Pulse Profiler [QuantraSystems]Pulse Profiler
Introduction
The Pulse Profiler ( ℙℙ ) is specifically designed to unambiguously indicate weakening momentum after a strong impulse. The upper and lower standard deviation bands also allow the user to assess the strength of an impulse and differentiate it from general noise.
Due to the ℙℙ ’s rapid responsiveness to exhaustion in price movement it is ideally used for the trader to recognize when to start taking profit when combined with other indicators.
The novum is that by dynamically balancing its sensitivity to recent movements the ℙℙ considers the asset’s inherent volatility. By reducing noise without sacrificing signal, and by visualizing it in our typical modern QuantraAI style, the ℙℙ enhances the traders’ ability to distinguish impulses with weakening momentum from strong trending movements.
Legend
Impulse: The ℙℙ showing strength based on momentum and volume.
Dynamic standard deviation bands: Rolling probability based bands based on a rolling normal distribution. Adjustable, recommended are σ = 1.5 to σ = 2.5.
Neutral lines: Dynamic thresholds which get often respected as support or resistance.
Case Study
To properly employ the ℙℙ , the trader should use it to identify out-of-the-ordinary 𝓲𝓶𝓹𝓾𝓵𝓼𝓮𝓼 which cause a following exhaustion.
The rolling standard deviation bands incorporate the asset’s historical behavior in regards to its inherent volatility on a rolling basis. If the asset shows strong 𝓲𝓶𝓹𝓾𝓵𝓼𝓮𝓼 that go beyond the rolling standard deviation, the event has been highly improbable. The trader then needs to determine if the price change was caused by critical external factors. If not, it is highly probable that the momentum exhausts and that price movement plateaus to enter a range.
These signals indicate that it is highly probable that closing a position upon these conditions is the correct choice.
If the 𝓲𝓶𝓹𝓾𝓵𝓼𝓮 reverses and retraces into the opposite direction, while moving more than 1.5σ across just 3 bars on the 4H chart, the signal indicates that a reversal is pushing the price down – in both momentum and volume.
A sharp reversal thus becomes more probable than not.
The ℙℙ can also be calibrated to find possible trend exhaustions on a longer timeframe (1D).
Please always use multiple Quantra indicators to add confirmations to your signals.
Recommended Settings
Swing Trading (4H chart)
Standard Deviation Lookback: 150
Standard Deviation Multiplier (σ): 2.5
Display Variant: Classic
Choose Mode for Bar Coloring: Signal
Trend exhaustion (1D chart)
Standard Deviation Lookback: 200
Standard Deviation Multiplier (σ): 2.0
Display Variant: Classic
Choose Mode for Bar Coloring: Extremes
Notes
Quantra Standard Value Contents:
The Heikin-Ashi (HA) candle visualization smoothes out the signal line to provide more informative insights into momentum and trends. This allows earlier entries and exits by observing the indicator values transformed by the HA.
Various visualization options are available to adjust the indicator to the user’s preference: Aside from HA, a classic line, or a hybrid of both.
A special feature of Quantra’s indicators is that they are probabilistically built - therefore they work well as confluence and can easily be stacked to increase signal accuracy.
To add to Quantra's indicators’ utility we have added the option to change the price bars colors based on different signals:
Choose Mode for Coloring
Trend Following (Indicator above mid line counts as uptrend, below is downtrend)
Extremes (Everything beyond the SD bands is highlighted to signal mean reversion)
Candles (Color of HA candles as barcolor)
Reversions (Only for HA) (Reversion Signals via the triangles if HA candles change trend while beyond the SD bands, high probability entries/exits)
The ℙℙ is also sensitive to divergences for those interested in utilizing this feature.
Through a special combination of price, volume and momentum you get a holistic overview on the impulse strengths of movements.
The two neutral lines in the center act as dynamic, volume and volatility adjusted thresholds. Often the signal line respects them as support and resistance.
The upper and lower standard deviation lines express the rarity of an impulse based on the asset’s inherent volatility.
The indicator needs a long enough timespan to build up its probability estimation, therefore the asset needs sufficient price history.
The indicator requires thorough volume data. If the source of an asset pair does not forward it, try to find another source or exchange for the same pair.
Signal Mode on the 4H chart is a relevant part of this indicator when used in isolation and helps to analyze momentum adjusted by volatility.
Methodology
The ℙℙ combines the Arnaud Legoux Moving Average (ALMA) with a bespoke volume and momentum calculation, with a classical Exponential Moving Average (EMA) on price data.
The ℙℙ itself integrates ALMA for volume and momentum with an EMA calculation on price, creating a unique blend that expresses impulses using their three raw main components.
The indicator calculates dynamic standard deviation bands based on an adjustable lookback period and the adjustable sigma (σ), to signal when the impulse strength is just uncommon or even extraordinary when compared to the usual price movements:
σ = 1.5 the probability of similar impulse strength occuring is 13.37% / 2, hence ~ 6.69%
σ = 2.0 the probability of similar impulse strength occuring is ~ 2.28%
σ = 2.5 the probability of similar impulse strength occuring is ~ 0.62%
By detecting extremely improbable conditions the indicator can create an inversely highly probable signal to its user.
Neutral bands are calculated based on the ℙℙ alongside a rolling, dynamic multiplier. This effectively provides dynamic thresholds for approximating common volatility.
Heikin Ashi method: The indicator uses a custom function to calculate Heikin Ashi values, useful for smoothing impulse data and identifying trends.
Reversion Signals: Specifically for Heikin Ashi displays, we plot triangles as signals, useful to easily spot potential reversals.
The Signal Mode uses these different thresholds to highlight significant market moves.
Buythedip
Dip & Rip Patterns - The Quant Science🇺🇸
GENERAL OVERVIEW
This indicator detects Dip and Rip patterns by quickly highlighting them on the chart.
These patterns have become popular during the pandemic period mainly in the stock, ETF and cryptocurrency markets on which traders use two interesting strategies:
Buy The Dip
Sell The Rip
Before going into the merits of this technical indicator, let's understand what these two patterns mean and what they identify precisely.
Rip (Rise In Price) : wants to identify a market condition in which the price rises rapidly, for example from $100 to $110 in a few minutes or hours.
Dip (Drop In Price) : wants to identify a market condition in which the price drops rapidly, for example from $100 to $90 in a few minutes or hours.
HOW TO USE
For a better user experience, we recommend choosing a neutral colour for the candles while analysing with this indicator. You can quickly change the colour in Chart Settings > Symbol > Candles .
Depending on the configuration set by the user, the indicator will show Dip (Dip In Price) patterns in red and Rip (Rise In Price) patterns in green.
When the pattern forms, a circle will be displayed and a vertical line will be coloured on the chart along with the body of the candle. The user will then be able to quickly and easily track the configured market conditions.
In this example, we decided to use a 4H timeframe on the BTC/USDT pair (Binance).
Set in the user interface:
Period: 20
Dip (%): -25
Rip (%): 20
Price falls by 25% or more in 80 hours (Dip Pattern).
Price rise by 25% or more in 80 hours (Rip Pattern).
The user can easily configure the parameters via the user interface in the Inputs section (A) and change the indicator design in the Properties section (B).
🇮🇹
PANORAMICA GENERALE
Questo indicatore rileva i Dip e Rip patterns evidenziandoli velocemente sul grafico.
Questi patterns sono diventati famosi durante il periodo pandemico principalmente nel mercato delle azioni, ETF e Criptovalute su cui i trader utilizzano due interessanti strategie:
Buy The Dip
Sell The Rip
Prima di entrare nel merito di questo indicatore tecnico, comprendiamo il significato di questi due pattern e cosa identificano precisamente.
Rip (Rise In Price) : vuole identificare una condizione di mercato in cui il prezzo sale rapidamente, per esempio passando da 100$ a 110$ in pochi minuti o poche ore.
Dip (Drop In Price) : vuole identificare una condizione di mercato in cui il prezzo cala rapidamente, per esempio passando da 100$ a 90$ in pochi minuti o poche ore.
UTILIZZO
Per una migliore esperienza utente consigliamo di scegliere un colore neutro per le candele mentre si analizza con questo indicatore. Puoi cambiare velocemente il colore in Chart Settings > Symbol > Candles .
In base alla configurazione impostata dall'utente l'indicatore mostrerà in rosso i pattern Dip (Dip In Price) e in verde i pattern Rip (Rise In Price).
Quando il pattern si forma verrà visualizzato un cerchio e una linea verticale sul grafico che sarà colorata insieme al corpo della candela. L'utente quindi potrà tracciare facilmente e velocemente le condizioni di mercato configurate.
In questo esempio abbiamo deciso di utilizzare un timeframe 4H con l'obbiettivo di ricercare i patterns sul pair BTC/USDT (Binance).
Impostiamo nell'interfaccia utente:
Period: 20
Dip (%): -25
Rip (%): 20
Il prezzo diminuisce del 25% o più in 80 ore (Dip Pattern).
Il prezzo aumenta del 25% o più in 80 ore (Rip Pattern).
L' utente può configurare facilmente i parametri attraverso l'interfaccia utente nella sezione Inputs (A) e modificare il design dell'indicatore nella sezione Properties (B).
BTFD strategy [3min]Hello
I would like to introduce a very simple strategy to buy lows and sell with minimal profit
This strategy works very well in the markets when there is no clear trend and in other words, the trend going sideways
this strategy works very well for stable financial markets like spx500, nasdaq100 and dow jones 30
two indicators were used to determine the best time to enter the market:
volume + rsi values
volume is usually the number of stocks or contracts traded over a certain period of time. Thus, it is an important indicator of market activity and liquidity. Each transaction constitutes an individual exchange between the buyer and the seller and constitutes the trading volume of a given instrument or asset.
The RSI measures the strength of uptrends versus downtrends. The signal is the entry or exit of the indicator value of the oversold or overbought level of the market. It is assumed that a value below or equal 30 indicates an oversold level of the market, and an RSI value above or equal 70 indicates an overbought level.
the strategy uses a maximum of 5 market entries after each candle that meets the condition
uses 5 target point levels to close the position:
tp1= 0.4%
tp2= 0.6%
tp3= 0.8%
tp4= 1.0%
tp5= 1.2%
after reaching a given profit value, a piece of the position is cut off gradually, where tp5 closes 100% of the remaining position
each time you enter a position, a stop loss of 5.0% is set, which is quite a high value, however, when buying each, sometimes very active downward price movement, you need a lot of space for market decisions in which direction it wants to go
to determine the level of stop loss and target point I used a piece of code by RafaelZioni , here is the script from which a piece of code was taken
this strategy is used for automation, however, I would recommend brokers that have the lowest commission values when opening and closing positions, because the strategy generates very high commission costs
Enjoy and trade safe ;)
LNL Pullback ArrowsBuying the dip has never been easier! LNL Pullback Arrows are here to pinpoint the best possible entries for the trend following setups. With the Pullback Arrows, trader can pick his own approach and risk level thanks to four different types of arrows. The goal of these arrows is to force the traders to scale in & out of trades which is in my opinion crucial when it comes to trend following strategies. These arrows were designed primarily for the daily & weekly time frame (swing trading).
Four Types of Pullback Arrows:
1. Aggro Arrows - Ideal for aggresive approach during parabolic trends. Sometimes trends are so strong that the price barely revisits the daily 8 EMA. This is where the aggro arrows can perfectly pinpoint the aggresive high risk entries. Ideal for halfsize or 1/4 size of the full position. Aiming for quick 1-2 day moves targeting the recent high/low. These arrows could be also named as scalping arrows for the swing traders. A quick In & Out.
2. HalfSize Arrows - Medium risk approach. First arrows to scale in. HalfSize arrows are the first sign that the pullback might be ending, yet there is still some space left for an even deeper pullback. That is the reason why they are called half-size. Ideally taken with half-sized position. When trading the HalfSize Arrows, It is better to have some "spare ammo in the gun" ready to use.
3. FullSize Arrows - Regular risk approach. These arrows represent a zone where the core of the posititon should be taken. The point of validity for the trend is not that far away, meaning the risk can be kept tight. Ideal for scailing the other halfs or quarters of the full position. Also great for more conservative traders or environments with higher volatility.
4. Rare Arrows - Offer the best risk to reward entries during the trend. Rare Arrows should be the "last kick" of the retracement, therefore stops can be positioned really tight. They either trigger the stop immidiately or they provide another juicy leg up or down in the direction of the trend. However, they really do appear rarely.
Simple EMA Cloud:
A simple cloud based on 21 and 55 exponential moving averages. This default length creates a pullback zone that is wide enough for the conservative traders but also give the opportunities to more aggresive traders. Alternatives such as 8 & 21, or 21 & 34 are forming the zone that is too aggresive and usually too thin. Of course, cloud can be fully adjusted or turned off completely. The only role of the cloud is to gauge the trend.
Tips & Tricks:
1.Importance of the Scailing
- As already stated, scailing is crucial to this since there is no way of knowing the exact level at which the price magically bounce every time. It is hard to tell where and which EMA will be respected. How can we know it will be 21 EMA every time? or 34 EMA or 10 EMA or 100 SMA or 50 DMA ... Single MA does not make a trend. This is the reason why scailing is so important. Scailing can make a difference.
2. Nothing is Perfect
- Same as any other study, nothing works 100% perfectly. Sometimes the setup will go right against you and sometimes the price will fade away sideways and breaks off the structure of the trend. This is not a magic certainty tool. This is just another probability tool.
3. Point of Validity & Other Studies
- Even though the pullback arrows can be a stand-alone strategy. It is important to use other indicators that visualize the actual trend. Whether its EMA Cloud or EMAs or DMI Bars or Keltner Channels, there should be something that validates the trend, something that tells the trend is over. (Pullback Arrows are not showing the actual stops!).
Hope it helps.
LTDP: Long Trade on Drop Price (ETH/USDT, Timeframe 4H)How it works
The script analyses drawdown periods and negative price variation in order to search for ideal entry points for long positions.
"Has 'buy the dip' really produced profitable results so far?" "How do you define a buy the dip entry?" "What are the best setups to take advantage of a strong market drop?"
Many investors ask themselves these questions when they are buying during a strong drop price. Having an analysis tool that allows you to analyse the profitability of buying during a market drop is indispensable for dealing with it like a pro. We have decided to develop a script that gives you the ability to analyse this market condition in depth.
LTDP is a very light script created with Pine V.5 that has about 50 strings of code. We have developed a user interface capable of adjusting the analysis period from a few days to several years. We have chosen the Rate Of Change indicator to implement the function to analyse the period and the price variation. Finally, we have set the condition with which the script simulates a long entry with the intention of exploiting the volatility and the bearish moment. The trade is closed by stop losses and take profits which can be adjusted by the user interface.
What can you do with LTDP ?
1) Understand if a Buy The Dip approach can be profitable .
Using the interface you can adjust the periods and variations and analyse whether there is a possibility to use this strategy on that market. Understand if in the past this approach has produced positive results on the market under analysis.
2) Understand the best setup to approach a "Buy The Dip" strategy.
Once you understand and set up the best period and variation you can research which take profit and stop loss has worked best so far.
In this test
We used LTDP to answer this question on the ETH/USDT pair with 4H timeframe.
Buying after a drop of -17.5% over 28 hours, is it possible to achieve profitable conditions by opening only long positions with a 3% take profit and a 4% stop loss?
In this study case the result was that offered by the backtest. In this market using this simple strategy, positive results have been produced over the last 4 years.
The initial capital set is €10,000 (You can change this from the "Properties" section of the user interface).
Each individual trade uses 100% of the set capital, in this case €10,000.
The default commission per trade is 0.03% (You can change this in the "Properties" section of the user interface).
User Interface
1) General backtest time settings: Set the history period to be analysed
StartDate: backtest start date
StartMonth: backtest start month
StartYear: backtest start year
EndDate: backtest end day
EndMonth: backtest end month
EndYear: backtest end year
2) Buy The Dip analysis settings: Set the drawdown period and the variation to be taken into account
Period_on_analysis: Drawdown bars analysis
Source: Open, Close, High, Low
PercentDrawDown: The percentage of decline to be observed in Period_on_analysis
3) Money Management Settings: Set Take Profit and Stop Loss
TakeProfit: % Profit
StopLoss: % Loss
Please do not hesitate to contact us for any questions or information.
Disclaimer
Be careful, the past is not a guarantee of future performance, so remember to use the script as a pure analysis tool that cannot be intended as the sole reference in making and implementing financial investment strategies. The developer takes no responsibility for any use other than research and analysis and can in no way be held liable for damages resulting from misuse of this code.
CryptoFall v1.0.0Category: Trend Analysis
Timeframe:
- Best on 4H, D
- Faster on 30M, 1H
Suggested Use: In uptrend.
Input option: Is possible to use "Alternative Time Frame" using other candles on different Time Frame charts.
Logic: The tradable market range is calculated, on which the Fibonacci levels are automatically calculated, at this point the entries could be defined entering on the important zone levels.
The calculation takes into account a combination of indicators such as:
- Fibonacci Retracement ( FibRetr )
- Theory of W. D. Gann .
Entry: The indicator uses Fibonacci levels to identify a good time to enter using the Buy the Dip approach (i.e. considering that a typical pullback is in the range between 0.382 and 0.618).
Tips: The best way to enter the market is always to split the positions so as not to enter entirely and expose yourself with all your capital, @TheSocialCryptoClub insists on a careful management of the orders so as to be able to mediate the price depending on the depth of the retracements.
Exit: Defined by the investor's long-term objective.
Thanks for attention.
Automatic half priceJapanese below / 日本語説明は下記
This indicator automatically draws half price lines based on the logic below.
Today’s half price: Half price between today’s high and low
Yesterday’s half price: Half price between yesterday’s high and low
Half price as hidden support and resistance
As a characteristic of market, price sometimes tests previous day’s half price first when previous day ends with bullish candle, then tries new high.
Example1: USDJPY Daily chart: New high after testing previous day’s half price
July9 ends with bullish candle. July10 candle tests previous day’s half first, then records new high.
Example2: USDJPY 1H chart: New high after testing today’s half price
Another example is that today’s half is tested by NY session.
In this case, Asian & European session is an uptrend. When the NY session starts, it tests the half of Asian & Euro sessions’ gain then records new high.
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押し目戻り目として意識される半値を自動描画するインジケーターです。
当日半値: 当日日足ローソク足の高値と安値の半値
先日半値: 先日日足ローソク足の高値と安値の半値
<参考>
押し目戻り目として意識される半値
相場の動きの特徴として、例えば前日の日足ローソク足が陽線で引けた場合、前日の陽線の半値付近を一度試してから上昇するという動きがよく見られます。
例1 ドル円日足: 前日の半値を試してから上昇
7/9は陽線で引けています。翌日7/10のローソク足は前日の半値付近を試した後、高値更新をしています。
例2 ドル円 1時間足: 当日の半値を試してから上昇
8/10のアジア時間と欧州時間は上昇トレンドです。NY時間がスタートした時、アジア時間と欧州時間の上昇の半値付近を試した後、高値更新をしています。
BuyTheDip V2This is enhanced version of BuyTheDip Strategy which can be used for stocks and cryptos as well along with indices.
In addition to V1, the enhancement include breaking the zone into multiple levels based on multiple standard deviation Bollinger bands. Dip is confirmed only when price bounce back certain levels from the bottom. If price keeps going down, strategy does not generate signal.
Input parameters are as below:
ATR Parameters : AtrLength and AtrMult to calculate trailing stops
Trailing Condition parameters : TrailAfterBars, TrailTargetState - Trailing does not happen immediately. It either waits for TrailAfterBars to complete or price moves up by TrailTargetState levels in multi bollinger band level setup - whichever happens first.
Force Exit Parameters : If the price state based on multi-bollinger bands drop by TargetStopStateDiff level from its peak, then it will force exit from the trade if ExitOnFailureSignal is checked.
Entry Filters : It is not a dip if the instrument is already in downtrend. ConsiderYearlyHighLow , ConsiderNewLongTermHighLows and ConsiderMAAlignment are used for filtering entries so that we only buy the dip for uptrending instruments.
Optimized RSI Strategy - Buy The Dips (by Coinrule)Buy low and sell high is every trader's mantra. While this approach looks straightforward in theory, it's sometimes challenging to put into practice. That requires stress-management to buy when price drops and resolution in selling when the price is rising. RSI is a useful tool to implement long-term and effective trading strategies. The script presents an optimized RSI trading strategy that uses a Moving average to spot the best time to buy the dip.
The strategy buys when the RSI is lower than 35, and at the same time, the price is below the MA100. In this way, the approach helps avoid catching early dips, increasing buying when the bottom approaches.
The position closes when the RSI value is above 65 . Depending on the volatility of the coins that the strategy will trade, it's possible to adjust the RSI exit value to chase larger profits.
The setup is optimized on a 15-minutes time frame and trading cryptocurrencies versus USD or stable coins.
The strategies was backtested over 150 times with multiple setups and coin to assess the best long-term system.
The strategy assumes each order to trade 30% of the available capital. A trading fee of 0.1% is taken into account. The fee is aligned to the base fee applied on Binance, which is the largest cryptocurrency exchange.
Multi Time Frame Buy the Dips (by Coinrule)Buying the dips is a relatively easy automated trading strategy that can return impressive profits, especially during uptrend times. Not all price drops are for buying, though. This trading system is based on a multi time frame buy-the-dip approach to optimize each trade.
The strategy catches sudden price drops on a 1-hr time frame when the price increases significantly in the last 12 hours. During steep uptrends, profit-taking price actions result in flash crashes that provide great opportunity to enter at convenient prices.
Buy Condition
The setup of the script is optimized on a 30 min time frame. You can adjust the parameters to fit different time frames.
The system gets a buy signal when
- the price drops 1% from the two previous candles (1 hour time frame = two 30-min candles)
- the price is up 3% from the last 12 hours (twenty-four 30-min candles equal the desired time frame)
Sell Condition
Each trade comes with a stop loss of 3% and a take profit of 4%.
This setup has been optimized, running over 150 backtests on more than 20 different crypto trading pairs.
The strategy assumes each order to trade 30% of the available capital. A trading fee of 0.1% is taken into account. The fee is aligned to the base fee applied on Binance, which is the largest cryptocurrency exchange.
Buy the Dips (by Coinrule)Taking your first steps into automated trading may be challenging. Coinrule's mission is to make it as easy as possible, also for beginners.
Here follows the best trading strategy to get started with Coinrule. This strategy doesn't involve complex indicators, yet was proved to be effective in the long term for many coins. Results seem to be improved when trading a coin vs Bitcoin.
The strategy buys the dips of a coin to sell with a profit. A stop-loss protects every trade.
Crypto markets offer high volatility and, thus, excellent opportunities for trading. Excluding times of severe downtrend, buying the dip is a simple and effective long-term trading strategy. The buy-signal is set to a 2% drop in a 30-minutes time frame.
Each trade comes with a take profit and a stop loss. Both set at 2%.
You can adjust these percentages to the market volatility as an advanced setup. You can backtest the outcomes using the backtesting tool from Tradingview
The strategy assumes each order to trade 30% of the available capital. A trading fee of 0.1% is taken into account. The fee is aligned to the base fee applied on Binance, which is the largest cryptocurrency exchange.
BuyTheDipWell, I often had arguments in online forum with a guy who claimed to time the market perfectly without any technical analysis or prior experience. He often claimed that technical analysis does not work and it only works when you trade on other's emotions. He also argued that algorithmic trading isn't profitable - if so, everyone would do that. Hence, I thought I will convert his idea to algorithm.
In his own words, the strategy is as below:
Chose an instrument which is in full uptrend.
Wait for the panic sell and buy the dip
Once market recovers back exit immediately
It seems to do just fine with indexes. But, not so good when it comes to stocks.
A Physicist's Bitcoin Trading Strategy
1. Summary
This strategy and indicator were designed for, and intended to be used to guide trading activity in, crypto markets, particularly Bitcoin. This strategy uses a custom indicator to determine the state of the market (bullish vs bearish) and allocates funds accordingly. This particular variation also uses the custom indicator to determine when the market is significantly oversold and takes advantage of the opportunity (it buys the dip). The specific mathematical formula that is used to calculate the underlying custom indicator allows the trader to get in before, or near the start of, the bull trends, and get out before the bear trends. The strategy's properties dialogue box includes many display settings and parameters for optimization and customization to meet the user's needs and risk tolerance; this is both a tool to gauge the market, as well as a trading strategy to beat the market. Guidelines for parameter settings are provided. A sample dataset of backtest results using randomized parameters, both within the guidelines and outside the guidelines, is available upon request; notably, all trials outperformed the intended market (Bitcoin) during the 9-year backtest period.
2. The Indicator and Strategy
2.1. The Indicator
A mathematical formula is used to determine the state of the market according to three different "frequencies", which, for lack of better terminology, are called fast, moderate, and slow indicators. There are two parameters for each of the three indicators, one called response time and the other is a simple look-back period. Finally, four exponential moving averages are used to smooth each indicator. In total, there are 18 different levels of bullishness/bearishness. The purpose of using three indicators, rather than one, is to capture the full character of the market, from a macro/global scope down to a micro/local scope. I.e. the full indicator looks at the forest, the trees, and the branches, simultaneously.
2.2. The Strategy
The trend-trading strategy is very simple; there are only four types of orders: 1) The entire position (e.g. all bitcoins held) is sold (if it hasn't already been totally sold) when the indicator becomes maximally bearish, 2) When the movement of the indicator is in the bullish direction, the strategy dollar-cost-average (DCA) buys at an exponentially decreasing rate, i.e. it buys more in the early stages of the transition from bear->bull. 3) When the indicator is maximally bullish, it goes "all-in" † (if it hasn't already gone all-in), i.e. it converts all available cash into the underlying security/token. And, 4) when the movement of the indicator is in the bearish direction, the strategy DCA sells (again, exponentially decreasing) to get out quickly. No leverage is used in this strategy. The strategy never takes a short position.
A second "buy-the-dip" strategy is also used, and it is the synergy of these two strategies, together, that is responsible for most of the outperformance in the backtests (this strategy handily beats the non-dip-buying variation in backtests). To do this, the custom indicator is used to determine when the market is significantly oversold on a short-term basis, and the strategy responds by DCA buying. However, unlike the DCA buying during bull/bear transitions, the buy-the-dip DCA buying increases with time. Specifically, within each candle that is short-term oversold, the strategy converts 10% x # of candles since becoming oversold (up to a max of 6 candles) of available cash into the underlying security/token. I.e. the first buy is 10% of available cash and occurs in the first oversold candle, the second buy is 20% of available cash and occurs in the second oversold candle, etc. up to six consecutive oversold candles. Lastly, to ensure no conflicting orders and no leverage (buying more than what is affordable with the available cash in the fund), buy-the-dip orders take precedence over the trend-trading orders enumerated in the previous paragraph.
† Technically the strategy goes 99.5% in when it goes "all-in". This is to ensure no leverage is used given that there may be a commission of 0.5%.
3. Backtest Results
Backtest results demonstrate significant outperformance over buy-and-hold. The default parameters of the strategy/indicator have been set by the author to achieve maximum (or, close to maximum) outperformance on backtests executed on the BTCUSD (Bitcoin) chart. However, significant outperformance over buy-and-hold is still easily achievable using non-default parameters. Basically, as long as the parameters are set to adequately capture the full character of the market, significant outperformance on backtests is achievable and is quite easy. In fact, after some experimentation, it seems as if underperformance hardly achievable and requires deliberately setting the parameters illogically (e.g. setting one parameter of the slow indicator faster than the fast indicator). In the interest of providing a quality product to the user, suggestions and guidelines for parameter settings are provided in section (6). Finally, some metrics of the strategy's outperformance on the BTCUSD chart are listed below, both for the default (optimal) parameters as well as for a random sample of parameter settings that adhere to the guidelines set forth in section (6).
Using the default parameters, relative to buy-and-hold strategy, backtested from August 2011 to August 2020,
Total cumulative outperformance (total return of strategy minus total return of buy-n-hold): 13,000,000%.
Rolling 1-year outperformance: mean 318%, median 84%, 1st quartile 55%, 3rd quartile, 430%.
Rolling 1-month outperformance: mean 2.8% (annualized, 39%), median -2.1%, 1st quartile -7.7%, 3rd quartile 13.2%, 10th percentile -13.9%, 90th percentile 24.5%.
Using the default parameters, relative to buy-and-hold strategy, during specific periods,
Cumulative outperformance during the past year (August 2019-August 2020): 37%.
12/17/2016 - 12/17/2017 (2017 bull market) absolute performance of 2563% vs buy-n-hold absolute performance of 2385%
11/29/2012 - 11/29/2013 (2013 bull market) absolute performance of 14033% vs buy-n-hold absolute performance of 9247%
Using a random sample (n=20) of combinations of parameter settings that adhere to the guidelines outlined in section (6), relative to buy-and-hold strategy, backtested from August 2011 to August 2020,
Average total cumulative outperformance, from August 2011 to August 2020: 2,000,000%.
Median total cumulative outperformance, from August 2011 to August 2020: 1,000,000%.
4. Limitations
This strategy is basically a DCA-swing trading strategy, and as such it is intended to be used on the 6-hr chart. Similar performance is expected on daily chart, 12-hr chart, and 4-hr chart, but performance is likely to be limited when used on charts of shorter time-frames. However, due to the flexibility afforded by the large quantity of parameters, as well as the tools included, it may be possible to tweak the indicator settings to get some outperformance on smaller time-frames. Admittedly, the author did not spend much time investigating this.
As is apparent in the backtests, this strategy has very limited absolute performance during large bear markets, such as Bitcoin's 2018 bear market. As described, it does outperform the underlying security by a large amount in backtests, but a large absolute return is unlikely during large and prolonged declines (unless, of course, your unit of account is the underlying token, in which case an outperformance of the underlying is, by definition, an absolute positive return).
This strategy is likely to underperform if used to trade ETFs of broad equity markets. This strategy may produce a small amount of outperformance when used to trade precious metals ETFs, given that the parameters are set optimally by the user.
5. Use
The default parameters have already been set for highly optimal backtest results on the chart of BTCUSD (Bitcoin / US Dollar BITSTAMP), (although, a different combination of parameter settings may yet produce better results). Still, there is a great number of combinations that can be explored, so the user is free to tweak the settings to meet his/her/their needs. Some display options are provided to give the user a visual aid while tweaking the parameters. These include a blue/red background display of the custom indicator, a calibration system, and options to display information about the backtest results. The background pattern represents the various levels of bullishness/bearishness as semi-transparent layers of blue and red, with blue corresponding with bullish and red corresponding with bearish.
The parameters that affect the indicator are the response times, the periods, and some EMA lengths. The parameters that affect the quantity of contracts (tokens/shares/bitcoins/etc) to be bought/sold are the transitionary buy/sell rates. There are also two sets of date parameters.
The response time and period parameters are direct inputs into the underlying math formula and are used to create the base-level indicators (fast, moderate, and slow). The response times control the speed of each of the three indicators (shorter is fast, longer is slower) and the period controls how much historical data is used in computation. Information about how these should be set are included in section (6). Another set of parameters control EMA look-back periods that serve to smooth the base-level indicators. Increasing these EMA lengths makes the overall indicator less sensitive to short-term price action, while reducing them does the opposite. The effect of these parameters are obvious when the background blue/red visualization is displayed. Another EMA length is an EMA for the entire indicator. Increasing this parameter reduces the responsiveness of the trading strategy (buy/sell orders) to quick/small changes of the overall level of the indicator, so as to avoid unnecessary buying and selling in times of relatively small and balanced price perturbations. Note, changing this parameter does not have an effect on the overall indicator itself, and thus will not affect the blue/red background representation.
The transitionary buy/sell rates control the portion of the available asset to be converted to the other. E.g. if the buy rate is set to 90%, then 90% of the available cash will be used to buy contracts/tokens/shares/bitcoins during transitions bullish transitions, e.g. if the available cash at the start of the bullish transition is $10,000 and the parameter is set to 90%, then $9,000 will be used to buy in the first candle during which the transition is bullish, then $900 will be used to buy in the second candle, then $90 in the third candle, etc.
There are two dates that can be set. The first is the date at which the strategy goes all in. This is included because the buy-and-hold strategy is the benchmark against which this strategy is compared, so setting this date to some time before the strategy starts to make trades will show, very clearly, the outperformance of the strategy, especially when the initial capital parameter in the Properties tab is equal to the price of one unit of the underlying security on the date that is set, e.g. all-in on Bitcoin on 8/20/2011 and set initial capital to the BTCUSD price on that date, which was $11.70. The second date is a date to control when the strategy can begin to place trades.
Finally (actually, firstly in the Inputs dialogue box), a set of checkbox inputs controls whether or not the backtest is on or off, and what is displayed. The display options are the blue/red (bull/bear) background layers †, a set of calibrators, a plot of the total strategy equity, a plot of the cash position of the strategy, a plot of the size of the position of the strategy in contracts/shares/units (labeled as BTC position), and a plot of the rolling 1-year performances of buy-and-hold and the strategy.
About the calibrators: The calibration system allows the user to quickly assess and calibrate how well the indicator... indicates. Quite simply, the system has two parts: one plot that is the cumulative sum of the product of the indicator level and the change in the underlying price, i.e. sum of ‡, over all candles. The second part is a similar plot that is reduced according to the quickness with which the indicator changes, i.e. sum of . Maximizing the first plot at the expense of the second will cause the indicator to match the price action very well but therefore it will change very rapidly, from bullish to bearish, which is visualized by a background pattern that changes frequently from blue to red to blue. Ignoring the first plot and maximizing the second will also cause the indicator to more closely match the price action, but the transitions will be slower and less frequent, and will therefore focus on identifying the major trends of the market.
† The blue/red background has many layers and will make the chart lag as the user interacts with it.
‡ Bearish states are coded as negative quantities, so a bearish state x negative price action = positive number, and bullish state x positive price action = positive number.
6. Suggestions and Guidelines
As described in section (2.1), the indicator used in this strategy was designed to determine the state of the market--whether it is bullish or bearish--as well as the change in the state of the market--whether it is increasingly bullish or increasingly bearish. As such, the following suggestions are provided based on the principles of the indicator's design,
1. Response Time 1 should be less than (<) Response Time 2 which should be < Response Time 3
2. Fast Period < Moderate Period < Slow Period
3. In terms of the period of a full market cycle (e.g. ~ 4 years for BTC, ~ 5.5 years for equities, etc.), response times 1, 2, and 3 should be about 0.3% to 1%, 3% to 20%, and 20% to 50% of a full market cycle period, respectively. However, this is a loose guideline.
4. In terms of the period of a full market cycle, periods 1, 2, and 3 should all be about 25% to 75% of a full cycle period. Again, this is a loose guideline.
4. EMA 1 Length < EMA 2 Length < EMA 3 Length < EMA 4 Length
5. EMA Lengths 1, 2, 3, and 4 should be limited to about 1/4th the length of a full market cycle. Note, EMA lengths are measured in bars (candles), not in days. 1/4th of 1000 days is 250 days which is 250 x 4 = 1000 6-hr candles.
The following guidelines are provided based on results of over 100 backtests on the BTCUSD chart using randomized parameters †,
1. 9 days < Response Time 1 < 14 days
2. 5 days < EMA 1 Length < 100 days
3. 600 days < EMA 4 length < 1000 days
4. The ratio of the EMA range (EMA 4 len - EMA 1 len) to the sum of EMA lengths (EMA 1 len + EMA 2 len + ...) be greater than 0.4
5. The ratio of the sum of EMA 1 and EMA 2 lengths to the sum of EMA 3 and EMA 4 lengths be less than 0.3.
A suggestion from the author: Given that backtests show a high degree of outperformance using the guidelines enumerated above, a good trading strategy may be to not rely on any one particular combination of parameters. Rather, a random set of combinations of parameter settings that adhere to the guidelines above could be used to create multiple instances of the strategy in a TradingView chart, each of which varies by a small amount due to their unique parameter settings. The proportion of the entire set of strategy instances that agree about the current state of the market could indicate to the trader the level of confidence of the indicator, in aggregate.
† A sample dataset of backtest results using randomized parameters is available upon request; notably, all trials outperformed the intended market (Bitcoin).
7. General Remarks About the Indicator
Other than some exponential moving averages, no traditional technical indicators or technical analysis tools are employed in this strategy. No MACD, no RSI, no CMF, no Bollinger bands, parabolic SARs, Ichimoku clouds, hoosawatsits, XYZs, ABCs, whatarethese. No tea leaves can be found in this strategy, only mathematics. It is in the nature of the underlying math formula, from which the indicator is produced, to quickly identify trend changes.
8. Remarks About Expectations of Future Results and About Backtesting
8.1. In General
As it's been stated in many prospectuses and marketing literature, "past performance is no guarantee of future results." Backtest results are retrospective, and hindsight is 20/20. Therefore, no guarantee can, nor should, be expressed by me or anybody else who is selling a financial product (unless you have a money printer, like the Federal Reserve does).
8.2. Regarding This Strategy
No guarantee of future results using this strategy is expressed by the author, not now nor at any time in the future.
With that written, the author is free to express his own expectations and opinions based on his intimate knowledge of how the indicator works, and the author will take that liberty by writing the following: As described in section (7), this trading strategy does not include any traditional technical indicators or TA tools (other than smoothing EMAs). Instead, this strategy is based on a principle that does not change, it employs a complex indicator that is based on a math formula that does not change, and it places trades based on five simple rules that do not change. And, as described in section (2.1), the indicator is designed to capture the full character of the market, from a macro/global scope down to a micro/local scope. Additionally, as described in section (3), outperformance of the market for which this strategy was intended during backtesting does not depend on luckily setting the parameters "just right." In fact, all random combinations of parameter settings that followed the guidelines outperformed the intended market in backtests. Additionally, no parameters are included within the underlying math formula from which the indicator is produced; it is not as if the formula contains a "5" and future outperformance would depend on that "5" being a "6" instead. And, again as described, it is in the nature of the formula to quickly identify trend changes. Therefore, it is the opinion of the author that the outperformance of this strategy in backtesting is directly attributable to the fundamental nature of the math formula from which the indicator is produced. As such, it is also the opinion of the author that continued outperformance by using this strategy, applied to the crypto (Bitcoin) market, is likely, given that the parameter settings are set reasonably and in accordance with the guidelines. The author does not, however, expect future outperformance of this strategy to match or exceed the outperformance observed in backtests using the default parameters, i.e. it probably won't outperform by anything close to 13,000,000% during the next 9 years.
Additionally, based on the rolling 1-month outperformance data listed in section (3), expectations of short-term outperformance should be kept low; the median 1-month outperformance was -2%, so it's basically a 50/50 chance that any significant outperformance is seen in any given month. The true strength of this strategy is to be out of the market during large, sharp declines and capitalizing on the opportunities presented at the bottom of those declines by buying the dip. Given that such price action does not happen every month, outperformance in the initial months of use is approximately as likely as underperformance.
9. Access
Those who are interested in using this strategy may send a personal message to inquire about how to gain access. Those who are interested in acquiring the sample dataset of backtest results may send a personal message to request a copy of the data.
Buy The Dips - MA200 OptimisedThe strategy combines a contrarian approach (buying the dips) with a trend-following logic (only when the price is above the MA200)
The strategy seeks to find the best times when buying the dips on the asset should result to be more profitable.
The price above a long-term moving average indicates momentum that increases the possibility of profiting from buying the asset on short-term weakness.
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