Mogo Inc Stock Market Value
| MOGO Stock | CAD 2.05 0.04 1.99% |
| Symbol | Mogo |
Mogo Inc Price To Book Ratio
Mogo '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 Mogo'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 Mogo.
| 05/30/2024 |
| 11/26/2024 |
If you would invest 0.00 in Mogo on May 30, 2024 and sell it all today you would earn a total of 0.00 from holding Mogo Inc or generate 0.0% return on investment in Mogo over 180 days. Mogo is related to or competes with Telus Corp, Toronto Dominion, Manulife Financial, Canadian Natural, TC Energy, Athabasca Oil, and Bank of Nova Scotia. Mogo Inc. operates as a financial technology company in Canada More
Mogo 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 Mogo'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 Mogo Inc upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 3.04 | |||
| Information Ratio | 0.0599 | |||
| Maximum Drawdown | 32.13 | |||
| Value At Risk | (4.26) | |||
| Potential Upside | 10.45 |
Mogo Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Mogo's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Mogo's standard deviation. In reality, there are many statistical measures that can use Mogo historical prices to predict the future Mogo's volatility.| Risk Adjusted Performance | 0.0744 | |||
| Jensen Alpha | 0.1682 | |||
| Total Risk Alpha | (0.35) | |||
| Sortino Ratio | 0.0959 | |||
| Treynor Ratio | 0.2013 |
Mogo Inc Backtested Returns
Mogo appears to be dangerous, given 3 months investment horizon. Mogo Inc has Sharpe Ratio of 0.0904, which conveys that the firm had a 0.0904% return per unit of risk over the last 3 months. We have found twenty-nine technical indicators for Mogo, which you can use to evaluate the volatility of the firm. Please exercise Mogo's Risk Adjusted Performance of 0.0744, downside deviation of 3.04, and Mean Deviation of 3.07 to check out if our risk estimates are consistent with your expectations. On a scale of 0 to 100, Mogo holds a performance score of 7. The company secures a Beta (Market Risk) of 2.04, which conveys 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, Mogo will likely underperform. Please check Mogo's downside deviation, standard deviation, total risk alpha, as well as the relationship between the coefficient of variation and jensen alpha , to make a quick decision on whether Mogo's current price movements will revert.
Auto-correlation | -0.53 |
Good reverse predictability
Mogo Inc has good reverse predictability. Overlapping area represents the amount of predictability between Mogo time series from 30th of May 2024 to 28th of August 2024 and 28th of August 2024 to 26th of November 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 Mogo Inc price movement. The serial correlation of -0.53 indicates that about 53.0% of current Mogo price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.53 | |
| Spearman Rank Test | 0.15 | |
| Residual Average | 0.0 | |
| Price Variance | 0.05 |
Mogo Inc lagged returns against current returns
Autocorrelation, which is Mogo 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 Mogo's stock expected returns. We can calculate the autocorrelation of Mogo returns to help us make a trade decision. For example, suppose you find that Mogo 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 |
Mogo 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 Mogo stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Mogo stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Mogo stock over time.
Current vs Lagged Prices |
| Timeline |
Mogo Lagged Returns
When evaluating Mogo's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Mogo stock have on its future price. Mogo 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, Mogo autocorrelation shows the relationship between Mogo stock current value and its past values and can show if there is a momentum factor associated with investing in Mogo Inc.
Regressed Prices |
| Timeline |
Pair Trading with Mogo
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Mogo position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Mogo will appreciate offsetting losses from the drop in the long position's value.Moving against Mogo Stock
The ability to find closely correlated positions to Mogo could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Mogo when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Mogo - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Mogo Inc to buy it.
The correlation of Mogo is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Mogo moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Mogo Inc moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Mogo can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.Check out Mogo Correlation, Mogo Volatility and Mogo Alpha and Beta module to complement your research on Mogo. You can also try the Equity Valuation module to check real value of public entities based on technical and fundamental data.
Mogo 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.