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GBPAUD: Time to Sell?! 🇬🇧🇦🇺 GBPAUD nicely respected a supply zone based on a falling trend line and a horizontal resistance. A formation of a bearish imbalance candle on a 4H time frame after an extended consolidation leaves a strong bearish clue. I expect a retracement at least to 2.056 ❤️Please, support my work with like, thank you!❤️ I am part of Trade Nation's Influencer program and receive a monthly fee for using their TradingView charts in my analysis.
Short
by VasilyTrader
1
What Are Autoregressive Models in Trading?What Are Autoregressive Models in Trading? Autoregressive (AR) models help traders analyse market movements by identifying statistical relationships in historical price data. These models assume that past values influence current prices, making them useful for spotting trends and price behaviour. This article explores “What is autoregression?”, how AR models function, their role in trading, and how traders apply them to market analysis. What Is an Autoregressive Model? Autoregressive (AR) models are statistical tools that can be used in numerous spheres, including market prices, weather, and traffic conditions. They analyse market movements by using past price data to understand current trends. The autoregressive definition refers to a model where each value in a time series depends on previous values plus an error term. The number of previous values considered is called the “lag order,” denoted as AR(p), where ‘p’ represents the number of lags. In an autoregressive model example, an AR(1) model looks at just the previous value to estimate the current one, while an AR(3) model considers the last three. In trading, the key idea is that if historical prices show a consistent pattern—whether trending or reverting to a mean—an AR model can help identify that structure. This approach differs from other time series models. Moving averages (MA) smooth out fluctuations by averaging past prices, while autoregressive integrated moving averages (ARIMA) combine both approaches and adjust for trends. AR models, however, focus purely on the statistical relationship between past and present values, making them particularly useful in markets where past behaviour has a clear influence on future movements. Traders use an autoregressive process to explore trends, momentum, and potential reversals in markets that exhibit persistent patterns. However, their effectiveness depends on market conditions and the assumption that past relationships remain relevant—something that isn’t always guaranteed, especially in volatile or news-driven environments. How Autoregressive Models Work in Trading Traders use AR models to examine how past prices influence current movements. An autoregressive model trading strategy often involves assessing whether an asset’s price exhibits momentum or mean reversion tendencies. For example, if an AR(1) model shows that today’s price is strongly influenced by yesterday’s price, it may suggest a continuation bias—meaning traders could expect trends to persist in the short term. In contrast, if an AR(2) or AR(3) model highlights a tendency for prices to move back toward an average after a few periods, it could indicate mean reversion. This is particularly relevant in range-bound markets where prices frequently return to support and resistance levels. The number of past values included in an AR model is a key decision. Too few lags might miss relevant patterns, while too many can add unnecessary complexity. Traders typically determine the appropriate lag length by evaluating past data and statistical criteria like the Akaike Information Criterion (AIC). AR models are more popular in markets where historical relationships hold for extended periods. It’s common to use autoregressive models for trading forex, equities, and commodities, especially in detecting short-term trends or cycles. While they aren’t predictive tools, they provide a structured way to analyse price behaviour, offering traders a statistical foundation for evaluating market movements. Stationarity and Its Role in AR Models For an autoregressive time series model to work, the data must be stationary. This means the statistical properties of the time series—such as its mean, variance, and autocorrelation—remain constant over time. If a dataset is non-stationary, meaning its trends, volatility, or relationships shift unpredictably, the AR model's analysis can become unreliable. Why Stationarity Matters The autoregressive model, meaning it assumes a consistent statistical structure, can struggle with shifting market conditions if stationarity is not ensured. If a time series is non-stationary, it might show an upward or downward drift, meaning price relationships aren’t consistent over time. This makes it difficult to analyse patterns. For example, a stock experiencing long-term growth won’t have a stable mean, which can distort AR-based analysis. Testing for Stationarity Traders often check for stationarity using statistical tests like the Augmented Dickey-Fuller (ADF) test. This test helps determine whether a time series has a unit root—a key characteristic of non-stationary data. If the test suggests a unit root is present, traders may need to adjust the data before using an AR model. Transforming Data to Stationarity When data is non-stationary, traders often apply transformations to stabilise it and convert it to an autoregressive model time series. Differencing is a common method, where they subtract the previous value from the current value to remove trends. Log transformations can also reduce the impact of volatility. Once stationarity is achieved, an AR model is believed to be more effective to analyse price movements. Using an Autoregressive Model in Practice Understanding how autoregressive models work is one thing—actually applying them in trading is another. These models are primarily used in quantitative strategies, where traders rely on statistical methods rather than gut feelings or news events. While AR models aren’t a complete trading strategy on their own, they can provide valuable insights when used correctly. Building an AR Model The first step in using an AR model is preparing the data. Traders typically start with a time series dataset—such as daily closing prices—and ensure it is stationary. If the data shows trends or changing volatility, they may apply differencing or log transformations to stabilise it. Once the data is ready, the next step is determining the lag order—how many past values should be included in an AR(p) model. This is done through statistical tests like the Akaike Information Criterion (AIC) or Partial Autocorrelation Function (PACF), which help identify how far back price movements remain relevant. For instance, an AR1 model considers only the previous price point, while an AR3 model incorporates the last three observations. Choosing too few lags might miss important relationships, while too many can overcomplicate the model. After selecting the lag order, traders fit the AR model using statistical software such as Python’s statsmodels or R’s forecast package. The model estimates how past prices influence current ones, producing a set of coefficients that define these relationships. The trader then analyses these results to determine if the model aligns with market behaviour. Applying AR Models to Trading Once built, an AR model provides insights into how past price behaviour influences future movement. For example: - If an AR(1) model shows a strong positive coefficient, it suggests that today’s price is closely linked to yesterday’s, reinforcing a short-term trend. - If an AR(2) or AR(3) model suggests a return toward a long-term mean, it may indicate a market where price cycles are present. Traders use these insights in different ways. Some apply AR models to analyse short-term market momentum, while others use them to examine mean-reverting assets like certain forex pairs or commodities. They can also compare AR-based analysis with other indicators like moving averages or Bollinger Bands to refine their decision-making process. Autoregressive models are also used in machine learning for time series forecasting, helping algorithms detect patterns in sequential data. In trading, autoregressive model machine learning techniques can refine models by dynamically adjusting lag parameters, improving adaptability to changing market conditions and reducing reliance on fixed assumptions. ARIMA: Extending AR Models While AR models work well on stationary data, many financial time series contain trends or seasonality that a basic AR model can’t handle. This is a scenario where Autoregressive Integrated Moving Average (ARIMA) models become useful. ARIMA combines AR components with moving averages (MA) and differencing (I for “integrated”) to account for non-stationary behaviour. For example, if a stock price has an upward drift, an AR model alone won’t be sufficient. An ARIMA model can first remove the trend through differencing, and then apply AR and MA components to analyse underlying patterns. This makes ARIMA more flexible for complex market environments. Challenges and Considerations When Using AR Models Autoregressive models can be useful for analysing price movements, but they come with limitations that traders should consider. Financial markets are complex, and historical price patterns don’t always repeat in the same way. Understanding where AR models fall short might help traders apply them more effectively. Overfitting and Choosing the Right Lag Order One of the biggest challenges in using AR models is selecting the right lag order. Including too many past values can lead to overfitting, where the model becomes overly sensitive to historical fluctuations that may not be relevant going forward. Overfitting can create misleading analysis, making the model seem accurate in hindsight but ineffective in real-time market conditions. Traders typically balance complexity with statistical tests like the Akaike Information Criterion (AIC) to determine an optimal lag length. Market Noise and Unexpected Events AR forecasting assumes that past price relationships remain relatively consistent. However, financial markets are influenced by a wide range of external factors—economic reports, central bank decisions, and geopolitical events—that models based purely on past prices cannot account for. A market that has historically followed a trend can abruptly reverse due to news or institutional flows, reducing the usefulness of AR-based analysis. Data Quality and Stationarity The reliability of an AR model depends on the quality of the data used. Non-stationary data, sudden regime changes, or structural shifts in the market can distort results. Traders often need to check for stationarity and adjust their approach when market conditions change, ensuring that their models remain relevant rather than assuming past relationships always hold. The Bottom Line Autoregressive models offer traders a statistical approach to analysing price movements, helping them identify trends and market behaviour based on historical data. While they are not standalone trading signals, they can be valuable when combined with other analytical tools. FAQ What Is an Autoregressive Model? An autoregressive (AR) model is a type of statistical model that analyses time series data by expressing a variable as a function of its past values. It assumes that past observations influence current values, making it useful for identifying patterns in sequential data. What Is an Autoregressive Model in Finance? In finance, AR models are used to analyse price movements by examining historical data. Traders apply them to identify trends, momentum, or mean-reverting behaviour in assets like stocks, forex, and commodities. AR models help quantify how past price changes relate to current movements. What Is an Autoregressive Model for Stock Analysis? AR models in stock analysis assess price patterns by using historical data to determine potential relationships between past and present values. They can highlight statistical trends but do not account for external market drivers like news or economic events. This article represents the opinion of the Companies operating under the FXOpen brand only. It is not to be construed as an offer, solicitation, or recommendation with respect to products and services provided by the Companies operating under the FXOpen brand, nor is it to be considered financial advice.
Education
by FXOpen
1
GBPUSD Technical Breakdown – High-Probability Rejection Play📉 GBPUSD Technical Breakdown – High-Probability Rejection Play 🔥 Clean Structure | Strong Confluences | Smart Money Insight This GBPUSD setup is a textbook example of price action meeting institutional behavior. 🧠 Key Observations: • Break of Structure (BOS) identified multiple times confirming clear trend shifts. • Price tapped into a well-defined resistance zone and showed an aggressive rejection, validating seller presence. • Liquidity grab from the highs led to an immediate drop, marking the start of bearish momentum. 🎯 Target Zones: • First TP: 1.33009 • Second TP: 1.32375 • Final Target: 1.31443 (aligned with major support zone and BOS retest) 🛡 Why This Setup Matters: • Strong rejection from premium zone • BOS confirms direction • Volume and structure align for high RR potential • Clean imbalance fill expectations ✅ Plan: Sell from rejection zone with SL above the wick high. Trail stops as price approaches each target.
Short
by Mentor_Michael03
GBP/USD Professional Analysis – “Trap Trigger at Support”GBP/USD Professional Analysis – “Trap Trigger at Support” 📈 Market Overview: • Pair: GBP/USD • Timeframe: Likely 1H or 2H based on candle spacing • Date: July 28, 2025 • Current Price: 1.33529 ⸻ 🔍 Technical Breakdown 🔴 Resistance Zone: 1.35800 – 1.36200 • Strong supply area where the last bullish impulse failed. • Price got rejected hard, initiating a new downtrend. • Sell-side pressure was confirmed with Supertrend turning red. 🟤 Support Zone: 1.32860 – 1.33400 • Major demand area where price previously reversed sharply. • Currently being tested again after a clean sweep into the Trap Trigger zone. ⚠ Trap Trigger Zone (Liquidity Sweep Area): • Price wicked just below support, tapping into a low-volume/high-liquidity area. • This wick likely cleared sell-side liquidity and trapped breakout sellers. • Followed by a bullish rejection wick, implying smart money accumulation. ⸻ 🛠 Indicators & Tools: • Supertrend (10,3): Currently red, indicating short-term bearish momentum. • However, if price closes above 1.34032 (Supertrend level), it could flip bullish. • Volume Profile (VRVP): • Low-volume node under support suggests a quick “stop hunt” move, not genuine selling. • High-volume acceptance area sits higher, near 1.34500–1.35000. ⸻ 🎯 Forecast: 🔴 Bearish Invalidations: • Price closing below 1.32860 with volume would invalidate this setup. • That could signal continuation to deeper liquidity (1.32500 or below). ⸻ 🧠 Smart Money Perspective: • Liquidity engineered beneath support • Trap Trigger activated — ideal for institutional reversal setups • This is a classic “Stop Hunt → Reclaim → Expand” model
Long
by Mentor_Michael03
GBP/CAD (Two Trade Recaps) EUR/NZD Long and GBP/JPY LongEUR/NZD Long Minimum entry requirements: - If tight non-structured 15 min continuation forms, 5 min risk entry within it if the continuation is structured on the 5 min chart or reduced risk entry on the break of it. - If tight structured 15 min continuation forms, reduced risk entry on the break of it or 15 min risk entry within it. - If tight non-structured 1H continuation forms, 15 min risk entry within it if the continuation is structured on the 15 min chart or reduced risk entry on the break of it. - If tight structured 1H continuation forms, 1H risk entry within it or reduced risk entry on the break of it. GBP/JPY Long Minimum entry requirements: - Tap into area of value. - 1H impulse up above area of value. - If tight non-structured 15 min continuation follows, 5 min risk entry within it if the continuation is structured on the 5 min chart or reduced risk entry on the break of it. - If tight structured 15 min continuation follows, reduced risk entry on the break of it or 15 min risk entry within it.
Long
by StewySongs
Market next target 🚀 Bullish Disruption Analysis 1. Support Holds Above 35.80 The market may dip slightly but find strong support around the 35.90–36.00 zone. Instead of continuing lower, buyers absorb the selling pressure, leading to a sharp bullish reversal. 2. Bullish Continuation After Consolidation The current pullback could just be a healthy retracement following the strong recovery move from the previous dip. This could form a bullish flag or ascending triangle, eventually breaking above 36.20 and pushing higher. 3. Volume Clue If the pullback happens with declining red volume, while previous green candles had strong volume, it signals a temporary correction rather than a trend reversal. Watch for a bullish engulfing candle backed by strong volume to confirm. 4. Macro Trigger / Fundamental Support Any dovish signal from the Fed, rising inflation, or weakening USD could increase investor demand for silver, pushing prices back up. A news-driven reversal could invalidate the bearish path quickly. 5. Bullish Price Target If buyers take control, silver could retest and break above 36.30–36.40, aiming toward 36.60 or even 36.80.
TVC:SILVERLong
by Gold_Free_Signals
EUR/AUD Short, EUR/NZD Short, NZD/USD Long and AUD/NZD ShortEUR/AUD Short Minimum entry requirements: - If tight non-structured 1H continuation forms, 15 min risk entry within it if the continuation is structured on the 15 min chart or reduced risk entry on the break of it. - If tight structured 1H continuation forms, 1H risk entry within it or reduced risk entry on the break of it. EUR/NZD Short Minimum entry requirements: - If tight non-structured 1H continuation forms, 15 min risk entry within it if the continuation is structured on the 15 min chart or reduced risk entry on the break of it. - If tight structured 1H continuation forms, 1H risk entry within it or reduced risk entry on the break of it. NZD/USD Long Minimum entry requirements: - If tight non-structured 1H continuation forms, 15 min risk entry within it if the continuation is structured on the 15 min chart. - If tight structured 1H continuation forms, 1H risk entry within it. AUD/NZD Short Minimum entry requirements: - If tight non-structured 1H continuation forms, 15 min risk entry within it if the continuation is structured on the 15 min chart. - If tight structured 1H continuation forms, 1H risk entry within it.
by StewySongs
1
EUR/AUD ShortEUR/AUD Short Minimum entry requirements: - 1H impulse down below area of interest. - If tight non-structured 5 min continuation follows, reduced risk entry on the break of it. - If tight structured 5 min continuation follows, reduced risk entry on the break of it or 5 min risk entry within it. - If tight non-structured 15 min continuation follows, 5 min risk entry within it if the continuation is structured on the 5 min chart or reduced risk entry on the break of it. - If tight structured 15 min continuation follows, reduced risk entry on the break of it or 15 min risk entry within it.
Short
by StewySongs
Learn The Difference Between Beginner and Expert in Trading In the today's post, we will discuss the evolution of a mindset of a trader as he matures in trading. ✔️Beginner For some unknown reasons, beginners assume that a couple of educational videos and books about trading is more than enough to start trading successfully. They believe that they got a comprehensive knowledge and that very few things remain to learn. They start trading, but quickly realize that their knowledge is not enough to make even small gains. ✔️COMPETENT After practicing a couple of years, traders come to the conclusion that they know everything in that field. That they learned, tested and tried all concepts and techniques that are available. They consider themselves to be the experts in the field BUT for some unknown reasons, these traders still are not able to trade profitably. ✔️EXPERT After many years of learning, training and practicing, eyes finally open. Traders realize how limited is their knowledge and how much more there is to learn . While they already have the skills to trade in profits, they understand now that even the entire life is not enough to learn all the subtleties of trading. And here is a little lifehack for you: if you are a beginner, embrace a mindset of an expert. Start from realizing how little you actually know and how much more there is to know, that will help you a lot in your trading journey. ❤️Please, support my work with like, thank you!❤️ I am part of Trade Nation's Influencer program and receive a monthly fee for using their TradingView charts in my analysis.
TRADENATION:XAUUSDEducation
by VasilyTrader
10
EUR/USD Short and GBP/USD ShortEUR/USD Short Minimum entry requirements: - If tight non-structured 15 min continuation forms, 5 min risk entry within it if the continuation is structured on the 5 min chart or reduced risk entry on the break of it. - If tight structured 15 min continuation forms, reduced risk entry on the break of it or 15 min risk entry within it. - If tight non-structured 1H continuation forms, 15 min risk entry within it if the continuation is structured on the 15 min chart or reduced risk entry on the break of it. - If tight structured 1H continuation forms, 1H risk entry within it or reduced risk entry on the break of it. GBP/USD Short Minimum entry requirements: - If tight non-structured 1H continuation forms, 15 min risk entry within it if the continuation is structured on the 15 min chart. - If tight structured 1H continuation forms, 1H risk entry within it.
Short
by StewySongs
USD/CHF ShortUSD/CHF Short Minimum entry requirements: - Corrective tap into area of value. - 4H risk entry or 1H risk entry after 2 x 1H rejection candles. Minimum entry requirements: - Tap into area of value. - 1H impulse down below area of value. - If tight non-structured 5 min continuation follows, reduced risk entry on the break of it. - If tight structured 5 min continuation follows, reduced risk entry on the break of it or 5 min risk entry within it. - If tight non-structured 15 min continuation follows, 5 min risk entry within it if the continuation is structured on the 5 min chart or reduced risk entry on the break of it. - If tight structured 15 min continuation follows, reduced risk entry on the break of it or 15 min risk entry within it.
Short
by StewySongs
AUD/JPY Short, EUR/JPY Short, GBP/JPY Short and USD/CHF ShortAUD/JPY Short Minimum entry requirements: - 1H impulse down below area of value. - If tight non-structured 5 min continuation follows, reduced risk entry on the break of it. - If tight structured 5 min continuation follows, reduced risk entry on the break of it or 5 min risk entry within it. - If tight non-structured 15 min continuation follows, 5 min risk entry within it if the continuation is structured on the 5 min chart or reduced risk entry on the break of it. - If tight structured 15 min continuation follows, reduced risk entry on the break of it or 15 min risk entry within it. EUR/JPY Short Minimum entry requirements: - If structured 1H continuation forms, 1H risk entry within it. GBP/JPY Short Minimum entry requirements: - If tight non-structured 1H continuation forms, 15 min risk entry within it if the continuation is structured on the 15 min chart. - If tight structured 1H continuation forms, 1H risk entry within it. USD/CHF Short Minimum entry requirements: - Corrective tap into area of value. - 4H risk entry or 1H risk entry after 2 x 1H rejection candles. Minimum entry requirements: - Tap into area of value. - 1H impulse down below area of value. - If tight non-structured 5 min continuation follows, reduced risk entry on the break of it. - If tight structured 5 min continuation follows, reduced risk entry on the break of it or 5 min risk entry within it. - If tight non-structured 15 min continuation follows, 5 min risk entry within it if the continuation is structured on the 5 min chart or reduced risk entry on the break of it. - If tight structured 15 min continuation follows, reduced risk entry on the break of it or 15 min risk entry within it.
Short
by StewySongs
USD/JPY Short, AUD/NZD Short, AUD/JPY Neutral and EUR/USD ShortUSD/JPY Short Minimum entry requirements: - If tight non-structured 5 min continuation forms, reduced risk entry on the break of it. - If tight structured 5 min continuation forms, reduced risk entry on the break of it or 5 min risk entry within it. - If tight non-structured 15 min continuation forms, 5 min risk entry within it if the continuation is structured on the 5 min chart or reduced risk entry on the break of it. - If tight structured 15 min continuation forms, reduced risk entry on the break of it or 15 min risk entry within it. AUD/NZD Short Minimum entry requirements: - If tight non-structured 15 min continuation forms, 5 min risk entry within it if the continuation is structured on the 5 min chart or reduced risk entry on the break of it. - If tight structured 15 min continuation forms, reduced risk entry on the break of it or 15 min risk entry within it. AUD/JPY Neutral Minimum entry requirements: - If structured 1H continuation forms, 1H risk entry within it. Minimum entry requirements: - 1H impulse down below area of value. - If tight non-structured 5 min continuation follows, reduced risk entry on the break of it. - If tight structured 5 min continuation follows, reduced risk entry on the break of it or 5 min risk entry within it. - If tight non-structured 15 min continuation follows, 5 min risk entry within it if the continuation is structured on the 5 min chart or reduced risk entry on the break of it. - If tight structured 15 min continuation follows, reduced risk entry on the break of it or 15 min risk entry within it. EUR/USD Short Minimum entry requirements: - Tap into area of value. - 1H impulse down below area of value. - If tight non-structured 15 min continuation follows, 5 min risk entry within it if the continuation is structured on the 5 min chart or reduced risk entry on the break of it. - If tight structured 15 min continuation follows, reduced risk entry on the break of it or 15 min risk entry within it.
by StewySongs
2
Market next move 🧨 Disruption Points: 1. Overbought Condition / RSI Divergence Even though the price is surging (+3.30%), there could be an overbought condition forming. If RSI or other momentum indicators (not shown here) diverge, it might signal weakness in bullish momentum. > Disruptive idea: Price may fake the breakout (blue arrow) and then sharply reverse, trapping late buyers. --- 2. False Breakout Trap The red-box area could be a liquidity zone where smart money might induce a fake breakout before dumping. > Alternative path: Price breaks above temporarily (as in blue path), but then reverses violently back into the range, forming a “bull trap.” --- 3. Volume Anomaly The volume appears to be decreasing on recent bullish candles after the initial spike. This suggests that the uptrend may be losing strength, making the yellow arrow scenario less likely. > Contrary outlook: Lack of volume confirmation could mean a sideways consolidation or reversal is more probable.
TVC:SILVERLong
by Gold_Free_Signals
Market next move 🔻 Disruptive Bearish Analysis: 🧱 1. Failed Breakout Attempt Price is hovering at resistance but showing indecisive candles (small bodies, wicks on both sides). This hints at buyer exhaustion rather than breakout momentum. 📉 2. Bearish Divergence (Possible) If momentum indicators (e.g., RSI or MACD—not shown here) are diverging from price, it could signal a reversal. Price rising while momentum flattens or drops suggests a fakeout is likely. 🕳️ 3. Liquidity Grab Trap The chart may show a classic “bull trap”: Price broke resistance briefly but quickly fell back. This signals institutional liquidity grab, possibly before a downward push. 🔽 4. Volume Imbalance The spike in volume earlier may be followed by decreasing bullish volume, indicating weak follow-through. Sellers could take over if bulls can’t sustain pressure.
Long
by Gold_Free_Signals