White Mountains Insurance Stock Market Value
| WTM Stock | USD 1,971 47.98 2.50% |
| Symbol | White |
White Mountains Insurance Price To Book Ratio
Is Property & Casualty Insurance space expected to grow? Or is there an opportunity to expand the business' product line in the future? Factors like these will boost the valuation of White Mountains. If investors know White will grow in the future, the company's valuation will be higher. The financial industry is built on trying to define current growth potential and future valuation accurately. All the valuation information about White Mountains listed above have to be considered, but the key to understanding future value is determining which factors weigh more heavily than others.
Quarterly Earnings Growth 6.582 | Dividend Share 1 | Earnings Share 252.48 | Revenue Per Share 1.1 K | Quarterly Revenue Growth 0.835 |
The market value of White Mountains Insurance is measured differently than its book value, which is the value of White that is recorded on the company's balance sheet. Investors also form their own opinion of White Mountains' value that differs from its market value or its book value, called intrinsic value, which is White Mountains' true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because White Mountains' market value can be influenced by many factors that don't directly affect White Mountains' underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between White Mountains' value and its price as these two are different measures arrived at by different means. Investors typically determine if White Mountains is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, White Mountains' price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.
White Mountains '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 White Mountains' 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 White Mountains.
| 12/18/2023 |
| 12/12/2024 |
If you would invest 0.00 in White Mountains on December 18, 2023 and sell it all today you would earn a total of 0.00 from holding White Mountains Insurance or generate 0.0% return on investment in White Mountains over 360 days. White Mountains is related to or competes with NI Holdings, Donegal Group, Donegal Group, Hanover Insurance, RLI Corp, Chubb, and Progressive Corp. White Mountains Insurance Group, Ltd., through its subsidiaries, provides insurance and other financial services in the ... More
White Mountains 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 White Mountains' 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 White Mountains Insurance upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 1.07 | |||
| Information Ratio | 0.0415 | |||
| Maximum Drawdown | 8.76 | |||
| Value At Risk | (1.73) | |||
| Potential Upside | 2.5 |
White Mountains Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for White Mountains' investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as White Mountains' standard deviation. In reality, there are many statistical measures that can use White Mountains historical prices to predict the future White Mountains' volatility.| Risk Adjusted Performance | 0.098 | |||
| Jensen Alpha | 0.0444 | |||
| Total Risk Alpha | (0.05) | |||
| Sortino Ratio | 0.0554 | |||
| Treynor Ratio | 0.1538 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of White Mountains' price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
White Mountains Insurance Backtested Returns
White Mountains appears to be very steady, given 3 months investment horizon. White Mountains Insurance shows Sharpe Ratio of 0.16, which attests that the company had a 0.16% return per unit of risk over the last 3 months. We have found thirty technical indicators for White Mountains Insurance, which you can use to evaluate the volatility of the company. Please utilize White Mountains' Mean Deviation of 0.9816, market risk adjusted performance of 0.1638, and Downside Deviation of 1.07 to validate if our risk estimates are consistent with your expectations. On a scale of 0 to 100, White Mountains holds a performance score of 12. The firm maintains a market beta of 1.13, which attests to a somewhat significant risk relative to the market. White Mountains returns are very sensitive to returns on the market. As the market goes up or down, White Mountains is expected to follow. Please check White Mountains' maximum drawdown, as well as the relationship between the skewness and day typical price , to make a quick decision on whether White Mountains' historical returns will revert.
Auto-correlation | 0.27 |
Poor predictability
White Mountains Insurance has poor predictability. Overlapping area represents the amount of predictability between White Mountains time series from 18th of December 2023 to 15th of June 2024 and 15th of June 2024 to 12th of December 2024. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of White Mountains Insurance price movement. The serial correlation of 0.27 indicates that nearly 27.0% of current White Mountains price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.27 | |
| Spearman Rank Test | 0.25 | |
| Residual Average | 0.0 | |
| Price Variance | 7815.11 |
White Mountains Insurance lagged returns against current returns
Autocorrelation, which is White Mountains stock's lagged correlation, explains the relationship between observations of its time series of returns over different periods of time. The observations are said to be independent if autocorrelation is zero. Autocorrelation is calculated as a function of mean and variance and can have practical application in predicting White Mountains' stock expected returns. We can calculate the autocorrelation of White Mountains returns to help us make a trade decision. For example, suppose you find that White Mountains has exhibited high autocorrelation historically, and you observe that the stock is moving up for the past few days. In that case, you can expect the price movement to match the lagging time series.
Current and Lagged Values |
| Timeline |
White Mountains regressed lagged prices vs. current prices
Serial correlation can be approximated by using the Durbin-Watson (DW) test. The correlation can be either positive or negative. If White Mountains stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if White Mountains stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in White Mountains stock over time.
Current vs Lagged Prices |
| Timeline |
White Mountains Lagged Returns
When evaluating White Mountains' market value, investors can use the concept of autocorrelation to see how much of an impact past prices of White Mountains stock have on its future price. White Mountains autocorrelation represents the degree of similarity between a given time horizon and a lagged version of the same horizon over the previous time interval. In other words, White Mountains autocorrelation shows the relationship between White Mountains stock current value and its past values and can show if there is a momentum factor associated with investing in White Mountains Insurance.
Regressed Prices |
| Timeline |
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White Mountains 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.