
The BB IQ strategy utilizes the Momentum effect by purchasing stocks that are in the Exponential Move phase and those that are among the strongest in the index.

Inspirations
The BB IQ strategy leverages the widely discussed Momentum effect in the stock market. Unlike a pure trend, it requires a stock to enter the Exponential Move phase and simultaneously be among the TOP fastest-growing companies in a given index.
The strategy buys the strength of such assets when they achieve the momentum effect and follows the position until the trend is exhausted. A strong point of the strategy is the distinct forces it utilizes compared to reversal strategies, making it a valuable component of a well-balanced portfolio.
Key Components
Custom settings for Bollinger Bands to identify the Momentum effect
Additional filters to exclude opening positions in market conditions unfavorable for the strategy.
Stockpicker Mechanism, which searches for and automatically selects stocks meeting the criteria.
Backtest 1, Fixed $ Money Management
In this variant, we consistently invest the same amount of $100k, which is divided by the maximum number of open positions.
We are testing the period of the last 30 years from 1994 to 10.2024.
You can find the latest backtest results below by clicking the yellow button.
The backtest automatically selects stocks that meet the criteria from the S&P500 index. Let's remember that the list of stocks included in the index has changed over the years, which is accounted for by the data used in Stockpicker (survival bias).
Invested capital: $100k
Tested period in years: 30
Tested years: 1994-10.2024
Tested Index: S&P500
Equity Chart for this test:
Basic statistics and results month by month:
The above table in percentage format looks as follows:
It should be noted that the above results only show values for closed positions. Therefore, the high value indicated in the last month of the test results from closing all open positions at the end of the test.
Summary of statistics - all data according to the closing date of positions.
Click the button to see the latest backtest:
Backtest 2, % Money Management
In this backtest, we invest in the strategy with a constant 100% of the current capital (with a $100k initial capital). This means that as the capital increases or decreases, the position value changes proportionally. The rest of the parameters remain unchanged.
The Equity Chart for this test and the comparison with the Benchmark are presented below. The imperfection of this view means that transactions closed only at the end of the test (and they represent a large value) are barely visible on the chart. However, we have a complementary table view here.
Basic statistics resulting from the test:
Net Profit and CAGR
Net profit above $5.9 million is significantly higher than the Benchmark (S&P 500 Index in the form of ETF SPY marked in yellow on the chart), which amounts to $2.1 million, translating to a CAGR of 14.62% vs 10.94%. This means that the studied strategy achieves a higher net profit and a higher average annual return rate, indicating its very good efficiency in generating profits over the long term.
Drawdown and Return/Drawdown Ratio
The Max Drawdown in the studied strategy was 15.1%, resulting in a Return/Drawdown ratio of 20.17.
Important
In backtests of Stockpicker-type strategies, at the time of writing this article (10.2024), the Open Drawdown result is not shown. Therefore, Max Drawdown only pertains to closed positions, and one should be prepared for a larger Open DD in real trading.
According to our tests, the lack of capturing Open DD does not have significant importance in short-term strategies like Reversal, where positions are held for an average of a few days, and Open DD is quickly converted to Closed DD. However, in Momentum or Trend strategies, where the average holding period is close to 200 days as in this case, Open Drawdown can be significant and should be taken into account.
To estimate if Open DD could be significant for this strategy, I ran a simulation by adding a Stop Loss percentage. By default, the strategy only includes a conditional Trailing Stop, not a Stop Loss.
The simulation is conducted under the same conditions as in Backtest 1, i.e., for MM$ 100k USD.
Here are the Net profit results with SL introduced at different levels (from 1% to 40%):
As can be seen, the introduction of SL significantly reduces Net Profit only for the lowest SL values (up to 10%).
Similarly, this is the case with Max Closed Drawdown expressed in $:
As can be seen, the possible introduction of SL provides stable results at the level of Net Profit and Drawdown. The exception is SL values below 10%, which significantly worsen the strategy.
The equity chart for the strategy with a sample 20% SL is as follows.
Additionally, we checked how Closed Drawdown vs. Open Drawdown looked on this strategy by testing it individually on randomly selected tickers (we opened all available positions without filtering these companies in relation to others in the index at that time). For individual tickers, Open DD is reasonably shown in SQX. The test was conducted on data from 1994 with MM%. Here are the results:
The sample is not large and not representative, but we wanted to get an idea of how hidden Open Drawdown might affect the strategy. The difference here was about 5-6%.
For safety, I would assume that the Max Open Drawdown for this strategy should be at least 10% greater than the Max Closed Drawdown.
Introducing a Stop Loss (SL) could additionally provide greater comfort in using the strategy. If you have any dilemmas on how to do this, feel free to contact us.
Exposure
The average exposure in the studied strategy was 80% vs 100% in the benchmark. Here's how it looked historically:
As you can see, the average exposure was about 80%. However, during Bull Market periods, the strategy practically always traded at 100%, and during periods unfavorable for the stock market, it reduced positions or remained entirely in cash. This is a logical and correct behavior.
The study was conducted on the underlying instrument, i.e., S&P500 stocks. We measure exposure with a dedicated tool, which you can read about here.
Winning percent and avg. Win/Loss
The winning percent in the studied strategy was 54.0%. This means that the majority of transactions were profitable, which is a very good result for Momentum or Trend strategies, whose statistical advantage mainly lies in capturing large prominent trends and so-called outliers, rather than a high Winrate.
At the same time, the Avg. Win was nearly 2.9 times greater than the Avg. Loss, which is clearly visible in the MM$ test results. Thus, the strategy profited from both the Winrate and the avg. Win/Loss ratio.
SL
The strategy doesn't use a stop loss by default, but it can be easily added, as shown in the study above. Protection against a significant price change of a single stock affecting the entire portfolio is provided by the Exit Rule. This rule acts as a Trailing Stop. Additionally, the strategy includes diversification with 20 parallel positions by default. We also recommend diversifying strategies within the strategy portfolio.
Market regime
The strategy has been tested in all major market regimes and includes filters implemented based on this testing.
Trading costs
The backtests took into account trading costs and slippage that occurred on a real account in our tests for the broker Alpaca (detailed study). With a diversified stock and strategy portfolio, transaction costs can determine your profit or loss, so take the time to thoroughly test and choose a broker.
Robustness
The robustness was examined by conducting a very large number of stock transactions for the period from 1994 to October 2024 for the S&P500 indices (2,929 transactions with Max Open Positions 100), Russel1000 (6,023 transactions with Max Open Positions 200), and Nasdaq100 (1,028 transactions with Max Open Positions 50). The study was conducted using %MM to capture comparable parameters.
The results are as follows:
As can be seen, the results at the level of individual indicators are very similar, which indicates the robustness of the strategy across different categories of stocks.
Additionally, this strategy has passed our conducted tests of parameter modifications (System Parameter Permutation). The applied parameters are in robust areas and can be modified by +/-25% without significantly affecting the strategy.
We adhere to the principle that the fewer parameters, the greater the robustness of the strategy. Therefore, we strive to ensure that our strategies have as few parameters as possible and to select only those parameters that have a significant impact on the strategy's effectiveness while aligning with its nature.
Recommended Instruments
The recommended primary instrument for this strategy in Algocloud Stockpicker is the S&P 500 companies, but as shown by the above research, the strategy should perform comparably well on other indices. When trading small-cap stocks like those in the Russell index, one should account for greater slippage and potential liquidity constraints (it is recommended to introduce a minimum daily transaction value filter, i.e., price x volume, for this index).
Primary Instrument: S&P 500
Additional Instruments: Stocks from other US indices
Pattern Day Trader
The strategy did not close any transactions on the same day, so it does not meet the Pattern Day Trader (PDT) criteria. This means it can also successfully operate on accounts below $25k.
Correlation
To check the correlation of the strategy with others, go to the page dedicated to correlations.
The strategy shows an inverse correlation to reversal strategies, which is a significant advantage.
This means that:
if the market is rising strongly, Reversal strategies have often already taken profits, while BB IQ will keep us in the trend, often outperforming the market.
if the market falls sharply in an upward trend, Reversal strategies may incur short term losses, while BB IQ collects long-earned profits from its positions, thus balancing the losses of the former.
Like all strategies of this kind, it is expected to cut losses quickly after implementation. Only in the long term will it start taking profits.
Summary & Strengths and Weaknesses
Strengths
Net profit above $5.9 million, which is significantly higher than the Benchmark (S&P 500 Index), which was $2.1 million, with CAGR 14.62% vs 10.94%. The Max Closed Drawdown was 15.1%, and the Return/Drawdown ratio is 20.17.
Avg. Win was simultaneously 2.9x greater than Avg. Loss and Winning percent at 54.0%, which is a very good result for this type of strategy.
Inverse correlation to reversal strategies: It shows an inverse correlation to reversal strategies, making it a valuable component of a well-balanced portfolio, especially during periods of strong growth impulses.
Robustness: The strategy successfully passed parameter modification tests and tests on 3 different indices, indicating its resilience to various categories of stocks and different market behaviors in the future.
Weaknesses
Long holding period: The average holding period is about 200 days. This means that during bull markets, practically all entrusted capital is engaged here.
Not fully recognized level of Open Drawdown, as detailed above.
Different significance in different periods. Momentum strategies can add value in various markets. However, we believe their main role in a portfolio is during the early phase of a Bull Market. In a mature Bull Market, reversal strategies might play a bigger role, while Momentum can help balance the portfolio.
Summary
Momentum is a strong trading concept that has been active in markets for hundreds of years. A trend is more likely to continue than to reverse, and BB IQ effectively captures the strongest trends and follows them until they are exhausted. Despite its simple rules, backtests over the last 30 years show very good results. It offers a different approach compared to reversal strategies, making it an attractive option for investors seeking active capital growth. While its weaknesses should be considered, this strategy can be a valuable part of a balanced investment portfolio.
What you get in the package for this strategy:
Ebook describing detailed rules and results of the strategy.
SQX file ready to use on the Algocloud and StrategyQuant platforms.
Pseudocode that describes all the rules in an easy-to-understand way.
Key indicators in a format intended for TradingView (pine script).
BONUS - Strategy showing basic signals on the TradingView chart (in pine script format).
If you need the code for this strategy in the following formats: Tradestation (easylanguage), Multicharts, MT4, or MT5 (MQL), contact us on this topic.
Disclaimer
The results obtained from historical data do not guarantee future outcomes. The effectiveness of a strategy can change over time. Backtesting is a tool that allows for the analysis and evaluation of an investment strategy based on historical data. Various factors, such as market changes or economic conditions, can influence the effectiveness of a strategy over time.
Investing always involves risk. This material is not investment advice. We share our experience and algorithms for educational purposes. We make efforts to ensure that our algorithms are error-free, but neither we nor the tools we use guarantee the absence of technical issues. Any decisions to use a particular strategy are made at your own risk and should be preceded by careful understanding and verification. You should always carefully consider your investment goals and risk tolerance before making investment decisions.
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