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Alpha Gauge

The TK Alpha Gauge is a proprietary, comprehensive daily updated indicator developed by Tradingkey that reflects our outlook on specific financial instruments. Utilizing a long-proven AI framework, the index analyzes hundreds of proprietary price-volume, fundamental, and alternative data predictors. Values range from -100 to 100. Negative values signify a bearish (pessimistic) outlook, while positive values indicate a bullish (optimistic) stance. The further the value from zero, the stronger the quantitative signal. It provides quantitative insight into directional forecasts.

The Alpha Score indicates mixed or insufficient market conviction. The strategy remains flat or maintains only limited exposure until a clearer directional signal emerges.

Neutral1.0x Long

Daily Alpha score

--Latest
--5 Days
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+527.15%Since Inception
-0.16%Today's Return
+27.06%Annualized
1.18Sharpe Ratio

Strategy vs GLD

Historical Return

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Relevant data have not been disclosed by the company yet.

What Is TradingKey Macro Alpha Signal?

TradingKey Macro Alpha Signal combines multiple independent sources of market information into a single daily Alpha Score. It transforms multi-factor market data—including macroeconomic indicators, technical analysis, price trends, volatility, and market-regime data—into clear quantitative trading signals for each supported asset.

The Alpha Score indicates both the expected market direction and the recommended level of exposure for the next trading day. Based on statistical evidence and predefined risk controls, the score is mapped to a clear long, flat, or short position.

Macro Alpha Signal currently supports selected exchange-traded funds (ETFs) and representative market assets, including QQQ, SPY, gold, silver, BTC, and ETH, across equities, commodities, and cryptocurrencies. View these multi-asset insights in one place to inform your market timing strategy.

Multi-Asset Trading Signal Directory

What you can verify before you act

01

Signal clarity

A daily TK Alpha Score ranging from -100 to +100, reflecting the strategy's directional conviction and target market exposure.
A positive score indicates long exposure, a negative score indicates short exposure, and a score near zero indicates a flat position.
The Alpha Score is recalculated once per trading day after all required market and factor data become available.

02

Performance evidence

Strategy performance is presented alongside an appropriate benchmark. The reporting framework includes:
- Strategy and benchmark cumulative-return curves
- Total strategy return
- Latest daily return
- Annualized return
- Sharpe ratio
These measures allow users to assess both absolute performance and risk-adjusted results.

03

Risk boundaries

The backtest begins in 2018 and covers supported instruments across equities, precious metals, and cryptocurrencies.
Signals are generated daily and implemented with a one-trading-day delay, excluding transaction costs, slippage, financing, borrowing costs, and market impact.
Strategy exposure ranges from -10× to +10×, subject to asset-specific leverage and risk controls.

Methodology

The strategy combines several independent sources of market information into a single daily Alpha Score.

It evaluates factor, macroeconomic, technical, trend, volatility, and market-regime evidence. The aggregated signal then passes through asset-class-specific scaling and risk controls before the resulting position is applied with a one-trading-day delay.

Multi-factor input

Price, volume, fundamentals, macroeconomic indicators, alternative data, technical signals, and market-regime information.

TK Alpha score

A daily score ranging from -100 to +100, representing the direction and strength of the strategy's conviction.

Exposure mapping

The Alpha Score is mapped to long, neutral, short, or leveraged exposure according to predefined score ranges and applicable risk controls.

Performance tracking

Performance is monitored using strategy return, daily return, annualized return, annualized volatility, and Sharpe ratio.

Stock Trading Signals FAQ

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What is TK Alpha Gauge?

The TK Alpha Gauge is a proprietary, daily updated indicator designed to provide a clear outlook on specific financial instruments. Developed by TradingKey, the gauge acts as a quantitative compass for market direction. Much like how sentiment indices track the "mood" of the market, the Alpha Gauge utilizes a long-proven AI framework to strip away emotional bias and provide a high-conviction forecast based on cold, hard data.

How is TK Alpha Gauge Calculated?

The Gauge is powered by a long-proven AI framework that analyzes hundreds of predictors across three categories: Price-Volume: Historical and real-time movement trends. Fundamentals: Underlying financial health and valuation metrics. Alternative Data: Unique datasets that capture non-traditional market signals. The final score represents the signal's strength; the further the value is from zero, the higher the quantitative conviction.

How often is TK Alpha Gauge calculated?

Every component and the Index are calculated as soon as new data becomes available daily.

How to use TK Alpha Gauge?

The Index serves as a systematic tool to remove emotional bias and determine position sizing. Depending on the asset and strategy, it can be applied in two primary ways: 1. Long-Only Strategy (e.g., GLD) Commonly used for ETFs like GLD, the gauge dictates exposure based only on positive momentum: Positive Reading: Scale long exposure proportionally to the gauge value. Negative Reading: Maintain a flat position (zero lots) to avoid downside risk. 2. Long/Short Strategy (e.g., Gold Futures) In highly liquid markets like gold futures, the gauge allows for active trading in both directions: Bullish (>0): Take a long position, scaling the size as the value moves toward 100. Bearish (<0): Take a short position, increasing the short exposure as the value moves toward -100. Neutral (0): Exit all positions to remain flat during periods of no clear signal.

What exactly is an "Alpha"?

An Alpha is a proprietary mathematical formula designed to identify and exploit specific market inefficiencies. Think of it as a quantitative "rule" that has demonstrated a historical ability to forecast price movements. By translating complex market patterns into actionable signals, Alpha provides the statistical edge necessary to consistently outperform the market.

How does AI improve the investment process?

Unlike static technical indicators, machine learning models recognize complex, non-linear patterns, allowing for more precise predictions of price movements in volatile markets. AI can facilitate the processing of massive dataset and synthesizes hundreds of high-performance predictors to generate meaningful trading signals. Adaptive models continuously learn from live market shifts, automatically tuning strategy parameters to maintain peak performance across different economic regimes.

How do you use Volume and Price together?

We analyze the relationship between price action and market participation (volume) to measure the conviction behind a move. Ideally, price and volume should trend in harmony. Our system is designed to monitor the synergy between these two variables. By identifying the periods of decoupling, our framework can proactively shift to a defensive posture, prioritizing capital preservation.

How does the "Super Alpha" ensemble help me?

Rather than relying on a single “rule”, the "Super Alpha" ensemble aggregates hundreds of diverse predictors across three distinct categories. This creates a robust system: If one predictor is skewed by temporary market noise, the remaining signals provide a stabilizing correction. This multi-predictor ensemble approach is designed to maintain portfolio resilience and steady performance, even during periods of high market volatility.

What are Deep Learning and Neural Networks?

Deep learning is a subset of machine learning that uses highly sophisticated artificial neural networks to model and replicate the way the human brain processes information. At its core, deep learning relies on multi-layered deep neural networks. These networks consist of interconnected nodes (called neurons) organized in multiple layers. Data flows through these layers in a highly connected manner, allowing the model to automatically learn complex patterns and representations from large amounts of data. This architecture makes deep learning particularly powerful for tasks such as prediction, classification, and pattern recognition.
Risk Warning:

Macro Alpha Signal is provided for informational and research purposes only and does not constitute investment advice, a recommendation, or an offer to buy or sell any financial instrument. Alpha Scores, trading signals and strategy performance are generated using quantitative models, historical data and backtested assumptions; they do not represent actual trading results and may not reflect future market conditions.

Signals are updated once daily after the required market and factor data become available; they are not real-time and may not reflect intraday market movements until the next scheduled update. Update timing may vary because of data availability, processing delays, market calendars or system interruptions.

Past performance and backtested results do not guarantee future results. Actual outcomes may differ materially due to execution delays, transaction costs, bid-ask spreads, slippage, financing and borrowing costs, liquidity constraints, data errors, model limitations, leverage limits, short-selling restrictions and other risk controls.

Long, short and leveraged exposure can amplify losses as well as gains and may result in the loss of some or all invested capital. Users should independently assess the methodology, assumptions, benchmark and risks, and consider their own investment objectives and risk tolerance before making any trading decision.

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