Technical analysis uses history to forecast future price movements and what is likely going to happen in the future. There is no form of analysis that guarantees what is going to happen in the future to a price of a stock, however, technical analysis is used to anticipate what could happen based on previous price history. Technical analysis can be used to assess the following 3 factors:

• Direction - Will the stock move higher/lower?
• Magnitude - How much higher/lower will the stock move
• Timing - How long will a bullish/bearish move last?

Benefits of Technical Analysis

Provides an objective view on price when using a methodological approach. To stay as objective as possible, it is important to stick to the same strategy or indicator used in previous trades. Many traders will change their indicator or strategy based on their bias on a stock. Technical analysis is applicable to all instruments with a price and can be used on all time frames whether it be a 1 minute forex chart or a monthly fixed income chart.

Limitations of Technical Analysis

Strategies may only work in certain market conditions. Some technical strategies will work better in sideways markets, and others work better in trending markets. Traders should analyze whether the strategy implemented was in the right environment. There is no such thing as a best strategy or best indicator. What separates successful traders from the rest isn't what indicator they use, but rather how consistent and methodological their use of an indicator is. One way to implement a consistent methodological approach is to not change indicators based on a bias. For example, if a trader has a bias that XYZ stock is bearish but a 21 period moving average says otherwise, the trader may be tempted to use a 50 period moving average that provides a false confirmation of their own bias.

Technical Indicators

Technical indicators aim to forecast future price movement based on historic price or volume and generate bullish or bearish signals to give traders a better idea of the possible future price movement in a stock. Technical indicators can either be lagging or leading:

Lagging Indicators – (Example - Moving Averages)

These indicators are based on previous price action to help make decisions on what can happen in the future. One popular strategy is the moving average crossover strategy. Moving averages can sometimes act as a dynamic support or resistance level as shown in the chart below. When price moves above a moving average, sentiment may change to bullish for that particular stock (and vice versa). Using the moving average crossover strategy helps give a clear sense of direction but an unclear sense of magnitude as moving averages do not tell the trader how far above or below the moving average line price will go. 

Leading Indicators – (Example - MACD, RSI, Stochastics)

Leading indicators are used to signal momentum reversals and not magnitude. Leading indicators give a clear sense of direction but unclear sense of magnitude. These indicators are used to show when momentum is speeding up and slowing down - when momentum is overbought and oversold:

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Leading indicators are often misused by traders as sometimes the actual price chart is overlooked. These indicators are better used to confirm the trader's views instead of being the sole instrument in deciding the trend of the stock. For example, if a stock is trading at resistance and a reversal is expected, leading indicators should be used as additional confirmation to short the stock only after looking at the actual price chart. When using leading indicators, selling credit spreads is the best strategy to utilize. This is because that these indicators alone cannot confirm a reversal in price. Even if the RSI shows that the stock is overbought, price may still hover in that area for a long time. Selling credit works best as there is a more neutral sentiment due to the fact that the stock moving much higher is unlikely when it is already overbought. 

Technical Indicator Performance

At OptionsPlay, we evaluated some of the most popular technical indicators and strategies to see how well they performed. Firstly, we calculated a benchmark return to compare our strategies against. This was calculated by entering a long and short position in completely random stocks on randomly selected dates in the S&P 100 with a holding period of 30 days. We then tested the same method of buying or selling a stock on a date where a technical indicator generated a buy or sell signal for 30 days. While this does not represent the best possible back-test, it provides a level playing field to gauge all the indicators under equal conditions. The back test was conducted on price data from 2007 to 2020. 

The benchmark returns calculations showed that the return on long positions in 10,000 randomly selected stocks on random dates, held for 30 days, had an average win ratio was 54.3% with an annualized return of 11.5%. 

After the benchmark returns were calculated, we proceeded to test each indicator under the same conditions for both long and short positions, during the same period (2007 – 2020) and the same holding period of 30 days. Analysis of the results provided some surprising observations.

Observations Summary:

• We were surprised as to how strongly randomly selected stocks on random dates that were held it for 30 days performed. This set a very high bar for each technical indicator to beat. 
• Sell signals from the technical analysis strategies performed extremely poorly. Not a single technical indicator performed better than the benchmark annualized return for short entries. This speaks to the market’s natural upward drift that puts short positions in a statistically disadvantage and proves how difficult it is to consistently call short trades using technical analysis. 
• The CCI indicator proved to yield the best annualized return for buy signals. CCI provide a standout performance compared to other similar momentum oscillator type indicators. 
• Most strategies had a surprising high number of consecutive losses. This is critical for trader’s risk management strategy. With limited amounts of capital to risk for each trade, traders need to understand in a worst-case scenario. The number of consecutive false signals have historically ever generated by each indicator is important to determine the amount of capital to risk on each trade and avoid account blowups even in a worse case scenario. 
• The Simple Moving Average (SMA) performed better than the Exponential Moving Average (EMA). Moving averages are widely used and fiercely debated as to their efficacy and success rates. While the Moving Average period will vary widely dependent on an investor’s time horizon, we have found that simple moving averages lead to higher returns vs. a faster adapting exponential moving average. 
• Most momentum indicators yielded very similar results, which was an important observation to highlight. We have always advocated for investors to not mix multiple momentum indicators. We have found no evidence of better returns by using multiple momentum indicators at the same time. 

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Benchmark Returns

The benchmark returns between 2007 and 2020 were calculated by entering a long/short position with a randomly selected stock and holding this position for 30 days. This resulted in the following benchmarks for long and short positions:

Long

Win ratio: 54.3%

Annualized return: 11.5%

Short

Win ratio: 42.7%

Annualized return: -7.1%

All the results of the strategy back testing are compared to the benchmark return to give an idea of how well they perform.