Ontology Market Value
| ONT Crypto | USD 0.41 0.02 4.65% |
| Symbol | Ontology |
Ontology '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 Ontology's crypto coin 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 Ontology.
| 03/26/2024 |
| 04/25/2024 |
If you would invest 0.00 in Ontology on March 26, 2024 and sell it all today you would earn a total of 0.00 from holding Ontology or generate 0.0% return on investment in Ontology over 30 days. Ontology is related to or competes with Ethereum, Cardano, Avalanche, Near, Internet Computer, Hedera Hashgraph, and Cronos. Ontology is peer-to-peer digital currency powered by the Blockchain technology.
Ontology 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 Ontology's crypto coin 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 Ontology upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 10.27 | |||
| Information Ratio | 0.1657 | |||
| Maximum Drawdown | 41.11 | |||
| Value At Risk | (12.12) | |||
| Potential Upside | 12.9 |
Ontology Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Ontology's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Ontology's standard deviation. In reality, there are many statistical measures that can use Ontology historical prices to predict the future Ontology's volatility.| Risk Adjusted Performance | 0.1207 | |||
| Jensen Alpha | 1.18 | |||
| Total Risk Alpha | 0.2929 | |||
| Sortino Ratio | 0.1161 | |||
| Treynor Ratio | 1.12 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Ontology's 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.
Ontology Backtested Returns
Ontology is unreasonably risky given 3 months investment horizon. Ontology maintains Sharpe Ratio (i.e., Efficiency) of 0.15, which implies digital coin had a 0.15% return per unit of risk over the last 3 months. We were able to interpolate and analyze data for twenty-nine different technical indicators, which can help you to evaluate if expected returns of 1.12% are justified by taking the suggested risk. Use Ontology Semi Deviation of 6.72, risk adjusted performance of 0.1207, and Coefficient Of Variation of 558.95 to evaluate coin specific risk that cannot be diversified away. The crypto holds a Beta of 1.14, which implies a somewhat significant risk relative to the market. Ontology returns are very sensitive to returns on the market. As the market goes up or down, Ontology is expected to follow.
Auto-correlation | 0.01 |
Virtually no predictability
Ontology has virtually no predictability. Overlapping area represents the amount of predictability between Ontology time series from 26th of March 2024 to 10th of April 2024 and 10th of April 2024 to 25th of April 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 Ontology price movement. The serial correlation of 0.01 indicates that just 1.0% of current Ontology price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.01 | |
| Spearman Rank Test | 0.24 | |
| Residual Average | 0.0 | |
| Price Variance | 0.0 |
Ontology lagged returns against current returns
Autocorrelation, which is Ontology crypto coin'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 Ontology's crypto coin expected returns. We can calculate the autocorrelation of Ontology returns to help us make a trade decision. For example, suppose you find that Ontology has exhibited high autocorrelation historically, and you observe that the crypto coin 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 |
Ontology 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 Ontology crypto coin is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Ontology crypto coin is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Ontology crypto coin over time.
Current vs Lagged Prices |
| Timeline |
Ontology Lagged Returns
When evaluating Ontology's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Ontology crypto coin have on its future price. Ontology 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, Ontology autocorrelation shows the relationship between Ontology crypto coin current value and its past values and can show if there is a momentum factor associated with investing in Ontology.
Regressed Prices |
| Timeline |
Some cryptocurrency investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. However, unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards Ontology in the overall investment community. So, suppose investors can accurately measure the crypto's market sentiment. In that case, they can use it for their benefit. For example, some tools provided by cryptocurrency exchanges to gauge market sentiment could be utilized to time the market in a somewhat predictable way.
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Try AI Portfolio ArchitectCheck out Ontology Correlation, Ontology Volatility and Investing Opportunities module to complement your research on Ontology. You can also try the Economic Indicators module to top statistical indicators that provide insights into how an economy is performing.
Ontology technical crypto coin 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, crypto market cycles, or different charting patterns.