Innodata Stock Price Prediction
| INOD Stock | USD 49.20 2.89 6.24% |
Momentum 55
Impartial
Oversold | Overbought |
Quarterly Earnings Growth 6.333 | EPS Estimate Next Quarter 0.21 | EPS Estimate Current Year 0.835 | EPS Estimate Next Year 1.23 | Wall Street Target Price 64.4 |
Using Innodata hype-based prediction, you can estimate the value of Innodata from the perspective of Innodata response to recently generated media hype and the effects of current headlines on its competitors. We also analyze overall investor sentiment towards Innodata using Innodata's stock options and short interest. It helps to benchmark the overall future attitude of investors towards Innodata using crowd psychology based on the activity and movement of Innodata's stock price.
Innodata Short Interest
A significant increase or decrease in Innodata's short interest from the previous month could be a good indicator of investor sentiment towards Innodata. Short interest can provide insight into the potential direction of Innodata stock and how bullish or bearish investors feel about the market overall.
200 Day MA 39.6227 | Short Percent 0.1388 | Short Ratio 1.67 | Shares Short Prior Month 4.7 M | 50 Day MA 45.1392 |
Innodata Hype to Price Pattern
Investor biases related to Innodata's public news can be used to forecast risks associated with an investment in Innodata. The trend in average sentiment can be used to explain how an investor holding Innodata can time the market purely based on public headlines and social activities around Innodata. Please note that most equities that are difficult to arbitrage are affected by market sentiment the most.
Some investors profit by finding stocks that are overvalued or undervalued based on market sentiment. The correlation of Innodata's market sentiment to its price can help taders to make decisions based on the overall investors consensus about Innodata.
Innodata Implied Volatility | 1.01 |
Innodata's implied volatility exposes the market's sentiment of Innodata stock's possible movements over time. However, it does not forecast the overall direction of its price. In a nutshell, if Innodata's implied volatility is high, the market thinks the stock has potential for high price swings in either direction. On the other hand, the low implied volatility suggests that Innodata stock will not fluctuate a lot when Innodata's options are near their expiration.
The fear of missing out, i.e., FOMO, can cause potential investors in Innodata to buy its stock at a price that has no basis in reality. In that case, they are not buying Innodata because the equity is a good investment, but because they need to do something to avoid the feeling of missing out. On the other hand, investors will often sell stocks at prices well below their value during bear markets because they need to stop feeling the pain of losing money.
Innodata after-hype prediction price | USD 50.36 |
There is no one specific way to measure market sentiment using hype analysis or a similar predictive technique. This prediction method should be used in combination with more fundamental and traditional techniques such as stock price forecasting, technical analysis, analysts consensus, earnings estimates, and various momentum models.
Prediction based on Rule 16 of the current Innodata contract
Based on the Rule 16, the options market is currently suggesting that Innodata will have an average daily up or down price movement of about 0.0631% per day over the life of the 2025-09-19 option contract. With Innodata trading at USD 49.2, that is roughly USD 0.0311 . If you think that the market is fully incorporating Innodata's daily price movement you should consider acquiring Innodata options at the current volatility level of 1.01%. But if you have an opposite viewpoint you should avoid it and even consider selling them.
Check out Innodata Basic Forecasting Models to cross-verify your projections. Innodata After-Hype Price Prediction Density Analysis
As far as predicting the price of Innodata at your current risk attitude, this probability distribution graph shows the chance that the prediction will fall between or within a specific range. We use this chart to confirm that your returns on investing in Innodata or, for that matter, your successful expectations of its future price, cannot be replicated consistently. Please note, a large amount of money has been lost over the years by many investors who confused the symmetrical distributions of Stock prices, such as prices of Innodata, with the unreliable approximations that try to describe financial returns.
Next price density |
| Expected price to next headline |
Innodata Estimiated After-Hype Price Volatility
In the context of predicting Innodata's stock value on the day after the next significant headline, we show statistically significant boundaries of downside and upside scenarios based on Innodata's historical news coverage. Innodata's after-hype downside and upside margins for the prediction period are 44.88 and 55.84, respectively. We have considered Innodata's daily market price in relation to the headlines to evaluate this method's predictive performance. Remember, however, there is no scientific proof or empirical evidence that news-based prediction models outperform traditional linear, nonlinear models or artificial intelligence models to provide accurate predictions consistently.
Current Value
Innodata is very steady at this time. Analysis and calculation of next after-hype price of Innodata is based on 3 months time horizon.
Innodata Stock Price Prediction Analysis
Have you ever been surprised when a price of a Company such as Innodata is soaring high without any particular reason? This is usually happening because many institutional investors are aggressively trading Innodata backward and forwards among themselves. Have you ever observed a lot of a particular company's price movement is driven by press releases or news about the company that has nothing to do with actual earnings? Usually, hype to individual companies acts as price momentum. If not enough favorable publicity is forthcoming, the Stock price eventually runs out of speed. So, the rule of thumb here is that as long as this news hype has nothing to do with immediate earnings, you should pay more attention to it. If you see this tendency with Innodata, there might be something going there, and it might present an excellent short sale opportunity.
| Expected Return | Period Volatility | Hype Elasticity | Related Elasticity | News Density | Related Density | Expected Hype |
0.55 | 5.48 | 1.16 | 0.04 | 11 Events / Month | 4 Events / Month | In about 11 days |
| Latest traded price | Expected after-news price | Potential return on next major news | Average after-hype volatility | ||
49.20 | 50.36 | 2.36 |
|
Innodata Hype Timeline
Innodata is currently traded for 49.20. The entity has historical hype elasticity of 1.16, and average elasticity to hype of competition of -0.04. Innodata is estimated to increase in value after the next headline, with the price projected to jump to 50.36 or above. The average volatility of media hype impact on the company the price is over 100%. The price growth on the next news is projected to be 2.36%, whereas the daily expected return is currently at 0.55%. The volatility of related hype on Innodata is about 8339.13%, with the expected price after the next announcement by competition of 49.16. Innodata currently holds 4.66 M in liabilities with Debt to Equity (D/E) ratio of 0.24, which may suggest the company is not taking enough advantage from borrowing. Given the investment horizon of 90 days the next estimated press release will be in about 11 days. Check out Innodata Basic Forecasting Models to cross-verify your projections.Innodata Related Hype Analysis
Having access to credible news sources related to Innodata's direct competition is more important than ever and may enhance your ability to predict Innodata's future price movements. Getting to know how Innodata's peers react to changing market sentiment, related social signals, and mainstream news is a great way to find investing opportunities and time the market. The summary table below summarizes the essential lagging indicators that can help you analyze how Innodata may potentially react to the hype associated with one of its peers.
| HypeElasticity | NewsDensity | SemiDeviation | InformationRatio | PotentialUpside | ValueAt Risk | MaximumDrawdown | |||
| BBAI | BigBearai Holdings | (0.44) | 8 per month | 4.05 | 0.21 | 20.58 | (7.80) | 34.85 | |
| NOTE | FiscalNote Holdings | 0.01 | 10 per month | 4.87 | 0.07 | 12.00 | (9.43) | 22.60 | |
| GDYN | Grid Dynamics Holdings | (0.26) | 8 per month | 0.00 | (0.18) | 4.74 | (4.73) | 16.58 | |
| ISSC | Innovative Solutions and | (0.21) | 9 per month | 1.66 | 0.26 | 8.36 | (3.71) | 39.02 | |
| KTCC | Key Tronic | 0.17 | 9 per month | 1.99 | 0.06 | 6.17 | (3.53) | 17.82 | |
| LDWY | Lendway | 0.23 | 5 per month | 3.74 | 0.07 | 7.39 | (5.86) | 24.73 | |
| III | Information Services Group | 0.04 | 8 per month | 1.83 | 0.07 | 4.20 | (3.26) | 20.73 |
Innodata Additional Predictive Modules
Most predictive techniques to examine Innodata price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Innodata using various technical indicators. When you analyze Innodata charts, please remember that the event formation may indicate an entry point for a short seller, and look at 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 |
About Innodata Predictive Indicators
The successful prediction of Innodata stock price could yield a significant profit to investors. But is it possible? The efficient-market hypothesis suggests that all published stock prices of traded companies, such as Innodata, already reflect all publicly available information. This academic statement is a fundamental principle of many financial and investing theories used today. However, the typical investor usually disagrees with a 'textbook' version of this hypothesis and continually tries to find mispriced stocks to increase returns. We use internally-developed statistical techniques to arrive at the intrinsic value of Innodata based on analysis of Innodata hews, social hype, general headline patterns, and widely used predictive technical indicators.
We also calculate exposure to Innodata's market risk, different technical and fundamental indicators, relevant financial multiples and ratios, and then comparing them to Innodata's related companies. | 2022 | 2023 | 2024 | 2025 (projected) | Days Sales Outstanding | 44.02 | 60.1 | 59.98 | 69.22 | PTB Ratio | 4.31 | 8.91 | 18.16 | 19.07 |
Story Coverage note for Innodata
The number of cover stories for Innodata depends on current market conditions and Innodata's risk-adjusted performance over time. The coverage that generates the most noise at a given time depends on the prevailing investment theme that Innodata is classified under. However, while its typical story may have numerous social followers, the rapid visibility can also attract short-sellers, who usually are skeptical about Innodata's long-term prospects. So, having above-average coverage will typically attract above-average short interest, leading to significant price volatility.
Contributor Headline
Latest Perspective From Macroaxis
Innodata Short Properties
Innodata's future price predictability will typically decrease when Innodata's long traders begin to feel the short-sellers pressure to drive the price lower. The predictive aspect of Innodata often depends not only on the future outlook of the potential Innodata's investors but also on the ongoing dynamics between investors with different trading styles. Because the market risk indicators may have small false signals, it is better to identify suitable times to hedge a portfolio using different long/short signals. Innodata's indicators that are reflective of the short sentiment are summarized in the table below.
| Common Stock Shares Outstanding | 32.2 M | |
| Cash And Short Term Investments | 46.9 M |
Complementary Tools for Innodata Stock analysis
When running Innodata's price analysis, check to measure Innodata'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 Innodata is operating at the current time. Most of Innodata's value examination focuses on studying past and present price action to predict the probability of Innodata's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Innodata's price. Additionally, you may evaluate how the addition of Innodata to your portfolios can decrease your overall portfolio volatility.
| Insider Screener Find insiders across different sectors to evaluate their impact on performance | |
| Commodity Directory Find actively traded commodities issued by global exchanges | |
| Cryptocurrency Center Build and monitor diversified portfolio of extremely risky digital assets and cryptocurrency | |
| Balance Of Power Check stock momentum by analyzing Balance Of Power indicator and other technical ratios | |
| My Watchlist Analysis Analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like | |
| Sectors List of equity sectors categorizing publicly traded companies based on their primary business activities | |
| Portfolio Manager State of the art Portfolio Manager to monitor and improve performance of your invested capital | |
| Portfolio Diagnostics Use generated alerts and portfolio events aggregator to diagnose current holdings | |
| FinTech Suite Use AI to screen and filter profitable investment opportunities |