The random entry and exit strategy is a strategy that randomly decides entry and exit timing during trading. It utilizes a random number generator to simulate entry and exit decisions.
The core logic of this strategy is:
Every candlestick will randomly generate a number between 0 to 100.
If the random number is lower than the set entry threshold, a position will be opened. The default entry probability is 10%.
If the random number is lower than the set exit threshold, the position will be closed. The default exit probability is 3%.
There are three direction choices: long only, short only, or random direction. The default is long only.
The start year can also be set to avoid years with huge market swings.
By setting different combinations of entry probability, exit probability and direction, we can simulate random trading behaviors of different types of traders and examine the performance of random trading in different markets.
Simulates real trader’s random decision making, close to real market situations.
Can test the performance differences of random trading in various markets.
Can find which markets can generate positive returns even with random trading.
Can use random trading as a benchmark strategy to test advantages of other strategies.
Unable to profit from market trends, unable to determine optimal entry timing.
Random exit may stop loss at unfavorable levels.
Performs poorly in markets with a clear directional bias.
Need to optimize entry/exit probability to avoid over-trading or insufficient holding period.
Consider adding stop loss to avoid enlarged losses.
Adjust entry/exit probability to find suitable combinations for different markets.
Add stop loss strategies to control single trade loss.
Optimize position sizing to lower single trade risk.
Switch to trend following strategies when trend is clear.
Use statistical analysis to find which markets favor random trading.
The random entry and exit strategy tests different markets’ performance under simulated random trader decisions. The strategy logic is simple and can serve as a benchmark to examine other strategies. However, it has its flaws like failing to capture trends and lack of proper stop loss management. We can improve the strategy by adjusting parameter combinations, adding stops, optimizing position sizing etc, to turn it into a viable quant trading strategy.
/*backtest
start: 2022-10-04 00:00:00
end: 2023-10-10 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
args: [["v_input_1",2]]
*/
//@version=4
// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © gregoirejohnb
//
// "tHe MaRkEtS aRe RaNdOm", say moron academics.
//
// The purpose of this study is to show that most markets are NOT random! Most markets show a clear bias where we can make such easy money, that a random number generator can do it.
//
// === HOW THE INDICATOR WORKS ===
//
// -The study will randomly enter the market
// -The study will randomly exit the market if in a trade
// -You can choose a Long Only, Short Only, or Bidirectional strategy
//
// === DEFAULT VALUES AND THEIR LOGIC ===
//
// Percent Chance to Enter Per Bar: 10%
// Percent Chance to Exit Per Bar: 1%
// Direction: Long Only
// Commission: 0
//
// Each bar has a 10% chance to enter the market. Each bar has a 1% to exit the market [if in a trade]. It will only enter long.
//
// I included zero commission for simplication. It's a good exercise to include a commission/slippage to see just how much trading fees take from you.
//
// === TIPS ===
//
// -Increasing "Percent Chance to Exit" will shorten the time in a trade. You can see the "Avg # Bars In Trade" go down as you increase. If "Percent Chance to Exit" is too high, the study won't be in the market long enough to catch any movement, possibly exiting on the same bar most of the time.
// -If you're getting the red screen, that means the strategy lost so much money it went broke. Try reducing the percent equity on the Properties tab.
// -Switch the start year to avoid black swan events like the covid drop in 2020.
// -
// === FINDINGS ===
//
// Most markets lose money with a "Random" direction strategy.
// Most markets lose ALL money with a "Short Only" strategy.
// Most markets make money with a "Long Only" strategy.
//
// Try this strategy on: Bitcoin (BTCUSD) and the NASDAQ (QQQ).
//
// There are two popular memes right now: "Bitcoin to the moon" and "Stocks only go up". Both are seemingly true. Bitcoin was the best performing asset of the 2010's, gaining several billion percent in gains. The stock market is on a 100 year long uptrend. Why? BECAUSE FIAT CURRENCIES ALWAYS GO DOWN! This is inflation. If we measure the market in terms of others assets instead of fiat, the Long Only strategy doesn't work anymore.
// Try this strategy on: Bitcoin/GLD (BTCUSD/GLD), the Eurodollar (EURUSD), and the S&P 500 measured in gold (SPY/GLD).
//
// Bitcoin measured in gold (BTCUSD/GLD) still works with a Long Only strategy because Bitcoin increased in value over both USD and gold.
// The Eurodollar (EURUSD) generally loses money no matter what, especially if you add any commission. This makes sense as they are both fiat currencies with similar inflation schedules.
// Gold and the S&P 500 have gained roughly the same amount since ~2000. Some years will show better results for a long strategy, while others will favor a short strategy. Now look at just SPY or GLD (which are both measured in USD by default!) and you'll see the same trend again: a Long Only strategy crushes even when entering and exiting randomly.
//
// === "JUST TELL ME WHAT TO DO, YOU NERD!" ===
//
// Bulls always win and Bears always lose because fiat currencies go to zero.
//
strategy(title="Random Entries Work", shorttitle="REW", overlay=true, pyramiding=0, default_qty_type=strategy.percent_of_equity, default_qty_value=100, currency=currency.USD,commission_type=strategy.commission.percent,commission_value=0)
// === GENERAL INPUTS ===
strategy = input(defval="Long Only",title="Direction",options=["Long Only", "Short Only", "Random"])
enter_frequency = input(defval=10,minval=1,maxval=100,title="Percent Chance to Enter")
exit_frequency = input(defval=3, minval=0,maxval=100,title="Percent Chance to Exit",tooltip="This should be much lower than Percent Chance to Enter. Higher values decrease time in market. Lower values increase time in market.")
start_year = input(defval=2020, title="Start Year")
// === LOGIC ===
r = random(0,100)
enter = enter_frequency > r[0]
exit = exit_frequency > r[0]
direction = random(0,100) >= 50
// === STRATEGY - LONG POSITION EXECUTION ===
enterLong() =>
strategy.opentrades == 0 and enter and (strategy == "Long Only" or (strategy == "Random") and direction) and
time > timestamp(start_year, 01, 01, 01, 01)
exitLong() =>
exit
strategy.entry(id="Long", long=strategy.long, when=enterLong())
strategy.close(id="Long", when=exitLong())
// === STRATEGY - SHORT POSITION EXECUTION ===
enterShort() =>
strategy.opentrades == 0 and enter and (strategy == "Short Only" or (strategy == "Random" and not direction)) and
time > timestamp(start_year, 01, 01, 01, 01)
exitShort() =>
exit
strategy.entry(id="Short", long=strategy.short, when=enterShort())
strategy.close(id="Short", when=exitShort())