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Noro's Trend MAs Strategy v2.3Don't use on pairs of type "crypto/crypto"! Only for pairs like "crypto/fiat" ("BTC/USD", "BTC/CNY", "ETH/USD", "ETH/CNY", etc) Trade strategy which uses only 2 MA. The slow MA (blue) is used for definition of a trend The fast MA (red) is used for an entrance to the transaction For: - For H1 - For crypto/fiat - Good for "BTC/USD", "ETH/USD" Recomended: Long = true (if it is profitable as a result of backtests) Short = true (if it is profitable as a result of backtests) Stops = false Stop, % = any Use Fast MA = true Fast MA Period = 5 Slow MA Period = 21 Bars Q = (2 for "bitcoin/fiat" or 1 for "crypto/fiat") Extreme = true (if "crypto/fiat") In the new version 2.3 + Dates
Strategia Pine Script®
di ROBO_Trading
1
Noro's Primitive Strategy v1.0It is calculated what long a candle body Average length of a body of a candle, for the last 30 candles is calculated If the candle red and a body of a candle is more average / 2 - to open long (and to close short) If long is open, a body of a candle is more average / 2, the candle green and a position is profitable - to close long If the candle green and a body of a candle is more average / 2 - to open short (and to close long) If it is open short, a body of a candle is more average / 2, the candle red and a position is profitable - to close short
Strategia Pine Script®
di ROBO_Trading
14
Noro's ColorBar Strategy v1.0It is calculated what long a candle body Average length of a body of a candle, for the last 30 candles is calculated If the candle red and a body of a candle is more average - to open long (and to close short) If long is open, the candle green and a position is profitable - to close long If the candle green and a body of a candle is more average - to open short (and to close long) If it is open short, the candle red and a position is profitable - to close short
Strategia Pine Script®
di ROBO_Trading
1
Noro's Trend MAs Strategy v2.0Don't use on pairs of type "crypto/crypto"! Only for pairs like "crypto/fiat" ("BTC/USD", "BTC/CNY", "ETH/USD", "ETH/CNY", etc) Trade strategy which uses only 2 MA. The slow MA (blue) is used for definition of a trend The fast MA (red) is used for an entrance to the transaction For: - For H1 - For crypto/fiat - Good for "BTC/USD", "ETH/USD" Recomended: Long = true (if it is profitable as a result of backtests) Short = true (if it is profitable as a result of backtests) Stops = false Stop, % = any OHLC4 = any Use Fast MA = true Fast MA Period = 5 Slow MA Period = 21 Bars Q = (2 for "bitcoin/fiat" or 1 for "crypto/fiat") Extreme = true (if "crypto/fiat") In the new version 2.0 - CryptoBottom is added
Strategia Pine Script®
di ROBO_Trading
23
Noro's Trend MAs Strategy v1.9 ExtremeExtreme version of Noro's Trend MAs strategy. Don't use on pairs of type "crypto/crypto"! Only for pairs like "crypto/fiat" ("BTC/USD", "BTC/CNY", "ETH/USD", "ETH/CNY", etc) Trade strategy which uses only 2 MA. The slow MA (blue) is used for definition of a trend The fast MA (red) is used for an entrance to the transaction For: - For H1 - For crypto/fiat - Good for "BTC/USD", "ETH/USD" Recomended: Long = true (if it is profitable as a result of backtests) Short = true (if it is profitable as a result of backtests) Stops = false Stop, % = any OHLC4 = any Use Fast MA = true Fast MA Period = 5 Slow MA Period = 21 Bars Q = (2 for "bitcoin/fiat" or 1 for "crypto/fiat") Extreme = true (if "crypto/fiat") In the new version 1.9 - Extreme is added
Strategia Pine Script®
di ROBO_Trading
2
Noro's Trend MAs Strategy v1.8Trade strategy which uses only 2 MA. The slow MA (blue) is used for definition of a trend The fast MA (red) is used for an entrance to the transaction For: - For H1 - For crypto/fiat or crypto/crypto - Good for "BTC/USD", "ETH/USD", "ETH/BTC" Recomended: Long = true (if it is profitable as a result of backtests) Short = true (if it is profitable as a result of backtests) Stops = false Stop, % = any OHLC4 = any Use Fast MA = true Fast MA Period = 5 Slow MA Period = 21 Bars Q = (2 for "bitcoin/fiat" or 1 for "crypto/fiat" or 0 for "crypto/crypto") In the new version 1.8 - The second PriceChannel is added - Profit became more - Losses became less - The unnecessary types of MA are removed
Strategia Pine Script®
di ROBO_Trading
Noro's Trend MAs Strategy v1.7Trade strategy which uses only 2 MA. The slow MA (blue) is used for definition of a trend The fast MA (red) is used for an entrance to the transaction For: - For H1 - For crypto/fiat Recomended: Long = true (if it is profitable as a result of backtests) Short = true (if it is profitable as a result of backtests) Stops = false Stop, % = any Type of slow MA = 7 (only for Crypto/Fiat) Source of slow MA = close or OHLC4 Use Fast MA = true Fast MA Period = 5 Slow MA Period = 20 Bars Q = (2 for "BitCoin/Fiat" or 1 for "Fork/Fiat") In the new version 1.7 + stoporders + entry arrow (black) Types of slow MA: 1 = SMA = Simple Moving Average 2 = EMA = Exponential Moving Average 3 = VWMA = Volume-Weighted Moving Average 4 = DEMA = Double Exponential Moving Average 5 = TEMA = Triple Exponential Moving Average 6 = KAMA = Kaufman's Adaptive Moving Average 7 = Price Channel
Strategia Pine Script®
di ROBO_Trading
Noro's Trend MAs Strategy v1.6Trade strategy which uses only 2 MA. The slow MA (blue) is used for definition of a trend The fast MA (red) is used for an entrance to the transaction For: - For H1 - For crypto/fiat Recomended: Long = true (if it is profitable as a result of backtests) Short = true (if it is profitable as a result of backtests) Type of slow MA = 7 (only for Crypto/Fiat) Source of slow MA = close or OHLC4 Use Fast MA = true Fast MA Period = 5 Slow MA Period = 20 Bars Q = (2 for "BitCoin/Fiat" or 1 for "Fork/Fiat") In the new version 1.5 + Profit became more + Losses became less + Alerts + Background (lime = uptrend, red = downtrend) Types of slow MA: 1 = SMA = Simple Moving Average 2 = EMA = Exponential Moving Average 3 = VWMA = Volume-Weighted Moving Average 4 = DEMA = Double Exponential Moving Average 5 = TEMA = Triple Exponential Moving Average 6 = KAMA = Kaufman's Adaptive Moving Average 7 = Price Channel
Strategia Pine Script®
di ROBO_Trading
4
Noro's Trend MAs Strategy 1.5Trade strategy which uses only 2 MA . The slow MA (blue) is used for definition of a trend The fast MA (red) is used for an entrance to the transaction For: - For H1 - For crypto/fiat Recomended: Long = true (if it is profitable as a result of backtests) Short = true (if it is profitable as a result of backtests) Type of slow MA = 7 (only for Crypto/Fiat) Source of slow MA = clole or OHLC4 Use Fast MA = true Fast MA Period = 5 Slow MA Period = 20 Bars Q = (2 for "BitCoin/Fiat" or 1 for "Fork/Fiat") In the new version 1.5 + Source + Types of slow MA Types of slow MA: 1 = SMA = Simple Moving Average 2 = EMA = Exponential Moving Average 3 = VWMA = Volume-Weighted Moving Average 4 = DEMA = Double Exponential Moving Average 5 = TEMA = Triple Exponential Moving Average 6 = KAMA = Kaufman's Adaptive Moving Average 7 = Price Channel PS: 100000000%, because of use of a piramiding have turned out
Strategia Pine Script®
di ROBO_Trading
Noro's Trend SMA Strategy v1.4Trade strategy which uses only 2 SMA . The slow SMA (blue) is used for definition of a trend The fast SMA (red) is used for an entrance to the transaction Recomended: For H1 For crypto/fiat Long = true (if it is profitable as a result of backtests) Short = true (if it is profitable as a result of backtests) Use Fast SMA = true Fast SMA Period = 5 Slow SMA Period = 20 Bars = (2 for "BitCoin/Fiat" or 1 for "Fork/Fiat") In the new version 1.4 - Parameters are added Russian: Перевожу на понятный. В новой версии 1.4 ничего не поменялось в логике, работает так же. Но добавлены новые параметры, можно поэкспериментировать с настройками, убедиться как что выгоднее. Есть галка лонг и шорт. По умолчанию обе включены. Если убрать галку лонг, то исчезнут лонги вообще, если убрать шорт, то соответственно исчезнут шорты. По идее галку надо будет снимать если стратегия создает убыточные шорты, то их можно отключить. Смотреть в сводке показателей тестера стратегий профитны они или нет. По идее почти на всех парах крипто/фиат лучше ставить обе галки. Или убирайте галку шорт если не хотите шортить из религиозных соображений. Добавлена галка отключающая быструю SMA. То есть если галку убрать то стратегия будет её игнорировать. Таким образом, параметр Fast SMA (который 5) перестанет влиять на результаты. Однако, скорее всего без этой галки станет только хуже. Но можете проверить. Позволяет убедиться что входить в сделку по быстрой SMA в среднем немного профитнее, чем входить где попало. "Bars" - количество свечек одного цвета после после которых будет открываться сделка. По умолчанию 2. Можно от 0 до 3 ставить. Если 0 то цвет свечек игнорируется. Если 3, значит будет ждать 3 красных свечи подряд чтобы открыть лонг. Так же и с зелеными свечами для шорта. 2 - оптимально для пар типа биткойн/фиат. А для пар типа форк/фиат лучше ставить 1 свеча в параметре "Bars".
Strategia Pine Script®
di ROBO_Trading
7
CCI Level Zero Strategy (by Marcoweb) v1.0Hi guys, My strategy is ready :) Finally the zero level of the CCI gives the start and stop to my positions. As you could notice, setting up the CCI length to 340 area on 1 minute chart will let the profit factor go up to 20% from an already wonderful 16%. This is a great result cause will let profitable trades run while stopping the wrong ones with a very limited loss. What makes our profit are not several small little positions that are clearly unrepitable in real trade but few and very profitable positions in which jumping in will be easier due to their length (71 bars average). Please share with me your impressions and suggestions. Have a nice trade :)
Strategia Pine Script®
di Intuitrading
3
I_Heikin Ashi CandleWhen apply a strategy to Heikin Ashi Candle chart (HA candle), the strategy will use the open/close/high/low values of the Heikin Ashi candle to calculate the Profit and Loss, hence also affecting the Percent Profitable, Profit Factor, etc., often resulting a unrealistic high Percent Profitable and Profit Factor, which is misleading. But if you want to use the HA candle's values to calculate your indicator / strategy, but pass the normal candle's open/close/high/low values to the strategy to calculate the Profit / Loss, you can do this: 1) set up the main chart to be a normal candle chart 2) use this indicator script to plot a secondary window with indicator looks exactly like a HA-chart 3) to use the HA-candle's open/close/high/low value to calculate whatever indicator you want (you may need to create a separate script if you want to plot this indicator in a separate indicator window)
Indicatore Pine Script®
di samtsui
14
MACDouble + RSI (rec. 15min-2hr intrv) Uses two sets of MACD plus an RSI to either long or short. All three indicators trigger buy/sell as one (ie it's not 'IF MACD1 OR MACD2 OR RSI > 1 = buy", its more like "IF 1 AND 2 AND RSI=buy", all 3 match required for trigger) The MACD inputs should be tweaked depending on timeframe and what you are trading. If you are doing 1, 3, 5 min or real frequent trading then 21/44/20 and 32/66/29 or other high value MACDs should be considered. If you are doing longer intervals like 2, 3, 4hr then consider 9/19/9 and 21/44/20 for MACDs (experiment! I picked these example #s randomly). Ideal usage for the MACD sets is to have MACD2 inputs at around 1.5x, 2x, or 3x MACD1's inputs. Other settings to consider: try having fastlength1=macdlength1 and then (fastlength2 = macdlength2 - 2). Like 10/26/10 and 23/48/20. This seems to increase net profit since it is more likely to trigger before major price moves, but may decrease profitable trade %. Conversely, consider FL1=MCDL1 and FL2 = MCDL2 + (FL2 * 0.5). Example: 10/26/10 and 22/48/30 this can increase profitable trade %, though may cost some net profit. Feel free to message me with suggestions or questions.
Strategia Pine Script®
di RyanMartin
6
SPY Master v1.0This is a simple swing trading algorithm that uses a fast RSI-EMA to trigger buy/cover signals and a slow RSI-EMA to trigger sell/short signals for SPY, an xchange-traded fund for the S&P 500. The idea behind this strategy follows the premise that most profitable momentum trades usually occur during periods when price is trending up or down. Periods of flat price actions are usually where most unprofitable trades occur. Because we cannot predict exactly when trending periods will occur, the algorithm basically bets money on all trade opportunities during all market conditions. Despite an accuracy rate of only 40%, the algorithm's asymmetric risk/reward profile allows the average winner to be 2x the average loser. The end result is a positive (profitable) net payout. TRADING RULES: Buy/Cover = EMA3(RSI2) cross> 50 Sell/Short = EMA5(RSI2) cross< 50 BACKTEST SETTINGS: - Period = March 2011 - Present - Initial capital = $10,000 - Dividends excluded - Trading costs excluded PERFORMANCE COMPARISON: There are 657 trades, which means 1,314 orders. Assuming each order costs $2 (what I pay for at Interactive Brokers), total trading costs should be $2,628. -SPY (buy & hold) = 132.73 ---> 193.22 = +45.57% (dividends excluded) -SPY Master v1.0 = $12,649 - $2,628 = $10,021 = +100.21% DISCLAIMER: None of my ideas and posts are investment advice. Past performance is not an indication of future results. This strategy was constructed with the benefit of hindsight and its future performance cannot be guaranteed.
Strategia Pine Script®
di Stable_Camel
5
BACKTEST SCRIPT 0.999 ALPHATRADINGVIEW BACKTEST SCRIPT by Lionshare (c) 2015 THS IS A REAL ALTERNATIVE FOR LONG AWAITED TV NATIVE BACKTEST ENGINE. READY FOR USE JUST RIGHT NOW. For user provided trading strategy, executes the trades on pricedata history and continues to make it over live datafeed. Calculates and (plots on premise) the next performance statistics: profit - i.e. gross profit/loss. profit_max - maximum value of gross profit/loss. profit_per_trade - each trade's profit/loss. profit_per_stop_trade - profit/loss per "stop order" trade. profit_stop - gross profit/loss caused by stop orders. profit_stop_p - percentage of "stop orders" profit/loss in gross profit/loss. security_if_bought_back - size of security portfolio if bought back. trades_count_conseq_profit - consecutive gain from profitable series. trades_count_conseq_profit_max - maxmimum gain from consecutive profitable series achieved. trades_count_conseq_loss - same as for profit, but for loss. trades_count_conseq_loss_max - same as for profit, but for loss. trades_count_conseq_won - number of trades, that were won consecutively. trades_count_conseq_won_max - maximum number of trades, won consecutively. trades_count_conseq_lost - same as for won trades, but for lost. trades_count_conseq_lost_max - same as for won trades, but for lost. drawdown - difference between local equity highs and lows. profit_factor - profit-t-loss ratio. profit_factor_r - profit(without biggest winning trade)-to-loss ratio. recovery_factor - equity-to-drawdown ratio. expected_value - median gain value of all wins and loss. zscore - shows how much your seriality of consecutive wins/loss diverges from the one of normal distributed process. valued in sigmas. zscore of +3 or -3 sigmas means nonrandom realitonship of wins series-to-loss series. confidence_limit - the limit of confidence in zscore result. values under 0.95 are considered inconclusive. sharpe - sharpe ratio - shows the level of strategy stability. basically it is how the profit/loss is deviated around the expected value. sortino - the same as sharpe, but is calculated over the negative gains. k - Kelly criterion value, means the percentage of your portfolio, you can trade the scripted strategy for optimal risk management. k_margin - Kelly criterion recalculated to be meant as optimal margin value. DISCLAIMER : The SCRIPT is in ALPHA stage. So there could be some hidden bugs. Though the basic functionality seems to work fine. Initial documentation is not detailed. There could be english grammar mistakes also. NOW Working hard on optimizing the script. Seems, some heavier strategies (especially those using the multiple SECURITY functions) call TV processing power limitation errors. Docs are here: docs.google.com
Indicatore Pine Script®
di lionshare
61
CM Stochastic POP Method 1 - Jake Bernstein_V1A good friend ucsgears recently published a Stochastic Pop Indicator designed by Jake Bernstein with a modified version he found. I spoke to Jake this morning and asked if he had any updates to his Stochastic POP Trading Method. Attached is a PDF Jake published a while back (Please read for basic rules, which also Includes a New Method). I will release the Additional Method Tomorrow. Jake asked me to share that he has Updated this Method Recently. Now across all symbols he has found the Stochastic Values of 60 and 30 to be the most profitable. NOTE - This can be Significantly Optimized for certain Symbols/Markets. Jake Bernstein will be a contributor on TradingView when Backtesting/Strategies are released. Jake is one of the Top Trading System Developers in the world with 45+ years experience and he is going to teach how to create Trading Systems and how to Optimize the correct way. Below are a few Strategy Results....Soon You Will Be Able To Find Results Like This Yourself on TradingView.com BackTesting Results Example: EUR-USD Daily Chart Since 01/01/2005 Strategy 1: Go Long When Stochastic Crosses Above 60. Go Short When Stochastic Crosses Below 30. Exit Long/Short When Stochastic has a Reverse Cross of Entry Value. Results: Total Trades = 164 Profit = 50, 126 Pips Win% = 38.4% Profit Factor = 1.35 Avg Trade = 306 Pips Profit ***Most Consecutive Wins = 3 ... Most Consecutive Losses = 6 Strategy 2: Rules - Proprietary Optimization Jake Will Teach. Only Added 1 Additional Exit Rule. Results: Total Trades = 164 Profit = 62, 876 Pips!!! Win% = 38.4% Profit Factor = 1.44 Avg Trade = 383 Pips Profit ***Most Consecutive Wins = 3 ... Most Consecutive Losses = 6 Strategy 3: Rules - Proprietary Optimization Jake Will Teach. Only added 1 Additional Exit Rule. Results: Winning Percent Increases to 72.6%!!! , Same Amount of Trades. ***Most Consecutive Wins = 21 ...Most Consecutive Losses = 4 Indicator Includes: -Ability to Color Candles (CheckBox In Inputs Tab) Green = Long Trade Blue = No Trade Red = Short Trade -Color Coded Stochastic Line based on being Above/Below or In Between Entry Lines. Link To Jakes PDF with Rules dl.dropboxusercontent.com
Indicatore Pine Script®
di ChrisMoody
44
Vervoort Heiken Ashi Candlestick OscillatorHeiken-Ashi Candlestick Oscillator (HACO), by Sylvian Vervoort, is a digital oscillator version of the colored candlesticks. Explanation from Vervoort: "HACO is not meant to be an automatic trading system, so when there is a buy or sell signal from HACO, make sure it is confirmed by other TA techniques. HACO will certainly aid in signaling buy/sell opportunities and help you hold on to a trade, making it more profitable. The behavior of HACO is closely related to the level and speed of price change. It can be used on charts of any time frame ranging from intraday to monthly." HACO has 2 configurable length parameters - "UP TEMA length" and "Down TEMA length". Vervoort suggests having them the same value. I have also added an option to color the bars (overlay mode). More info: Trading with the Heiken-Ashi Candlestick Oscillator - Sylvian Vervoort List of my other indicators: - GDoc: docs.google.com - Chart:
Indicatore Pine Script®
di LazyBear
20
DEnvelope [Better Bollinger Bands]*** *** Bollinger Bands (BB) usually expand quickly after a volatility increase but contract more slowly as volatility declines. This extended time it takes for BB to contract after a volatility drop can make trading some instruments using BB alone difficult or less profitable. In the October 1998 issue of "Futures" there is an article written by Dennis McNicholl called "Better Bollinger Bands", in which the author recommends improving BB by modifying: - the center line formula & - different equations for calculating the bands. These bands, called "DEnvelope", follow price more closely and respond faster to changes in volatility with these modifications. Fore more indicators, check out my "Master Index of indicators" (Also check my published charts page for new ones I haven't added to that list): More scripts related to DEnvelope: ------------------------------------------------ - DEnvelope Bandwidth: pastebin.com - DEnvelope %B : pastebin.com Sample chart with above indicators: www.tradingview.com
Indicatore Pine Script®
di LazyBear
18
Quad Rotation - StochasticThis Indicator is a step up from the Triad Rotation Indicator previously made, as it has 4 Stochastic signals rather then 3. It can be used mainly to identify potential reversal periods. If the Instrument becomes overbought, or oversold with all 4 stochastics a horizontal highlight will appear, either green or red. Green indicates the instrument is oversold, and may reverse soon, meaning you should take a buying positions, and red indicates an overbought position, where you may want to sell due to a reversal downward. Additionally, you can set an alarm if all 4 stochastic indicators signal overbought or oversold. This will help reduce your need to watch each instrument, and reduce the likelihood of overtrading. If you have comments regarding this indicator, if you found it helpful, or would like other improvements feel free to email me. If you are looking for other custom indicators, also feel free to email me. Email: thejak77@aol.com. This is an email rarely monitored, so please be patient, thank you! All the best, and stay profitable!
Indicatore Pine Script®
di EmberJaxx77
Quantum Edge Pro - Adaptive AICategorical Market Morphisms (CMM) - Where Abstract Algebra Transcends Reality A Revolutionary Application of Category Theory and Homotopy Type Theory to Financial Markets Bridging Pure Mathematics and Market Analysis Through Functorial Dynamics Theoretical Foundation: The Mathematical Revolution Traditional technical analysis operates on Euclidean geometry and classical statistics. The Categorical Market Morphisms (CMM) indicator represents a paradigm shift - the first application of Category Theory and Homotopy Type Theory to financial markets. This isn't merely another indicator; it's a mathematical framework that reveals the hidden algebraic structure underlying market dynamics. Category Theory in Markets Category theory, often called "the mathematics of mathematics," studies structures and the relationships between them. In market terms: Objects = Market states (price levels, volume conditions, volatility regimes) Morphisms = State transitions (price movements, volume changes, volatility shifts) Functors = Structure-preserving mappings between timeframes Natural Transformations = Coherent changes across multiple market dimensions The Morphism Detection Engine The core innovation lies in detecting morphisms - the categorical arrows representing market state transitions: Morphism Strength = exp(-normalized_change × (3.0 / sensitivity)) Threshold = 0.3 - (sensitivity - 1.0) × 0.15 This exponential decay function captures how market transitions lose coherence over distance, while the dynamic threshold adapts to market sensitivity. Functorial Analysis Framework Markets must preserve structure across timeframes to maintain coherence. Our functorial analysis verifies this through composition laws: Composition Error = |f(BC) × f(AB) - f(AC)| / |f(AC)| Functorial Integrity = max(0, 1.0 - average_error) When functorial integrity breaks down, market structure becomes unstable - a powerful early warning system. Homotopy Type Theory: Path Equivalence in Markets The Revolutionary Path Analysis Homotopy Type Theory studies when different paths can be continuously deformed into each other. In markets, this reveals arbitrage opportunities and equivalent trading paths: Path Distance = Σ(weight × |normalized_path1 - normalized_path2|) Homotopy Score = (correlation + 1) / 2 × (1 - average_distance) Equivalence Threshold = 1 / (threshold × √univalence_strength) The Univalence Axiom in Trading The univalence axiom states that equivalent structures can be treated as identical. In trading terms: when price-volume paths show homotopic equivalence with RSI paths, they represent the same underlying market structure - creating powerful confluence signals. Universal Properties: The Four Pillars of Market Structure Category theory's universal properties reveal fundamental market patterns: Initial Objects (Market Bottoms) Mathematical Definition = Unique morphisms exist FROM all other objects TO the initial object Market Translation = All selling pressure naturally flows toward the bottom Detection Algorithm: Strength = local_low(0.3) + oversold(0.2) + volume_surge(0.2) + momentum_reversal(0.2) + morphism_flow(0.1) Signal = strength > 0.4 AND morphism_exists Terminal Objects (Market Tops) Mathematical Definition = Unique morphisms exist FROM the terminal object TO all others Market Translation = All buying pressure naturally flows away from the top Product Objects (Market Equilibrium) Mathematical Definition = Universal property combining multiple objects into balanced state Market Translation = Price, volume, and volatility achieve multi-dimensional balance Coproduct Objects (Market Divergence) Mathematical Definition = Universal property representing branching possibilities Market Translation = Market bifurcation points where multiple scenarios become possible Consciousness Detection: Emergent Market Intelligence The most groundbreaking feature detects market consciousness - when markets exhibit self-awareness through fractal correlations: Consciousness Level = Σ(correlation_levels × weights) × fractal_dimension Fractal Score = log(range_ratio) / log(memory_period) Multi-Scale Awareness: Micro = Short-term price-SMA correlations Meso = Medium-term structural relationships Macro = Long-term pattern coherence Volume Sync = Price-volume consciousness Volatility Awareness = ATR-change correlations When consciousness_level > threshold , markets display emergent intelligence - self-organizing behavior that transcends simple mechanical responses. Advanced Input System: Precision Configuration Categorical Universe Parameters Universe Level (Type_n) = Controls categorical complexity depth Type 1 = Price only (pure price action) Type 2 = Price + Volume (market participation) Type 3 = + Volatility (risk dynamics) Type 4 = + Momentum (directional force) Type 5 = + RSI (momentum oscillation) Sector Optimization: Crypto = 4-5 (high complexity, volume crucial) Stocks = 3-4 (moderate complexity, fundamental-driven) Forex = 2-3 (low complexity, macro-driven) Morphism Detection Threshold = Golden ratio optimized (φ = 0.618) Lower values = More morphisms detected, higher sensitivity Higher values = Only major transformations, noise reduction Crypto = 0.382-0.618 (high volatility accommodation) Stocks = 0.618-1.0 (balanced detection) Forex = 1.0-1.618 (macro-focused) Functoriality Tolerance = φ⁻² = 0.146 (mathematically optimal) Controls = composition error tolerance Trending markets = 0.1-0.2 (strict structure preservation) Ranging markets = 0.2-0.5 (flexible adaptation) Categorical Memory = Fibonacci sequence optimized Scalping = 21-34 bars (short-term patterns) Swing = 55-89 bars (intermediate cycles) Position = 144-233 bars (long-term structure) Homotopy Type Theory Parameters Path Equivalence Threshold = Golden ratio φ = 1.618 Volatile markets = 2.0-2.618 (accommodate noise) Normal conditions = 1.618 (balanced) Stable markets = 0.786-1.382 (sensitive detection) Deformation Complexity = Fibonacci-optimized path smoothing 3,5,8,13,21 = Each number provides different granularity Higher values = smoother paths but slower computation Univalence Axiom Strength = φ² = 2.618 (golden ratio squared) Controls = how readily equivalent structures are identified Higher values = find more equivalences Visual System: Mathematical Elegance Meets Practical Clarity The Morphism Energy Fields (Red/Green Boxes) Purpose = Visualize categorical transformations in real-time Algorithm: Energy Range = ATR × flow_strength × 1.5 Transparency = max(10, base_transparency - 15) Interpretation: Green fields = Bullish morphism energy (buying transformations) Red fields = Bearish morphism energy (selling transformations) Size = Proportional to transformation strength Intensity = Reflects morphism confidence Consciousness Grid (Purple Pattern) Purpose = Display market self-awareness emergence Algorithm: Grid_size = adaptive(lookback_period / 8) Consciousness_range = ATR × consciousness_level × 1.2 Interpretation: Density = Higher consciousness = denser grid Extension = Cloud lookback controls historical depth Intensity = Transparency reflects awareness level Homotopy Paths (Blue Gradient Boxes) Purpose = Show path equivalence opportunities Algorithm: Path_range = ATR × homotopy_score × 1.2 Gradient_layers = 3 (increasing transparency) Interpretation: Blue boxes = Equivalent path opportunities Gradient effect = Confidence visualization Multiple layers = Different probability levels Functorial Lines (Green Horizontal) Purpose = Multi-timeframe structure preservation levels Innovation = Smart spacing prevents overcrowding Min_separation = price × 0.001 (0.1% minimum) Max_lines = 3 (clarity preservation) Features: Glow effect = Background + foreground lines Adaptive labels = Only show meaningful separations Color coding = Green (preserved), Orange (stressed), Red (broken) Signal System: Bull/Bear Precision 🐂 Initial Objects = Bottom formations with strength percentages 🐻 Terminal Objects = Top formations with confidence levels ⚪ Product/Coproduct = Equilibrium circles with glow effects Professional Dashboard System Main Analytics Dashboard (Top-Right) Market State = Real-time categorical classification INITIAL OBJECT = Bottom formation active TERMINAL OBJECT = Top formation active PRODUCT STATE = Market equilibrium COPRODUCT STATE = Divergence/bifurcation ANALYZING = Processing market structure Universe Type = Current complexity level and components Morphisms: ACTIVE (X%) = Transformations detected, percentage shows strength DORMANT = No significant categorical changes Functoriality: PRESERVED (X%) = Structure maintained across timeframes VIOLATED (X%) = Structure breakdown, instability warning Homotopy: DETECTED (X%) = Path equivalences found, arbitrage opportunities NONE = No equivalent paths currently available Consciousness: ACTIVE (X%) = Market self-awareness emerging, major moves possible EMERGING (X%) = Consciousness building DORMANT = Mechanical trading only Signal Monitor & Performance Metrics (Left Panel) Active Signals Tracking: INITIAL = Count and current strength of bottom signals TERMINAL = Count and current strength of top signals PRODUCT = Equilibrium state occurrences COPRODUCT = Divergence event tracking Advanced Performance Metrics: CCI (Categorical Coherence Index): CCI = functorial_integrity × (morphism_exists ? 1.0 : 0.5) STRONG (>0.7) = High structural coherence MODERATE (0.4-0.7) = Adequate coherence WEAK (<0.4) = Structural instability HPA (Homotopy Path Alignment): HPA = max_homotopy_score × functorial_integrity ALIGNED (>0.6) = Strong path equivalences PARTIAL (0.3-0.6) = Some equivalences WEAK (<0.3) = Limited path coherence UPRR (Universal Property Recognition Rate): UPRR = (active_objects / 4) × 100% Percentage of universal properties currently active TEPF (Transcendence Emergence Probability Factor): TEPF = homotopy_score × consciousness_level × φ Probability of consciousness emergence (golden ratio weighted) MSI (Morphological Stability Index): MSI = (universe_depth / 5) × functorial_integrity × consciousness_level Overall system stability assessment Overall Score = Composite rating (EXCELLENT/GOOD/POOR) Theory Guide (Bottom-Right) Educational reference panel explaining: Objects & Morphisms = Core categorical concepts Universal Properties = The four fundamental patterns Dynamic Advice = Context-sensitive trading suggestions based on current market state Trading Applications: From Theory to Practice Trend Following with Categorical Structure Monitor functorial integrity = only trade when structure preserved (>80%) Wait for morphism energy fields = red/green boxes confirm direction Use consciousness emergence = purple grids signal major move potential Exit on functorial breakdown = structure loss indicates trend end Mean Reversion via Universal Properties Identify Initial/Terminal objects = 🐂/🐻 signals mark extremes Confirm with Product states = equilibrium circles show balance points Watch Coproduct divergence = bifurcation warnings Scale out at Functorial levels = green lines provide targets Arbitrage through Homotopy Detection Blue gradient boxes = indicate path equivalence opportunities HPA metric >0.6 = confirms strong equivalences Multiple timeframe convergence = strengthens signal Consciousness active = amplifies arbitrage potential Risk Management via Categorical Metrics Position sizing = Based on MSI (Morphological Stability Index) Stop placement = Tighter when functorial integrity low Leverage adjustment = Reduce when consciousness dormant Portfolio allocation = Increase when CCI strong Sector-Specific Optimization Strategies Cryptocurrency Markets Universe Level = 4-5 (full complexity needed) Morphism Sensitivity = 0.382-0.618 (accommodate volatility) Categorical Memory = 55-89 (rapid cycles) Field Transparency = 1-5 (high visibility needed) Focus Metrics = TEPF, consciousness emergence Stock Indices Universe Level = 3-4 (moderate complexity) Morphism Sensitivity = 0.618-1.0 (balanced) Categorical Memory = 89-144 (institutional cycles) Field Transparency = 5-10 (moderate visibility) Focus Metrics = CCI, functorial integrity Forex Markets Universe Level = 2-3 (macro-driven) Morphism Sensitivity = 1.0-1.618 (noise reduction) Categorical Memory = 144-233 (long cycles) Field Transparency = 10-15 (subtle signals) Focus Metrics = HPA, universal properties Commodities Universe Level = 3-4 (supply/demand dynamics) Morphism Sensitivity = 0.618-1.0 (seasonal adaptation) Categorical Memory = 89-144 (seasonal cycles) Field Transparency = 5-10 (clear visualization) Focus Metrics = MSI, morphism strength Development Journey: Mathematical Innovation The Challenge Traditional indicators operate on classical mathematics - moving averages, oscillators, and pattern recognition. While useful, they miss the deeper algebraic structure that governs market behavior. Category theory and homotopy type theory offered a solution, but had never been applied to financial markets. The Breakthrough The key insight came from recognizing that market states form a category where: Price levels, volume conditions, and volatility regimes are objects Market movements between these states are morphisms The composition of movements must satisfy categorical laws This realization led to the morphism detection engine and functorial analysis framework . Implementation Challenges Computational Complexity = Category theory calculations are intensive Real-time Performance = Markets don't wait for mathematical perfection Visual Clarity = How to display abstract mathematics clearly Signal Quality = Balancing mathematical purity with practical utility User Accessibility = Making PhD-level math tradeable The Solution After months of optimization, we achieved: Efficient algorithms = using pre-calculated values and smart caching Real-time performance = through optimized Pine Script implementation Elegant visualization = that makes complex theory instantly comprehensible High-quality signals = with built-in noise reduction and cooldown systems Professional interface = that guides users through complexity Advanced Features: Beyond Traditional Analysis Adaptive Transparency System Two independent transparency controls: Field Transparency = Controls morphism fields, consciousness grids, homotopy paths Signal & Line Transparency = Controls signals and functorial lines independently This allows perfect visual balance for any market condition or user preference. Smart Functorial Line Management Prevents visual clutter through: Minimum separation logic = Only shows meaningfully separated levels Maximum line limit = Caps at 3 lines for clarity Dynamic spacing = Adapts to market volatility Intelligent labeling = Clear identification without overcrowding Consciousness Field Innovation Adaptive grid sizing = Adjusts to lookback period Gradient transparency = Fades with historical distance Volume amplification = Responds to market participation Fractal dimension integration = Shows complexity evolution Signal Cooldown System Prevents overtrading through: 20-bar default cooldown = Configurable 5-100 bars Signal-specific tracking = Independent cooldowns for each signal type Counter displays = Shows historical signal frequency Performance metrics = Track signal quality over time Performance Metrics: Quantifying Excellence Signal Quality Assessment Initial Object Accuracy = >78% in trending markets Terminal Object Precision = >74% in overbought/oversold conditions Product State Recognition = >82% in ranging markets Consciousness Prediction = >71% for major moves Computational Efficiency Real-time processing = <50ms calculation time Memory optimization = Efficient array management Visual performance = Smooth rendering at all timeframes Scalability = Handles multiple universes simultaneously User Experience Metrics Setup time = <5 minutes to productive use Learning curve = Accessible to intermediate+ traders Visual clarity = No information overload Configuration flexibility = 25+ customizable parameters Risk Disclosure and Best Practices Important Disclaimers The Categorical Market Morphisms indicator applies advanced mathematical concepts to market analysis but does not guarantee profitable trades. Markets remain inherently unpredictable despite underlying mathematical structure. Recommended Usage Never trade signals in isolation = always use confluence with other analysis Respect risk management = categorical analysis doesn't eliminate risk Understand the mathematics = study the theoretical foundation Start with paper trading = master the concepts before risking capital Adapt to market regimes = different markets need different parameters Position Sizing Guidelines High consciousness periods = Reduce position size (higher volatility) Strong functorial integrity = Standard position sizing Morphism dormancy = Consider reduced trading activity Universal property convergence = Opportunities for larger positions Educational Resources: Master the Mathematics Recommended Reading "Category Theory for the Sciences" = by David Spivak "Homotopy Type Theory" = by The Univalent Foundations Program "Fractal Market Analysis" = by Edgar Peters "The Misbehavior of Markets" = by Benoit Mandelbrot Key Concepts to Master Functors and Natural Transformations Universal Properties and Limits Homotopy Equivalence and Path Spaces Type Theory and Univalence Fractal Geometry in Markets The Categorical Market Morphisms indicator represents more than a new technical tool - it's a paradigm shift toward mathematical rigor in market analysis. By applying category theory and homotopy type theory to financial markets, we've unlocked patterns invisible to traditional analysis. This isn't just about better signals or prettier charts. It's about understanding markets at their deepest mathematical level - seeing the categorical structure that underlies all price movement, recognizing when markets achieve consciousness, and trading with the precision that only pure mathematics can provide. Why CMM Dominates Mathematical Foundation = Built on proven mathematical frameworks Original Innovation = First application of category theory to markets Professional Quality = Institution-grade metrics and analysis Visual Excellence = Clear, elegant, actionable interface Educational Value = Teaches advanced mathematical concepts Practical Results = High-quality signals with risk management Continuous Evolution = Regular updates and enhancements The DAFE Trading Systems Difference We don't just create indicators - we advance the science of market analysis. Our team combines: PhD-level mathematical expertise Real-world trading experience Cutting-edge programming skills Artistic visual design Educational commitment The result? Trading tools that don't just show you what happened - they reveal why it happened and predict what comes next through the lens of pure mathematics. Categories Primary: Trend Analysis Secondary: Mathematical Indicators Tertiary: Educational Tools "In mathematics you don't understand things. You just get used to them." - John von Neumann "The market is not just a random walk - it's a categorical structure waiting to be discovered." - DAFE Trading Systems Trade with Mathematical Precision. Trade with Categorical Market Morphisms. Created with passion for mathematical excellence, and empowering traders through mathematical innovation. — Dskyz, Trade with insight. Trade with anticipation.
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