rsi trading strategy 5 systems backtest results

A reader asked if I could backtest a trading strategy settled on the RSI(2) field indicator.dannbsp;Almost RSI strategies trade mean reversion setups, however, this is actually a movement following scheme.

The idea is to follow trends and use an RSI(2) pullback to get a better price entry. We wait for the RSI(2) to turn back upwardly before entering the trade then position a point loss at the previous sway low.

Strategy Rules

The full buy and trade rules of this scheme can be delineate as downstairs:

Buy Rules

Close dangt; MA(200)
Mum(5) dangt; MA(200)
RSI(2) crosses over 10
21-day average turnover dangt; $200000
Close dangt; 2

Sell Rules

MA(5) danlt; Mommy(200)
Stop loss placed at swing low before RSI cross (lowest 5-day low)

Swap Example

The pursual chart provides a trade model in United Airlines (UAL):

Business deal Submission in UAL. Chart: Amibroker.

If you look closely you can determine that RSI(2) drops under 10 on the 26th April 2022. It then crosses back supra 10 on the next taproo.

Interim, the private is above the 200-twenty-four hours Mummy (nonindulgent) and the 5-Clarence Shepard Day Jr. MA (orange) is also above the 200-daytime MA. The stock also meets our liquidity rules with an average turnover dangt; $200,000 and a buy in price dangt; $2.

A buy ordering is hence conveyed for the next open (green arrow) and a intercept loss is placed at the recent baseball swing low of $65.45 (red demarcation).

The unoriginal comes close to fetching out the stop loss on May 10th but fortunately the stop is never hit.

218 days later, we get our exit signal every bit the Bay State(5) crosses under the MA(200). The trade is closed happening the following ajar (red pointer) for a add profit of 21.81% after costs.

This trade example shows how the system is able to hold happening to some relatively sudden upward trends in stocks.

Backtest Settings

To backtest this strategy I wish glucinium using the software Amibroker with existent data from Norgate. This information includes delisted stocks and is adjusted for capital actions and dividends.

I leave first run an All Trades essa which will mental test every trade signal over the time period. I will then run a portfolio test to account for more realistic trading conditions.

A portfolio tryout represents how a trading strategy could be implemented in genuine life as information technology accounts for trading constraints much arsenic emplacement sizing, portfolio sized and transaction costs.

Backtest Results – All Trades

To run over the all trades test we will utilise the following backtest conditions:

Universe: Sdanamp;P 100, Sdanamp;P 500, Russell 3000
Date: 01/01/2000 – 01/01/2019
Execution: Next daytime open
Position sizing: $500
Transaction Toll: 0

The following table shows backtest results for all signals across Sdanamp;P 100, Sdanamp;P 500 and Russell 3000 stocks between 1/2000 to 1/2019:

As you can see from these results, the strategy has been profitable over the last 19 years. We recorded an median profit per trade of 1.83% in the Sdanamp;P 100, 2.15% in the Sdanamp;P 500 and 1.91% in the Russell 3000.

The risk-adjusted generate of 9.34% in the SdanAMP;P 500 is many than the buy and grip go back which was 4.85% happening SPY.

However, these are less than stellar returns. The win rate is specially insufficient at only 15-16%. The Sharpe ratio is also poor.

Backtest Results – Portfolio

Before we advance, we can see how this strategy stacks up with full portfolio implementation. We leave use the next backtest settings for the portfolio simulation:

Existence: Sdanamp;P 500
Date: 01/01/2000 – 01/01/2019
Transaction Cost: $0.01 per share
Execution: Next day open
Starting Capital: $25,000
Max open positions: 20
Put together size: 5% (equal system of weights)
Ranking: RSI(2) highest first

The following results and equity curve show the carrying out of the scheme as a portfolio between 2000 and 2022 on Sdanamp;P 500 stocks:

# Trades: 1806
Lucre: $83358.42
CAR: 8.02%
MDD: -47.5%
Motorcar/MDD: 0.17
RAR: 8.31%
Make headway Rate: 19.49%
Avg P/L Per Trade: 2.58%
Average parallel bars held: 51.38
Payoff Ratio: 8.21
Sharpe: 0.11

Equity curve for the RSI(2) cross scheme. Chart: amibroker.

Hold over of results for the RSI(2) cross strategy. Graph: Amibroker.

As you can see from the above results, this trading strategy has been profitable on Sdanamp;P 500 stocks with an annualised return of 8.02% and a RAR of 8.31% which beat generation the SPY buy and hold return of 4.85% over the same time period.

The results are non impressive but there are some good features present in these results.

For instance, the system ready-made 44.5% in 2022 and 38.7% in 2022. Those are beardown results. The strategy appears to do a good job of capturing returns in up years.

This system picked out a nice trend in NVDA.

However, there are still bulky concerns over the baritone win value and walloping drawdowns.

Simple Adjustments To Amend Profits

A distich of things surpass when analysing these results.

Kickoff, the win rate is very low (to a lesser degree 20%). This leads to a upper limit losing streak of 63 consecutive trades in the backtest. Most traders would not be able to trade through such a poor losing period.

Second, the CAR/MDD is not good. The Georgia home boy drawdown is almost six times larger than the annualised return.

However, there are numerous adjustments that could personify made to improve public presentation.

For example:

We could introduce a regime filter to keep the system flat during down markets.
We could alter the trade rules to better win rate and shorten trade duration.
We could use sphere and portfolio rules to demarcation line trades to certain sectors or industries.
We could utilize more dynamic position sizing and investigate different senior.

Of course, in that respect is nary limit to the number of ideas that could be added operating theatre taken away from this system.

As an example, I induce ready-made threesome simple adjustments to this scheme as below:

Instead of exiting by the stop personnel casualty intraday we volition delay the exit to the following commercialize open. This volition give the swap a trifle more prison term to convalesce and simultaneously reduce slippage costs.
We will use an SPX filter so that we can only enter trades when the Sdanamp;P 500 is over the Bay State(200). This will help to keep us out of unstable markets.
Instead of senior by RSI(2) we will rank aside ATRP and choose the lowest volatility stocks first. The melodic theme is that we can find trends that are less credible to impinge on their initial stop loss.

Backtest Results After Improvements

The following results and equity curve render the carrying out after devising these three adjustments:

# Trades: 1458
Net Profit: $87266.46
CAR: 8.22%
MDD: -18.31%
CAR/MDD: 0.45
RAR: 10.67%
Acquire Rate: 27.30%
Avg P/L Per Trade: 2.77%
Average bars held: 50.36
Payoff Ratio: 7.44
Sharpe: 0.15

You can see that the maximum drawdown has dropped from -47.5% to -18.31% and the win charge per unit has increased to 27.30%. Meanwhile yearly return has cleared to 8.22% and RAR has improved to 10.67%:

RSI(2) cross scheme with adjustments equity. Chart: Amibroker.

RSI(2) cross strategy with adjustments profit mesa. Chart: Amibroker.

The trading system is straightaway a lot more than stable although we did begin with three consecutive losing years and the annual return key is even not impressive.

Final Thoughts

In this clause we have backtested a readers RSI strategy and produced some meaningful results.

The low win rate and poor annual return are non up to scratch for most traders and this can result in long-handled losing streaks.

However, the system does a reasonably good job of picking out winning trends in up markets. Not many systems were able to father thirty to forty per cent returns in 2022.

This scheme may therefore let some potential if it can be limited to bull through markets only. It may also be interesting to test on intraday information.

A trader WHO is skilled at distinguishing market regimes May be able to use this scheme (or something similar) every bit a base to help capture trends. Merely in its present form it could do with some work.

Simulations produced in Amibroker using historical data from Norgate.

joe marwood profile picture Joe Marwood is an independent trader and the founder of Decoding Markets. He worked as a professed futures trader and has a passion for investing and building mechanized trading strategies. If you are interested in Sir Thomas More amount trading strategies, investing ideas and tutorials make a point to run down our program Marwood Research.

This post expresses the opinions of the writer and is for information Oregon entertainment purposes simply. It is not a recommendation or personalised investment advice. Joe Marwood is not a listed financial consultant or certified analyst. The lecturer agrees to assume wholly risk resulting from the practical application of any of the information provided. Past functioning, historical or imitation resultsdannbsp; are not a reliable indicator of emerging returns and may not account for real world settings. Financial trading is untasted of risk and margin trading can lead to financial losses totalling to a higher degree what is in your investment account. We take care to present right analysis but mistakes in backtesting and presenting of psychoanalysis on a regular basis occur. Delight read the Full disclaimer.

Thank you to everyone who takes the time to leave a comment. Your feedback, constructive criticism and identification of mistakes is welcome. In order to concentrate on work I May non have clock time to respond to all comments.