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Technical Analysis

NASDAQ Biotechnology Strategy

The strategy trades long-only the top 20 stocks in the NASDAQ biotechnology index according to entry and ranking criteria in the monthly timeframe. This article includes backtest results and code for subscribers.

NASDAQ biotechnology is a challenging sector for developing strategies because of the high historical volatility and an extended consolidation period from 2004 to 2010. Both trend-following and mean-reversion strategies struggle to generate acceptable returns at relatively low maximum drawdown due to the dynamics of this sector. Survivorship bias is also an issue with developing strategies to trade portfolio of stocks but now thanks to Norgate data we can remove the bias with their newly made available current and past series.

For the backtests in this article we used Norgate data for NASDAQ Biotechnology Index (NBI) that include current and past constituents to remove survivorship bias. We highly recommend this data service to those who would like to remove survivorship bias from backtests (we do not have a referral arrangement with the company. Click on the image below for the company website.)

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Data-mining bias issues

We tested a few different momentum and mean-reversion strategies before identifying one that had satisfactory performance. This practice usually suffers from data-mining bias and the final strategy may be a random result. However, we did not use rules extracted from the data and strategies in their respective group, momentum or mean-reversion, were modified slightly to deal with volatility. Therefore, although data-mining bias is present, we believe it is small since the core of the strategy has worked well in other markets. We could have obtained a much better backtested performance by adding additional rules and filters in hindsight after observing the results, but that would not have served any useful purpose. Data snooping bias is prevalent in quant and pseudo-quant space and it is impossible to now the number of trials and modifications made to arrive at a final result.

Backtest details

Time-frame: Monthly (adjusted data)
Strategy type: Long-only
Market: NASDAQ Biotechnology Index constituents, past and current
Backtest period: 01/02/2003 – 12/30/2020
Commission per share: none
Maximum positions: 20
Position size: Equity/20
Position entry and exit: Open of next bar

Results (Equity curve, monthly returns and drawdown profile)

Below is the buy and hold equity curve of IBB ETF followed by a performance comparison table.

Strategy IBB ETF B&H
CAGR 15.2% 13.2%
Maximum Drawdown -42% -34%
Sharpe 0.58 0.65
MAR (CAGR/Max. DD) 0.36 0.34

The strategy outperforms IBB B&H on absolute and risk-adjusted basis (MAR) but that may be due to a small data-mining bias. However, although IBB ETF performance is mostly achieved in a few years between 2010 and 2015, the performance of the strategy is much more uniform across the full backtest period.

Below is the code of the strategy for subscribers of Premium Articles, Premium Insights or Market Signals.

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Conclusion

Biotechnology is a difficult market to trade due to high volatility and extended periods of consolidation. We tried relatively simple strategies and we were not able to achieve significantly better results than buy and hold on the average but only in the way returns were distributed. Maybe this is a market suitable for stock picking and not for quantitative strategies but this conclusion cannot be made from only this limited analysis.


Charting and backtesting program: Amibroker

Data provider: Norgate Data

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