The equity curve of this simple strategy is interesting as it reveals a major regime shift in market dynamics.
With so many tech stocks surging recently and especially before or after earnings announcements, I thought of looking at the historical performance of a simple strategy that buys these stocks after 20% or larger daily gain.
For the backtests in this article I used Norgate data for NASDAQ-100 index that also include current and past constituents to remove survivorship bias. In the backtest the strategy trades the stocks that were part of the index at the time the signals were generated.
Initial capital is $100K and a fixed dollar amount of $20K is allocated to open positions when there is a signal. If there are more signals than available equity, they are ignored. No leverage in used in the results.
Portfolio backtest settings
Strategy: Buy a stock if the daily return is larger than 20%
Time-frame: Daily (adjusted data)
Strategy type: Long-only
Universe: NASDAQ-100 past and current constituents
Backtest period: 01/04/1993 – 09/01/2020
Commission per share: $0
Position size per stock: $20K fixed dollar amount
Trade entry: close of signal bar.
Trade exit: 5 or 10 days after entry at the close.
Backtest equity curve for 5-day exit (Log scale, Click on image to enlarge.)
The strategy was unprofitable in the 90s. The equity of the strategy became chaotic during the dot com bear market and then there was a flattish period. The strategy became profitable after the financial crisis with a steady equity uptrend.
Apparently then, there was a major regime shift after 2008. Specifically, in the past there was profit taking after large up moves but in the last 10 years it seems the market favors short-term continuation.
If we increase the holding period to 10 days, below is what happens to the equity curve.
Backtest equity curve for 10-day exit (Log scale, Click on image to enlarge.)
The chaotic region during the dot com bear market is smoothed out due to longer holding period. The strategy losses practically all of the starting capital from 2000 to 2009 but then the equity curve starts moving on an uptrend. Here the regime shift is even more evident: what failed before 2008 has worked well afterwards.
Regimes shifts are important and this was the main point of this brief analysis. These shifts in market dynamics are one reason that trading strategy development is hard. Knowing when market conditions change is often more important than strategy development and analysis.
If you have any questions or comments, happy to connect on Twitter: @mikeharrisNY
Disclaimer: No part of the analysis in this blog constitutes a trade recommendation. The past performance of any trading system or methodology is not necessarily indicative of future results. Read the full disclaimer here.
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