Springfield Properties Plc (SPR) - LSE

This chart represents support and resistance levels in a stock's price history, helping investors identify key price points where buying or selling pressure has historically influenced movement. It includes historical closing prices (blue line), major resistance and support levels, and the volume-weighted average price (VWAP), which reflects the average trading price based on volume. The highest resistance level marks a historical ceiling where prices have struggled to rise above, while the lowest support level highlights a historical floor where the price has found stability. The closest resistance level provides an immediate reference for potential upward movement.

Volume bars indicate the intensity of market activity, showing how much interest exists at different price levels. High volume near resistance suggests strong selling pressure, making further upward movement more difficult, while increased volume near support indicates buying interest, potentially preventing further declines. The VWAP serves as a benchmark to assess whether the stock is trading above or below its average market value over a given period.

For investors, this chart is a valuable tool for identifying long‑term price trends and assessing risk. Recognizing support and resistance levels helps investors make informed decisions about potential entry points, long‑term holding strategies, and areas where a stock may face challenges in maintaining its trend. By combining historical price movement with volume analysis, investors can better understand market sentiment and position their investments accordingly.

The Price Trend with SMAs Chart is a powerful tool for tracking price movements and identifying potential investment opportunities based on moving average analysis. This chart features closing prices (cyan line) overlaid with the 10-week simple moving average (SMA) (dashed white) and 30-week SMA (dashed yellow), providing insight into the stock’s trend direction over short and long-term periods. Moving averages help smooth out price fluctuations, making it easier to identify underlying trends and determine support and resistance levels.

The 10-week SMA represents short-term price movement and reacts more quickly to changes, making it useful for identifying early trend shifts. The 30-week SMA, on the other hand, is a longer-term trend indicator that provides a broader perspective on the stock’s overall trajectory. When the 10-week SMA crosses above the 30-week SMA, it suggests that momentum is shifting upward, potentially signaling an emerging uptrend. Conversely, when the 10-week SMA crosses below the 30-week SMA, it may indicate weakening momentum and the start of a downtrend.

A key feature of this chart is the Fair Value Line (purple dashed), representing an estimated price equilibrium based on historical data. The chart also integrates an experimental optimal buy signal, generated by a predictive model that assesses whether the stock has a higher probability of increasing in value over time. This model factors in historical price patterns, volume trends, and statistical probabilities to identify points where market conditions favor price appreciation. While experimental, this feature aims to provide investors with data-driven insights into potential long‑term value opportunities.

One of the standout tools in Sharemaestro is the Dynamic Momentum Indicator - an indicator designed to spot shifts in market sentiment. Powered by a highly accurate machine learning model (test MSE ~0.011194; R-squared ~0.885268, explaining about 88% of the variance in test data), it identifies early signals based on 17 key factors. The goal isn’t to predict every move but to highlight when something interesting is happening before the broader market catches on.

Unlike traditional momentum indicators that rely on rigid formulas, this system adapts dynamically to changing market conditions. It operates by analyzing historical price data and volume dynamics, recognizing patterns of accumulation and distribution. These are critical phases in a stock’s movement - accumulation (green signals) suggesting increased buying pressure and distribution (red signals) indicating heightened selling activity.

At the heart of this system is a proprietary machine learning model that continuously learns from past price behavior, refining its ability to detect emerging trends. Accumulation signals appear when the model identifies conditions historically linked to upward momentum - typically near the tail end of a downtrend, when institutions and informed investors start quietly buying in. Conversely, distribution signals emerge when the model spots subtle volume and price shifts that often precede a market peak, hinting that a stock’s strong run might be coming to an end.

The beauty of the Dynamic Momentum Indicator is that it cuts through the noise. It doesn’t follow hype or guess trends based on gut feeling - it works purely on data, helping investors stay ahead of the market by recognizing key inflection points before they become obvious.

Model Performance Overview:
Model Accuracy: The test MSE of ~0.0119 and an R-squared of ~0.879 indicate that the model explains about 88% of the variance in the test data, suggesting strong predictive performance.

The Volume Analysis Chart provides a detailed view of trading activity by analyzing buy and sell volume dynamics, combined with a 6‑week simple moving average (SMA) of volume and the mean volume level. This chart helps investors assess whether price movements are backed by strong market participation, giving insights into the sustainability of trends. The color‑coded volume bars distinguish between buying and selling pressure: green bars indicate buy volume, where the stock closed higher than it opened, while red bars represent sell volume, where the stock closed lower than it opened.

The 6‑week SMA (white line) smooths out short‑term fluctuations in trading volume, making it easier to identify persistent trends in market participation. When volume consistently remains above the SMA, it suggests heightened interest and liquidity, potentially confirming price movements. Conversely, declining volume below the SMA can signal fading momentum or reduced market engagement. The mean volume line (dashed purple) represents the long‑term average trading activity, serving as a benchmark for determining whether current volume levels are above or below historical norms.

By tracking buy and sell volume, investors can better understand market sentiment. A surge in buy volume with rising prices suggests strong accumulation and bullish momentum, while a spike in sell volume during a price decline indicates increased distribution and potential downside pressure.

The Relative Strength Index (RSI) Chart is a widely used momentum oscillator that measures the speed and magnitude of recent price movements to identify overbought and oversold conditions in a stock. The RSI value fluctuates between 0 and 100, with key thresholds set at 30 (oversold) and 70 (overbought), indicated by the shaded regions in the chart. When the RSI falls below 30, it suggests that the stock may be oversold and could be due for a rebound. Conversely, an RSI above 70 signals that the stock may be overbought, potentially indicating an overextended rally and an increased likelihood of a price pullback.

This chart visualizes the RSI trend over time, allowing investors to see how the stock's momentum has evolved. The cyan RSI line represents the stock’s relative strength based on historical price changes, helping investors determine if a stock is gaining or losing momentum. A declining RSI suggests that the stock is experiencing selling pressure, while a rising RSI indicates growing buying interest. However, RSI alone does not confirm trend reversals; it must be used alongside other indicators to validate potential turning points.

By tracking the RSI in relation to the oversold and overbought zones, investors can gauge potential buying and selling opportunities. If RSI enters the oversold zone and starts rising, it may indicate a potential buy signal, as selling pressure could be weakening. Similarly, if RSI moves into the overbought zone and begins to decline, it may suggest that the stock is losing momentum, signaling a possible sell opportunity. However, strong stocks can remain overbought for extended periods during strong uptrends, and weak stocks can stay oversold in prolonged downtrends, making confirmation with other indicators crucial.

The RSI Chart is valuable for investors looking to assess market momentum, trend strength, and potential reversals. It provides a data-driven approach to understanding whether a stock is experiencing excessive buying or selling pressure, helping investors time their decisions more effectively. When used in conjunction with volume analysis, mean reversion trends, or moving averages, RSI enhances an investor's ability to navigate market conditions with greater confidence.

The MACD (Moving Average Convergence Divergence) Chart is a widely used momentum indicator that helps investors identify changes in trend strength, direction, and potential reversals. This chart consists of three key components: the MACD Line (blue), the Signal Line (orange), and the MACD Histogram (green/red bars). The MACD line represents the difference between two exponential moving averages (typically the 12-period and 26-period EMAs), while the signal line is a smoothed version of the MACD line, usually calculated using a 9-period EMA. The MACD histogram visualizes the difference between these two lines, helping to highlight shifts in momentum.

When the MACD line crosses above the signal line, it generates a bullish signal, suggesting that upward momentum is strengthening, which may indicate a buying opportunity. Conversely, when the MACD line crosses below the signal line, it signals bearish momentum, potentially indicating a selling opportunity. The zero line (dashed) serves as a reference point; when MACD values are above zero, it suggests an overall uptrend, while negative MACD values indicate a broader downtrend. The histogram bars amplify this information by showing whether momentum is increasing (larger bars) or fading (smaller bars).

This chart is particularly useful in identifying trend shifts before they occur. When the MACD histogram moves from negative to positive, it suggests that downward momentum is weakening, and an uptrend may be forming. Conversely, when the histogram shifts from positive to negative, it indicates that an uptrend is losing strength, and a downtrend could be emerging. Strong MACD movements often align with significant price trends, while divergences between MACD and price movements can signal potential reversals.

For investors, the MACD Indicator is an essential tool for understanding market momentum and trend direction. By analyzing MACD crossovers, histogram changes, and overall movement relative to the zero line, investors can make more informed decisions about entering and exiting positions. It is especially effective when combined with other indicators, such as RSI or volume analysis, to confirm trend strength and reduce the risk of false signals.

The Bollinger Bands Chart is a volatility-based technical indicator that helps investors assess price movement relative to recent trends. It consists of three key components: the middle band (yellow line), which is a simple moving average (SMA) that represents the stock’s average price over a period, and the upper (red dashed) and lower bands (green dashed), which are calculated by adding and subtracting a multiple of the stock’s standard deviation from the middle band. These bands expand and contract based on market volatility, making them useful for identifying potential price extremes.

When prices approach or exceed the upper band, it suggests that the stock may be overbought, indicating heightened bullish momentum that could lead to a pullback or consolidation. Conversely, when prices near or drop below the lower band, it signals oversold conditions, suggesting that the stock may be undervalued and could experience a rebound. Prices tend to revert to the middle band over time, following the principle of mean reversion.

Periods of high volatility cause the bands to widen, indicating greater price fluctuations, while low volatility results in narrower bands, signaling a period of consolidation. A breakout beyond the bands may suggest the start of a new trend, while a reversal after touching a band may indicate a continuation of the current trend.

The Bollinger Bands Chart is a valuable tool for assessing price volatility, potential reversals, and trend strength. By monitoring the relationship between price and the bands, investors can determine whether a stock is likely to continue in its current direction, revert to its mean, or experience a breakout. It is particularly effective when combined with momentum indicators like RSI or MACD to confirm signals and enhance decision-making.

The Weekly Mean Reversion Trend Chart is a specialized analytical tool that visualizes how far a stock’s price deviates from its long-term mean in percentage terms, rather than absolute price values. Unlike traditional price charts that display raw stock prices over time, this chart focuses on the relative distance from the mean, providing a clearer picture of overextensions and undervaluations. The mean baseline (blue line) represents the average price over a given period, while the bars above and below it indicate the percentage deviation. Positive deviations (green) show when prices are trading above the mean, while negative deviations (red) highlight when prices fall below it.

This approach is valuable because percentage-based deviations allow investors to compare different stocks and time periods on a normalized scale, rather than relying on raw price differences that may be misleading. The chart is generated through a data-driven statistical model that continuously calculates the mean price and tracks the stock’s movement relative to it. The crossover count displayed on the chart represents the number of times the stock has moved above or below its mean, providing insight into how frequently it reverts to its average level. Since this process is entirely automated, it removes human bias and ensures that signals are based purely on objective market behavior.

Positive deviations (green) indicate that the stock is trading at a premium compared to its historical average, which may signal strong momentum but also suggests that prices could be overextended. In contrast, negative deviations (red) highlight periods where the stock is significantly below its mean, often indicating potential undervaluation or temporary market weakness. By tracking these deviations, investors can better identify opportunities where a stock is mispriced relative to its historical trend, offering strategic entry or exit points.

For investors, this chart serves as a mean reversion analysis tool, helping them determine whether a stock is likely to revert to its average price after a significant deviation. If a stock consistently returns to its mean after extreme moves, it suggests a stable, cyclical pattern that can be used to inform investment decisions. By incorporating percentage-based deviations instead of absolute price movements, this chart provides a more precise and comparative method for evaluating long-term price behavior, making it an essential tool for investors looking to capitalize on price reversion trends.

The Weekly Activity Index with Close Price chart is a sophisticated indicator designed to measure the combined effects of price and volume deviations in the stock market. Unlike traditional price charts, which only track price changes over time, this chart introduces a composite activity index, calculated by analyzing deviations in both price and trading volume. The index is displayed as positive (green) and negative (red) bars, with the close price (white line) overlaid to provide context. By combining these two critical market factors, the chart helps investors gauge whether price movements are supported by underlying activity or if they are occurring in isolation.

This composite activity index is derived from a weighted calculation of both price and volume deviations. The system first calculates the average distance of price movements from their mean (price reversion metrics) and the average deviation of volume activity from its mean (volume reversion metrics). These two elements are then normalized to ensure equal weighting, before being combined into a single index. The positive activity index (green bars) indicates periods where both price and volume deviations suggest increased market participation, potentially signaling strong investor confidence. Conversely, the negative activity index (red bars) highlights periods where deviations suggest market weakness or declining participation, often preceding downturns.

By overlaying this index with closing prices, investors gain a clearer picture of market behavior. For instance, if the stock price is rising but the activity index is decreasing, it may indicate that the upward trend is losing strength and could reverse. On the other hand, a rising activity index alongside price increases suggests a robust trend supported by strong volume and price movement. Similarly, when prices decline but activity levels remain elevated, it may indicate strong selling pressure, potentially prolonging a downtrend.

This chart is a powerful tool for understanding market momentum beyond simple price movements. It helps investors identify whether price action is backed by real market activity, allowing for better risk assessment and investment decision-making. By integrating price and volume dynamics, the Weekly Activity Index provides a data-driven approach to assessing trend strength, enabling investors to detect potential turning points with greater confidence.

The Weekly Volume Reversion Trend Chart is a mean reversion analysis tool that measures the percentage deviation of trading volume from its long-term average, rather than absolute volume figures. Unlike traditional volume charts that display raw trading activity, this chart normalizes volume fluctuations by showing how much volume differs from its mean in percentage terms. This approach makes it easier to compare different time periods and detect unusual spikes or drops in market participation, regardless of the stock’s absolute trading levels. The mean baseline (blue line) represents the historical average volume, and the bars indicate whether current volume is significantly above (positive deviation, green) or below (negative deviation, red) this level.

By using percentage-based deviations, this chart provides a clearer picture of relative volume shifts. Positive deviations (green bars) highlight periods where trading volume is significantly above the norm, often signaling strong market interest, accumulation, or speculative activity. These spikes can indicate growing investor enthusiasm or significant institutional involvement, reinforcing the strength of a price move. Conversely, negative deviations (red bars) indicate volume is well below its historical average, suggesting a lack of participation, weakening trend momentum, or declining liquidity. Extended periods of negative deviation may signal that investors are losing interest, leading to stagnation or trend reversals.

Tracking volume reversion trends helps investors determine whether a stock's price movements are backed by meaningful trading activity. If a stock is experiencing a strong price increase but volume remains below average (negative deviation), it could be a sign that the rally lacks broad support and may be unsustainable. On the other hand, if price increases are accompanied by high positive volume deviations, it suggests that the move is backed by real buying demand, increasing the likelihood of a sustained trend. The crossover count in the chart provides additional context by tracking how often volume moves above or below its mean, helping investors assess whether a stock's trading activity follows consistent patterns of reversion.

By incorporating percentage-based volume reversion analysis, investors gain a more precise and normalized view of market participation trends. This allows them to spot anomalies, confirm price trends, and identify potential reversals with greater confidence. Since volume reflects market conviction, this chart acts as a powerful complementary tool to price-based indicators, improving decision-making by highlighting whether current price trends are supported by strong or weak trading activity.

The ADX and DMI Indicator Chart is a technical analysis tool used to assess the strength and direction of a trend in financial markets. It consists of three key components: the Average Directional Index (ADX), which measures trend strength, and the Directional Movement Indicators (+DI and -DI), which determine whether a trend is predominantly bullish or bearish. Unlike traditional price-based indicators, the ADX and DMI focus on the momentum behind price movements, helping investors identify whether a trend is strong enough to follow or likely to reverse.

The ADX line quantifies the overall strength of a trend, with higher values indicating a stronger trend and lower values suggesting a weak or non-trending market. Readings above a certain threshold typically signal a strong trend, while values below indicate consolidation or range-bound conditions. However, the ADX does not indicate trend direction—this is determined by the +DI and -DI lines.

The +DI (Positive Directional Indicator) and -DI (Negative Directional Indicator) measure buying and selling pressure, respectively. When the +DI is above the -DI, it suggests that upward momentum is dominant, indicating a potential bullish trend. Conversely, when the -DI is above the +DI, selling pressure is stronger, signaling a bearish trend. Crossovers between these two lines often act as trend signals—when the +DI crosses above the -DI, it may suggest a shift to an uptrend, while a -DI crossover above the +DI can indicate a transition to a downtrend.

By analyzing the interaction between the ADX and DMI components, investors can determine whether a market is trending, how strong that trend is, and whether momentum is shifting. A rising ADX alongside a dominant +DI or -DI confirms a strong trend, while a declining ADX suggests weakening momentum, potentially signaling a period of consolidation or reversal. This indicator is particularly useful in trend-following strategies, helping investors stay in strong trends and avoid false breakouts in weak market conditions.

The Linear Regression Channel Chart is a statistical tool used to identify the overall trend of a stock and measure how far prices deviate from the expected trajectory. This chart consists of a linear regression line (dashed yellow), which represents the best-fit line through the price data, and two parallel channel boundaries (green and red) that define the upper and lower deviations from this central trend. These boundaries are typically set at two standard deviations (2σ) from the regression line, capturing a majority of price movements within the channel.

The regression line serves as an equilibrium price level, showing the general direction of the stock over time. When prices move toward the upper boundary, it suggests that the stock may be overextended relative to its historical trend, potentially signaling an overbought condition. Conversely, when prices approach the lower boundary, it may indicate an oversold condition, suggesting the possibility of mean reversion or a buying opportunity. The channel helps investors assess whether price action remains within its expected range or if it is experiencing abnormal volatility.

One of the key applications of the Linear Regression Channel is identifying trend direction and strength. A rising channel indicates an uptrend, where prices generally follow an upward trajectory, while a declining channel signals a downtrend. The width of the channel reflects volatility—wider channels indicate greater price fluctuations, while narrower channels suggest a more stable price movement. When prices break above or below the channel, it may indicate the start of a new trend or a potential breakout.

This chart is particularly useful for trend analysis, mean reversion strategies, and breakout identification. Investors can use it to determine whether prices are moving within a predictable range, identify potential buying or selling opportunities, and confirm trend strength. By combining the regression line, deviation boundaries, and historical price action, the Linear Regression Channel provides a data-driven approach to assessing price movement in relation to historical trends.

The Price Forecast Chart is a forward-looking analytical tool designed to estimate potential future price movements based on historical data. It provides two distinct types of projections: Linear Forecast (dashed yellow line) and Hybrid Forecast (solid green line). These forecasting models help investors gain insight into potential trends for the next 12 months, allowing for better strategic decision-making.

The Linear Forecast is a simple trend projection that extends the existing price trend into the future using a linear regression model. It assumes that past price movements will continue at a consistent rate, making it useful for identifying long-term directional tendencies. However, because it does not account for market fluctuations, it provides a general trajectory rather than dynamic predictions based on changing conditions.

The Hybrid Forecast incorporates additional factors beyond linear trends, such as market conditions, volatility, and statistical adjustments, to provide a more flexible and adaptive projection. This method allows for deviations from a strict linear path, adjusting for historical price behavior and potential shifts in momentum. It is designed to reflect more realistic market movements rather than assuming a straight-line continuation of past trends.

By combining both forecasting approaches, investors can compare basic trend expectations (Linear Forecast) with a more adaptive model (Hybrid Forecast) to gain a broader perspective on future price movements. This chart is particularly useful for long-term planning, risk management, and identifying possible trend shifts, offering a structured approach to evaluating future price potential while acknowledging both steady trends and dynamic market influences.

Mean reversion is the idea that prices, over time, tend to move back toward their historical average. Picture it like that one friend who always claims they’re done with social media, only to reappear two weeks later with a fresh profile picture. No matter how far they stray, they eventually come back to the mean.

So, what happens when we apply this concept to RSI? Enter the Relative Strength Mean Deviation (RSMD). Instead of just looking at the RSI in isolation, we measure how far it deviates from its own moving average. It's like not just tracking your heart rate but also seeing how far it deviates from your average resting heart rate. The spikes tell you something interesting is happening.

How Does RSMD Work?

We take the RSI, smooth it out with a moving average (let’s say over 14 periods), and then calculate the deviation between the current RSI and its moving average. This deviation is the RSMD. When the RSMD is significantly positive, it suggests the RSI is stretched to the upside—momentum might be overdone, and demand could be cooling off. Conversely, a negative RSMD indicates the RSI is lagging behind its average, hinting at oversold conditions and potential for a bounce.

The Smoothed Mean Reversion Index is an analytical tool that helps investors recognize when an asset is straying significantly from its usual behavior. It does this by combining three main components: the asset price, momentum measured by the Relative Strength Index, and trading volume. This balanced approach gives investors a clear perspective on how far an asset has deviated from its historical average.

The index first looks at the asset price by comparing it with its recent average to determine whether it is notably higher or lower than normal. It then examines momentum by using the Relative Strength Index to assess if the asset is moving strongly in one direction. Finally, it considers trading volume to evaluate market activity and provide additional context to the price and momentum information.

Each component is measured on a common scale and is given equal importance in the overall calculation. Price, momentum, and volume each contribute equally to the final value of the index. For investors, a high reading may suggest that an asset is overbought and a correction could be on the horizon, while a low reading may indicate that an asset is oversold and likely to rebound. This makes the index a useful guide for identifying potential entry and exit opportunities in the market.

The Adaptive MACD Fusion indicator is an advanced tool built on the foundation of the traditional MACD indicator. This function improves the standard calculation by adjusting its components according to current market conditions such as volatility and trading volume. It combines various market signals such as price momentum, volume trends, and volatility measures to create a technical indicator that is highly responsive to real market changes.

The process starts by calculating the standard MACD line using two exponential moving averages of closing prices. A faster moving average is compared with a slower one to derive this line. Next, the signal line is adjusted dynamically using a volatility factor obtained from the average range of price movements. In situations where market conditions are turbulent, the sensitivity of the signal line adapts to reduce the possibility of false alerts. In addition, the MACD line is modified by incorporating volume data so that the level of market participation is taken into account.

Investors can use this comprehensive indicator to enhance the timing of their market entries and exits. It is designed to detect shifts in market conditions when volatility increases or when trading volume deviates from the norm. The analysis also includes a comparison of price changes with the MACD line to uncover inconsistencies that might indicate a potential change in market trends. Finally, the indicator provides an adaptive reference line based on long-term trends to offer insight into overall market direction. This makes the Adaptive MACD Fusion a valuable addition to the technical analysis toolkit for any investor.