BTCUSD Momentum After Abnormal DaysThis indicator identifies abnormal days in the Bitcoin market (BTCUSD) based on daily returns exceeding specific thresholds defined by a statistical approach. It is inspired by the findings of Caporale and Plastun (2020), who analyzed the cryptocurrency market's inefficiencies and identified exploitable patterns, particularly around abnormal returns.
Key Concept:
Abnormal Days:
Days where the daily return significantly deviates (positively or negatively) from the historical average.
Positive abnormal days: Returns exceed the mean return plus k times the standard deviation.
Negative abnormal days: Returns fall below the mean return minus k times the standard deviation.
Momentum Effect:
As described in the academic paper, on abnormal days, prices tend to move in the direction of the abnormal return until the end of the trading day, creating momentum effects. This can be leveraged by traders for profit opportunities.
How It Works:
Calculation:
The script calculates the daily return as the percentage difference between the open and close prices. It then derives the mean and standard deviation of returns over a configurable lookback period.
Thresholds:
The script dynamically computes upper and lower thresholds for abnormal days using the mean and standard deviation. Days exceeding these thresholds are flagged as abnormal.
Visualization:
The mean return and thresholds are plotted as dynamic lines.
Abnormal days are visually highlighted with transparent green (positive) or red (negative) backgrounds on the chart.
References:
This indicator is based on the methodology discussed in "Momentum Effects in the Cryptocurrency Market After One-Day Abnormal Returns" by Caporale and Plastun (2020). Their research demonstrates that hourly returns during abnormal days exhibit a strong momentum effect, moving in the same direction as the abnormal return. This behavior contradicts the efficient market hypothesis and suggests profitable trading opportunities.
"Prices tend to move in the direction of abnormal returns till the end of the day, which implies the existence of a momentum effect on that day giving rise to exploitable profit opportunities" (Caporale & Plastun, 2020).
標準偏差
Multi-Step FlexiSuperTrend - Strategy [presentTrading]At the heart of this endeavor is a passion for continuous improvement in the art of trading
█ Introduction and How it is Different
The "Multi-Step FlexiSuperTrend - Strategy " is an advanced trading strategy that integrates the well-known SuperTrend indicator with a nuanced and dynamic approach to market trend analysis. Unlike conventional SuperTrend strategies that rely on static thresholds and fixed parameters, this strategy introduces multi-step take profit mechanisms that allow traders to capitalize on varying market conditions in a more controlled and systematic manner.
What sets this strategy apart is its ability to dynamically adjust to market volatility through the use of an incremental factor applied to the SuperTrend calculation. This adjustment ensures that the strategy remains responsive to both minor and major market shifts, providing a more accurate signal for entries and exits. Additionally, the integration of multi-step take profit levels offers traders the flexibility to scale out of positions, locking in profits progressively as the market moves in their favor.
BTC 6hr Long/Short Performance
█ Strategy, How it Works: Detailed Explanation
The Multi-Step FlexiSuperTrend strategy operates on the foundation of the SuperTrend indicator, but with several enhancements that make it more adaptable to varying market conditions. The key components of this strategy include the SuperTrend Polyfactor Oscillator, a dynamic normalization process, and multi-step take profit levels.
🔶 SuperTrend Polyfactor Oscillator
The SuperTrend Polyfactor Oscillator is the heart of this strategy. It is calculated by applying a series of SuperTrend calculations with varying factors, starting from a defined "Starting Factor" and incrementing by a specified "Increment Factor." The indicator length and the chosen price source (e.g., HLC3, HL2) are inputs to the oscillator.
The SuperTrend formula typically calculates an upper and lower band based on the average true range (ATR) and a multiplier (the factor). These bands determine the trend direction. In the FlexiSuperTrend strategy, the oscillator is enhanced by iteratively applying the SuperTrend calculation across different factors. The iterative process allows the strategy to capture both minor and significant trend changes.
For each iteration (indexed by `i`), the following calculations are performed:
1. ATR Calculation: The Average True Range (ATR) is calculated over the specified `indicatorLength`:
ATR_i = ATR(indicatorLength)
2. Upper and Lower Bands Calculation: The upper and lower bands are calculated using the ATR and the current factor:
Upper Band_i = hl2 + (ATR_i * Factor_i)
Lower Band_i = hl2 - (ATR_i * Factor_i)
Here, `Factor_i` starts from `startingFactor` and is incremented by `incrementFactor` in each iteration.
3. Trend Determination: The trend is determined by comparing the indicator source with the upper and lower bands:
Trend_i = 1 (uptrend) if IndicatorSource > Upper Band_i
Trend_i = 0 (downtrend) if IndicatorSource < Lower Band_i
Otherwise, the trend remains unchanged from the previous value.
4. Output Calculation: The output of each iteration is determined based on the trend:
Output_i = Lower Band_i if Trend_i = 1
Output_i = Upper Band_i if Trend_i = 0
This process is repeated for each iteration (from 0 to 19), creating a series of outputs that reflect different levels of trend sensitivity.
Local
🔶 Normalization Process
To make the oscillator values comparable across different market conditions, the deviations between the indicator source and the SuperTrend outputs are normalized. The normalization method can be one of the following:
1. Max-Min Normalization: The deviations are normalized based on the range of the deviations:
Normalized Value_i = (Deviation_i - Min Deviation) / (Max Deviation - Min Deviation)
2. Absolute Sum Normalization: The deviations are normalized based on the sum of absolute deviations:
Normalized Value_i = Deviation_i / Sum of Absolute Deviations
This normalization ensures that the oscillator values are within a consistent range, facilitating more reliable trend analysis.
For more details:
🔶 Multi-Step Take Profit Mechanism
One of the unique features of this strategy is the multi-step take profit mechanism. This allows traders to lock in profits at multiple levels as the market moves in their favor. The strategy uses three take profit levels, each defined as a percentage increase (for long trades) or decrease (for short trades) from the entry price.
1. First Take Profit Level: Calculated as a percentage increase/decrease from the entry price:
TP_Level1 = Entry Price * (1 + tp_level1 / 100) for long trades
TP_Level1 = Entry Price * (1 - tp_level1 / 100) for short trades
The strategy exits a portion of the position (defined by `tp_percent1`) when this level is reached.
2. Second Take Profit Level: Similar to the first level, but with a higher percentage:
TP_Level2 = Entry Price * (1 + tp_level2 / 100) for long trades
TP_Level2 = Entry Price * (1 - tp_level2 / 100) for short trades
The strategy exits another portion of the position (`tp_percent2`) at this level.
3. Third Take Profit Level: The final take profit level:
TP_Level3 = Entry Price * (1 + tp_level3 / 100) for long trades
TP_Level3 = Entry Price * (1 - tp_level3 / 100) for short trades
The remaining portion of the position (`tp_percent3`) is exited at this level.
This multi-step approach provides a balance between securing profits and allowing the remaining position to benefit from continued favorable market movement.
█ Trade Direction
The strategy allows traders to specify the trade direction through the `tradeDirection` input. The options are:
1. Both: The strategy will take both long and short positions based on the entry signals.
2. Long: The strategy will only take long positions.
3. Short: The strategy will only take short positions.
This flexibility enables traders to tailor the strategy to their market outlook or current trend analysis.
█ Usage
To use the Multi-Step FlexiSuperTrend strategy, traders need to set the input parameters according to their trading style and market conditions. The strategy is designed for versatility, allowing for various market environments, including trending and ranging markets.
Traders can also adjust the multi-step take profit levels and percentages to match their risk management and profit-taking preferences. For example, in highly volatile markets, traders might set wider take profit levels with smaller percentages at each level to capture larger price movements.
The normalization method and the incremental factor can be fine-tuned to adjust the sensitivity of the SuperTrend Polyfactor Oscillator, making the strategy more responsive to minor market shifts or more focused on significant trends.
█ Default Settings
The default settings of the strategy are carefully chosen to provide a balanced approach between risk management and profit potential. Here is a breakdown of the default settings and their effects on performance:
1. Indicator Length (10): This parameter controls the lookback period for the ATR calculation. A shorter length makes the strategy more sensitive to recent price movements, potentially generating more signals. A longer length smooths out the ATR, reducing sensitivity but filtering out noise.
2. Starting Factor (0.618): This is the initial multiplier used in the SuperTrend calculation. A lower starting factor makes the SuperTrend bands closer to the price, generating more frequent trend changes. A higher starting factor places the bands further away, filtering out minor fluctuations.
3. Increment Factor (0.382): This parameter controls how much the factor increases with each iteration of the SuperTrend calculation. A smaller increment factor results in more gradual changes in sensitivity, while a larger increment factor creates a wider range of sensitivity across the iterations.
4. Normalization Method (None): The default is no normalization, meaning the raw deviations are used. Normalization methods like Max-Min or Absolute Sum can make the deviations more consistent across different market conditions, improving the reliability of the oscillator.
5. Take Profit Levels (2%, 8%, 18%): These levels define the thresholds for exiting portions of the position. Lower levels (e.g., 2%) capture smaller profits quickly, while higher levels (e.g., 18%) allow positions to run longer for more significant gains.
6. Take Profit Percentages (30%, 20%, 15%): These percentages determine how much of the position is exited at each take profit level. A higher percentage at the first level locks in more profit early, reducing exposure to market reversals. Lower percentages at higher levels allow for a portion of the position to benefit from extended trends.
Price Based Z-Trend - Strategy [presentTrading]█ Introduction and How it is Different
Z-score: a statistical measurement of a score's relationship to the mean in a group of scores.
Simple but effective approach.
The "Price Based Z-Trend - Strategy " leverages the Z-score, a statistical measure that gauges the deviation of a price from its moving average, normalized against its standard deviation. This strategy stands out due to its simplicity and effectiveness, particularly in markets where price movements often revert to a mean. Unlike more complex systems that might rely on a multitude of indicators, the Z-Trend strategy focuses on clear, statistically significant price movements, making it ideal for traders who prefer a streamlined, data-driven approach.
BTCUSD 6h LS Performance
█ Strategy, How It Works: Detailed Explanation
🔶 Calculation of the Z-score
"Z-score is a statistical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean. If a Z-score is 0, it indicates that the data point's score is identical to the mean score. A Z-score of 1.0 would indicate a value that is one standard deviation from the mean. Z-scores may be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean."
The Z-score is central to this strategy. It is calculated by taking the difference between the current price and the Exponential Moving Average (EMA) of the price over a user-defined length, then dividing this by the standard deviation of the price over the same length:
z = (x - μ) /σ
Local
🔶 Trading Signals
Trading signals are generated based on the Z-score crossing predefined thresholds:
- Long Entry: When the Z-score crosses above the positive threshold.
- Long Exit: When the Z-score falls below the negative threshold.
- Short Entry: When the Z-score falls below the negative threshold.
- Short Exit: When the Z-score rises above the positive threshold.
█ Trade Direction
The strategy allows users to select their preferred trading direction through an input option.
█ Usage
To use this strategy effectively, traders should first configure the Z-score thresholds according to their risk tolerance and market volatility. It's also crucial to adjust the length for the EMA and standard deviation calculations based on historical performance and the expected "noise" in price data.
The strategy is designed to be flexible, allowing traders to refine settings to better capture profitable opportunities in specific market conditions.
█ Default Settings
- Trade Direction: Both
- Standard Deviation Length: 100
- Average Length: 100
- Threshold for Z-score: 1.0
- Bar Color Indicator: Enabled
These settings offer a balanced starting point but can be customized to suit various trading styles and market environments. The strategy's parameters are designed to be adjusted as traders gain experience and refine their approach based on ongoing market analysis.
Z-score is a must-learn approach for every algorithmic trader.
Buy Sell Strategy With Z-Score [TradeDots]The "Buy Sell Strategy With Z-Score" is a trading strategy that harnesses Z-Score statistical metrics to identify potential pricing reversals, for opportunistic buying and selling opportunities.
HOW DOES IT WORK
The strategy operates by calculating the Z-Score of the closing price for each candlestick. This allows us to evaluate how significantly the current price deviates from its typical volatility level.
The strategy first takes the scope of a rolling window, adjusted to the user's preference. This window is used to compute both the standard deviation and mean value. With these values, the strategic model finalizes the Z-Score. This determination is accomplished by subtracting the mean from the closing price and dividing the resulting value by the standard deviation.
This approach provides an estimation of the price's departure from its traditional trajectory, thereby identifying market conditions conducive to an asset being overpriced or underpriced.
APPLICATION
Firstly, it is better to identify a stable trading pair for this technique, such as two stocks with considerable correlation. This is to ensure conformance with the statistical model's assumption of a normal Gaussian distribution model. The ideal performance is theoretically situated within a sideways market devoid of skewness.
Following pair selection, the user should refine the span of the rolling window. A broader window smoothens the mean, more accurately capturing long-term market trends, while potentially enhancing volatility. This refinement results in fewer, yet precise trading signals.
Finally, the user must settle on an optimal Z-Score threshold, which essentially dictates the timing for buy/sell actions when the Z-Score exceeds with thresholds. A positive threshold signifies the price veering away from its mean, triggering a sell signal. Conversely, a negative threshold denotes the price falling below its mean, illustrating an underpriced condition that prompts a buy signal.
Within a normal distribution, a Z-Score of 1 records about 68% of occurrences centered at the mean, while a Z-Score of 2 captures approximately 95% of occurrences.
The 'cool down period' is essentially the number of bars that await before the next signal generation. This feature is employed to dodge the occurrence of multiple signals in a short period.
DEFAULT SETUP
The following is the default setup on EURUSD 1h timeframe
Rolling Window: 80
Z-Score Threshold: 2.8
Signal Cool Down Period: 5
Commission: 0.03%
Initial Capital: $10,000
Equity per Trade: 30%
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Bitcoin Leverage Sentiment - Strategy [presentTrading]█ Introduction and How it is Different
The "Bitcoin Leverage Sentiment - Strategy " represents a novel approach in the realm of cryptocurrency trading by focusing on sentiment analysis through leveraged positions in Bitcoin. Unlike traditional strategies that primarily rely on price action or technical indicators, this strategy leverages the power of Z-Score analysis to gauge market sentiment by examining the ratio of leveraged long to short positions. By assessing how far the current sentiment deviates from the historical norm, it provides a unique lens to spot potential reversals or continuation in market trends, making it an innovative tool for traders who wish to incorporate market psychology into their trading arsenal.
BTC 4h L/S Performance
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█ Strategy, How It Works: Detailed Explanation
🔶 Data Collection and Ratio Calculation
Firstly, the strategy acquires data on leveraged long (**`priceLongs`**) and short positions (**`priceShorts`**) for Bitcoin. The primary metric of interest is the ratio of long positions relative to the total of both long and short positions:
BTC Ratio=priceLongs / (priceLongs+priceShorts)
This ratio reflects the prevailing market sentiment, where values closer to 1 indicate a bullish sentiment (dominance of long positions), and values closer to 0 suggest bearish sentiment (prevalence of short positions).
🔶 Z-Score Calculation
The Z-Score is then calculated to standardize the BTC Ratio, allowing for comparison across different time periods. The Z-Score formula is:
Z = (X - μ) / σ
Where:
- X is the current BTC Ratio.
- μ is the mean of the BTC Ratio over a specified period (**`zScoreCalculationPeriod`**).
- σ is the standard deviation of the BTC Ratio over the same period.
The Z-Score helps quantify how far the current sentiment deviates from the historical norm, with high positive values indicating extreme bullish sentiment and high negative values signaling extreme bearish sentiment.
🔶 Signal Generation: Trading signals are derived from the Z-Score as follows:
Long Entry Signal: Occurs when the BTC Ratio Z-Score crosses above the thresholdLongEntry, suggesting bullish sentiment.
- Condition for Long Entry = BTC Ratio Z-Score > thresholdLongEntry
Long Exit/Short Entry Signal: Triggered when the BTC Ratio Z-Score drops below thresholdLongExit for exiting longs or below thresholdShortEntry for entering shorts, indicating a shift to bearish sentiment.
- Condition for Long Exit/Short Entry = BTC Ratio Z-Score < thresholdLongExit or BTC Ratio Z-Score < thresholdShortEntry
Short Exit Signal: Happens when the BTC Ratio Z-Score exceeds the thresholdShortExit, hinting at reducing bearish sentiment and a potential switch to bullish conditions.
- Condition for Short Exit = BTC Ratio Z-Score > thresholdShortExit
🔶Implementation and Visualization: The strategy applies these conditions for trade management, aligning with the selected trade direction. It visualizes the BTC Ratio Z-Score with horizontal lines at entry and exit thresholds, illustrating the current sentiment against historical norms.
█ Trade Direction
The strategy offers flexibility in trade direction, allowing users to choose between long, short, or both, depending on their market outlook and risk tolerance. This adaptability ensures that traders can align the strategy with their individual trading style and market conditions.
█ Usage
To employ this strategy effectively:
1. Customization: Begin by setting the trade direction and adjusting the Z-Score calculation period and entry/exit thresholds to match your trading preferences.
2. Observation: Monitor the Z-Score and its moving average for potential trading signals. Look for crossover events relative to the predefined thresholds to identify entry and exit points.
3. Confirmation: Consider using additional analysis or indicators for signal confirmation, ensuring a comprehensive approach to decision-making.
█ Default Settings
- Trade Direction: Determines if the strategy engages in long, short, or both types of trades, impacting its adaptability to market conditions.
- Timeframe Input: Influences signal frequency and sensitivity, affecting the strategy's responsiveness to market dynamics.
- Z-Score Calculation Period: Affects the strategy’s sensitivity to market changes, with longer periods smoothing data and shorter periods increasing responsiveness.
- Entry and Exit Thresholds: Set the Z-Score levels for initiating or exiting trades, balancing between capturing opportunities and minimizing false signals.
- Impact of Default Settings: Provides a balanced approach to leverage sentiment trading, with adjustments needed to optimize performance across various market conditions.
Bollinger Bands StrategyBollinger Bands Strategy :
INTRODUCTION :
This strategy is based on the famous Bollinger Bands. These are constructed using a standard moving average (SMA) and the standard deviation of past prices. The theory goes that 90% of the time, the price is contained between these two bands. If it were to break out, this would mean either a reversal or a continuation. However, when a reversal occurs, the movement is weak, whereas when a continuation occurs, the movement is substantial and profits can be interesting. We're going to use BB to take advantage of this strong upcoming movement, while managing our risks reasonably. There's also a money management method for reinvesting part of the profits or reducing the size of orders in the event of substantial losses.
BOLLINGER BANDS :
The construction of Bollinger bands is straightforward. First, plot the SMA of the price, with a length specified by the user. Then calculate the standard deviation to measure price dispersion in relation to the mean, using this formula :
stdv = (((P1 - avg)^2 + (P2 - avg)^2 + ... + (Pn - avg)^2) / n)^1/2
To plot the two Bollinger bands, we then add a user-defined number of standard deviations to the initial SMA. The default is to add 2. The result is :
Upper_band = SMA + 2*stdv
Lower_band = SMA - 2*stdv
When the price leaves this channel defined by the bands, we obtain buy and sell signals.
PARAMETERS :
BB Length : This is the length of the Bollinger Bands, i.e. the length of the SMA used to plot the bands, and the length of the price series used to calculate the standard deviation. The default is 120.
Standard Deviation Multipler : adds or subtracts this number of times the standard deviation from the initial SMA. Default is 2.
SMA Exit Signal Length : Exit signals for winning and losing trades are triggered by another SMA. This parameter defines the length of this SMA. The default is 110.
Max Risk per trade (in %) : It's the maximum percentage the user can lose in one trade. The default is 6%.
Fixed Ratio : This is the amount of gain or loss at which the order quantity is changed. The default is 400, meaning that for each $400 gain or loss, the order size is increased or decreased by a user-selected amount.
Increasing Order Amount : This is the amount to be added to or subtracted from orders when the fixed ratio is reached. The default is $200, which means that for every $400 gain, $200 is reinvested in the strategy. On the other hand, for every $400 loss, the order size is reduced by $200.
Initial capital : $1000
Fees : Interactive Broker fees apply to this strategy. They are set at 0.18% of the trade value.
Slippage : 3 ticks or $0.03 per trade. Corresponds to the latency time between the moment the signal is received and the moment the order is executed by the broker.
Important : A bot has been used to test the different parameters and determine which ones maximize return while limiting drawdown. This strategy is the most optimal on BITSTAMP:BTCUSD in 8h timeframe with the following parameters :
BB Length = 120
Standard Deviation Multipler = 2
SMA Exit Signal Length = 110
Max Risk per trade (in %) = 6%
ENTER RULES :
The entry rules are simple:
If close > Upper_band it's a LONG signal
If close < Lower_band it's a SHORT signal
EXIT RULES :
If we are LONG and close < SMA_EXIT, position is closed
If we are SHORT and close > SMA_EXIT, the position is closed
Positions close automatically if they lose more than 6% to limit risk
RISK MANAGEMENT :
This strategy is subject to losses. We manage our risk using the exit SMA or using a SL sets to 6%. This SMA gives us exit signals when the price closes below or above, thus limiting losses. If the signal arrives too late, the position is closed after a loss of 6%.
MONEY MANAGEMENT :
The fixed ratio method was used to manage our gains and losses. For each gain of an amount equal to the fixed ratio value, we increase the order size by a value defined by the user in the "Increasing order amount" parameter. Similarly, each time we lose an amount equal to the value of the fixed ratio, we decrease the order size by the same user-defined value. This strategy increases both performance and drawdown.
NOTE :
Please note that the strategy is backtested from 2017-01-01. As the timeframe is 8h, this strategy is a medium/long-term strategy. That's why only 51 trades were closed. Be careful, as the test sample is small and performance may not necessarily reflect what may happen in the future.
Enjoy the strategy and don't forget to take the trade :)
VWAP Trendfollow Strategy [wbburgin]This is an experimental strategy that enters long when the instrument crosses over the upper standard deviation band of a VWAP and enters short when the instrument crosses below the bottom standard deviation band of the VWAP. I have added a trend filter as well, which stops entries that are opposite to the current trend of the VWAP. The trend filter will reduce total false breakouts, thus improving the % profitable while maintaining the overall returns of the strategy. Because this is a trend-following breakout strategy, the % profitable will typically be low but the average % return will be higher. As a rule, be sure to look at the average winning trade % compared to the average losing trade %, and compare that to the % profitable to judge the effectiveness of a strategy. Factor in fees and slippage as well.
This strategy appears to work better with the lower timeframes, and I was impressed with its results. It also appears to work on a wide range of asset classes. There isn't a stop loss or take profit built-in (other than the reversal signals, which close the current trade), so I would encourage you to expand on the strategy based on your own trading parameters.
You can toggle off the bar colors and the trend filter if you so desire.
Future updates to this script (or ideas of improving on it) might include a take profit level set at one standard deviation past the current level and a stop loss level set at one standard deviation closer to the vwap from the current level - or applying a multiple to the two based off of your reward/risk ratio.
About the strategy results below: this is with commissions of 0.5 % per trade.
GAVAD - Selling after a Strong MovimentThis strategy search for a moment whe the market make two candles are consistently strong, and open a Sell, searching the imediactly correction, on the new candle. It`s easy to see the bars on the histogram graph. Purple Bars represent the candle variation. when on candle cross ove the Signal line the graph plot an Yellow ci, if the second bar crossover the signal a green circle is ploted and the operation start on start of the next candle.
This strategy can be used in a lot of Stocks and other graphs. many times we need a small time of graph, maybe 1 or 5 minutes because the gain shoud be planned to a midle of the second candle. You need look the stocks you will use.
Stocks > 100 dolars isnt great, markets extremly volatly not too. but, Stocks that have a consistently development are very interisting. Look to markets searching maybe 0.5% or 1%.
For this moment, I make the development of a Brasilian Real x American Dollar. In 15 Minutes.
if you use in small timeframe the results can be better.
On this time we make more than 500 trades with a small lot of contracts, without a big percent profitable, but a small profit in each operation, maybe you search more than. To present a real trading system I insert a spreed to present a correct view of the results.
Each stock, Index, or crypto there is a specific configuration?
my suggestion for new stocks
You need choice a stock and using the setup search set over than 70% gain (percent profitable), using a 1% of gain and loss between 1-2%
as the exemple (WDO)
default I prepare a Brazilian Index
6-signal (6% is variation of a candle of the last candle)
10000- multiplicator (its important to configure diferences betwen a stock and an Indice)
gain 3 (this proportion will be set looking you target, how I say, 1% can be good)
loss 8 (this proportion will be set with you bankroll management, how I say, maybe 2%, you need evaluate)
for maximize operations I use in the 1 or 5 minute graph. Timeframes more large make slowlly results,
(but not unable that you use in a 1 hour or a 1 day.)
I make this script by zero. Maybe the code doesnt so organized, but is very easy to understand. If you have any doubts . leave a comment.
I hope help you.
[KL] Double Bollinger Bands Strategy (for Crypto/FOREX)This strategy uses a setup consisting of two Bollinger Bands based on the 20 period 20-SMA +/-
(a) upper/lower bands of two standard deviations apart, and
(b) upper/lower bands of one standard deviation apart.
We consider price at +/- one standard deviation apart from 20-SMA as the "Neutral Zone".
If price closes above Neutral Zone after a period of consolidation, then it's an opportunity for entry. Strategy will long, anticipating for breakout.
The illustration below shows price closing above the Neutral Zone after a period of consolidation.
a.c-dn.net
Position is exited when prices closes at Neutral Zone (being lower than prior bars)
[KL] Bollinger Bands Consolidation StrategyThis strategy will enter into long position based on the volatility of prices implied by indicators of (a) Bollinger bands, and (b) ATR.
Application of Bollinger bands ("BOLL")
Using plain vanilla settings for BOLL (i.e. 20 period moving average, and 2 standard deviations of closing prices), we are interested to know about the shape of the area that is bounded by the upper and lower bands.
In theory, consolidation happens when volatility of price decreases. Visually speaking, this is represented by the narrowing of the upper/lower bands. This strategy considers the narrowing of BOLL bands as the primary indicator for long-entry.
Application of ATRs (as confirmations)
Firstly, to confirm that BOLL bands are narrowing (as mentioned above), the ATR at a potential point of entry is compared against the standard deviation of prices over BOLL's lookback periods. Once again, visualizing the shape of BOLL bands during consolidation, we assume the lines begin to squeeze when the distance between the center line and upper/lower band is less than two current ATRs.
Secondly, this strategy looks into the moving average of ATRs to assure that prices are not too choppy when entering into market. If the moving average of ATR decreases at a point in time such that all the above conditions are met, then we can assert that the volatility of price is decreasing.
Thirdly, ATR is used for determining the size of our trailing stop loss. We will keep the multiplier fixed at two.
Bollinger Bands Strategy with Intraday Intensity IndexFor Educational Purposes. Results can differ on different markets and can fail at any time. Profit is not guaranteed.
This only works in a few markets and in certain situations. Changing the settings can give better or worse results for other markets.
This is a mean reversion strategy based on Bollinger Bands and the Intraday Intensity Index (a volume indicator). John Bollinger mentions that the Intraday Intensity Index can be used with Bollinger Bands and is one of the top indicators he recommends in his book. It seems he prefers it over the other volume indicators that he compares to for some reason. III looks a lot like Chaikin Money Flow but without the denominator in that calculation. On the default settings of the BBs, the III helps give off better entry signals. John Bollinger however is vague on how to use the BBs and it's hard to say if one should enter when it is below/above the bands or when the price crosses them. I find that with many indicators and strategies it's best to wait for a confirmation of some sort, in this case by waiting for some crossover of a band. Like most mean reversion strategies, the exit is very loose if using BBs alone. Usually the plan to exit is when the price finally reverts back to the mean or in this case the middle band. This can potentially lead to huge drawdowns and/or losses. Mean reversion strategies can have high win/loss ratios but can still end up unprofitable because of the huge losses that can occur. These drawdowns/losses that mean reversion strategies suffer from can potentially eat away at a large chunk of all that was previously made or perhaps up to all of it in the worst cases, can occur weeks or perhaps up to months after being profitable trading such a strategy, and will take a while and several trades to make it all back or keep a profitable track record. It is important to have a stop loss, trailing stop, or some sort of stop plan with these types of strategies. For this one, in addition to exiting the trade when price reverts to the middle band, I included a time-based stop plan that exits with a gain or with a loss to avoid potentially large losses, and to exit after only a few periods after taking the trade if in profit instead of waiting for the price to revert back to the mean.
Varprice4 - Price is the real KingWhen you use any indicators you suffer of lagging and possibile mistakes.
In this case, higher movements of the (daily) prices (long green candle) are a signal that market is appreciating your stock. The variation of a single candle is compared to standard deviation of the stock.
Besides normal money management (on fixed percentages), we have kept the possibily of exiting the position before stop loss adding a multiplier considering that red (or black) candles are normally wider than green (white) ones.
sma dipsparity and sdvFXBTCJPY 1min contrarian script (2020/1/30)
1分足の逆張りです．
If you want to use other timescale, need to change disparity rate and sdv.
To display disparity(sma) and standard deviation, and to draw a hline(pine function) a certain valu. And lets think. I thought disparity rate 1~1.3 or -1~-1.3 are able to use constrarian trade (and sdv>600).
In bottom, disparity index is auxiliary. It is different from the multiple in the script to make the value easier to understand.
Sorry if the expiration date of the script has expired.
Pair Trade cryptoPair trade for crypto with inputs:
* length of correlation and moving average
* trade pair
* spread threshold to enter long / short
* spread threshold to exit long / short
Pair TradePair trade with inputs:
* length of correlation and moving average
* trade pair
* spread threshold to enter long / short
* spread threshold to exit long / short
Bollinger Band BreakoutIt is a long only strategy.
1. Buy when price breaks out of the upper band.
2. Exit has two options. Option 1 allows you to exit using lower band. Option 2 allows you to exit using moving average.
3. Option 1 preferred over option 2 if the instrument is highly volatile.
4. Slippage and commissions are not considered in the return calculation.
Breakout Reversal Entry on WMA - NG1! Overnight ver 1This script is for learning purposes only
This strategy will plot arrows when price breaks so far above/below WMA. The strategy will enter when the price breaks away from WMA. All entries are reversals. Users can set WMA length and source; also the distance of the price away from WMA to enter. Adjustable bracket orders are placed for exit, with trailing stop or market stop choice. Last, users can set the time of day they want to enter a trade.
My Preference: I am testing this strategy on NG1! over night on 1 minute candle. with .003 on price drop/climb, I get entries almost every night. Also 10 tick stop and 5 tick profit seems backward to most, but with a high win/loss ratio, it performs quite well. Trailing stops generally help out as well.
INPUTS:
Length - The is the WMA length
Source - WMA source (High, Low, Open, Close...)
When Price Drops - This is the distance in ticks when the price drops away from WMA, an arrow is plotted, and reversal entry order is placed
When Price Climbs - Same as price drop, just in the opposite direction
Trailing Stop check box - Check if you want to place a trailing stop so many tick away from entry. Unchecked is Market (hard) stop so many ticks from entry.
Stop - Number of ticks away from entry a the stop or trailing stop is set (for NG 1 tick = $0.001)
Limit Out - Number of ticks away from entry a limit order is placed to take profits
Limit Time of day check box - check to use the time of day to limit what time of day order entry will occur.
Start/Stop Trades (Est Time) - First box is when the strategy will be allowed to start buying and stop is when the strategy will stop being allowed to buy. Sell orders continue until a stop or limit triggers an exit. These times are Eastern time zone
PROPERTIES:
Pyramiding - This feature will allow multiple entries to occur. If set to 1, the strategy should only trade 1 contract at a time. If set to 2, the strategy will enter a second order if entry requirements are met. This allows you to be holding 2 contracts. Basically on a good day, it will multiply your earnings, on a bad day, you'll just lose more. For testing, I keep this on 1.
TIPS:
- If you want to go long only, set "When Price Climbs" to an impossible number, like 10,000. It's not possible for NG to move $10 is a matter of minutes so it will not enter the market with a short order. Also keep in mind you can set different requirements for going long vs going short. If you think there is more pull on the market in a particular direction.
SD_Bull_Bear_Engulfing_Rsi_SdThis strategy combines the idea of a bullish or bearish candle engulfing coupled with standard deviation (a 100% increase or a 50% decrease). The exit condition is placed if the percentage increase is achieved or 35<rsi<65.
The strategy requires refinement so please test the script and let know what can be incorporated to improve the efficiency.
