**Introduction**

Swing trading is defined as a method where open positions can last a day, up to several weeks. Our aim with this article is to provide several of the indicators and modes of technical analysis as they apply to swing trading, with clear definitions and examples. We highlight the importance of cross-validation after fleshing out matters of definition.

**Basic Swing Charting and Use Cases**

Minimal stock charts used for swing trading encapsulate *trends*, rather than capturing *noise* (e.g. dividend yields, algorithmic trading). Hence, by diminishing these external noise factors on longer time dimensions, a swing chart reveals “network-wide” market sentiment on the whole via trend analysis.

There are several means of uncovering trends through simple metrics as well as more advanced technical indicators. We will first enumerate several simple means of price discovery, before moving into the definitions of the technical indicators that we use as apart of our swing trading strategies.

This list is, by no means, comprehensive, but is representative of many of the indicators that we use as part of our newsletter.

**Major Indicators and Definitions**

*Simple Metrics*

The following definitions lay down some basic notions, or something of an “axiomatic system”, from which higher forms of technical analysis can be generated from. These simple metrics largely ground themselves in the idea that price is a function of time, and try to find meaningful relationships between a given time dimension to anticipate the general trend of an equity.

Highs and Lows: As the name implies, highs and lows defines the upper and lower limits for the price of an equity for a given time dimension. The overall trend of an equity can be teased out by drawing trend lines through the highs and lows of a chart. A very naive swing trading strategy might be to use lows as stop-losses, and use progressively higher “steps” as take-profit points.

Price Channels: Unlike simple trend lines, creating a price channel entails directly connecting highs and lows in a chart. With this dynamic process, your stop-losses and take-profit points start *moving*, in the sense that progressively higher or lower limit points help inform trade decisions on a swing.

Bars and Pivots: On a regular candlestick or bar chart for an equity, there are ways of discerning the “turning points” of a trend using colour coding. These codes are distinguished between Up and Down Days versus Inside and Outside Days.

Using simple logic, one can then generate “pivots”, or bounce points, from which price creates a new trend. One example of this would be to alternate between up and down days (e.g. if day one was up, then day two will be down).

*Complex Analysis*

Stochastic Relative Strength Indicator (RSI): In name, measuring an equity’s “relative strength” implies using highs and lows relative to a time dimension you are trading on. The result of this calculation is a number between 0 and 1, which then generates a line plot, obtaining what is called an “oscillator”, or cyclical pattern.

The highs and lows of *this* plot entails whether an equity is overbought or oversold it is.

Stoch RSI = (RSI – Lowest Low RSI) / (Highest High RSI – Lowest Low RSI) As implied in the previous section, this indicator emerges directly as a consequence of understanding, or having a foundation for, calculating pivot points on a swing chart.

Squeeze Momentum: Derived from John Carter’s “TTM Squeeze”, this indicator is used as a measure of volatility. When represented visually, one can discern whether price is in a cycle of low or high volatility, and predict whether there will be upside or downside momentum in an “explosive trend”.

Under the hood, squeeze momentum is calculating using a mix of moving averages, standard deviation, and linear regression. Once again, these are metrics which largely emerge from a trader’s ability to uncover simple trends regardless of time dimension.

*Moving Average (MA)*: Also called a rolling or running average, MA’s are simply the averages of a fixed subset in a series of numbers. In a system such as a financial time series, this means taking the sum of prices and normalizing about the number of elements in that set of prices. When represented on a chart, using 200, 100, 50, and 20-day MA’s are useful in predicting the direction of price action. Before the advent of computers, this discipline constituted “tape reading” in early stock markets.

*Convergence/Divergence*: Convergence means “coming together”, while divergence means “moving apart”. In financial systems, these events refer to a directional trend with respect to price, and are represented on the “MACD” indicator.

*Volume*: Amount of shares traded between buyers and sellers. Used as a measure of power or activity in an equity.

*Geometric Indicators*

Symmetry Analysis: The method of using simple patterns and trend-lines within a bar or candlestick chart as a vehicle for predicting whether price will follow (or “remain symmetric”) in the future.

Fractal: Abstract pattern which retains a similar pattern, regardless of scale. For example, if one was to draw a series of trend or channel lines on a daily chart, it would be expected that price follows the same pattern on a tighter time dimension.

Fibonacci: In trading terms, this discipline refers to the method of retracing minimum and maximum points on a chart at higher time dimensions (as in a swing trade) to generate probabilities, or *extensions*, of where the trend may go. In combination with charting trend-lines, the overall pattern resembles a numerical sequence discovered by Italian mathematician Fibonacci.

**Bringing it all together**

Academic and financial circles have long been in a debate about the efficacy of technical analysis. While opinions have ranged from technicals being no better than astrology, up to technicals as being purely quantitative (and hence, powerful predictive systems), we strive to err on the side of cross-validation. None of these indicators on their own can ever constitute a “secret sauce”. Instead, using these indicators in concert with each other, and validating them against fundamental knowns about an equity, account for a high degree of risk factors.

As such, technical swing trading is a highly dynamic process in terms of predicting sentiment relative to multiple technical features, but diminishes many of the problems day traders have in terms of volatility. Hence, we consider it a stronger entry point to a trader’s education than the “bottom-up” approach of attempting to compete on tighter time-frames.

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