Northern Lights ETF Volatility
| HYTR ETF | USD 21.50 0.04 0.19% |
Sharpe Ratio = -0.0259
| Leading Returns | Top Quartile | |||
| Strong | ||||
| Moderate | ||||
| Modest | ||||
| Cash | Low | Moderate | Elevated | High |
| Below Benchmark | HYTR |
Northern Lights (HYTR) recorded a Market Risk Adjusted Performance of 0.7%, a Risk of 0.27, and a Risk Adjusted Performance of -0.04%. Based on monthly moving averages, the ETF is not performing at its full potential.
Key indicators related to Northern Lights' volatility include:90 Days Market Risk | Chance Of Distress | 90 Days Economic Sensitivity |
Key risk metrics for Northern Lights (3 Months):
Beta -0.02 | Alpha -0.01 | Risk 0.27 | Sharpe Ratio -0.03 | Expected Return -0.01 |
Moving together with Northern ETF
| 0.85 | UCON | First Trust TCW | PairCorr |
| 0.74 | AMAX | Starboard Investment | PairCorr |
| 0.65 | VPC | Virtus Private Credit | PairCorr |
| 0.77 | SSFI | Strategy Shares | PairCorr |
| 0.68 | HYIN | WisdomTree Alternative | PairCorr |
| 0.95 | PFFL | ETRACS 2xMonthly Pay | PairCorr |
| 0.7 | MDBX | Tradr 2X Long | PairCorr |
| 0.82 | GIGL | Goldman Sachs ETF | PairCorr |
| 0.71 | TSPA | T Rowe Price | PairCorr |
| 0.72 | AXP | American Express | PairCorr |
| 0.61 | BAC | Bank of America | PairCorr |
| 0.71 | PG | Procter Gamble | PairCorr |
| 0.61 | MSFT | Microsoft Earnings Call This Week | PairCorr |
| 0.85 | BA | Boeing | PairCorr |
Moving Against Northern ETF
Sensitivity To Market
Beta analysis for Northern Lights evaluates how its price movements correlate with the broader market. With a beta of -0.0208, Northern Lights reflects measurable exposure to systematic risk. Observed total volatility stands near 0.27%. Asymmetric risk in Northern Lights is visible through downside-focused metrics. Downside deviation reads 0.0% and semi-deviation reads 0.0%, isolating the loss-side component of total return variability. ETF volatility often reflects both the underlying basket and the trading layer. Premium/discount to NAV is often expressed as (Price − NAV) / NAV × 100 when NAV is available. Spread stability also shapes short-term movement.
3 Months Beta |Northern Lights Demand TrendCurrent 90-day Northern Lights correlation with market (Dow Jones Industrial)Downside Risk
The standard deviation reading for Northern summarizes how concentrated or dispersed daily returns have been around their mean. Volatile instruments have higher standard deviations; stable ones have lower. Comparing Northern standard deviation against sector peers reveals whether its volatility is typical or an outlier.
Standard Deviation | 0.27 |
Total price dispersion in Northern Lights captures both upside and downside movement. While standard deviation captures total volatility, downside deviation focuses exclusively on the loss side of Northern Lights' returns. A complete risk picture of Northern Lights emerges when standard deviation and downside deviation are examined together. Northern Lights (HYTR) recorded a Maximum Drawdown of 1.31.
ETF Volatility Analysis
Northern Lights ETF volatility is a measure of the speed and extent of Northern Lights' price movements. A higher-volatility ETF like Northern Lights may generate large gains or losses in a short timeframe. In most cases, the higher the volatility, the riskier the ETF.
Transformation |
This analysis covers sixty-one data points across the selected time horizon. The Average Price transformation calculates the mean of Northern Lights's open, high, low, and close for each trading period. By incorporating all four price components equally, it provides a balanced representation of each period's trading activity. Compared to using the closing price alone, the average price reduces the influence of end-of-day positioning and can serve as a smoother input for other technical indicators.
Projected Return Density Against Market
Given a 90-day horizon, Northern Lights has a beta of -0.0208. This usually indicates that as returns on the benchmark increase, returns on Northern Lights tend to move in the opposite direction, though by a smaller magnitude. During a bear market, however, Northern Lights tends to outperform the market.Systematic exposure aligns Northern Lights with broad ETF market volatility, while unsystematic drivers reflect company or sector-specific developments. Northern Lights (HYTR) recorded a Mean Deviation of 0.20 and a Standard Deviation of 0.27.
Predicted Return Distribution |
| Density |
What Drives Northern Lights' Price Volatility?
Holdings and Allocation
Concentration changes and sector rotation within the Nontraditional Bond category often influence how investors price Northern Lights' risk.Political and Economic Environment
Macro data and central-bank signals can change valuation assumptions and short-term positioning around Northern Lights.Northern Lights' Fund-Specific Factors
Creation and redemption activity, bid-ask spreads, and NAV premium or discount can trigger intraday volatility clusters.ETF Risk Measures
Given a 90-day horizon, the coefficient of variation of Northern Lights is -3861.39. The daily returns are distributed with a variance of 0.07 and standard deviation of 0.27. The mean deviation of Northern Lights is currently at 0.2. For similar time horizon, the selected benchmark (Dow Jones Industrial) has volatility of 0.94
α | Alpha over Dow Jones | -0.0146 | |
β | Beta against Dow Jones | -0.0208 | |
σ | Overall volatility | 0.27 | |
Ir | Information ratio | -0.0514 |
ETF Return Volatility
Daily return volatility for Northern Lights measures how far ETF returns deviate from their average on a day-to-day basis. The ETF shows 0.2705% volatility of returns over 90 trading days. For comparison, Dow Jones Industrial reported 0.9502% volatility on return distribution over a 90-day investment horizon. Performance |
| Timeline |
Related Correlations Analysis
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Correlation Matchups
Over a given time period, the two securities move together when the Correlation Coefficient is positive. Conversely, the two assets move in opposite directions when the Correlation Coefficient is negative. Determining your positions' relationship to each other is valuable for analyzing and projecting your portfolio's future expected return and risk.High positive correlations
| High negative correlations
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Northern Lights Constituents Risk-Adjusted Indicators
Evaluating Northern ETF requires separating price momentum from underlying operating strength versus competitors. Risk-adjusted metrics help compare Northern Lights' efficiency and downside exposure against peers on a like-for-like basis. These indicators are quantitative in nature and measure volatility and risk-adjusted expected returns across different positions.| Mean Deviation | Jensen Alpha | Sortino Ratio | Treynor Ratio | Semi Deviation | Expected Shortfall | Potential Upside | Value @Risk | Maximum Drawdown | ||
|---|---|---|---|---|---|---|---|---|---|---|
| GHYG | 0.29 | 0.00 | 0.00 | -0.03 | 0.34 | 0.61 | 1.67 | |||
| EDEN | 1.13 | -0.18 | 0.00 | -10.04 | 0.00 | 2.19 | 8.23 | |||
| GMOI | 0.80 | 0.12 | 0.11 | -0.66 | 0.90 | 1.77 | 4.42 | |||
| HEEM | 1.08 | 0.15 | 0.10 | -1.05 | 1.32 | 2.11 | 6.82 | |||
| FNK | 0.68 | 0.06 | 0.07 | -0.35 | 0.77 | 1.73 | 4.33 | |||
| AVXC | 1.32 | 0.19 | 0.10 | -1.13 | 1.69 | 2.74 | 7.62 | |||
| EPU | 2.05 | -0.04 | 0.00 | 0.23 | 0.00 | 3.61 | 10.83 | |||
| KMLM | 0.70 | 0.13 | 0.12 | -0.90 | 0.96 | 1.25 | 4.12 | |||
| FDEV | 0.75 | 0.04 | 0.04 | -0.29 | 1.06 | 1.54 | 4.34 | |||
| EWZS | 1.81 | 0.22 | 0.10 | -1.07 | 2.11 | 4.10 | 10.17 |
Risk Metrics, Assumptions & Methodology
Drawdown analysis for Northern Lights measures the largest peak-to-trough declines and their duration within the fund's price history. Position sizing should account for historical drawdown severity, not just average dispersion.
Northern Lights values are built from fund disclosures and market reference feeds, with reporting definitions aligned before display. Volatility and downside metrics are estimated from historical return dispersion.
Editorial review and methodology oversight provided by: Raphi Shpitalnik, Junior Member of Macroaxis Editorial Board
Northern Lights Volatility Profile Summary
Recent data suggests that Northern Lights is less volatile than Dow Jones Industrial by approximately 3.52x over the selected horizon. This differential reflects the relative dispersion of returns and frames how each asset responds to broader market conditions. Observed price behavior indicates modest directional movement within the current volatility regime. Across the current 90-day horizon, that places the security below 2% of the broader equity and portfolio universe on a pure volatility basis. This positioning reflects relative dispersion compared to peers rather than extreme instability.Northern Lights with characteristics aligned to broad market upside participation. This move summary looks at how the current session may translate into a basic near-term setup. It highlights whether the move looks ordinary, stressed, or unusually speculative for the instrument. a normal upward fluctuation. Return distributions derived from historical modeling outline a range of potential outcomes over the selected 90-day horizon. View Northern Lights probability analysis.
Very poor diversification
The correlation between Northern Lights and Dow Jones is 0.88, which Macroaxis classifies as Very poor diversification for the selected horizon. In portfolio terms, the overlap shows how much shared movement remains after combining both positions.
Northern Lights Additional Risk Indicators
Secondary risk indicators for Northern Lights evaluate exposure beyond standard deviation, beta, or one headline volatility measure. This is most informative when assessing whether the current opportunity is being compensated with reasonable risk.
| Risk Adjusted Performance | -0.04 | |||
| Market Risk Adjusted Performance | 0.7113 | |||
| Mean Deviation | 0.1954 | |||
| Coefficient Of Variation | -5,780 | |||
| Standard Deviation | 0.2651 | |||
| Variance | 0.0703 | |||
| Information Ratio | -0.05 |
Northern Lights Suggested Diversification Pairs
A pair-trading setup around Northern Lights shifts the return benchmark from the broad market to a second position, altering the risk profile. Pair trading is less about prediction in isolation and more about identifying relative mispricing between related positions.
Pair diversification lowers aggregate risk, though certain risk categories remain unaffected regardless of how positions are paired. Systematic risk - the risk tied to the broad market - cannot be eliminated by pairing Northern Lights with another position. However, Northern Lights' company-specific risk can be partially offset by selecting a pair that does not move in lockstep with Northern Lights.
More Resources for Northern ETF Analysis
Analysis of Northern Lights often begins with its portfolio holdings and historical return patterns. The following reports provide structured context for Northern Lights ETF:Diversification analysis starts with understanding how this position fits within a broader portfolio. The portfolio structure determines how individual positions contribute to the whole. Performance attribution across holdings reveals which positions drive aggregate returns. Broader economic conditions can influence Northern Lights's ETF valuation - related indicators include signals in manufacturing. For more information on Northern ETF please use our How to Invest in Northern Lights overview. It covers the key aspects of trading Northern ETF.Northern Lights analysis is best read alongside other ETF comparison and risk tools before adjusting allocations. The supplemental views below clarify how Northern Lights complements or overlaps with existing portfolio holdings. You can also try the Global Correlations module to find global opportunities by holding instruments from different markets.
Northern Lights can be assessed through both market price and NAV, which can tell different stories during volatile periods. Each measure contributes a different layer to the broad ETF evaluation.
Price and NAV for Northern Lights are related but not identical, and they can diverge during volatile periods. Context can include expense ratio, holdings concentration, performance attribution, and liquidity measures.