Graham Stock Market Value
| GHM Stock | USD 30.87 0.54 1.72% |
| Symbol | Graham |
Graham Price To Book Ratio
Is Industrial Machinery & Supplies & Components 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 Graham. If investors know Graham 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 Graham 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 8.143 | Earnings Share 0.81 | Revenue Per Share | Quarterly Revenue Growth 0.073 | Return On Assets |
The market value of Graham is measured differently than its book value, which is the value of Graham that is recorded on the company's balance sheet. Investors also form their own opinion of Graham's value that differs from its market value or its book value, called intrinsic value, which is Graham's 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 Graham's market value can be influenced by many factors that don't directly affect Graham's 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 Graham's value and its price as these two are different measures arrived at by different means. Investors typically determine if Graham is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Graham's 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.
Graham '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 Graham'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 Graham.
| 12/22/2024 |
| 03/22/2025 |
If you would invest 0.00 in Graham on December 22, 2024 and sell it all today you would earn a total of 0.00 from holding Graham or generate 0.0% return on investment in Graham over 90 days. Graham is related to or competes with Luxfer Holdings, Enerpac Tool, Kadant, Omega Flex, Helios Technologies, Enpro Industries, and Hurco Companies. Graham Corporation, together with its subsidiaries, designs and manufactures fluid, power, heat transfer, and vacuum equ... More
Graham 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 Graham'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 Graham upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.10) | |||
| Maximum Drawdown | 23.34 | |||
| Value At Risk | (6.47) | |||
| Potential Upside | 6.01 |
Graham Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Graham's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Graham's standard deviation. In reality, there are many statistical measures that can use Graham historical prices to predict the future Graham's volatility.| Risk Adjusted Performance | (0.1) | |||
| Jensen Alpha | (0.33) | |||
| Total Risk Alpha | (0.18) | |||
| Treynor Ratio | (0.22) |
Graham Backtested Returns
Graham holds Efficiency (Sharpe) Ratio of -0.0982, which attests that the entity had a -0.0982 % return per unit of standard deviation over the last 3 months. Graham exposes twenty-three different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please check out Graham's market risk adjusted performance of (0.21), and Risk Adjusted Performance of (0.1) to validate the risk estimate we provide. The company retains a Market Volatility (i.e., Beta) of 2.15, which attests to a somewhat significant risk relative to the market. As the market goes up, the company is expected to outperform it. However, if the market returns are negative, Graham will likely underperform. At this point, Graham has a negative expected return of -0.38%. Please make sure to check out Graham's standard deviation, kurtosis, period momentum indicator, as well as the relationship between the maximum drawdown and day median price , to decide if Graham performance from the past will be repeated at some point in the near future.
Auto-correlation | -0.42 |
Modest reverse predictability
Graham has modest reverse predictability. Overlapping area represents the amount of predictability between Graham time series from 22nd of December 2024 to 5th of February 2025 and 5th of February 2025 to 22nd of March 2025. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Graham price movement. The serial correlation of -0.42 indicates that just about 42.0% of current Graham price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.42 | |
| Spearman Rank Test | -0.37 | |
| Residual Average | 0.0 | |
| Price Variance | 21.69 |
Graham lagged returns against current returns
Autocorrelation, which is Graham 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 Graham's stock expected returns. We can calculate the autocorrelation of Graham returns to help us make a trade decision. For example, suppose you find that Graham 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 |
Graham 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 Graham stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Graham stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Graham stock over time.
Current vs Lagged Prices |
| Timeline |
Graham Lagged Returns
When evaluating Graham's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Graham stock have on its future price. Graham 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, Graham autocorrelation shows the relationship between Graham stock current value and its past values and can show if there is a momentum factor associated with investing in Graham.
Regressed Prices |
| Timeline |
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Try AI Portfolio ArchitectCheck out Graham Correlation, Graham Volatility and Graham Alpha and Beta module to complement your research on Graham. To learn how to invest in Graham Stock, please use our How to Invest in Graham guide.You can also try the ETF Categories module to list of ETF categories grouped based on various criteria, such as the investment strategy or type of investments.
Graham 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.