Ultimate Oscillator Trading StrategyThe Ultimate Oscillator Trading Strategy implemented in Pine Script™ is based on the Ultimate Oscillator (UO), a momentum indicator developed by Larry Williams in 1976. The UO is designed to measure price momentum over multiple timeframes, providing a more comprehensive view of market conditions by considering short-term, medium-term, and long-term trends simultaneously. This strategy applies the UO as a mean-reversion tool, seeking to capitalize on temporary deviations from the mean price level in the asset’s movement (Williams, 1976).
Strategy Overview:
Calculation of the Ultimate Oscillator (UO):
The UO combines price action over three different periods (short-term, medium-term, and long-term) to generate a weighted momentum measure. The default settings used in this strategy are:
Short-term: 6 periods (adjustable between 2 and 10).
Medium-term: 14 periods (adjustable between 6 and 14).
Long-term: 20 periods (adjustable between 10 and 20).
The UO is calculated as a weighted average of buying pressure and true range across these periods. The weights are designed to give more emphasis to short-term momentum, reflecting the short-term mean-reversion behavior observed in financial markets (Murphy, 1999).
Entry Conditions:
A long position is opened when the UO value falls below 30, indicating that the asset is potentially oversold. The value of 30 is a common threshold that suggests the price may have deviated significantly from its mean and could be due for a reversal, consistent with mean-reversion theory (Jegadeesh & Titman, 1993).
Exit Conditions:
The long position is closed when the current close price exceeds the previous day’s high. This rule captures the reversal and price recovery, providing a defined point to take profits.
The use of previous highs as exit points aligns with breakout and momentum strategies, as it indicates sufficient strength for a price recovery (Fama, 1970).
Scientific Basis and Rationale:
Momentum and Mean-Reversion:
The strategy leverages two well-established phenomena in financial markets: momentum and mean-reversion. Momentum, identified in earlier studies like those by Jegadeesh and Titman (1993), describes the tendency of assets to continue in their direction of movement over short periods. Mean-reversion, as discussed by Poterba and Summers (1988), indicates that asset prices tend to revert to their mean over time after short-term deviations. This dual approach aims to buy assets when they are temporarily oversold and capitalize on their return to the mean.
Multi-timeframe Analysis:
The UO’s incorporation of multiple timeframes (short, medium, and long) provides a holistic view of momentum, unlike single-period oscillators such as the RSI. By combining data across different timeframes, the UO offers a more robust signal and reduces the risk of false entries often associated with single-period momentum indicators (Murphy, 1999).
Trading and Market Efficiency:
Studies in behavioral finance, such as those by Shiller (2003), show that short-term inefficiencies and behavioral biases can lead to overreactions in the market, resulting in price deviations. This strategy seeks to exploit these temporary inefficiencies, using the UO as a signal to identify potential entry points when the market sentiment may have overly pushed the price away from its average.
Strategy Performance:
Backtests of this strategy show promising results, with profit factors exceeding 2.5 when the default settings are optimized. These results are consistent with other studies on short-term trading strategies that capitalize on mean-reversion patterns (Jegadeesh & Titman, 1993). The use of a dynamic, multi-period indicator like the UO enhances the strategy’s adaptability, making it effective across different market conditions and timeframes.
Conclusion:
The Ultimate Oscillator Trading Strategy effectively combines momentum and mean-reversion principles to trade on temporary market inefficiencies. By utilizing multiple periods in its calculation, the UO provides a more reliable and comprehensive measure of momentum, reducing the likelihood of false signals and increasing the profitability of trades. This aligns with modern financial research, showing that strategies based on mean-reversion and multi-timeframe analysis can be effective in capturing short-term price movements.
References:
Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383-417.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65-91.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications. New York Institute of Finance.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Shiller, R. J. (2003). From Efficient Markets Theory to Behavioral Finance. Journal of Economic Perspectives, 17(1), 83-104.
Williams, L. (1976). Ultimate Oscillator. Market research and technical trading analysis.
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Heikin Ashi EMA v5 no repaint This script was inspired by the "Heikin/Kaufman Strategy" from marco valente built on v2.
The script was rebuilt on the v5 and most importantly removed the repaint function that was driving surrealistic backtesting inflated numbers.
This script is now fully functional and not repainting - At the time of testing worked efficiently 90% WR and 2x profit factor on CFD WTI OIL with a 15m time frame indexed on forex.com price.
You should utilize this script with caution, especially on high volatility cycles you can try plotting against a volatility relative index or stop.
I also strongly recommend understanding the fundamentals of WTI OIL to balance the indications of the strategy with fundamentals.
Thanks to Clovis Warlop and Nilesh Sharma for their contribution.
Cheers,
Gustavo Bramao
GMH : ATH 200d All-Time High Strategy for Tech Stock
In a bull market where valuation is completely neglected. For risk protect we choose a trade set up with stock that is going its break all time high.
Given All-Time High days as input parameter for strategy.
And stoploss by ema crossunder.
Should give decent profit factor for bull run.
EMA RSI ATR Hidden Div Strat - 1 MinHey there!
Hereby I present you the EMA RSI Lowest Low Hidden Divergence strategy, which I discovered on a youtube channel.
He has tested the strategy hundreds of times manually, herewith I try to automate the whole thing.
Since I use the strategy with a bot, it can only enter long positions for now. But in the future I will add the possibility to trade short positions.
The strategy was tested with BTC/ USDT in 1m chart (8 days). The values must be adjusted depending on the timeframe and coin.
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How does the strategy work?
First of all, we need a bullish hidden divergence.
Once this is detected, the following parameters are checked:
The 50 EMA must cross the 250 EMA .
Then, the candle must close above the 50 EMA .
The K line of the RSI STOCH indicator need to crosses the D line.
If the next candle closes above the 50 EMA , a long position is opened.
The stop loss is determined with the "lowest low/highest high lookback".
The profit factor is multiplied by the value of the lowest low/highest high lookback.
The results of the strategy are without commissions and levers.
If you have any questions or feedback, please let me know in the comments.
In the future I will add other types of stop loss / take profits. (ATR; %; eg.)
I wish you good luck with the strategy!
Tripple super Trend + EMA + RSI StrategyGreetings!
Here I show you the Tripple Super Trend Strategy.
I discovered the strategy on a YouTube channel and tried to transfer it as a strategy into a script.
Tested with the currency pair EUR/USD in the one hour chart.
Period: beginning of 2020 until today.
The strategy should also work with cryptocurrencies. But then the settings have to be adjusted.
There is the possibility to activate only long or only short position.
The EMA can be used in a time different from the chart.
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How does the strategy work?
For long positions, the candle must be above the EMA .
The candle must be closed above at least two of the supertrend lines.
The stochastic RSI must show oversold and the k line must cross over the D line.
For short positions, the candle must be below the EMA .
The candle must be closed below at least two of the supertrend lines.
The stochastic RSI must indicate overbought and the K line must cross below the D line.
The stop loss is determined with the "lowest low/highest high lookback".
The profit factor is multiplied by the value of the lowest low/highest high lookback.
The results of the strategy are without commissions and levers.
If you have any questions or feedback, please let me know in the comments.
In the future I will add other types of stop loss / take profits. (ATR; %; eg.)
If you need more information about the strategy and want to know exactly how to apply it, check out my profile.
I wish you good luck with the strategy!
MACD Trendprediction Strategy V1A trend following indicator based on the MACD and EMA. In this case, signals are not generated by crossing the signal lines as with the MACD, but as soon as the distance between the signal lines increases or decreases. A profit factor of 1.6-3.5 is achieved.
Ein Trendfolge-Indikator, auf der Basis des MACD und EMA. Dabei werden Signale nicht wie bei dem MACD per Kreuzung der Signallinien generiert, sondern sobald ein der Abstand der Signallinien zu oder abnimmt.
Trend Finder V2 StudyStudy version of the script with alert conditions for up and down
Note* The study version will not trigger at the same points the strategy version does due to the strategy limiting the orders to a buy then a sell, back testing didn't seem to change the results to much though
Please experiment with the pyramid function in the strategy script to change how many buy orders can be made in a row before using the alert conditions, a profit factor over 2 is considered good
Profit and Stoploss CalculatorThis script is designed to display three stop loss areas to assist either with automation of risk management or identify and alert when price is in a range of a trade for risk to reward ratio.
In this version there are three stop losses and 1 PT. Mainly because i will most likely only be using 1 of the SL to pair with the PT.
Stoploss areas are displayed on both sides of the price for long and short calculations along with the two profit factors but the settings in the indicator it self apply to both sides in terms of percentage.
yuthavithi BB Scalper 2 strategyIf you are searching a high win rate strategy with good profit factor ratio strategy. this one may be your choice.
Designed to be used with BTC or LTC. with 5 minute time frame or less. This BB strategy achieve win rate over 50% easily, with some tuning you can get even 60%+.
EMA Crossover with Volume + Stacked TP & Trailing SLI am relatively new here. Here is my humble contribution to the community. Simple does it! Ema 21,55 with volume. Surprisingly high win rates and good profit factors on USDJPY, EURJPY, BTCUSD, XAGUSD,XAUUSD, USOIL, USDCAD, EURGBP and AUDNZD. I cannot write a single line of code. I used Copilot for this.
Line Break StrategyLine Break Strategy
Entry rule:
Long on a bullish line and short on a bearish line.
Backtest:
Profit factors are shown below for three-line break.
Daily time frame, FXCM broker.
EURUSD: 1.267, USDJPY: 1.039, GBPUSD: -0.816, AUDUSD: -0.959
S&P500: -0.783, Nikkei225: 1.099
CrudeOil: 1.03, Gold: 1.196
BTCUSD: -0.883
Reference:
Steve Nison, Beyond Candlesticks - New Japanese Charting Techniques Revealed
Note:
This strategy doesn't work properly on the linebreak chart.
A good example is shown below. The entry prices are not always correct.
If you have signal, but the next candle moves in the opposite direction, the entry price is drawn at the Open of the new candle instead of the Close of the previous candle.
The results of backtest are unreliable due to this reason.
