossover method indicates to a trader potential trade entries and potential exits depending on what is displayed. If the MACD line moves from below the signal line and crosses the signal line, this indicates potential bullish movement upwards and is thus is a buying signal. Likewise if the MADC line moves from above the signal line and comes down and crosses the signal line, this indicates potential downward movement and a potential selling zone. An application of this method is shown below.
The second method discussed is the center line cross over. This method is used by traders to also indicate potential trade entries and exits. The application of this method is simple: trades are entered or exited based on the MACD line's position relative to the center line. Using the example shown below the application will be explained in further detail. A bullish buy signal is triggered when the MACD line moves from below the center line and intersects the center line. A bearish sell signal is triggered when the MACD line moves from above the center line and intersects the center line. From the results shown, this method can be known to lead or lag the optimal positions slightly but still provides a good buy and sell method which is geared for longer term trading.
This method can also be combined with the previous method detailed to provide added bullish and bearish buy and sell signals. This is done by looking at where the crossover positions occur. If a bullish crossover occurs above the center line this gives added confidence that the share price will move positively upwards. Likewise if the share price has a bearish crossover underneath the centreline this can if more confidence in the share price moving downwards.
We have now established two methods that can be used to determine potential trade entries and exits using the standard MACD settings. However, for traders wanting more responsive signals the standard settings will not suffice. This is because the standard settings usually lag the optimal trade entry or exit point. Using the established buy and sell triggers we will apply this to a more responsive MACD setup. This setup is a 5-14-3 MACD setup as opposed to the standard 12-26-9 setup. Below one can see how these two methods compare with the top graph being the more responsive 5-14-3 MACD and the bottom graph being the standard MACD. Its very easy to see that the first settings gave better buy and sell signals than the second. If one had traded the MACD in both going long on the buy signals and shorting on the sell signals the profit margins would have been an amazing 83% for the 5-14-3 MACD and 15% for the 12-26-9 MACD. The negative aspect to the more responsive 5-14-3 MACD is that is has a greater chance of a mixed signal as seen in the graph with the narrow crossover labels. For this method it’s better to act on strong crossovers.
Intro to ratio analysis
A Du Pont analysis is a fundamental model that aims to measure how well a company is managing its finances to maximize wealth. This model determines success by the return on equity that a company generates. What makes this a strong financial model is that it combines several confusing financial ratios into three main categories. These are: income, investment and capital structure.
The equation is shown below with the input variables being:
1) Net profit: the profit after working expenses. Calculated by taking revenue generated – cost of goods sold – all expenses – interest – taxes).
2) Total assets: sum of all current and non-current assets.
3) Sales: total revenue generated through sales of a product or services provided.
4) Ordinary equity: this is the total value of a company’s ordinary shares on the market (excluding preference shares). Thus if a company’s stock is trading at $10 and there are 3 000 shares then the ordinary equity is $30 000.
The interpreting of the results is simple. When comparing companies or comparing a company to its sector the one with the highest ROE percentage value will be the most favorable. The individual parts of the formula can also be broken down. A higher (net profit/sales) means that, that company is more profitable. A higher (sales/assets) means that, that company has a better asset turnover. A higher (assets/equity) means that, that company has better financial leverage.
Financial ratios can be subjective in their interpretation. This is where financial distress models come in, as their results are objective in how there are interpreted. The financial distress model that will be explained will be a multivariate discrimination analysis (MDA), this calculation will classify a company as either “failed” or “successful”. This is done by the equation using predetermined ratios dealing with the input data. The output of this calculation will state if a company is in financial distress or not with a company in distress being “failed” and a company not in distress being “successful”. The Model used is the Altman model which is one of the most well-known financial distress models.
The equation is as shown below with the input variables being:
1) Working capital: this is the capital a company uses in operations. Calculated as the current assets – current liabilities
2) Total assets: sum of all the current and non-current assets.
3) Earnings before interest and tax (EBIT): this is a company’s profit before interest and taxes. Also known as the difference between the operating revenues and operating expenses.
4) Market value of equity: This is the total value of a company’s shares on the market. Thus if a stock is trading at $10 and there are 3 000 shares, the market value of equity is $30 000.
5) Book value of total liabilities: this is the total value of liabilities on a company’s financial statement.
6) Sales: this is the total revenue generated through sales of a product or services provided.
