Multiple MACD RSI simple strategySimple strategy script I've had for a while but looks like I never published.
Although it is one of my most simple it seems to have the best profitability. It is pretty rough though. the Stoch RSI has only a little weight to the trade trigger. I'll refine it more over time or you can by all means. Basically the Stoch RSI current K line has to be OVER 40 to trigger a SELL. It has no effect on buy side.
The triggers are roughly as follows:
Year - since so many assets have gone 2x, 3x, 10x+ since 2013 having a strategy that earns a 500% return from 2013 to now isn't that good if buy-and-holding would have got you 800%. This eliminates some of that noise and makes it a little easier to quickly gauge success. So buy/sell trigger need a value of greater or equal to 2018 (default)
MACD 1 - First MACD (short) needs to indicate greater than 0 to buy or less than 0 to sell.
MACD 2 - Same as MACD1 but for second MACD set (long)
Uptrend - Latest close + high divided by last periods close + high needs to be grater than 1. So if latest is 34.30 close and 34.60 high and previous interval is 34.80 close and 34.82 high, that is 0.99 and will not trigger a buy trade.
Downtrend - Same thing but close + low and less than 1.
This script/strategy is pretty rough but if there is interest I'll polish it more since it is a pretty solid but simple strategy for most assets.
In den Scripts nach "ha溢价率" suchen
Breakout/Consolidation Filter [jwammo12]This indicator acts as a filter for determining recent breakouts and consolidations in price.
The first way to use the indicator is with a short lookback period. It then will paint yellow most of the time, with red marking a sharp recent breakdown in price and green marking a sharp breakout in price. This can be used to follow the breakout, or to fade it.
The second way to use the indicator is a long lookback period. This will change the output to be colored most of the time, with small sections of yellow. The yellow indicators areas where price has not made a large move in a while, or periods of consolidation. This can then be used to plan reversal trades, or follows any new trend.
The blue line is a Average True Range Percent Rank, when this value is high, it means that breakouts are less likely to trigger, since price has been moving rapidly recently, and a relative breakout would have to be a large move. When the line is low, breakouts will trigger more easily, since price has been moving relatively slowly
Pullback Trading [Fhenry0331]The indicator is taken from Alexander Elders "Triple Screen System," minus using the Weekly MACD as a filter/trend. I believe waiting for the force index and the weekly MACD histogram to line-up is uber conservative and a trader will miss too many signals (In my opinion).
The indicator is for a pullback trader. A trader that waits for a trend to develop then enters on a pullback.
The indicator defines an uptrend start: as the 13 ema crossing above the 26 ema. It defines a downtrend start: as the 13 ema crossing below the 26 ema.
The pullback in an uptrend: 13 ema is above the 26 ema. Elders-Force-Index is below the zero line. Price low has crossed below the 13 ema (one can also say price closes below the 13 ema if they so wish).
The pullback in a downtrend: 13 ema is below the 26 ema. Elders-Force-Index is above the zero line. Price high has also crossed above the 13 ema.
Please note that the pullback signals do not necessitate an automatic buy or sell (the instrument can be still pulling back deeper and not ready to resume it's trend.) One should place orders above (long) or below (short) bars with the pullback signals. Do so on signals until orders are filled.
Although the indicator is meant for pullbacks one can make an aggressive entry at the onset of a crossover of ema's.
For clarity background colors has been added to the indicator.
works well on daily time frame. Also look at intraday (5) minute time frame on trending stocks (news, earnings, volume, etc.)
Keep It Simple.
Enjoy!
U&Dif price has moved up since 1 to 3 candles ago = buy
if price has moved down since 1 to 3 candles ago = sell
has internal SL & TP
tested on
BITFINEX:ETHUSD
BITFINEX:BTCUSD
BITFINEX:LTCUSD
BITFINEX:ETHBTC
4 hour charts
Net XRP Margin PositionTotal XRP Longs minus XRP Shorts in order to give you the total outstanding XRP margin debt.
ie: If 500,000 XRP has been longed, and 400,000 XRP has been shorted, then 500,000 has been bought, and 400,000 sold, leaving us with 100,000 XRP (net) remaining to be sold to give us an overall neutral margin position.
That isn't to say that the net margin position must move towards zero, but it is a sensible reference point, and historical net values may provide useful insights into the current circumstances.
[BoTo] Pump&Dump StrategyThis strategy uses only long positions. It isn't used short positions, it doesn't use marginal trade, it doesn't use a pyramiding.
It is strategy uses only one indicator. Ourselves have constructed the indicator for cryptocurrencies. We called it 'Pump&Dump Ocsilator'. You can read as this indicator works here:
Not usual stop
Strategy uses 2 ways for closing of an unprofitable position. But it is possible to use only one way.
Way 1: if the indicator has distinguished a dump, then the long position needs to be closed when the candle is closed (for an example: to close a position when time 00:00 if you have chosen daily timeframe)
Way 2: the user himself chooses the size in settings of this script. Percent. If the user has chosen 100%, means isn't used absolutely. Because the price will never fall by 100%. If the user has chosen less than 100%, for example 5%, then the long position needs to be closed if the low of a candle was less than this price level of choosed stop-loss. But the position needs to be closed too when the candle is closed.
Strategy
A pump-signal: if the candle green and her body is 3 times more than norm
A dump-signal: on the contrary, if the candle red and her body is 3 times more than norm
For opening of a long position: it is necessary any pump-signal (if the position hasn't been open yet)
For closing of a long position: several ways:
1) Or any dump-signal is necessary
2) Or a stop-loss which was chosen by the user is necessary
Net DASH Margin PositionTotal DASH Longs minus DASH Shorts in order to give you the total outstanding DASH margin debt.
ie: If 500,000 DASH has been longed, and 400,000 DASH has been shorted, then 500,000 has been bought, and 400,000 sold, leaving us with 100,000 DASH (net) remaining to be sold to give us an overall neutral margin position.
That isn't to say that the net margin position must move towards zero, but it is a sensible reference point, and historical net values may provide useful insights into the current circumstances.
(Anyone know what category this script should be in?)
Net EOS Margin PositionTotal EOS Longs minus EOS Shorts in order to give you the total outstanding EOS margin debt.
ie: If 5,000,000 EOS has been longed, and 4,000,000 EOS has been shorted, then 5,000,000 has been bought, and 4,000,000 sold, leaving us with 1,000,000 EOS (net) remaining to be sold to give us an overall neutral margin position.
That isn't to say that the net margin position must move towards zero, but it is a sensible reference point, and historical net values may provide useful insights into the current circumstances.
(Anyone know what category this script should be in?)
Net XMR Margin PositionTotal XMR Longs minus XMR Shorts in order to give you the total outstanding XMR margin debt.
ie: If 50,000 XMR has been longed, and 40,000 XMR has been shorted, then 50,000 has been bought, and 40,000 sold, leaving us with 10,000 XMR (net) remaining to be sold to give us an overall neutral margin position.
That isn't to say that the net margin position must move towards zero, but it is a sensible reference point, and historical net values may provide useful insights into the current circumstances.
Net NEO Margin PositionTotal NEO Longs minus NEO Shorts in order to give you the total outstanding NEO margin debt.
ie: If 500,000 NEO has been longed, and 400,000 NEO has been shorted, then 500,000 has been bought, and 400,000 sold, leaving us with 100,000 NEO (net) remaining to be sold to give us an overall neutral margin position.
That isn't to say that the net margin position must move towards zero, but it is a sensible reference point, and historical net values may provide useful insights into the current circumstances.
(Anyone know what category this script should be in?)
Inverse Fisher Transform on STOCHASTIC (modified graphics)Modified the graphic representation of the script from John Ehlers - From California, USA, he is a veteran trader. With 35 years trading experience he has seen it all. John has an engineering background that led to his technical approach to trading ignoring fundamental analysis (with one important exception). John strongly believes in cycles. He’d rather exit a trade when the cycle ends or a new one starts. He uses the MESA principle to make predictions about cycles in the market and trades one hundred percent automatically.
In the show John reveals:
• What is more appropriate than trading individual stocks
• The one thing he relies upon in his approach to the market
• The detail surrounding his unique trading style
• What important thing underpins the market and gives every trader an edge
About INVERSE FISHER TRANSFORM:
The purpose of technical indicators is to help with your timing decisions to buy or sell. Hopefully, the signals are clear and unequivocal. However, more often than not your decision to pull the trigger is accompanied by crossing your fingers. Even if you have placed only a few trades you know the drill. In this article I will show you a way to make your oscillator-type indicators make clear black-or-white indication of the time to buy or sell. I will do this by using the Inverse Fisher Transform to alter the Probability Distribution Function (PDF) of your indicators. In the past12 I have noted that the PDF of price and indicators do not have a Gaussian, or Normal, probability distribution. A Gaussian PDF is the familiar bell-shaped curve where the long “tails” mean that wide deviations from the mean occur with relatively low probability. The Fisher Transform can be applied to almost any normalized data set to make the resulting PDF nearly Gaussian, with the result that the turning points are sharply peaked and easy to identify. The Fisher Transform is defined by the equation
1)
Whereas the Fisher Transform is expansive, the Inverse Fisher Transform is compressive. The Inverse Fisher Transform is found by solving equation 1 for x in terms of y. The Inverse Fisher Transform is:
2)
The transfer response of the Inverse Fisher Transform is shown in Figure 1. If the input falls between –0.5 and +0.5, the output is nearly the same as the input. For larger absolute values (say, larger than 2), the output is compressed to be no larger than unity. The result of using the Inverse Fisher Transform is that the output has a very high probability of being either +1 or –1. This bipolar probability distribution makes the Inverse Fisher Transform ideal for generating an indicator that provides clear buy and sell signals.
Strenght and MomentumThe scope of this script is to measure momentum and strenght of EURO and DOLLAR using their indexes.
Forza (line) above 0 means EURO is stonger than DOLLAR
Momento (histogram) above 0 means EURO has a positive momentum against DOLLAR
The added value to see MACD and RSI directly on EURUSD chart is that indexes consider also other pairs so their RSI and MACD has a larger view on forex markets.
Script has also an option for multi timeframes.
I think that could be used as filters for LONG or SHORT positions in lower time frames.
XPloRR MA-Trailing-Stop StrategyXPloRR MA-Trailing-Stop Strategy
Long term MA-Trailing-Stop strategy with Adjustable Signal Strength to beat Buy&Hold strategy
None of the strategies that I tested can beat the long term Buy&Hold strategy. That's the reason why I wrote this strategy.
Purpose: beat Buy&Hold strategy with around 10 trades. 100% capitalize sold trade into new trade.
My buy strategy is triggered by the fast buy EMA (blue) crossing over the slow buy SMA curve (orange) and the fast buy EMA has a certain up strength.
My sell strategy is triggered by either one of these conditions:
the EMA(6) of the close value is crossing under the trailing stop value (green) or
the fast sell EMA (navy) is crossing under the slow sell SMA curve (red) and the fast sell EMA has a certain down strength.
The trailing stop value (green) is set to a multiple of the ATR(15) value.
ATR(15) is the SMA(15) value of the difference between the high and low values.
The scripts shows a lot of graphical information:
The close value is shown in light-green. When the close value is lower then the buy value, the close value is shown in light-red. This way it is possible to evaluate the virtual losses during the trade.
the trailing stop value is shown in dark-green. When the sell value is lower then the buy value, the last color of the trade will be red (best viewed when zoomed)(in the example, there are 2 trades that end in gain and 2 in loss (red line at end))
the EMA and SMA values for both buy and sell signals are shown as a line
the buy and sell(close) signals are labeled in blue
How to use this strategy?
Every stock has it's own "DNA", so first thing to do is tune the right parameters to get the best strategy values voor EMA , SMA, Strength for both buy and sell and the Trailing Stop (#ATR).
Look in the strategy tester overview to optimize the values Percent Profitable and Net Profit (using the strategy settings icon, you can increase/decrease the parameters)
Then keep using these parameters for future buy/sell signals only for that particular stock.
Do the same for other stocks.
Important : optimizing these parameters is no guarantee for future winning trades!
Here are the parameters:
Fast EMA Buy: buy trigger when Fast EMA Buy crosses over the Slow SMA Buy value (use values between 10-20)
Slow SMA Buy: buy trigger when Fast EMA Buy crosses over the Slow SMA Buy value (use values between 30-100)
Minimum Buy Strength: minimum upward trend value of the Fast SMA Buy value (directional coefficient)(use values between 0-120)
Fast EMA Sell: sell trigger when Fast EMA Sell crosses under the Slow SMA Sell value (use values between 10-20)
Slow SMA Sell: sell trigger when Fast EMA Sell crosses under the Slow SMA Sell value (use values between 30-100)
Minimum Sell Strength: minimum downward trend value of the Fast SMA Sell value (directional coefficient)(use values between 0-120)
Trailing Stop (#ATR): the trailing stop value as a multiple of the ATR(15) value (use values between 2-20)
Example parameters for different stocks (Start capital: 1000, Order=100% of equity, Period 1/1/2005 to now) compared to the Buy&Hold Strategy(=do nothing):
BEKB(Bekaert): EMA-Buy=12, SMA-Buy=44, Strength-Buy=65, EMA-Sell=12, SMA-Sell=55, Strength-Sell=120, Stop#ATR=20
NetProfit: 996%, #Trades: 6, %Profitable: 83%, Buy&HoldProfit: 78%
BAR(Barco): EMA-Buy=16, SMA-Buy=80, Strength-Buy=44, EMA-Sell=12, SMA-Sell=45, Strength-Sell=82, Stop#ATR=9
NetProfit: 385%, #Trades: 7, %Profitable: 71%, Buy&HoldProfit: 55%
AAPL(Apple): EMA-Buy=12, SMA-Buy=45, Strength-Buy=40, EMA-Sell=19, SMA-Sell=45, Strength-Sell=106, Stop#ATR=8
NetProfit: 6900%, #Trades: 7, %Profitable: 71%, Buy&HoldProfit: 2938%
TNET(Telenet): EMA-Buy=12, SMA-Buy=45, Strength-Buy=27, EMA-Sell=19, SMA-Sell=45, Strength-Sell=70, Stop#ATR=14
NetProfit: 129%, #Trade
Inverse Fisher Transform COMBO STO+RSI+CCIv2 by KIVANÇ fr3762A combined 3in1 version of pre shared INVERSE FISHER TRANSFORM indicators on RSI , on STOCHASTIC and on CCIv2 to provide space for 2 more indicators for users...
About John EHLERS:
From California, USA, John is a veteran trader. With 35 years trading experience he has seen it all. John has an engineering background that led to his technical approach to trading ignoring fundamental analysis (with one important exception).
John strongly believes in cycles. He’d rather exit a trade when the cycle ends or a new one starts. He uses the MESA principle to make predictions about cycles in the market and trades one hundred percent automatically.
In the show John reveals:
• What is more appropriate than trading individual stocks
• The one thing he relies upon in his approach to the market
• The detail surrounding his unique trading style
• What important thing underpins the market and gives every trader an edge
About INVERSE FISHER TRANSFORM:
The purpose of technical indicators is to help with your timing decisions to buy or
sell. Hopefully, the signals are clear and unequivocal. However, more often than
not your decision to pull the trigger is accompanied by crossing your fingers.
Even if you have placed only a few trades you know the drill.
In this article I will show you a way to make your oscillator-type indicators make
clear black-or-white indication of the time to buy or sell. I will do this by using the
Inverse Fisher Transform to alter the Probability Distribution Function ( PDF ) of
your indicators. In the past12 I have noted that the PDF of price and indicators do
not have a Gaussian, or Normal, probability distribution. A Gaussian PDF is the
familiar bell-shaped curve where the long “tails” mean that wide deviations from
the mean occur with relatively low probability. The Fisher Transform can be
applied to almost any normalized data set to make the resulting PDF nearly
Gaussian, with the result that the turning points are sharply peaked and easy to
identify. The Fisher Transform is defined by the equation
1)
Whereas the Fisher Transform is expansive, the Inverse Fisher Transform is
compressive. The Inverse Fisher Transform is found by solving equation 1 for x
in terms of y. The Inverse Fisher Transform is:
2)
The transfer response of the Inverse Fisher Transform is shown in Figure 1. If
the input falls between –0.5 and +0.5, the output is nearly the same as the input.
For larger absolute values (say, larger than 2), the output is compressed to be no
larger than unity . The result of using the Inverse Fisher Transform is that the
output has a very high probability of being either +1 or –1. This bipolar
probability distribution makes the Inverse Fisher Transform ideal for generating
an indicator that provides clear buy and sell signals.
Creator: John EHLERS
Inverse Fisher Transform on SMI (Stochastic Momentum Index)Inverse Fisher Transform on SMI (Stochastic Momentum Index)
About John EHLERS:
From California, USA, John is a veteran trader. With 35 years trading experience he has seen it all. John has an engineering background that led to his technical approach to trading ignoring fundamental analysis (with one important exception).
John strongly believes in cycles. He’d rather exit a trade when the cycle ends or a new one starts. He uses the MESA principle to make predictions about cycles in the market and trades one hundred percent automatically.
In the show John reveals:
• What is more appropriate than trading individual stocks
• The one thing he relies upon in his approach to the market
• The detail surrounding his unique trading style
• What important thing underpins the market and gives every trader an edge
About INVERSE FISHER TRANSFORM:
The purpose of technical indicators is to help with your timing decisions to buy or
sell. Hopefully, the signals are clear and unequivocal. However, more often than
not your decision to pull the trigger is accompanied by crossing your fingers.
Even if you have placed only a few trades you know the drill.
In this article I will show you a way to make your oscillator-type indicators make
clear black-or-white indication of the time to buy or sell. I will do this by using the
Inverse Fisher Transform to alter the Probability Distribution Function (PDF) of
your indicators. In the past12 I have noted that the PDF of price and indicators do
not have a Gaussian, or Normal, probability distribution. A Gaussian PDF is the
familiar bell-shaped curve where the long “tails” mean that wide deviations from
the mean occur with relatively low probability. The Fisher Transform can be
applied to almost any normalized data set to make the resulting PDF nearly
Gaussian, with the result that the turning points are sharply peaked and easy to
identify. The Fisher Transform is defined by the equation
1)
Whereas the Fisher Transform is expansive, the Inverse Fisher Transform is
compressive. The Inverse Fisher Transform is found by solving equation 1 for x
in terms of y. The Inverse Fisher Transform is:
2)
The transfer response of the Inverse Fisher Transform is shown in Figure 1. If
the input falls between –0.5 and +0.5, the output is nearly the same as the input.
For larger absolute values (say, larger than 2), the output is compressed to be no
larger than unity. The result of using the Inverse Fisher Transform is that the
output has a very high probability of being either +1 or –1. This bipolar
probability distribution makes the Inverse Fisher Transform ideal for generating
an indicator that provides clear buy and sell signals.
DepthHouse - Moving Average ChannelsThe indicator Moving Average Channels was created for experimental purposes due to the parabolic moves BTC has made in the recent past.
How it works:
The basis, or center line, is a standard moving average that is set by the user.
The bands are then a customizable percentage of the basis.
Which based on the settings, could serve as possible support and resistance.
DepthHouse – Moving Average Channels has been published for you all to see and try for yourselves.
Maybe this indicator has uses elsewhere? If you find something feel free to post it in the comments below!
If you like this indicator, please drop a like or comment!
They are very much appreciated!
Be sure to go to my profile and check out my other indicators!
OHLC Volatility Estimators by @Xel_arjonaDISCLAIMER:
The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets.
The embedded code and ideas within this work are FREELY AND PUBLICLY available on the Web for NON LUCRATIVE ACTIVITIES and must remain as is by Creative-Commons as TradingView's regulations. Any use, copy or re-use of this code should mention it's origin as it's authorship.
WARNING NOTICE!
THE INCLUDED FUNCTION MUST BE CONSIDERED AS DEBUGING CODE The models included in the function have been taken from openly sources on the web so they could have some errors as in the calculation scheme and/or in it's programatic scheme. Debugging are welcome.
WHAT'S THIS?
Here's a full collection of candle based (compressed tick) Volatility Estimators given as a function, openly available for free, it can print IMPLIED VOLATILITY by an external symbol ticker like INDEX:VIX.
Models included in the volatility calculation function:
CLOSE TO CLOSE: This is the classic estimator by rule, sometimes referred as HISTORICAL VOLATILITY and is the must common, accepted and widely used out there. Is based on traditional Standard Deviation method derived from the logarithm return of current close from yesterday's.
ELASTIC WEIGHTED MOVING AVERAGE: This estimator has been used by RiskMetriks®. It's calculation is based on an ElasticWeightedMovingAverage Standard Deviation method derived from the logarithm return of current close from yesterday's. It can be viewed or named as an EXPONENTIAL HISTORICAL VOLATILITY model.
PARKINSON'S: The Parkinson number, or High Low Range Volatility, developed by the physicist, Michael Parkinson, in 1980 aims to estimate the Volatility of returns for a random walk using the high and low in any particular period. IVolatility.com calculates daily Parkinson values. Prices are observed on a fixed time interval. n=10, 20, 30, 60, 90, 120, 150, 180 days.
ROGERS-SATCHELL: The Rogers-Satchell function is a volatility estimator that outperforms other estimators when the underlying follows a Geometric Brownian Motion (GBM) with a drift (historical data mean returns different from zero). As a result, it provides a better volatility estimation when the underlying is trending. However, this Rogers-Satchell estimator does not account for jumps in price (Gaps). It assumes no opening jump. The function uses the open, close, high, and low price series in its calculation and it has only one parameter, which is the period to use to estimate the volatility.
YANG-ZHANG: Yang and Zhang were the first to derive an historical volatility estimator that has a minimum estimation error, is independent of the drift, and independent of opening gaps. This estimator is maximally 14 times more efficient than the close-to-close estimator.
LOGARITHMIC GARMAN-KLASS: The former is a pinescript transcript of the model defined as in iVolatility . The metric used is a combination of the overnight, high/low and open/close range. Such a volatility metric is a more efficient measure of the degree of volatility during a given day. This metric is always positive.
Fractals and Levels by JustUncleLEven though there are a many other Fractal and Level indicators, this indicator has some unique features. The indicator will display Fractals, fractal levels and HH/LL points, they will only be drawn after they have completed. Also the indicator has options to :
Show Ideal Fractals Only.
Use Renko Style Fractals, where open/close values are used instead of high/low to find Fractals. This is used to show the correct Fractals when Renko Wicks are enabled.
Has an optional Filter to only display Fractals that are above/below a MA Ribbon.
References:
This code is based on Fractal Levels V8 by RicardoSantos
This is a Renko Chart with "Renko Style Fractals" enabled, notice that the wicks are ignored and only the true Bricks are used for Fractals:
Adaptive Donchian ChannelThis indicator adds a level of adaptivity to the simple Donchian Channel by adjusting the sensitivity (lookback periods) of the channel's upper and lower bounds based on the amount of time that has elapsed since the price has hit/expanded the channel boundaries. Comparing the results of this indicator to the standard Donchian Channel, the readier level of responsiveness may prove self-evident.
METHODOLOGY:
Specifically, the more recently the channel was expanded in one direction, the longer the lookback period grows in that direction. Conversely, if the channel has not been expanded in a given direction, the lookback period will contract so as to allow for a tighter channel.
For example, let the initial lookback period be 20 bars and let the factor argument be 0.1 (or 2 bars to start, as 20*0.1 = 2). Now say the current bar sets a new 20-period high. Then the lookback period for the upper bound is expanded by 2 bars to 22, and the lookback period for the lower bound is contracted by 2 bars to 18, thereby making it simultaneously harder to set new highs and easier to set new lows (and vice versa for hitting new lows). If neither a new high nor a new low is formed, both periods contract by the given factor.
Guth_3X_ConfirmThis indicator has three built in indicators based on the SMA of HIGH, SMA of LOW, and Stochastic. The baseline indicator is the retreats after departures from SMA of HIGH and LOW.
The first time a HIGH that is above the SMA HIGH has a lower HIGH but it still above the SMA HIGH, a (-) will appear at the bottom. This signals an aggressive entry point for potential coming downtrend. The second time the HIGH produces a lower high but is still above the SMA HIGH, a (S) will appear at the bottom which signals a more conservative entry point for potential coming downtrend. All of the opposite information is true of reversals beyond the SMA LOW.
When these reversals appear the same time the Stochastic is overbought or oversold, a red bar (overbought and potentially coming down) or a green bar (oversold and potentially coming up) will appear. NOTE: Aggressive symbols occur more often and will always occur when a conservative symbol appears. When a conservative indicator and respective overbought/oversold level occur at the same time, the bar is darker in color.
You can enter positions at any one of the indicators, however, the darker bars are what I look for. This has a high success rate but cannot guarantee results every time. I recommend adjusting the SMA, and Stoch parameters as well as time periods. I have had success with this indicator while day trading the 5, 10, 15, 30, 65 minute periods as well as daily and weekly periods. Every symbol traded can provide differing results based on the parameters used.
Please feel free to leave feedback and I know this can work well for you!
AlphaAlpha is a measure of the active return on an investment, the performance of that investment compared to the S&P500 index, where 0.01 = 1%
alpha < 0: the investment has earned too little for its risk (or, was too risky for the return)
alpha = 0: the investment has earned a return adequate for the risk taken
alpha > 0: the investment has a return in excess of the reward for the assumed risk
Mister Transistor 3.0This is a general purpose very flexible program to test the effectiveness of HA bars.
Please note that if you are charting at tradingview using Heikin-Ashi charting, your system will be trading fictitious prices even if you check the "use real prices" box. Thought you might like to know that before you lose all your money.
This program performs the HA calcs internally thus allowing you to use HA bars on a standard bar chart and obtaining real prices for your trades.
Courtesy of Boffin Hollow Lab
Author: Tarzan the Ape Man
Trailing Sharpe RatioThe Sharpe ratio allows you to see whether or not an investment has historically provided a return appropriate to its risk level. A Sharpe ratio above one is acceptable, above 2 is good, and above 3 is excellent. A Sharpe ratio less than one would indicate that an investment has not returned a high enough return to justify the risk of holding it. Interesting in this example, SPY's one year avg Sharpe ratio is above 3. This would mean on average SPY returns 3x better returns than the risk associated with holding it, implying there is some sort of underlying value to the investment.
When the sharpe ratio is above its signal, this implies the investment is currently outperforming compared to its typical return, below the signal means the investment is currently under performing. A negative Shape would mean that the investment has not provided a positive return, and may be a possible short candidate.
