Hanover Insurance (Brazil) Technical Analysis
| THGI34 Stock | 460.00 0.00 0.00% |
Hanover Insurance Momentum Analysis
Momentum indicators are widely used technical indicators which help to measure the pace at which the price of specific equity, such as Hanover, fluctuates. Many momentum indicators also complement each other and can be helpful when the market is rising or falling as compared to HanoverHanover |
Hanover Insurance 'What if' Analysis
In the world of financial modeling, what-if analysis is part of sensitivity analysis performed to test how changes in assumptions impact individual outputs in a model. When applied to Hanover Insurance's stock what-if analysis refers to the analyzing how the change in your past investing horizon will affect the profitability against the current market value of Hanover Insurance.
| 11/04/2025 |
| 02/02/2026 |
If you would invest 0.00 in Hanover Insurance on November 4, 2025 and sell it all today you would earn a total of 0.00 from holding The Hanover Insurance or generate 0.0% return on investment in Hanover Insurance over 90 days.
Hanover Insurance Upside/Downside Indicators
Understanding different market momentum indicators often help investors to time their next move. Potential upside and downside technical ratios enable traders to measure Hanover Insurance's stock current market value against overall market sentiment and can be a good tool during both bulling and bearish trends. Here we outline some of the essential indicators to assess The Hanover Insurance upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.82) | |||
| Maximum Drawdown | 0.3885 |
Hanover Insurance Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Hanover Insurance's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Hanover Insurance's standard deviation. In reality, there are many statistical measures that can use Hanover Insurance historical prices to predict the future Hanover Insurance's volatility.| Risk Adjusted Performance | (0.05) | |||
| Jensen Alpha | (0) | |||
| Total Risk Alpha | (0.01) | |||
| Treynor Ratio | 2.74 |
Hanover Insurance February 2, 2026 Technical Indicators
| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
| Risk Adjusted Performance | (0.05) | |||
| Market Risk Adjusted Performance | 2.75 | |||
| Mean Deviation | 0.0116 | |||
| Coefficient Of Variation | 812.4 | |||
| Standard Deviation | 0.0478 | |||
| Variance | 0.0023 | |||
| Information Ratio | (0.82) | |||
| Jensen Alpha | (0) | |||
| Total Risk Alpha | (0.01) | |||
| Treynor Ratio | 2.74 | |||
| Maximum Drawdown | 0.3885 | |||
| Skewness | 8.12 | |||
| Kurtosis | 66.0 |
Hanover Insurance Backtested Returns
At this point, Hanover Insurance is very steady. Hanover Insurance holds Efficiency (Sharpe) Ratio of 0.13, which attests that the entity had a 0.13 % return per unit of risk over the last 3 months. We have found seventeen technical indicators for Hanover Insurance, which you can use to evaluate the volatility of the firm. Please check out Hanover Insurance's Risk Adjusted Performance of (0.05), standard deviation of 0.0478, and Market Risk Adjusted Performance of 2.75 to validate if the risk estimate we provide is consistent with the expected return of 0.0066%. Hanover Insurance has a performance score of 10 on a scale of 0 to 100. The company retains a Market Volatility (i.e., Beta) of -0.0015, which attests to not very significant fluctuations relative to the market. As returns on the market increase, returns on owning Hanover Insurance are expected to decrease at a much lower rate. During the bear market, Hanover Insurance is likely to outperform the market. Hanover Insurance right now retains a risk of 0.0506%. Please check out Hanover Insurance standard deviation, information ratio, maximum drawdown, as well as the relationship between the variance and jensen alpha , to decide if Hanover Insurance will be following its current trending patterns.
Auto-correlation | Huge |
Perfect predictability
The Hanover Insurance has perfect predictability. Overlapping area represents the amount of predictability between Hanover Insurance time series from 4th of November 2025 to 19th of December 2025 and 19th of December 2025 to 2nd of February 2026. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Hanover Insurance price movement. The serial correlation of 9.223372036854776E16 indicates that 9.223372036854776E16% of current Hanover Insurance price fluctuation can be explain by its past prices.
| Correlation Coefficient | 92233.7 T | |
| Spearman Rank Test | 1.0 | |
| Residual Average | 0.0 | |
| Price Variance | 0.0 |
Hanover Insurance technical stock analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, stock market cycles, or different charting patterns.
Hanover Insurance Technical Analysis
The output start index for this execution was twenty-four with a total number of output elements of thirty-seven. The Average True Range was developed by J. Welles Wilder in 1970s. It is one of components of the Welles Wilder Directional Movement indicators. The ATR is a measure of Hanover Insurance volatility. High ATR values indicate high volatility, and low values indicate low volatility.
Hanover Insurance February 2, 2026 Technical Indicators
Most technical analysis of Hanover help investors determine whether a current trend will continue and, if not, when it will shift. We provide a combination of tools to recognize potential entry and exit points for Hanover from various momentum indicators to cycle indicators. When you analyze Hanover charts, please remember that the event formation may indicate an entry point for a short seller, and look at different other indicators across different periods to confirm that a breakdown or reversion is likely to occur.
| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
| Risk Adjusted Performance | (0.05) | |||
| Market Risk Adjusted Performance | 2.75 | |||
| Mean Deviation | 0.0116 | |||
| Coefficient Of Variation | 812.4 | |||
| Standard Deviation | 0.0478 | |||
| Variance | 0.0023 | |||
| Information Ratio | (0.82) | |||
| Jensen Alpha | (0) | |||
| Total Risk Alpha | (0.01) | |||
| Treynor Ratio | 2.74 | |||
| Maximum Drawdown | 0.3885 | |||
| Skewness | 8.12 | |||
| Kurtosis | 66.0 |
Hanover Insurance February 2, 2026 Daily Trend Indicators
Traders often use several different daily volumes and price technical indicators to supplement a more traditional technical analysis when analyzing securities such as Hanover stock. With literally thousands of different options, investors must choose the best indicators for them and familiarize themselves with how they work. We suggest combining traditional momentum indicators with more near-term forms of technical analysis such as Accumulation Distribution or Daily Balance Of Power. With their quantitative nature, daily value technical indicators can also be incorporated into your automated trading systems.
| Accumulation Distribution | 0.00 | ||
| Daily Balance Of Power | 0.00 | ||
| Rate Of Daily Change | 1.00 | ||
| Day Median Price | 460.00 | ||
| Day Typical Price | 460.00 | ||
| Price Action Indicator | 0.00 |
Complementary Tools for Hanover Stock analysis
When running Hanover Insurance's price analysis, check to measure Hanover Insurance's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Hanover Insurance is operating at the current time. Most of Hanover Insurance's value examination focuses on studying past and present price action to predict the probability of Hanover Insurance's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Hanover Insurance's price. Additionally, you may evaluate how the addition of Hanover Insurance to your portfolios can decrease your overall portfolio volatility.
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