Marcius Studio® - Fishing Net™Fishing Net™ — a dynamic grid trading strategy with predefined entry levels and built-in risk management.
The strategy gradually builds positions as the price pulls back, and closes all trades when the Take Profit level is reached.
The main concept is to accumulate positions at multiple levels, like a net, and capture potential upward movement without promising guaranteed profits.
Important! This strategy is designed for HIGH-LIQUIDITY assets (ETH / BTC / SOL etc.) and is not suitable for LOW-LIQUIDITY assets.
Strategy Parameters
Level Step (%) : distance between grid levels.
Shift (%) : offset of the first entry level relative to price.
Take Profit (%) : target for closing all open positions.
Number of Orders (1–10) : total number of grid levels.
Risk per Trade (%) : capital risk per trade (1–100%), defines maximum position size.
Example Settings
Applicable for OKX:BTCUSDT.P / OKX:ETHUSDT.P / OKX:SOLUSDT.P etc.
Timeframe : 1H
Level Step : 1.0
Shift : 1.0
Take Profit : 5
Number of Orders : 10
Risk per Trade : 10%
How the Code Works
The script calculates a grid of entry levels below the current price.
When the price touches a level, an order is placed with size based on equity × risk % .
The strategy scales into the position gradually (up to the number of levels).
When the Take Profit target is reached, all positions are closed simultaneously.
All levels and the TP line are plotted on the chart for visual clarity.
Past performance is not indicative of future results.
Disclaimer
Trading involves risk — always do your own research (DYOR) and seek professional financial advice. We are not responsible for any potential financial losses.
Meanreversion
Backtest - Strategy Builder [AlgoAlpha]🟠 OVERVIEW
This script by AlgoAlpha is a modular Strategy Builder designed to let traders test custom trade entry and exit logic on TradingView without writing their own Pine code. It acts as a framework where users can connect multiple external signals, chain them in sequences, and run backtests with built-in leverage, margin, and risk controls. Its main strength is flexibility—you can define up to five sequential steps for entry and exit conditions on both long and short sides, with logic connectors (AND/OR) controlling how conditions combine. This lets you test complex multi-step confirmation workflows in a controlled, visual backtesting environment.
🟠 CONCEPTS
The system works by linking external signals —these can be values from other indicators, and/or custom sources—to conditional checks like “greater than,” “less than,” or “crossover.” You can stack these checks into steps , where all conditions in a step must pass before the sequence moves to the next. This creates a chain of logic that must be completed before a trade triggers. On execution, the strategy sizes positions according to your chosen leverage mode ( Cross or Isolated ) and allocation method ( Percent of equity or absolute USD value]). Liquidation prices are simulated for both modes, allowing realistic margin behaviour in testing. The script also tracks performance metrics like Sharpe, Sortino, profit factor, drawdown, and win rate in real time.
🟠 FEATURES
Up to 5 sequential steps for both long and short entries, each with multiple conditions linked by AND/OR logic.
Two leverage modes ( Cross and Isolated ) with independent long/short leverage multipliers.
Separate multi-step exit triggers for longs and shorts, with optional TP/SL levels or opposite-side triggers for flipping positions.
Position sizing by equity percent or fixed USD amount, applied before leverage.
Realistic liquidation price simulation for margin testing.
Built-in trade gating and validation—prevents trades if configuration rules aren’t met (e.g., no exit defined for an active side).
Full performance dashboard table showing live strategy status, warnings, and metrics.
Configurable bar coloring based on position side and TP/SL level drawing on chart.
Integration with TradingView's strategy backtester, allowing users to view more detailed metrics and test the strategy over custom time horizons.
🟠 USAGE
Add the strategy to your chart. In the settings, under Master Settings , enable longs/shorts, select leverage mode, set leverage multipliers, and define position sizing. Then, configure your Long Trigger and Short Trigger groups: turn on conditions, pick which external signal they reference, choose the comparison type, and assign them to a sequence step. For exits, use the corresponding Exit Long Trigger and Exit Short Trigger groups, with the option to link exits to opposite-side entries for auto-flips. You can also enable TP and/or SL exits with custom sources for the TP/SL levels. Once set, the strategy will simulate trades, show performance stats in the on-chart table, and highlight any configuration issues before execution. This makes it suitable for testing both simple single-signal systems and complex, multi-filtered strategies under realistic leverage and margin constraints.
🟠 EXAMPLE
The backtester on its own does not contain any indicator calculation; it requires input from external indicators to function. In this example, we'll be using AlgoAlpha's Smart Signals Assistant indicator to demonstrate how to build a strategy using this script.
We first define the conditions beforehand:
Entry :
Longs – SSA Bullish signal (strong OR weak)
Shorts – SSA Bearish signal (strong OR weak)
Exit
Longs/Shorts: (TP/SL hit OR opposing signal fires)
Other Parameters (⚠️Example only, tune this based on proper risk management and settings)
Long Leverage: default (3x)
Short Leverage: default (3x)
Position Size: default (10% of equity)
Steps
Load up the required indicators (in this example, the Smart Signals Assistant).
Ensure the required plots are being output by the indicator properly (signals and TP/SL levels are being plotted).
Open the Strategy Builder settings and scroll down to "CONDITION SETUP"; input the signals from the external indicator.
Configure the exit conditions, add in the TP/SL levels from the external indicator, and add an additional exit condition → {{Opposite Direction}} Entry Trigger.
After configuring the entry and exit conditions, the strategy should now be running. You can view information on the strategy in TradingView's backtesting report and also in the Strategy Builder's information table (default top right corner).
It is important to note that the strategy provided above is just an example, and the complexity of possible strategies stretches beyond what was shown in this short demonstration. Always incorporate proper risk management and ensure thorough testing before trading with live capital.
Spread Mean Reversion Strategy [SciQua]╭───────────────────────────────────────╮
Spread Mean Reversion Strategy
╰───────────────────────────────────────╯
This invite-only futures spread strategy applies a statistical mean reversion framework, executing limit orders exclusively at calculated Z-score thresholds for precise, rules-based entries and exits. It is designed for CME-style spreads and synthetic instruments with well-defined reversion tendencies.
╭────────────╮
Core Concept
╰────────────╯
The strategy calculates a rolling mean and standard deviation of a chosen spread or synthetic price series, then computes the Z-score to measure deviation from the mean in standard deviation units.
Long entries trigger when Z crosses upward through a negative entry threshold (`-devEnter`). A buy limit is placed exactly at the price corresponding to that Z-score, optionally offset by a configurable tick amount.
Short entries trigger when Z crosses downward through a positive entry threshold (`+devEnter`). A sell limit is placed at the corresponding threshold price, also with optional offset.
Exits use the same threshold method, with an independent `Close Limit Offset` to fine-tune exit placement.
╭────────────╮
Key Features
╰────────────╯
Persistence filter – Requires the Z-score to remain beyond threshold for a configurable number of bars before entry.
Cooldown after exits – Prevents immediate re-entry to reduce over-trading.
Daily and weekend flattening – Force-flattens positions via limit orders before exchange maintenance breaks and weekend closes.
Auto-rollover detection with persistence – Detects when the second contract month’s daily volume exceeds the first for a set number of days, then blocks new entries (optional).
Configurable tick offsets – Independently adjust entry and exit levels relative to threshold prices.
Minimum spread width filter – Blocks trades when long/short entry thresholds are too close together.
Contract multiplier override – Allows correct sizing for synthetic symbols where `syminfo.pointvalue` is incorrect or missing.
Limit-only execution – All entries, exits, and forced-flat actions are executed with limit orders for price control.
╭────────────────────╮
Entry Blocking Rules
╰────────────────────╯
New trades are blocked:
During daily maintenance break pre-windows
During weekend close pre-windows
After rollover triggers, if `Block After Roll` is enabled
╭────────────────────────╮
Intended Markets & Usage
╰────────────────────────╯
Built for futures spreads and synthetic instruments , including calendar spreads.
Performs best in markets with clear seasonal or statistical mean-reverting tendencies.
Not designed for strongly trending, non-reverting markets.
╭──────────────────────────╮
Risk Management & Defaults
╰──────────────────────────╯
Fixed default position size of 1 contract (qty calc function available for customization).
Realistic commission and slippage assumptions pre-set.
Pyramiding disabled by default.
Default Z-score levels: Entry at ±2.0, Exit at ±0.5.
Separate tick offset controls for entries and exits.
Note: This strategy is for research and backtesting purposes only. Past performance does not guarantee future results. All use is subject to explicit written permission from the author.
Buy The Dip - ENGThis script implements a grid trading strategy for long positions in the USDT market. The core idea is to place a series of buy limit orders at progressively lower prices below an initial entry point, aiming to lower the average entry price as the price drops. It then aims to exit the entire position when the price rises a certain percentage above the average entry price.
Here's a detailed breakdown:
1. Strategy Setup (`strategy` function):
`'거미줄 자동매매 250227'`: The name of the strategy.
`overlay = true`: Draws plots and labels directly on the main price chart.
`pyramiding = 15`: Allows up to 15 entries in the same direction (long). This is essential for grid trading, as it needs to open multiple buy orders.
`initial_capital = 600`: Sets the starting capital for backtesting to 600 USDT.
`currency = currency.USDT`: Specifies the account currency as USDT.
`margin_long/short = 0`: Doesn't define specific margin requirements (might imply spot trading logic or rely on exchange defaults if used live).
`calc_on_order_fills = false`: Strategy calculations happen on each bar's close, not just when orders fill.
2. Inputs (`input`):
Core Settings:
`lev`: Leverage (default 10x). Used to calculate position sizes.
`Investment Percentage %`: Percentage of total capital to allocate to the initial grid (default 80%).
`final entry Percentage %`: Percentage of the *remaining* capital (100 - `Investment Percentage %`) to use for the "semifinal" entry (default 50%). The rest goes to the "final" entry.
`Price Adjustment Length`: Lookback period (default 4 bars) to determine the initial `maxPrice`.
`price range`: The total percentage range downwards from `maxPrice` where the grid orders will be placed (default -10%, meaning 10% down).
`tp`: Take profit percentage above the average entry price (default 0.45%).
`semifinal entry price percent`: Percentage drop from `maxPrice` to trigger the "semifinal" larger entry (default -12%).
`final entry price percent`: Percentage drop from `maxPrice` to trigger the "final" larger entry (default -15%).
Rounding & Display:
`roundprice`, `round`: Decimal places for rounding price and quantity calculations.
`texts`, `label_style`: User interface preferences for text size and label appearance on the chart.
Time Filter:
`startTime`, `endTime`: Defines the date range for the backtest.
3. Calculations & Grid Setup:
`maxPrice`: The highest price point for the grid setup. Calculated as the lowest low of the previous `len` bars only if no trades are open. If trades are open, it uses the entry price of the very first order placed in the current sequence (`strategy.opentrades.entry_price(0)`).
`minPrice`: The lowest price point for the grid, calculated based on `maxPrice` and `range1`.
`totalCapital`: The amount of capital (considering leverage and `per1`) allocated for the main grid orders.
`coinRatios`: An array ` `. This defines the *relative* size ratio for each of the 11 grid orders. Later orders (at lower prices) will be progressively larger.
`totalRatio`: The sum of all ratios (66).
`positionSizes`: An array calculated based on `totalCapital` and `coinRatios`. It determines the actual quantity (size) for each of the 11 grid orders.
4. Order Placement Logic (`strategy.entry`):
Initial Grid Orders:
Runs only if within the specified time range and no position is currently open (`strategy.opentrades == 0`).
A loop places 11 limit buy orders (`Buy 1` to `Buy 11`).
Prices are calculated linearly between `maxPrice` and `minPrice`.
Order sizes are taken from the `positionSizes` array.
Semifinal & Final Entries:
Two additional, larger limit buy orders are placed simultaneously with the grid orders:
`semifinal entry`: At `maxPrice * (1 - semifinal / 100)`. Size is based on `per2`% of the capital *not* used by the main grid (`1 - per1`).
`final entry`: At `maxPrice * (1 - final / 100)`. Size is based on the remaining capital (`1 - per2`% of the unused portion).
5. Visualization (`line.new`, `label.new`, `plot`, `plotshape`, `plotchar`):
Grid Lines & Labels:
When a position is open (`strategy.opentrades > 0`), horizontal lines and labels are drawn for each of the 11 grid order prices and the "final" entry price.
Lines extend from the bar where the *first* entry occurred.
Labels show the price and planned size for each level.
Dynamic Coloring: If the price drops below a grid level, the corresponding line turns green, and the label color changes, visually indicating that the level has been reached or filled.
Plotted Lines:
`maxPrice` (initial high point for the grid).
`strategy.position_avg_price` (current average entry price of the open position, shown in red).
Target Profit Price (`strategy.position_avg_price * (1 + tp / 100)`, shown in green).
Markers:
A flag marks the `startTime`.
A rocket icon (`🚀`) appears below the bar where the `final entry` triggers.
A stop icon (`🛑`) appears below the bar where the `semifinal entry` triggers.
6. Exit Logic (`strategy.exit`, `strategy.entry` with `qty=0`):
Main Take Profit (`Full Exit`):
Uses `strategy.entry('Full Exit', strategy.short, qty = 0, limit = target2)`. This places a limit order to close the entire position (`qty=0`) at the calculated take profit level (`target2 = avgPrice * (1 + tp / 100)`). Note: Using `strategy.entry` with `strategy.short` and `qty=0` is a way to close a long position, though `strategy.exit` is often clearer. This exit seems intended to apply whenever any part of the grid position is open.
First Order Trailing Stop (`1st order Full Exit`):
Conditional: Only active if `trail` input is true AND the *last* order filled was "Buy 1" (meaning only the very first grid level was entered).
Uses `strategy.exit` with `trail_points` and `trail_offset` based on ATR values to implement a trailing stop loss/profit mechanism for this specific scenario.
This trailing stop order is cancelled (`strategy.cancel`) if any subsequent grid orders ("Buy 2", etc.) are filled.
Final/Semifinal Take Profit (`final Full Exit`):
Conditional: Only active if more than 11 entries have occurred (meaning either the "semifinal" or "final" entry must have triggered).
Uses `strategy.exit` to place a limit order to close the entire position at the take profit level (`target3 = avgPrice * (1 + tp / 100)`).
7. Information Display (Tables & UI Label):
`statsTable` (Top Right):
A comprehensive table displaying grouped information:
Market Info (Entry Point, Current Price)
Position Info (Avg Price, Target Price, Unrealized PNL $, Unrealized PNL %, Position Size, Position Value)
Strategy Performance (Realized PNL $, Realized PNL %, Initial/Total Balance, MDD, APY, Daily Profit %)
Trade Statistics (Trade Count, Wins/Losses, Win Rate, Cumulative Profit)
`buyAvgTable` (Bottom Left):
* Shows the *theoretical* entry price and average position price if trades were filled sequentially up to each `buy` level (buy1 to buy10). It uses hardcoded percentage drops (`buyper`, `avgper`) based on the initial `maxPrice` and `coinRatios`, not the dynamically changing actual average price.
`uiLabel` (Floating Label on Last Bar):
Updates only on the most recent bar (`barstate.islast`).
Provides real-time context when a position is open: Size, Avg Price, Current Price, Open PNL ($ and %), estimated % drop needed for the *next* theoretical buy (based on `ui_gridStep` input), % rise needed to hit TP, and estimated USDT profit at TP.
Shows "No Position" and basic balance/trade info otherwise.
In Summary:
This is a sophisticated long-only grid trading strategy. It aims to:
1. Define an entry range based on recent lows (`maxPrice`).
2. Place 11 scaled-in limit buy orders within a percentage range below `maxPrice`.
3. Place two additional, larger buy orders at deeper percentage drops (`semifinal`, `final`).
4. Calculate the average entry price as orders fill.
5. Exit the entire position for a small take profit (`tp`) above the average entry price.
6. Offer a conditional ATR trailing stop if only the first order fills.
7. Provide extensive visual feedback through lines, labels, icons, and detailed information tables/UI elements.
Keep in mind that grid strategies can perform well in ranging or slowly trending markets but can incur significant drawdowns if the price trends strongly against the position without sufficient retracements to hit the take profit. The leverage (`lev`) input significantly amplifies both potential profits and losses.
Reverse Keltner Channel StrategyReverse Keltner Channel Strategy
Overview
The Reverse Keltner Channel Strategy is a mean-reversion trading system that capitalizes on price movements between Keltner Channels. Unlike traditional Keltner Channel strategies that trade breakouts, this system takes the contrarian approach by entering positions when price returns to the channel after overextending.
Strategy Logic
Long Entry Conditions:
Price crosses above the lower Keltner Channel from below
This signals a potential reversal after an oversold condition
Position is entered at market price upon signal confirmation
Long Exit Conditions:
Take Profit: Price reaches the upper Keltner Channel
Stop Loss: Placed at half the channel width below entry price
Short Entry Conditions:
Price crosses below the upper Keltner Channel from above
This signals a potential reversal after an overbought condition
Position is entered at market price upon signal confirmation
Short Exit Conditions:
Take Profit: Price reaches the lower Keltner Channel
Stop Loss: Placed at half the channel width above entry price
Key Features
Mean Reversion Approach: Takes advantage of price tendency to return to mean after extreme moves
Adaptive Stop Loss: Stop loss dynamically adjusts based on market volatility via ATR
Visual Signals: Entry points clearly marked with directional triangles
Fully Customizable: All parameters can be adjusted to fit various market conditions
Customizable Parameters
Keltner EMA Length: Controls the responsiveness of the channel (default: 20)
ATR Multiplier: Determines channel width/sensitivity (default: 2.0)
ATR Length: Affects volatility calculation period (default: 10)
Stop Loss Factor: Adjusts risk management aggressiveness (default: 0.5)
Best Used On
This strategy performs well on:
Currency pairs with defined ranging behavior
Commodities that show cyclical price movements
Higher timeframes (4H, Daily) for more reliable signals
Markets with moderate volatility
Risk Management
The built-in stop loss mechanism automatically adjusts to market conditions by calculating position risk relative to the current channel width. This approach ensures that risk remains proportional to potential reward across varying market conditions.
Notes for Optimization
Consider adjusting the EMA length and ATR multiplier based on the specific asset and timeframe:
Lower values increase sensitivity and generate more signals
Higher values produce fewer but potentially more reliable signals
As with any trading strategy, thorough backtesting is recommended before live implementation.
Past performance is not indicative of future results. Always practice sound risk management.
Breadth-Driven Swing StrategyWhat it does
This script trades the S&P 500 purely on market breadth extremes:
• Data source : INDEX:S5TH = % of S&P 500 stocks above their own 200-day SMA (range 0–100).
• Buy when breadth is washed-out.
• Sell when breadth is overheated.
It is long-only by design; shorting and ATR trailing stops have been removed to keep the logic minimal and transparent.
⸻
Signals in plain English
1. Long entry
A. A 200-EMA trough in breadth is printed and the trough value is ≤ 40 %.
or
B. A 5-EMA trough appears, its prominence passes the user threshold, and the lowest breadth reading in the last 20 bars is ≤ 20 %.
(Toggle this secondary trigger on/off with “ Enter also on 5-EMA trough ”.)
2. Exit (close long)
First 200-EMA peak whose breadth value is ≥ 70 %.
3. Risk control
A fixed stop-loss (% of entry price, default 8 %) is attached to every long trade.
⸻
Key parameters (defaults shown)
• Long EMA length 200 • Short EMA length 5
• Peak prominence 0.5 pct-pts • Trough prominence 3 pct-pts
• Peak level 70 % • Trough level 40 % • 5-EMA trough level 20 %
• Fixed stop-loss 8 %
• “Enter also on 5-EMA trough” = true (allows additional entries on extreme momentum reversals)
Feel free to tighten or relax any of these thresholds to match your risk profile or account for different market regimes.
⸻
How to use it
1. Load the script on a daily SPX / SPY chart.
(The price chart drives order execution; the breadth series is pulled internally and does not need to be on the chart.)
2. Verify the breadth feed.
INDEX:S5TH is updated after each session; your broker must provide it.
3. Back-test across several cycles.
Two decades of daily data is recommended to see how the rules behave in bear markets, range markets, and bull trends.
4. Adjust position sizing in the Properties tab.
The default is “100 % of equity”; change it if you prefer smaller allocations or pyramiding caps.
⸻
Why it can help
• Breadth signals often lead price, allowing entries before index-level momentum turns.
• Simple, rule-based exits prevent “waiting for confirmation” paralysis.
• Only one input series—easy to audit, no black-box math.
Trade-offs
• Relies on a single breadth metric; other internals (advance/decline, equal-weight returns, etc.) are ignored.
• May sit in cash during shallow pullbacks that never push breadth ≤ 40 %.
• Signals arrive at the end of the session (breadth is EoD data).
⸻
Disclaimer
This script is provided for educational purposes only and is not financial advice. Markets are risky; test thoroughly and use your own judgment before trading real money.
ストラテジー概要
本スクリプトは S&P500 のマーケットブレッド（内部需給） だけを手がかりに、指数をスイングトレードします。
• ブレッドデータ : INDEX:S5TH
（S&P500 採用銘柄のうち、それぞれの 200 日移動平均線を上回っている銘柄比率。0–100 %）
• 買い : ブレッドが極端に売られたタイミング。
• 売り : ブレッドが過熱状態に達したタイミング。
余計な機能を削り、ロングオンリー & 固定ストップ のシンプル設計にしています。
⸻
シグナルの流れ
1. ロングエントリー
• 条件 A : 200-EMA がトラフを付け、その値が 40 % 以下
• 条件 B : 5-EMA がトラフを付け、
・プロミネンス条件を満たし
・直近 20 本のブレッドス最小値が 20 % 以下
• B 条件は「5-EMA トラフでもエントリー」を ON にすると有効
2. ロング決済
最初に出現した 200-EMA ピーク で、かつ値が 70 % 以上 のバーで手仕舞い。
3. リスク管理
各トレードに 固定ストップ（初期価格から 8 %）を設定。
⸻
主なパラメータ（デフォルト値）
• 長期 EMA 長さ : 200 • 短期 EMA 長さ : 5
• ピーク判定プロミネンス : 0.5 %pt • トラフ判定プロミネンス : 3 %pt
• ピーク水準 : 70 % • トラフ水準 : 40 % • 5-EMA トラフ水準 : 20 %
• 固定ストップ : 8 %
• 「5-EMA トラフでもエントリー」 : ON
相場環境やリスク許容度に合わせて閾値を調整してください。
⸻
使い方
1. 日足の SPX / SPY チャート にスクリプトを適用。
2. ブレッドデータの供給 (INDEX:S5TH) がブローカーで利用可能か確認。
3. 20 年以上の期間でバックテスト し、強気相場・弱気相場・レンジ局面での挙動を確認。
4. 資金配分 は プロパティ → 戦略実行 で調整可能（初期値は「資金の 100 %」）。
⸻
強み
• ブレッドは 価格より先行 することが多く、天底を早期に捉えやすい。
• ルールベースの出口で「もう少し待とう」と迷わずに済む。
• 入力 series は 1 本のみ、ブラックボックス要素なし。
注意点・弱み
• 単一指標に依存。他の内部需給（A/D ライン等）は考慮しない。
• 40 % を割らない浅い押し目では機会損失が起こる。
• ブレッドは終値ベースの更新。ザラ場中の変化は捉えられない。
⸻
免責事項
本スクリプトは 学習目的 で提供しています。投資助言ではありません。
実取引の前に必ず自己責任で十分な検証とリスク管理を行ってください。
IBS (Internal Bar Strength) Trading Strategy for SPY and NDQImplementation by AlgoTradeKit
Overview
The IBS Trading Strategy is a daily bars long-only trading system, based on the concept of Internal Bar Strength (IBS). The strategy aims to identify potential reversals by monitoring how the previous bar’s close positions itself within its high-low range. It is suitable for stock and US indices. The default parameters are optimized for SPY/SPX and NDQ/QQQ
Strategy Concept
The Internal Bar Strength (IBS) is calculated using the formula:
IBS = (Previous Close - Previous Low) / (Previous High - Previous Low)
This value always lies between 0 and 1. An IBS value below 0.2 is typically interpreted as an oversold condition, while a value above 0.9 suggests an overbought state.
Trading Rules
- Long Entry :
- Condition 1 : IBS is below the user-defined entry threshold (default is 0.2).
- Condition 2 : The current price is above an N-period Exponential Moving Average (EMA) (default period is 252).
- Note : You can disable the EMA condition by setting the EMA period to 0.
- Long Exit
- The position is closed when IBS rises above the user-defined exit threshold (default is 0.9).
Customization Options
- IBS Entry Threshold : Adjust to set the sensitivity for entering a long trade based on oversold conditions.
- IBS Exit Threshold : Customize to define the exit point when the market becomes overbought.
- EMA Period : Set the lookback period for the EMA to align with your trend bias; disable this condition by setting the period to 0.
Risk Management & Trading Considerations
- Designed for daily charts, the strategy captures higher timeframe trends and minimizes noise.
- The entry and exit conditions are straightforward, aiming to avoid over-trading while letting clear signals dictate trade management.
- Always use proper risk management techniques and test the strategy thoroughly on historical data and in a simulated environment before applying it in live markets.
Disclaimer
This strategy is for educational and informational purposes only and does not constitute financial advice. Trading involves risk, and past performance is not indicative of future results. Always conduct your own research and consider your risk tolerance before making any trades.
3 Red / 3 Green Strategy with Volatility CheckStrategy Name: 3 Red / 3 Green Strategy with Volatility Check by AlgoTradeKit
Overview
This long-only strategy is designed for daily bars on NASDAQ (or similar instruments) and combines simple price action with a volatility filter. It “tells it like it is” – enter when the market shows weakness, but only in sufficiently volatile conditions, and exit either on signs of a reversal or after a set number of days.
Entry Conditions
- Price Action :
Enter a long position when there are 3 consecutive red days (each day's close is below its open).
- Volatility Filter :
The entry is allowed only if the current ATR (Average True Range) calculated over the specified ATR Period (default 12) is greater than its 30-day simple moving average. This ensures the market has enough volatility to justify the trade.
Exit Conditions
- Reversal Signal :
Exit the long position when 3 consecutive green days occur (each day's close is above its open), signaling a potential reversal.
- Time Limit :
Regardless of market conditions, any open trade is closed if it reaches the Maximum Trade Duration (default 22 days). This helps limit exposure during stagnant or unfavorable market conditions.
- You can toggle the three-green-day exit if you want to isolate the time-based exit.
Input Parameters
- Maximum Trade Duration (days): Default is 22 days.
- ATR Period: Default is 12.
- Use 3 Green Days Exit: Toggle to enable or disable the three-green-day exit condition.
How It Works
1. Entry: The strategy monitors daily price action for 3 consecutive down days. When this occurs and if the market is volatile enough (current ATR > 30-day ATR average), it opens a long position.
2. Exit: The position is closed if the price action reverses with 3 consecutive up days or if the trade has been open for the maximum allowed duration - i.e. use it on daily chart.
Risk Management
- The built-in maximum trade duration prevents trades from lingering too long in a non-trending or consolidating market.
- The volatility filter helps ensure that trades are only taken when there is sufficient price movement, potentially increasing the odds of a meaningful move.
Disclaimer
This strategy is provided “as is” without any warranties. It is essential to backtest and validate the performance on your specific instrument and market conditions before deploying live capital. Trading involves significant risk, and you should adjust parameters to match your risk tolerance.
Test and tweak this strategy to see if it fits your trading style and market conditions. Happy trading!
[SHORT ONLY] 10 Bar Low Pullback█ STRATEGY DESCRIPTION
The "10 Bar Low Pullback" strategy is a contrarian short trading system designed to capture pullbacks after a new 10‐bar low is made. it identifies a potential short opportunity when the current bar’s low breaks below the lowest low of the previous 10 bars, provided that the bar exhibits strong internal momentum as measured by its IBS value. An optional trend filter further refines entries by requiring that the close is below a 200-period EMA.
█ WHAT IS INTERNAL BAR STRENGTH (IBS)?
Internal Bar Strength (IBS) measures where the closing price falls within the high-low range of a bar. It is calculated as:
ibs = (close - low) / (high - low)
- Low IBS (≤ 0.2): Indicates the close is near the bar's low, suggesting oversold conditions.
- High IBS (≥ 0.8): Indicates the close is near the bar's high, suggesting overbought conditions.
█ SIGNAL GENERATION
1. SHORT ENTRY
A Short Signal is triggered when:
The current bar’s low is below the lowest low of the past X bars (default: 10).
The bar’s IBS is greater than the specified threshold (default: 0.85).
The signal occurs within the defined trading window (between Start Time and End Time).
If the EMA Filter is enabled, the close must be below the 200-period EMA.
2. EXIT CONDITION
An exit Signal is generated when the current close falls below the previous bar’s low (close < low ), indicating a potential bearish reversal and prompting the strategy to close its short position.
█ ADDITIONAL SETTINGS
Lookback Period: Defines the number of bars (default is 10) over which the lowest low is calculated.
IBS Threshold: Sets the minimum required IBS value (default is 0.85) to qualify as a pullback.
Trading Window: Trades are only executed between the user-defined Start Time and End Time.
EMA Filter (Optional): When enabled, short entries are only considered if the current close is below the 200-period EMA, with the EMA period being adjustable (default is 200).
█ PERFORMANCE OVERVIEW
Designed for shorting opportunities, this strategy aims to capture pullbacks following an aggressive 10-bar low break.
It leverages a combination of a lookback low and IBS measurement to identify overextended bullish moves that may revert.
The optional EMA filter helps confirm a bearish market environment by ensuring the price remains under the trend line.
Suitable for use on various assets, including stocks and ETFs, on daily or similar timeframes.
Backtesting and parameter optimization are recommended to tailor the strategy to specific market conditions.
[SHORT ONLY] ATR Sell the Rip Mean Reversion Strategy█ STRATEGY DESCRIPTION
The "ATR Sell the Rip Mean Reversion Strategy" is a contrarian system that targets overextended price moves on stocks and ETFs. It calculates an ATR‐based trigger level to identify shorting opportunities. When the current close exceeds this smoothed ATR trigger, and if the close is below a 200-period EMA (if enabled), the strategy initiates a short entry, aiming to profit from an anticipated corrective pullback.
█ HOW IS THE ATR SIGNAL BAND CALCULATED?
This strategy computes an ATR-based signal trigger as follows:
Calculate the ATR
The strategy computes the Average True Range (ATR) using a configurable period provided by the user:
atrValue = ta.atr(atrPeriod)
Determine the Threshold
Multiply the ATR by a predefined multiplier and add it to the current close:
atrThreshold = close + atrValue * atrMultInput
Smooth the Threshold
Apply a Simple Moving Average over a specified period to smooth out the threshold, reducing noise:
signalTrigger = ta.sma(atrThreshold, smoothPeriodInput)
█ SIGNAL GENERATION
1. SHORT ENTRY
A Short Signal is triggered when:
The current close is above the smoothed ATR signal trigger.
The trade occurs within the specified trading window (between Start Time and End Time).
If the EMA filter is enabled, the close must also be below the 200-period EMA.
2. EXIT CONDITION
An exit Signal is generated when the current close falls below the previous bar’s low (close < low ), indicating a potential bearish reversal and prompting the strategy to close its short position.
█ ADDITIONAL SETTINGS
ATR Period: The period used to calculate the ATR, allowing for adaptability to different volatility conditions (default is 20).
ATR Multiplier: The multiplier applied to the ATR to determine the raw threshold (default is 1.0).
Smoothing Period: The period over which the raw ATR threshold is smoothed using an SMA (default is 10).
Start Time and End Time: Defines the time window during which trades are allowed.
EMA Filter (Optional): When enabled, short entries are only executed if the current close is below the 200-period EMA, confirming a bearish trend.
█ PERFORMANCE OVERVIEW
This strategy is designed for use on the Daily timeframe, targeting stocks and ETFs by capitalizing on overextended price moves.
It utilizes a dynamic, ATR-based trigger to identify when prices have potentially peaked, setting the stage for a mean reversion short entry.
The optional EMA filter helps align trades with broader market trends, potentially reducing false signals.
Backtesting is recommended to fine-tune the ATR multiplier, smoothing period, and EMA settings to match the volatility and behavior of specific markets.
[SHORT ONLY] Consecutive Bars Above MA Strategy█ STRATEGY DESCRIPTION
The "Consecutive Bars Above MA Strategy" is a contrarian trading system aimed at exploiting overextended bullish moves in stocks and ETFs. It monitors the number of consecutive bars that close above a chosen short-term moving average (which can be either a Simple Moving Average or an Exponential Moving Average). Once the count reaches a preset threshold and the current bar’s close exceeds the previous bar’s high within a designated trading window, a short entry is initiated. An optional EMA filter further refines entries by requiring that the current close is below the 200-period EMA, helping to ensure that trades are taken in a bearish environment.
█ HOW ARE THE CONSECUTIVE BULLISH COUNTS CALCULATED?
The strategy utilizes a counter variable, `bullCount`, to track consecutive bullish bars based on their relation to the short-term moving average. Here’s how the count is determined:
Initialize the Counter
The counter is initialized at the start:
var int bullCount = na
Bullish Bar Detection
For each bar, if the close is above the selected moving average (either SMA or EMA, based on user input), the counter is incremented:
bullCount := close > signalMa ? (na(bullCount) ? 1 : bullCount + 1) : 0
Reset on Non-Bullish Condition
If the close does not exceed the moving average, the counter resets to zero, indicating a break in the consecutive bullish streak.
█ SIGNAL GENERATION
1. SHORT ENTRY
A short signal is generated when:
The number of consecutive bullish bars (i.e., bars closing above the short-term MA) meets or exceeds the defined threshold (default: 3).
The current bar’s close is higher than the previous bar’s high.
The signal occurs within the specified trading window (between Start Time and End Time).
Additionally, if the EMA filter is enabled, the entry is only executed when the current close is below the 200-period EMA.
2. EXIT CONDITION
An exit signal is triggered when the current close falls below the previous bar’s low, prompting the strategy to close the short position.
█ ADDITIONAL SETTINGS
Threshold: The number of consecutive bullish bars required to trigger a short entry (default is 3).
Trading Window: The Start Time and End Time inputs define when the strategy is active.
Moving Average Settings: Choose between SMA and EMA, and set the MA length (default is 5), which is used to assess each bar’s bullish condition.
EMA Filter (Optional): When enabled, this filter requires that the current close is below the 200-period EMA, supporting entries in a downtrend.
█ PERFORMANCE OVERVIEW
This strategy is designed for stocks and ETFs and can be applied across various timeframes.
It seeks to capture mean reversion by shorting after a series of bullish bars suggests an overextended move.
The approach employs a contrarian short entry by waiting for a breakout (close > previous high) following consecutive bullish bars.
The adjustable moving average settings and optional EMA filter allow for further optimization based on market conditions.
Comprehensive backtesting is recommended to fine-tune the threshold, moving average parameters, and filter settings for optimal performance.
[SHORT ONLY] Consecutive Close>High[1] Mean Reversion Strategy█ STRATEGY DESCRIPTION
The "Consecutive Close > High " Mean Reversion Strategy is a contrarian daily trading system for stocks and ETFs. It identifies potential shorting opportunities by counting consecutive days where the closing price exceeds the previous day's high. When this consecutive day count reaches a predetermined threshold, and if the close is below a 200-period EMA (if enabled), a short entry is triggered, anticipating a corrective pullback.
█ HOW ARE THE CONSECUTIVE BULLISH COUNTS CALCULATED?
The strategy uses a counter variable called `bullCount` to track how many consecutive bars meet a bullish condition. Here’s a breakdown of the process:
Initialize the Counter
var int bullCount = 0
Bullish Bar Detection
Every time the close exceeds the previous bar's high, increment the counter:
if close > high
bullCount += 1
Reset on Bearish Bar
When there is a clear bearish reversal, the counter is reset to zero:
if close < low
bullCount := 0
█ SIGNAL GENERATION
1. SHORT ENTRY
A Short Signal is triggered when:
The count of consecutive bullish closes (where close > high ) reaches or exceeds the defined threshold (default: 3).
The signal occurs within the specified trading window (between Start Time and End Time).
2. EXIT CONDITION
An exit Signal is generated when the current close falls below the previous bar’s low (close < low ), prompting the strategy to exit the position.
█ ADDITIONAL SETTINGS
Threshold: The number of consecutive bullish closes required to trigger a short entry (default is 3).
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
EMA Filter (Optional): When enabled, short entries are only triggered if the current close is below the 200-period EMA.
█ PERFORMANCE OVERVIEW
This strategy is designed for Stocks and ETFs on the Daily timeframe and targets overextended bullish moves.
It aims to capture mean reversion by entering short after a series of consecutive bullish closes.
Further optimization is possible with additional filters (e.g., EMA, volume, or volatility).
Backtesting should be used to fine-tune the threshold and filter settings for specific market conditions.
[SHORT ONLY] Internal Bar Strength (IBS) Mean Reversion Strategy█ STRATEGY DESCRIPTION
The "Internal Bar Strength (IBS) Strategy" is a mean-reversion strategy designed to identify trading opportunities based on the closing price's position within the daily price range. It enters a short position when the IBS indicates overbought conditions and exits when the IBS reaches oversold levels. This strategy is Short-Only and was designed to be used on the Daily timeframe for Stocks and ETFs.
█ WHAT IS INTERNAL BAR STRENGTH (IBS)?
Internal Bar Strength (IBS) measures where the closing price falls within the high-low range of a bar. It is calculated as:
IBS = (Close - Low) / (High - Low)
- Low IBS (≤ 0.2) : Indicates the close is near the bar's low, suggesting oversold conditions.
- High IBS (≥ 0.8) : Indicates the close is near the bar's high, suggesting overbought conditions.
█ SIGNAL GENERATION
1. SHORT ENTRY
A Short Signal is triggered when:
The IBS value rises to or above the Upper Threshold (default: 0.9).
The Closing price is greater than the previous bars High (close>high ).
The signal occurs within the specified time window (between `Start Time` and `End Time`).
2. EXIT CONDITION
An exit Signal is generated when the IBS value drops to or below the Lower Threshold (default: 0.3). This prompts the strategy to exit the position.
█ ADDITIONAL SETTINGS
Upper Threshold: The IBS level at which the strategy enters trades. Default is 0.9.
Lower Threshold: The IBS level at which the strategy exits short positions. Default is 0.3.
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed for Stocks and ETFs markets and performs best when prices frequently revert to the mean.
The strategy can be optimized further using additional conditions such as using volume or volatility filters.
It is sensitive to extreme IBS values, which help identify potential reversals.
Backtesting results should be analyzed to optimize the Upper/Lower Thresholds for specific instruments and market conditions.
Bearish Wick Reversal█ STRATEGY OVERVIEW
The "Bearish Wick Reversal Strategy" identifies potential bullish reversals following significant bearish price rejection (long lower wicks). This counter-trend approach enters long positions when bearish candles show exaggerated downside wicks relative to closing prices, then exits on bullish confirmation signals. Includes optional EMA trend filtering for improved reliability.
█ What is a Bearish Wick?
A price rejection pattern where:
Bearish candle (close < open) forms with extended lower wick
Wick represents failed selloff: Low drops significantly below close
Measured as: (Low - Close)/Close × 100 (Negative percentage indicates downward extension)
█ SIGNAL GENERATION
1. LONG ENTRY CONDITION
Bearish candle forms with close < open
Lower wick exceeds user-defined threshold (Default: -1% of close price)
The signal occurs within the specified time window
If enabled, the close price must also be above the 200-period EMA (Exponential Moving Average)
2. EXIT CONDITION
A Sell Signal is generated when the current closing price exceeds the highest high of the previous seven bars (`close > _highest `). This indicates that the price has shown strength, potentially confirming the reversal and prompting the strategy to exit the position.
█ PERFORMANCE OVERVIEW
Ideal Market: Volatile instruments with frequent price rejections
Key Risk: False signals in sustained bearish trends
Optimization Tip: Test various thresholds
Filter Impact: EMA reduces trades but improves win rate and reduces drawdown
Gap Down Reversal Strategy█ STRATEGY OVERVIEW
The "Gap Down Reversal Strategy" capitalizes on price recovery patterns following bearish gap-down openings. This mean-reversion approach enters long positions on confirmed intraday recoveries and exits when prices breach previous session highs. This strategy is NOT optimized.
█ What is a Gap Down Reversal?
A gap down reversal occurs when:
An instrument opens significantly below its prior session's low (price gap)
Selling pressure exhausts itself during the session
Buyers regain control, pushing price back above the opening level
Creates a candlestick with:
• Open < Prior Session Low (true gap)
• Close > Open (bullish reversal candle)
█ SIGNAL GENERATION
1. LONG ENTRY CONDITION
Previous candle closes BELOW its opening price (bearish candle)
Current session opens BELOW prior candle's low (gap down)
Current candle closes ABOVE its opening price (bullish reversal)
Executes market order at session close
2. EXIT CONDITION
A Sell Signal is generated when the current closing price exceeds the highest high of the previous seven bars (`close > _highest `). This indicates that the price has shown strength, potentially confirming the reversal and prompting the strategy to exit the position.
█ PERFORMANCE OVERVIEW
Ideal Market: High volatility instruments with frequent gaps
Key Risk: False reversals in sustained downtrends
Optimization Tip: Test varying gap thresholds (1-3% ranges)
3 Down, 3 Up Strategy█ STRATEGY DESCRIPTION
The "3 Down, 3 Up Strategy" is a mean-reversion strategy designed to capitalize on short-term price reversals. It enters a long position after consecutive bearish closes and exits after consecutive bullish closes. This strategy is NOT optimized and can be used on any timeframes.
█ WHAT ARE CONSECUTIVE DOWN/UP CLOSES?
- Consecutive Down Closes: A sequence of trading bars where each close is lower than the previous close.
- Consecutive Up Closes: A sequence of trading bars where each close is higher than the previous close.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The price closes lower than the previous close for Consecutive Down Closes for Entry (default: 3) consecutive bars.
The signal occurs within the specified time window (between Start Time and End Time).
If enabled, the close price must also be above the 200-period EMA (Exponential Moving Average).
2. EXIT CONDITION
A Sell Signal is generated when the price closes higher than the previous close for Consecutive Up Closes for Exit (default: 3) consecutive bars.
█ ADDITIONAL SETTINGS
Consecutive Down Closes for Entry: Number of consecutive lower closes required to trigger a buy. Default = 3.
Consecutive Up Closes for Exit: Number of consecutive higher closes required to exit. Default = 3.
EMA Filter: Optional 200-period EMA filter to confirm long entries in bullish trends. Default = disabled.
Start Time and End Time: Restrict trading to specific dates (default: 2014-2099).
█ PERFORMANCE OVERVIEW
Designed for volatile markets with frequent short-term reversals.
Performs best when price oscillates between clear support/resistance levels.
The EMA filter improves reliability in trending markets but may reduce trade frequency.
Backtest to optimize consecutive close thresholds and EMA period for specific instruments.
Internal Bar Strength (IBS) Strategy█ STRATEGY DESCRIPTION
The "Internal Bar Strength (IBS) Strategy" is a mean-reversion strategy designed to identify trading opportunities based on the closing price's position within the daily price range. It enters a long position when the IBS indicates oversold conditions and exits when the IBS reaches overbought levels. This strategy was designed to be used on the daily timeframe.
█ WHAT IS INTERNAL BAR STRENGTH (IBS)?
Internal Bar Strength (IBS) measures where the closing price falls within the high-low range of a bar. It is calculated as:
IBS = (Close - Low) / (High - Low)
- **Low IBS (≤ 0.2)**: Indicates the close is near the bar's low, suggesting oversold conditions.
- **High IBS (≥ 0.8)**: Indicates the close is near the bar's high, suggesting overbought conditions.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The IBS value drops below the Lower Threshold (default: 0.2).
The signal occurs within the specified time window (between `Start Time` and `End Time`).
2. EXIT CONDITION
A Sell Signal is generated when the IBS value rises to or above the Upper Threshold (default: 0.8). This prompts the strategy to exit the position.
█ ADDITIONAL SETTINGS
Upper Threshold: The IBS level at which the strategy exits trades. Default is 0.8.
Lower Threshold: The IBS level at which the strategy enters long positions. Default is 0.2.
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed for ranging markets and performs best when prices frequently revert to the mean.
It is sensitive to extreme IBS values, which help identify potential reversals.
Backtesting results should be analyzed to optimize the Upper/Lower Thresholds for specific instruments and market conditions.
Buy on 5 day low Strategy█ STRATEGY DESCRIPTION
The "Buy on 5 Day Low Strategy" is a mean-reversion strategy designed to identify potential buying opportunities when the price drops below the lowest low of the previous five days. It enters a long position when specific conditions are met and exits when the price exceeds the high of the previous day. This strategy is optimized for use on daily or higher timeframes.
█ WHAT IS THE 5-DAY LOW?
The 5-Day Low is the lowest price observed over the last five days. This level is used as a reference to identify potential oversold conditions and reversal points.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The close price is below the lowest low of the previous five days (`close < _lowest `).
The signal occurs within the specified time window (between `Start Time` and `End Time`).
2. EXIT CONDITION
A Sell Signal is generated when the current closing price exceeds the high of the previous day (`close > high `). This indicates that the price has shown strength, potentially confirming the reversal and prompting the strategy to exit the position.
█ ADDITIONAL SETTINGS
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed for mean-reverting markets and performs best when the price frequently oscillates around key support levels.
It is sensitive to oversold conditions, as indicated by the 5-Day Low, and overbought conditions, as indicated by the previous day's high.
Backtesting results should be analyzed to optimize the strategy for specific instruments and market conditions.
3-Bar Low Strategy█ STRATEGY DESCRIPTION
The "3-Bar Low Strategy" is a mean-reversion strategy designed to identify potential buying opportunities when the price drops below the lowest low of the previous three bars. It enters a long position when specific conditions are met and exits when the price exceeds the highest high of the previous seven bars. This strategy is suitable for use on various timeframes.
█ WHAT IS THE 3-BAR LOW?
The 3-Bar Low is the lowest price observed over the last three bars. This level is used as a reference to identify potential oversold conditions and reversal points.
█ WHAT IS THE 7-BAR HIGH?
The 7-Bar High is the highest price observed over the last seven bars. This level is used as a reference to identify potential overbought conditions and exit points.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The close price is below the lowest low of the previous three bars (`close < _lowest `).
The signal occurs within the specified time window (between `Start Time` and `End Time`).
If the EMA Filter is enabled, the close price must also be above the 200-period Exponential Moving Average (EMA).
2. EXIT CONDITION
A Sell Signal is generated when the current closing price exceeds the highest high of the previous seven bars (`close > _highest `). This indicates that the price has shown strength, potentially confirming the reversal and prompting the strategy to exit the position.
█ ADDITIONAL SETTINGS
MA Period: The lookback period for the 200-period EMA used in the EMA Filter. Default is 200.
Use EMA Filter: Enables or disables the EMA Filter for long entries. Default is disabled.
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed for mean-reverting markets and performs best when the price frequently oscillates around key support and resistance levels.
It is sensitive to oversold conditions, as indicated by the 3-Bar Low, and overbought conditions, as indicated by the 7-Bar High.
Backtesting results should be analyzed to optimize the MA Period and EMA Filter settings for specific instruments.
Bollinger Bands Reversal + IBS Strategy█ STRATEGY DESCRIPTION
The "Bollinger Bands Reversal Strategy" is a mean-reversion strategy designed to identify potential buying opportunities when the price deviates below the lower Bollinger Band and the Internal Bar Strength (IBS) indicates oversold conditions. It enters a long position when specific conditions are met and exits when the IBS indicates overbought conditions. This strategy is suitable for use on various timeframes.
█ WHAT ARE BOLLINGER BANDS?
Bollinger Bands consist of three lines:
- **Basis**: A Simple Moving Average (SMA) of the price over a specified period.
- **Upper Band**: The basis plus a multiple of the standard deviation of the price.
- **Lower Band**: The basis minus a multiple of the standard deviation of the price.
Bollinger Bands help identify periods of high volatility and potential reversal points.
█ WHAT IS INTERNAL BAR STRENGTH (IBS)?
Internal Bar Strength (IBS) is a measure of where the closing price is relative to the high and low of the bar. It is calculated as:
IBS = (Close - Low) / (High - Low)
A low IBS value (e.g., below 0.2) indicates that the close is near the low of the bar, suggesting oversold conditions. A high IBS value (e.g., above 0.8) indicates that the close is near the high of the bar, suggesting overbought conditions.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The IBS value is below 0.2, indicating oversold conditions.
The close price is below the lower Bollinger Band.
The signal occurs within the specified time window (between `Start Time` and `End Time`).
2. EXIT CONDITION
A Sell Signal is generated when the IBS value exceeds 0.8, indicating overbought conditions. This prompts the strategy to exit the position.
█ ADDITIONAL SETTINGS
Length: The lookback period for calculating the Bollinger Bands. Default is 20.
Multiplier: The number of standard deviations used to calculate the upper and lower Bollinger Bands. Default is 2.0.
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed for mean-reverting markets and performs best when the price frequently deviates from the Bollinger Bands.
It is sensitive to oversold and overbought conditions, as indicated by the IBS, which helps to identify potential reversals.
Backtesting results should be analyzed to optimize the Length and Multiplier parameters for specific instruments.
Average High-Low Range + IBS Reversal Strategy█ STRATEGY DESCRIPTION
The "Average High-Low Range + IBS Reversal Strategy" is a mean-reversion strategy designed to identify potential buying opportunities when the price deviates significantly from its average high-low range and the Internal Bar Strength (IBS) indicates oversold conditions. It enters a long position when specific conditions are met and exits when the price shows strength by exceeding the previous bar's high. This strategy is suitable for use on various timeframes.
█ WHAT IS THE AVERAGE HIGH-LOW RANGE?
The Average High-Low Range is calculated as the Simple Moving Average (SMA) of the difference between the high and low prices over a specified period. It helps identify periods of increased volatility and potential reversal points.
█ WHAT IS INTERNAL BAR STRENGTH (IBS)?
Internal Bar Strength (IBS) is a measure of where the closing price is relative to the high and low of the bar. It is calculated as:
IBS = (Close - Low) / (High - Low)
A low IBS value (e.g., below 0.2) indicates that the close is near the low of the bar, suggesting oversold conditions.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The close price has been below the buy threshold (calculated as `upper - (2.5 * hl_avg)`) for a specified number of consecutive bars (`bars_below_threshold`).
The IBS value is below the specified buy threshold (`ibs_buy_treshold`).
The signal occurs within the specified time window (between `Start Time` and `End Time`).
2. EXIT CONDITION
A Sell Signal is generated when the current closing price exceeds the high of the previous bar (`close > high `). This indicates that the price has shown strength, potentially confirming the reversal and prompting the strategy to exit the position.
█ ADDITIONAL SETTINGS
Length: The lookback period for calculating the average high-low range. Default is 20.
Bars Below Threshold: The number of consecutive bars the price must remain below the buy threshold to trigger a Buy Signal. Default is 2.
IBS Buy Threshold: The IBS value below which a Buy Signal is triggered. Default is 0.2.
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed for mean-reverting markets and performs best when the price frequently deviates from its average high-low range.
It is sensitive to oversold conditions, as indicated by the IBS, which helps to identify potential reversals.
Backtesting results should be analyzed to optimize the Length, Bars Below Threshold, and IBS Buy Threshold parameters for specific instruments.
Turn of the Month Strategy on Steroids█ STRATEGY DESCRIPTION
The "Turn of the Month Strategy on Steroids" is a seasonal mean-reversion strategy designed to capitalize on price movements around the end of the month. It enters a long position when specific conditions are met and exits when the Relative Strength Index (RSI) indicates overbought conditions. This strategy is optimized for use on daily or higher timeframes.
█ WHAT IS THE TURN OF THE MONTH EFFECT?
The Turn of the Month effect refers to the observed tendency of stock prices to rise around the end of the month. This strategy leverages this phenomenon by entering long positions when the price shows signs of a reversal during this period.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The current day of the month is greater than or equal to the specified `dayOfMonth` threshold (default is 25).
The close price is lower than the previous day's close (`close < close `).
The previous day's close is also lower than the close two days ago (`close < close `).
The signal occurs within the specified time window (between `Start Time` and `End Time`).
There is no existing open position (`strategy.position_size == 0`).
2. EXIT CONDITION
A Sell Signal is generated when the 2-period RSI exceeds 65, indicating overbought conditions. This prompts the strategy to exit the position.
█ ADDITIONAL SETTINGS
Day of Month: The day of the month threshold for triggering a Buy Signal. Default is 25.
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed to exploit seasonal price patterns around the end of the month.
It performs best in markets where the Turn of the Month effect is pronounced.
Backtesting results should be analyzed to optimize the `dayOfMonth` threshold and RSI parameters for specific instruments.
Consecutive Bars Above/Below EMA Buy the Dip Strategy█ STRATEGY DESCRIPTION
The "Consecutive Bars Above/Below EMA Buy the Dip Strategy" is a mean-reversion strategy designed to identify potential buying opportunities when the price dips below a moving average for a specified number of consecutive bars. It enters a long position when the dip condition is met and exits when the price shows strength by exceeding the previous bar's high. This strategy is suitable for use on various timeframes.
█ WHAT IS THE MOVING AVERAGE?
The strategy uses either a Simple Moving Average (SMA) or an Exponential Moving Average (EMA) as a reference for identifying dips. The type and length of the moving average can be customized in the settings.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The close price is below the selected moving average for a specified number of consecutive bars (`consecutiveBarsTreshold`).
The signal occurs within the specified time window (between `Start Time` and `End Time`).
2. EXIT CONDITION
A Sell Signal is generated when the current closing price exceeds the high of the previous bar (`close > high `). This indicates that the price has shown strength, potentially confirming the reversal and prompting the strategy to exit the position.
█ ADDITIONAL SETTINGS
Consecutive Bars Threshold: The number of consecutive bars the price must remain below the moving average to trigger a Buy Signal. Default is 3.
MA Type: The type of moving average used (SMA or EMA). Default is SMA.
MA Length: The length of the moving average. Default is 5.
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed for mean-reverting markets and performs best when the price frequently oscillates around the moving average.
It is sensitive to the number of consecutive bars below the moving average, which helps to identify potential dips.
Backtesting results should be analysed to optimize the Consecutive Bars Threshold, MA Type, and MA Length for specific instruments.
