Monte Carlo Backtest Methodologies

Monte Carlo Backtest Methodologies






<link rel="canonical" href="https://www.example.com/monte-carlo-backtest-methodologies" /> </head><br /> <body></p> <p>Monte Carlo backtesting stands as a disciplined way to evaluate trading ideas by simulating a wide range of market paths. It embraces randomness to explore outcomes beyond the observed history. This educational overview focuses on definitions, mechanics, and the market context that surrounds these methods.</p> <p>In financial markets, backtesting has long relied on historical data to judge strategy viability. Monte Carlo methods offer a forward-looking complement by generating synthetic scenarios that stress different paths. As of 2026, advancements in computing have made these simulations more accessible and more nuanced for practitioners across asset classes.</p><div class='code-block code-block-2' style='margin: 8px auto; text-align: center; display: block; clear: both;'> <script async src="https://pagead2.googlesyndication.com/pagead/js/adsbygoogle.js?client=ca-pub-1130848125502204" crossorigin="anonymous"></script> <!-- Content --> <ins class="adsbygoogle" style="display:block" data-ad-client="ca-pub-1130848125502204" data-ad-slot="4736459886" data-ad-format="auto" data-full-width-responsive="true"></ins> <script> (adsbygoogle = window.adsbygoogle || []).push({}); </script></div> <p>This article traces core concepts, explains how the simulations operate, and connects those ideas to the evolution of markets and market data. We outline common methodologies, data considerations, and practical guidelines. The goal is to clarify how Monte Carlo backtesting fits within a broader risk and strategy framework.</p> <h2 id="sec_0" style="font-family: 'Poppins', sans-serif !important; font-weight: 800 !important; color: #000000 !important; border-left: 10px solid #6366f1 !important; padding: 10px 20px !important; background: #f1f5f9 !important; margin-top: 50px !important; text-transform: uppercase !important; border-bottom: none !important; line-height: 1.2 !important;"><b>What Is Monte Carlo Backtesting?</b></h2> <p><strong>Monte Carlo</strong> backtesting is a framework that uses stochastic sampling to assess how a trading idea would perform under many possible future states. It does not rely on a single historical path but on a distribution of potential outcomes. This approach helps quantify uncertainty and reveals tail risks that historical backtests might miss.</p> <p>At its core, the method involves modeling the source of randomness in returns, prices, and market dynamics. The backtest runs numerous simulations, each using different random seeds and parameter realizations. The aggregate results deliver a probabilistic picture of performance, drawdowns, and risk exposures.</p><div class='code-block code-block-2' style='margin: 8px auto; text-align: center; display: block; clear: both;'> <script async src="https://pagead2.googlesyndication.com/pagead/js/adsbygoogle.js?client=ca-pub-1130848125502204" crossorigin="anonymous"></script> <!-- Content --> <ins class="adsbygoogle" style="display:block" data-ad-client="ca-pub-1130848125502204" data-ad-slot="4736459886" data-ad-format="auto" data-full-width-responsive="true"></ins> <script> (adsbygoogle = window.adsbygoogle || []).push({}); </script></div> <p>For practitioners, Monte Carlo backtesting provides a way to test robustness across regimes. It can incorporate multi-asset interactions, liquidity constraints, and transaction costs under varied conditions. The result is a more resilient understanding of how a strategy might fare in the real world.</p> <h2 id="sec_1" style="font-family: 'Poppins', sans-serif !important; font-weight: 800 !important; color: #000000 !important; border-left: 10px solid #6366f1 !important; padding: 10px 20px !important; background: #f1f5f9 !important; margin-top: 50px !important; text-transform: uppercase !important; border-bottom: none !important; line-height: 1.2 !important;"><b>Mechanics and Variants</b></h2> <p>To implement Monte Carlo backtesting, one must specify how random paths are generated and how a strategy reacts to those paths. Common steps include defining a return distribution, selecting a time step, and deciding how to simulate correlations across assets. The combination of these choices shapes the realism and usefulness of the results.</p> <p>Different variants emphasize distinct aspects of market behavior. Parametric approaches rely on assumed distributions like normal or heavy-tailed forms. Non-parametric methods use resampling from historical data to preserve empirical patterns without imposing strict distributional assumptions. Both families have strengths and trade-offs.</p><div class='code-block code-block-2' style='margin: 8px auto; text-align: center; display: block; clear: both;'> <script async src="https://pagead2.googlesyndication.com/pagead/js/adsbygoogle.js?client=ca-pub-1130848125502204" crossorigin="anonymous"></script> <!-- Content --> <ins class="adsbygoogle" style="display:block" data-ad-client="ca-pub-1130848125502204" data-ad-slot="4736459886" data-ad-format="auto" data-full-width-responsive="true"></ins> <script> (adsbygoogle = window.adsbygoogle || []).push({}); </script></div> <p>In practice, Monte Carlo backtesting blends several elements: stochastic processes for price evolution, sampling methods for uncertain inputs, and a defined trading rule with clear entry and exit signals. The approach often includes rebalancing logic, liquidity frictions, and execution costs to reflect market realities. The combination yields a rich performance landscape rather than a single outcome.</p> <h3 style="font-family: 'Poppins', sans-serif !important; font-weight: 700 !important; color: #000000 !important; border-bottom: none !important; margin-top: 35px !important; padding-bottom: 0px !important; text-transform: capitalize !important;"><b>Sampling Methods</b></h3> <p>Parametric sampling draws random returns from specified distributions with set parameters. This makes the process transparent and fast, but it can misrepresent extreme events if the chosen distribution is too simple. Analysts may adjust tail behavior to better capture rare but impactful moves.</p> <p>Bootstrap and resampling methods rely on empirical data. They preserve observed dependencies and nonlinearities but may underrepresent unseen regimes. Hybrid techniques mix empirical data with parametric scaffolds to balance realism and extrapolation capability.</p><div class='code-block code-block-2' style='margin: 8px auto; text-align: center; display: block; clear: both;'> <script async src="https://pagead2.googlesyndication.com/pagead/js/adsbygoogle.js?client=ca-pub-1130848125502204" crossorigin="anonymous"></script> <!-- Content --> <ins class="adsbygoogle" style="display:block" data-ad-client="ca-pub-1130848125502204" data-ad-slot="4736459886" data-ad-format="auto" data-full-width-responsive="true"></ins> <script> (adsbygoogle = window.adsbygoogle || []).push({}); </script></div> <p>Time series models, such as ARIMA or GARCH variants, introduce autocorrelation and volatility dynamics into simulations. These models can mimic clustering of volatility and momentum effects that matter for strategy performance. When used carefully, they add realism without overfitting.</p> <h3 style="font-family: 'Poppins', sans-serif !important; font-weight: 700 !important; color: #000000 !important; border-bottom: none !important; margin-top: 35px !important; padding-bottom: 0px !important; text-transform: capitalize !important;"><b>Scenario Generation</b></h3> <p>Scenario generation defines the paths that market variables follow within each simulation. Scenarios can vary by drift, volatility calibration, and regime shifts. Practitioners often design scenarios to stress test strategies against crashes, volatility surges, and liquidity shocks.</p> <p>Beyond single-asset simulations, multi-asset or portfolio-level scenarios explore correlation structures and contagion effects. Time-varying correlations and regime-switching models help capture how assets move together in crisis periods. The richer the scenario set, the more informative the backtest becomes.</p><div class='code-block code-block-2' style='margin: 8px auto; text-align: center; display: block; clear: both;'> <script async src="https://pagead2.googlesyndication.com/pagead/js/adsbygoogle.js?client=ca-pub-1130848125502204" crossorigin="anonymous"></script> <!-- Content --> <ins class="adsbygoogle" style="display:block" data-ad-client="ca-pub-1130848125502204" data-ad-slot="4736459886" data-ad-format="auto" data-full-width-responsive="true"></ins> <script> (adsbygoogle = window.adsbygoogle || []).push({}); </script></div> <h3 style="font-family: 'Poppins', sans-serif !important; font-weight: 700 !important; color: #000000 !important; border-bottom: none !important; margin-top: 35px !important; padding-bottom: 0px !important; text-transform: capitalize !important;"><b>Data Considerations</b></h3> <p>Data quality and representativeness are central to credible Monte Carlo backtests. Historical data informs empirical distributions, volatilities, and correlation patterns used in simulations. Data cleaning, synchronization, and bias avoidance are essential steps in the preparation process.</p> <p>Calibration plays a crucial role: parameter choices should be justified by theory and validated with out-of-sample tests. Overfitting remains a risk when backtests tailor parameters too closely to a given dataset. Clear documentation helps auditors assess methodological soundness.</p> <h2 id="sec_2" style="font-family: 'Poppins', sans-serif !important; font-weight: 800 !important; color: #000000 !important; border-left: 10px solid #6366f1 !important; padding: 10px 20px !important; background: #f1f5f9 !important; margin-top: 50px !important; text-transform: uppercase !important; border-bottom: none !important; line-height: 1.2 !important;"><b>Historical Context: Market Evolution and Computational Foundations</b></h2> <p>The idea of testing ideas under uncertainty has long accompanied the evolution of markets. Early backtests relied heavily on past price trajectories and qualitative reasoning about risk. As markets grew more complex, practitioners sought quantitative frameworks that could quantify probability and capture variability across paths.</p><div class='code-block code-block-2' style='margin: 8px auto; text-align: center; display: block; clear: both;'> <script async src="https://pagead2.googlesyndication.com/pagead/js/adsbygoogle.js?client=ca-pub-1130848125502204" crossorigin="anonymous"></script> <!-- Content --> <ins class="adsbygoogle" style="display:block" data-ad-client="ca-pub-1130848125502204" data-ad-slot="4736459886" data-ad-format="auto" data-full-width-responsive="true"></ins> <script> (adsbygoogle = window.adsbygoogle || []).push({}); </script></div> <p>The Monte Carlo method itself has roots in the mid-20th century, with breakthroughs in physics and statistics. Its adoption in finance accelerated during the development of derivative pricing and risk management. In the ensuing decades, academics and industry professionals blended stochastic calculus with data-driven testing to address real-world decisions.</p> <p>Over time, market structure changes shaped how backtests are evaluated. The rise of high-frequency trading, cross-asset interdependencies, and liquidity-focused risks required more sophisticated simulation models. By the 2000s and into the 2020s, Monte Carlo backtesting had become a standard tool in risk departments and quant shops. In 2026, cloud computing and scalable software further democratized access to these techniques.</p> <h2 id="sec_3" style="font-family: 'Poppins', sans-serif !important; font-weight: 800 !important; color: #000000 !important; border-left: 10px solid #6366f1 !important; padding: 10px 20px !important; background: #f1f5f9 !important; margin-top: 50px !important; text-transform: uppercase !important; border-bottom: none !important; line-height: 1.2 !important;"><b>Core Methodologies and Practical Considerations</b></h2> <p>Effective Monte Carlo backtesting rests on thoughtful modeling choices and transparent reporting. The most important steps are to select appropriate input distributions, manage correlations, and define robust performance metrics. Clear assumptions help stakeholders interpret results and judge reliability.</p><div class='code-block code-block-2' style='margin: 8px auto; text-align: center; display: block; clear: both;'> <script async src="https://pagead2.googlesyndication.com/pagead/js/adsbygoogle.js?client=ca-pub-1130848125502204" crossorigin="anonymous"></script> <!-- Content --> <ins class="adsbygoogle" style="display:block" data-ad-client="ca-pub-1130848125502204" data-ad-slot="4736459886" data-ad-format="auto" data-full-width-responsive="true"></ins> <script> (adsbygoogle = window.adsbygoogle || []).push({}); </script></div> <p>In multi-asset contexts, modeling the joint distribution of returns is crucial. Time-varying correlations and regime shifts often drive tail risk and diversification benefits. Techniques such as copulas, dynamic conditional correlation, and regime-switching help capture dependence structures while remaining computationally tractable.</p> <p>Another practical concern is liquidity and market microstructure. Simulations should account for slippage, bid-ask spreads, and transaction costs that affect real-world performance. Incorporating these factors strengthens the relevance of backtest outcomes for asset allocation and trading decisions.</p> <h3 style="font-family: 'Poppins', sans-serif !important; font-weight: 700 !important; color: #000000 !important; border-bottom: none !important; margin-top: 35px !important; padding-bottom: 0px !important; text-transform: capitalize !important;"><b>Best Practices and Common Pitfalls</b></h3> <p>Use a clearly defined objective for the backtest, such as assessing drawdown risk or utility-based performance. Document all assumptions, data sources, and parameter choices. Transparent reporting helps with replication and external review.</p><div class='code-block code-block-2' style='margin: 8px auto; text-align: center; display: block; clear: both;'> <script async src="https://pagead2.googlesyndication.com/pagead/js/adsbygoogle.js?client=ca-pub-1130848125502204" crossorigin="anonymous"></script> <!-- Content --> <ins class="adsbygoogle" style="display:block" data-ad-client="ca-pub-1130848125502204" data-ad-slot="4736459886" data-ad-format="auto" data-full-width-responsive="true"></ins> <script> (adsbygoogle = window.adsbygoogle || []).push({}); </script></div> <p>Guard against overfitting by reserving independent data for calibration and validation. Explore a diverse set of scenarios beyond the most favorable conditions. Emphasize robustness over peak performance in any single synthetic path.</p> <p>Avoid excessive reliance on a single method; compare parametric and non-parametric approaches. Seek convergence across methods to build confidence in results. Finally, maintain version control for models and backtests to track changes over time.</p> <h2 id="sec_4" style="font-family: 'Poppins', sans-serif !important; font-weight: 800 !important; color: #000000 !important; border-left: 10px solid #6366f1 !important; padding: 10px 20px !important; background: #f1f5f9 !important; margin-top: 50px !important; text-transform: uppercase !important; border-bottom: none !important; line-height: 1.2 !important;"><b>Key Metrics and a Practical Data Table</b></h2> <p>Quantifying performance in Monte Carlo backtests requires a suite of metrics that summarize risk and return under uncertainty. Typical measures include mean return, standard deviation, downside risk, and tail probabilities. Presenting these metrics alongside distributional visuals helps stakeholders interpret outcomes effectively.</p><div class='code-block code-block-2' style='margin: 8px auto; text-align: center; display: block; clear: both;'> <script async src="https://pagead2.googlesyndication.com/pagead/js/adsbygoogle.js?client=ca-pub-1130848125502204" crossorigin="anonymous"></script> <!-- Content --> <ins class="adsbygoogle" style="display:block" data-ad-client="ca-pub-1130848125502204" data-ad-slot="4736459886" data-ad-format="auto" data-full-width-responsive="true"></ins> <script> (adsbygoogle = window.adsbygoogle || []).push({}); </script></div> <table style="width: 100% !important; border-collapse: collapse !important; margin: 45px 0 !important; border: 3px solid #000000 !important; box-shadow: 14px 14px 0px #6366f1 !important;" border="1" cellpadding="6" cellspacing="0" style="border-collapse: collapse; width: 100%;"> <th style="background: #000000 !important; color: #ffffff !important; padding: 18px !important; text-align: left !important; font-weight: 800 !important; text-transform: uppercase !important; font-size: 12px !important;"ead> <tr> <th style="background: #000000 !important; color: #ffffff !important; padding: 18px !important; text-align: left !important; font-weight: 800 !important; text-transform: uppercase !important; font-size: 12px !important;">Dimension</th> <th style="background: #000000 !important; color: #ffffff !important; padding: 18px !important; text-align: left !important; font-weight: 800 !important; text-transform: uppercase !important; font-size: 12px !important;">Example Approach</th> <th style="background: #000000 !important; color: #ffffff !important; padding: 18px !important; text-align: left !important; font-weight: 800 !important; text-transform: uppercase !important; font-size: 12px !important;">Notes</th> </tr> </thead> <tbody> <tr> <td style="padding: 16px !important; border-bottom: 1px solid #e2e8f0 !important; font-size: 15px !important; color: #334155 !important;">Return Distribution</td> <td style="padding: 16px !important; border-bottom: 1px solid #e2e8f0 !important; font-size: 15px !important; color: #334155 !important;">Normal, t-distribution, or empirical tails</td> <td style="padding: 16px !important; border-bottom: 1px solid #e2e8f0 !important; font-size: 15px !important; color: #334155 !important;">Impacts mean-variance assumptions and risk estimates</td> </tr> <tr> <td style="padding: 16px !important; border-bottom: 1px solid #e2e8f0 !important; font-size: 15px !important; color: #334155 !important;">Covariance Structure</td> <td style="padding: 16px !important; border-bottom: 1px solid #e2e8f0 !important; font-size: 15px !important; color: #334155 !important;">Constant, time-varying, or regime-based</td> <td style="padding: 16px !important; border-bottom: 1px solid #e2e8f0 !important; font-size: 15px !important; color: #334155 !important;">Shapes portfolio risk and diversification effects</td> </tr> <tr> <td style="padding: 16px !important; border-bottom: 1px solid #e2e8f0 !important; font-size: 15px !important; color: #334155 !important;">Time Horizon</td> <td style="padding: 16px !important; border-bottom: 1px solid #e2e8f0 !important; font-size: 15px !important; color: #334155 !important;">Daily, weekly, or monthly steps</td> <td style="padding: 16px !important; border-bottom: 1px solid #e2e8f0 !important; font-size: 15px !important; color: #334155 !important;">Affects compounding and drawdown dynamics</td> </tr> <tr> <td style="padding: 16px !important; border-bottom: 1px solid #e2e8f0 !important; font-size: 15px !important; color: #334155 !important;">Sampling Method</td> <td style="padding: 16px !important; border-bottom: 1px solid #e2e8f0 !important; font-size: 15px !important; color: #334155 !important;">Parametric vs Bootstrap</td> <td style="padding: 16px !important; border-bottom: 1px solid #e2e8f0 !important; font-size: 15px !important; color: #334155 !important;">Trade-off between realism and simplicity</td> </tr> </tbody> </table> <h2 id="sec_5" style="font-family: 'Poppins', sans-serif !important; font-weight: 800 !important; color: #000000 !important; border-left: 10px solid #6366f1 !important; padding: 10px 20px !important; background: #f1f5f9 !important; margin-top: 50px !important; text-transform: uppercase !important; border-bottom: none !important; line-height: 1.2 !important;"><b>Implementation Considerations: Tools, Data, and Governance</b></h2> <p>Practical implementation blends software, data pipelines, and governance. Many teams use modular codebases that separate data handling, model calibration, and backtest execution. Version control and reproducible environments are essential for auditability and collaboration.</p> <p>Choice of software often reflects organizational needs and regulatory expectations. Open-source libraries and commercial platforms offer accelerations but require careful validation. The key is to align tooling with defined objectives, uncertainty quantification, and clear reporting standards.</p> <p>Regulatory and governance perspectives emphasize model risk management. Regular reviews of model assumptions, parameter stability, and scenario coverage help prevent unrecognized biases. Documentation, external validation, and risk dashboards support ongoing oversight in 2026 and beyond.</p><div class='code-block code-block-2' style='margin: 8px auto; text-align: center; display: block; clear: both;'> <script async src="https://pagead2.googlesyndication.com/pagead/js/adsbygoogle.js?client=ca-pub-1130848125502204" crossorigin="anonymous"></script> <!-- Content --> <ins class="adsbygoogle" style="display:block" data-ad-client="ca-pub-1130848125502204" data-ad-slot="4736459886" data-ad-format="auto" data-full-width-responsive="true"></ins> <script> (adsbygoogle = window.adsbygoogle || []).push({}); </script></div> <h2 id="sec_6" style="font-family: 'Poppins', sans-serif !important; font-weight: 800 !important; color: #000000 !important; border-left: 10px solid #6366f1 !important; padding: 10px 20px !important; background: #f1f5f9 !important; margin-top: 50px !important; text-transform: uppercase !important; border-bottom: none !important; line-height: 1.2 !important;"><b>Future Outlook and Market Implications</b></h2> <p>The trajectory of Monte Carlo backtesting mirrors broader trends in finance. As markets become more interconnected and data-rich, simulation-based methods help practitioners understand structural shifts and tail risks. The balance between realism and computational efficiency continues to guide methodological advances.</p> <p>Advances in machine learning, probabilistic programming, and cloud-native architectures expand the practical reach of Monte Carlo backtesting. Researchers experiment with adaptive scenarios, online updating, and scenario-driven decision rules. These developments aim to translate uncertainty estimates into actionable risk management and strategy design.</p> <p>Across regions and asset classes, robust Monte Carlo backtests support better governance and more informed capital allocation. They complement traditional historical tests by highlighting how strategies perform under stress and across regimes. For educators and researchers, these methods offer a bridge between theory and market practice in a complex financial landscape.</p><div class='code-block code-block-2' style='margin: 8px auto; text-align: center; display: block; clear: both;'> <script async src="https://pagead2.googlesyndication.com/pagead/js/adsbygoogle.js?client=ca-pub-1130848125502204" crossorigin="anonymous"></script> <!-- Content --> <ins class="adsbygoogle" style="display:block" data-ad-client="ca-pub-1130848125502204" data-ad-slot="4736459886" data-ad-format="auto" data-full-width-responsive="true"></ins> <script> (adsbygoogle = window.adsbygoogle || []).push({}); </script></div> <h2 id="sec_7" style="font-family: 'Poppins', sans-serif !important; font-weight: 800 !important; color: #000000 !important; border-left: 10px solid #6366f1 !important; padding: 10px 20px !important; background: #f1f5f9 !important; margin-top: 50px !important; text-transform: uppercase !important; border-bottom: none !important; line-height: 1.2 !important;"><b>Conclusion</b></h2> <p>Monte Carlo backtest methodologies provide a structured way to quantify uncertainty and test resilience. By simulating a wide set of market paths, practitioners gain a richer view of potential outcomes, beyond what historical data alone can offer. The approach aligns with modern risk management practices that emphasize robustness, transparency, and scenario analysis.</p> <p>For market researchers and analysts, the method integrates statistical modeling, data quality, and governance. Understanding the mechanics, limitations, and market context helps ensure credible results. As markets evolve, Monte Carlo backtesting remains a critical tool for learning, planning, and decision-making in uncertain times.</p> <h3 style="font-family: 'Poppins', sans-serif !important; font-weight: 700 !important; color: #000000 !important; border-bottom: none !important; margin-top: 35px !important; padding-bottom: 0px !important; text-transform: capitalize !important;"><b>Frequently Asked Questions</b></h3> <h3 style="font-family: 'Poppins', sans-serif !important; font-weight: 700 !important; color: #000000 !important; border-bottom: none !important; margin-top: 35px !important; padding-bottom: 0px !important; text-transform: capitalize !important;"><b>What is the difference between Monte Carlo backtesting and historical backtesting?</b></h3> <p>Historical backtesting relies on observed past prices to test a strategy. Monte Carlo backtesting generates synthetic paths to explore additional scenarios. The former reflects actual history, while the latter probes uncertainty and tail risks beyond that history.</p><div class='code-block code-block-2' style='margin: 8px auto; text-align: center; display: block; clear: both;'> <script async src="https://pagead2.googlesyndication.com/pagead/js/adsbygoogle.js?client=ca-pub-1130848125502204" crossorigin="anonymous"></script> <!-- Content --> <ins class="adsbygoogle" style="display:block" data-ad-client="ca-pub-1130848125502204" data-ad-slot="4736459886" data-ad-format="auto" data-full-width-responsive="true"></ins> <script> (adsbygoogle = window.adsbygoogle || []).push({}); </script></div> <h3 style="font-family: 'Poppins', sans-serif !important; font-weight: 700 !important; color: #000000 !important; border-bottom: none !important; margin-top: 35px !important; padding-bottom: 0px !important; text-transform: capitalize !important;"><b>How do you validate a Monte Carlo backtest?</b></h3> <p>Validation includes backtesting on out-of-sample data, cross-method comparisons, and sensitivity analyses. It also involves documenting assumptions and conducting robustness checks across parameter sets. Transparent reporting supports credible validation.</p> <h3 style="font-family: 'Poppins', sans-serif !important; font-weight: 700 !important; color: #000000 !important; border-bottom: none !important; margin-top: 35px !important; padding-bottom: 0px !important; text-transform: capitalize !important;"><b>What data considerations matter most?</b></h3> <p>Data quality, frequency, and alignment across assets are crucial. Calibrating input distributions with reliable statistics reduces bias. Clean, well-documented data underpins trustworthy simulations and repeatable results.</p> <h3 style="font-family: 'Poppins', sans-serif !important; font-weight: 700 !important; color: #000000 !important; border-bottom: none !important; margin-top: 35px !important; padding-bottom: 0px !important; text-transform: capitalize !important;"><b>What are common pitfalls to avoid?</b></h3> <p>Overfitting to a single data set, ignoring model risk, and underestimating tail events are frequent issues. Avoid treating simulated results as certainties and ensure diverse scenarios. Regular audits and governance help catch these pitfalls early.</p><div class='code-block code-block-2' style='margin: 8px auto; text-align: center; display: block; clear: both;'> <script async src="https://pagead2.googlesyndication.com/pagead/js/adsbygoogle.js?client=ca-pub-1130848125502204" crossorigin="anonymous"></script> <!-- Content --> <ins class="adsbygoogle" style="display:block" data-ad-client="ca-pub-1130848125502204" data-ad-slot="4736459886" data-ad-format="auto" data-full-width-responsive="true"></ins> <script> (adsbygoogle = window.adsbygoogle || []).push({}); </script></div> <p></body><br /> </html> </div> </div> <!-- CONTENT END 1 --> </div> <footer class="entry-meta" aria-label="Entry meta"> <span class="cat-links"><span class="gp-icon icon-categories"><svg viewBox="0 0 512 512" aria-hidden="true" xmlns="http://www.w3.org/2000/svg" width="1em" height="1em"><path d="M0 112c0-26.51 21.49-48 48-48h110.014a48 48 0 0143.592 27.907l12.349 26.791A16 16 0 00228.486 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like Chrome/[0-9.]+ (?!Mobile)",SurfaceTablet:"Windows NT [0-9.]+; ARM;.*(Tablet|ARMBJS)",HPTablet:"HP Slate (7|8|10)|HP ElitePad 900|hp-tablet|EliteBook.*Touch|HP 8|Slate 21|HP SlateBook 10",AsusTablet:"^.*PadFone((?!Mobile).)*$|Transformer|TF101|TF101G|TF300T|TF300TG|TF300TL|TF700T|TF700KL|TF701T|TF810C|ME171|ME301T|ME302C|ME371MG|ME370T|ME372MG|ME172V|ME173X|ME400C|Slider SL101|\\bK00F\\b|\\bK00C\\b|\\bK00E\\b|\\bK00L\\b|TX201LA|ME176C|ME102A|\\bM80TA\\b|ME372CL|ME560CG|ME372CG|ME302KL| K010 | K011 | K017 | K01E |ME572C|ME103K|ME170C|ME171C|\\bME70C\\b|ME581C|ME581CL|ME8510C|ME181C|P01Y|PO1MA|P01Z|\\bP027\\b|\\bP024\\b|\\bP00C\\b",BlackBerryTablet:"PlayBook|RIM Tablet",HTCtablet:"HTC_Flyer_P512|HTC Flyer|HTC Jetstream|HTC-P715a|HTC EVO View 4G|PG41200|PG09410",MotorolaTablet:"xoom|sholest|MZ615|MZ605|MZ505|MZ601|MZ602|MZ603|MZ604|MZ606|MZ607|MZ608|MZ609|MZ615|MZ616|MZ617",NookTablet:"Android.*Nook|NookColor|nook browser|BNRV200|BNRV200A|BNTV250|BNTV250A|BNTV400|BNTV600|LogicPD Zoom2",AcerTablet:"Android.*; \\b(A100|A101|A110|A200|A210|A211|A500|A501|A510|A511|A700|A701|W500|W500P|W501|W501P|W510|W511|W700|G100|G100W|B1-A71|B1-710|B1-711|A1-810|A1-811|A1-830)\\b|W3-810|\\bA3-A10\\b|\\bA3-A11\\b|\\bA3-A20\\b|\\bA3-A30|A3-A40",ToshibaTablet:"Android.*(AT100|AT105|AT200|AT205|AT270|AT275|AT300|AT305|AT1S5|AT500|AT570|AT700|AT830)|TOSHIBA.*FOLIO",LGTablet:"\\bL-06C|LG-V909|LG-V900|LG-V700|LG-V510|LG-V500|LG-V410|LG-V400|LG-VK810\\b",FujitsuTablet:"Android.*\\b(F-01D|F-02F|F-05E|F-10D|M532|Q572)\\b",PrestigioTablet:"PMP3170B|PMP3270B|PMP3470B|PMP7170B|PMP3370B|PMP3570C|PMP5870C|PMP3670B|PMP5570C|PMP5770D|PMP3970B|PMP3870C|PMP5580C|PMP5880D|PMP5780D|PMP5588C|PMP7280C|PMP7280C3G|PMP7280|PMP7880D|PMP5597D|PMP5597|PMP7100D|PER3464|PER3274|PER3574|PER3884|PER5274|PER5474|PMP5097CPRO|PMP5097|PMP7380D|PMP5297C|PMP5297C_QUAD|PMP812E|PMP812E3G|PMP812F|PMP810E|PMP880TD|PMT3017|PMT3037|PMT3047|PMT3057|PMT7008|PMT5887|PMT5001|PMT5002",LenovoTablet:"Lenovo TAB|Idea(Tab|Pad)( A1|A10| K1|)|ThinkPad([ ]+)?Tablet|YT3-850M|YT3-X90L|YT3-X90F|YT3-X90X|Lenovo.*(S2109|S2110|S5000|S6000|K3011|A3000|A3500|A1000|A2107|A2109|A1107|A5500|A7600|B6000|B8000|B8080)(-|)(FL|F|HV|H|)|TB-X103F|TB-X304X|TB-X304F|TB-X304L|TB-X505F|TB-X505L|TB-X505X|TB-X605F|TB-X605L|TB-8703F|TB-8703X|TB-8703N|TB-8704N|TB-8704F|TB-8704X|TB-8704V|TB-7304F|TB-7304I|TB-7304X|Tab2A7-10F|Tab2A7-20F|TB2-X30L|YT3-X50L|YT3-X50F|YT3-X50M|YT-X705F|YT-X703F|YT-X703L|YT-X705L|YT-X705X|TB2-X30F|TB2-X30L|TB2-X30M|A2107A-F|A2107A-H|TB3-730F|TB3-730M|TB3-730X|TB-7504F|TB-7504X|TB-X704F|TB-X104F|TB3-X70F|TB-X705F|TB-8504F|TB3-X70L|TB3-710F|TB-X704L",DellTablet:"Venue 11|Venue 8|Venue 7|Dell Streak 10|Dell Streak 7",YarvikTablet:"Android.*\\b(TAB210|TAB211|TAB224|TAB250|TAB260|TAB264|TAB310|TAB360|TAB364|TAB410|TAB411|TAB420|TAB424|TAB450|TAB460|TAB461|TAB464|TAB465|TAB467|TAB468|TAB07-100|TAB07-101|TAB07-150|TAB07-151|TAB07-152|TAB07-200|TAB07-201-3G|TAB07-210|TAB07-211|TAB07-212|TAB07-214|TAB07-220|TAB07-400|TAB07-485|TAB08-150|TAB08-200|TAB08-201-3G|TAB08-201-30|TAB09-100|TAB09-211|TAB09-410|TAB10-150|TAB10-201|TAB10-211|TAB10-400|TAB10-410|TAB13-201|TAB274EUK|TAB275EUK|TAB374EUK|TAB462EUK|TAB474EUK|TAB9-200)\\b",MedionTablet:"Android.*\\bOYO\\b|LIFE.*(P9212|P9514|P9516|S9512)|LIFETAB",ArnovaTablet:"97G4|AN10G2|AN7bG3|AN7fG3|AN8G3|AN8cG3|AN7G3|AN9G3|AN7dG3|AN7dG3ST|AN7dG3ChildPad|AN10bG3|AN10bG3DT|AN9G2",IntensoTablet:"INM8002KP|INM1010FP|INM805ND|Intenso Tab|TAB1004",IRUTablet:"M702pro",MegafonTablet:"MegaFon V9|\\bZTE V9\\b|Android.*\\bMT7A\\b",EbodaTablet:"E-Boda (Supreme|Impresspeed|Izzycomm|Essential)",AllViewTablet:"Allview.*(Viva|Alldro|City|Speed|All TV|Frenzy|Quasar|Shine|TX1|AX1|AX2)",ArchosTablet:"\\b(101G9|80G9|A101IT)\\b|Qilive 97R|Archos5|\\bARCHOS (70|79|80|90|97|101|FAMILYPAD|)(b|c|)(G10| Cobalt| TITANIUM(HD|)| Xenon| Neon|XSK| 2| XS 2| PLATINUM| CARBON|GAMEPAD)\\b",AinolTablet:"NOVO7|NOVO8|NOVO10|Novo7Aurora|Novo7Basic|NOVO7PALADIN|novo9-Spark",NokiaLumiaTablet:"Lumia 2520",SonyTablet:"Sony.*Tablet|Xperia Tablet|Sony Tablet S|SO-03E|SGPT12|SGPT13|SGPT114|SGPT121|SGPT122|SGPT123|SGPT111|SGPT112|SGPT113|SGPT131|SGPT132|SGPT133|SGPT211|SGPT212|SGPT213|SGP311|SGP312|SGP321|EBRD1101|EBRD1102|EBRD1201|SGP351|SGP341|SGP511|SGP512|SGP521|SGP541|SGP551|SGP621|SGP641|SGP612|SOT31|SGP771|SGP611|SGP612|SGP712",PhilipsTablet:"\\b(PI2010|PI3000|PI3100|PI3105|PI3110|PI3205|PI3210|PI3900|PI4010|PI7000|PI7100)\\b",CubeTablet:"Android.*(K8GT|U9GT|U10GT|U16GT|U17GT|U18GT|U19GT|U20GT|U23GT|U30GT)|CUBE U8GT",CobyTablet:"MID1042|MID1045|MID1125|MID1126|MID7012|MID7014|MID7015|MID7034|MID7035|MID7036|MID7042|MID7048|MID7127|MID8042|MID8048|MID8127|MID9042|MID9740|MID9742|MID7022|MID7010",MIDTablet:"M9701|M9000|M9100|M806|M1052|M806|T703|MID701|MID713|MID710|MID727|MID760|MID830|MID728|MID933|MID125|MID810|MID732|MID120|MID930|MID800|MID731|MID900|MID100|MID820|MID735|MID980|MID130|MID833|MID737|MID960|MID135|MID860|MID736|MID140|MID930|MID835|MID733|MID4X10",MSITablet:"MSI \\b(Primo 73K|Primo 73L|Primo 81L|Primo 77|Primo 93|Primo 75|Primo 76|Primo 73|Primo 81|Primo 91|Primo 90|Enjoy 71|Enjoy 7|Enjoy 10)\\b",SMiTTablet:"Android.*(\\bMID\\b|MID-560|MTV-T1200|MTV-PND531|MTV-P1101|MTV-PND530)",RockChipTablet:"Android.*(RK2818|RK2808A|RK2918|RK3066)|RK2738|RK2808A",FlyTablet:"IQ310|Fly Vision",bqTablet:"Android.*(bq)?.*\\b(Elcano|Curie|Edison|Maxwell|Kepler|Pascal|Tesla|Hypatia|Platon|Newton|Livingstone|Cervantes|Avant|Aquaris ([E|M]10|M8))\\b|Maxwell.*Lite|Maxwell.*Plus",HuaweiTablet:"MediaPad|MediaPad 7 Youth|IDEOS S7|S7-201c|S7-202u|S7-101|S7-103|S7-104|S7-105|S7-106|S7-201|S7-Slim|M2-A01L|BAH-L09|BAH-W09|AGS-L09|CMR-AL19",NecTablet:"\\bN-06D|\\bN-08D",PantechTablet:"Pantech.*P4100",BronchoTablet:"Broncho.*(N701|N708|N802|a710)",VersusTablet:"TOUCHPAD.*[78910]|\\bTOUCHTAB\\b",ZyncTablet:"z1000|Z99 2G|z930|z990|z909|Z919|z900",PositivoTablet:"TB07STA|TB10STA|TB07FTA|TB10FTA",NabiTablet:"Android.*\\bNabi",KoboTablet:"Kobo Touch|\\bK080\\b|\\bVox\\b Build|\\bArc\\b Build",DanewTablet:"DSlide.*\\b(700|701R|702|703R|704|802|970|971|972|973|974|1010|1012)\\b",TexetTablet:"NaviPad|TB-772A|TM-7045|TM-7055|TM-9750|TM-7016|TM-7024|TM-7026|TM-7041|TM-7043|TM-7047|TM-8041|TM-9741|TM-9747|TM-9748|TM-9751|TM-7022|TM-7021|TM-7020|TM-7011|TM-7010|TM-7023|TM-7025|TM-7037W|TM-7038W|TM-7027W|TM-9720|TM-9725|TM-9737W|TM-1020|TM-9738W|TM-9740|TM-9743W|TB-807A|TB-771A|TB-727A|TB-725A|TB-719A|TB-823A|TB-805A|TB-723A|TB-715A|TB-707A|TB-705A|TB-709A|TB-711A|TB-890HD|TB-880HD|TB-790HD|TB-780HD|TB-770HD|TB-721HD|TB-710HD|TB-434HD|TB-860HD|TB-840HD|TB-760HD|TB-750HD|TB-740HD|TB-730HD|TB-722HD|TB-720HD|TB-700HD|TB-500HD|TB-470HD|TB-431HD|TB-430HD|TB-506|TB-504|TB-446|TB-436|TB-416|TB-146SE|TB-126SE",PlaystationTablet:"Playstation.*(Portable|Vita)",TrekstorTablet:"ST10416-1|VT10416-1|ST70408-1|ST702xx-1|ST702xx-2|ST80208|ST97216|ST70104-2|VT10416-2|ST10216-2A|SurfTab",PyleAudioTablet:"\\b(PTBL10CEU|PTBL10C|PTBL72BC|PTBL72BCEU|PTBL7CEU|PTBL7C|PTBL92BC|PTBL92BCEU|PTBL9CEU|PTBL9CUK|PTBL9C)\\b",AdvanTablet:"Android.* \\b(E3A|T3X|T5C|T5B|T3E|T3C|T3B|T1J|T1F|T2A|T1H|T1i|E1C|T1-E|T5-A|T4|E1-B|T2Ci|T1-B|T1-D|O1-A|E1-A|T1-A|T3A|T4i)\\b ",DanyTechTablet:"Genius Tab G3|Genius Tab S2|Genius Tab Q3|Genius Tab G4|Genius Tab Q4|Genius Tab G-II|Genius TAB GII|Genius TAB GIII|Genius Tab S1",GalapadTablet:"Android [0-9.]+; [a-z-]+; \\bG1\\b",MicromaxTablet:"Funbook|Micromax.*\\b(P250|P560|P360|P362|P600|P300|P350|P500|P275)\\b",KarbonnTablet:"Android.*\\b(A39|A37|A34|ST8|ST10|ST7|Smart Tab3|Smart Tab2)\\b",AllFineTablet:"Fine7 Genius|Fine7 Shine|Fine7 Air|Fine8 Style|Fine9 More|Fine10 Joy|Fine11 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1027",HCLTablet:"HCL.*Tablet|Connect-3G-2.0|Connect-2G-2.0|ME Tablet U1|ME Tablet U2|ME Tablet G1|ME Tablet X1|ME Tablet Y2|ME Tablet Sync",DPSTablet:"DPS Dream 9|DPS Dual 7",VistureTablet:"V97 HD|i75 3G|Visture V4( HD)?|Visture V5( HD)?|Visture V10",CrestaTablet:"CTP(-)?810|CTP(-)?818|CTP(-)?828|CTP(-)?838|CTP(-)?888|CTP(-)?978|CTP(-)?980|CTP(-)?987|CTP(-)?988|CTP(-)?989",MediatekTablet:"\\bMT8125|MT8389|MT8135|MT8377\\b",ConcordeTablet:"Concorde([ ]+)?Tab|ConCorde ReadMan",GoCleverTablet:"GOCLEVER TAB|A7GOCLEVER|M1042|M7841|M742|R1042BK|R1041|TAB A975|TAB A7842|TAB A741|TAB A741L|TAB M723G|TAB M721|TAB A1021|TAB I921|TAB R721|TAB I720|TAB T76|TAB R70|TAB R76.2|TAB R106|TAB R83.2|TAB M813G|TAB I721|GCTA722|TAB I70|TAB I71|TAB S73|TAB R73|TAB R74|TAB R93|TAB R75|TAB R76.1|TAB A73|TAB A93|TAB A93.2|TAB T72|TAB R83|TAB R974|TAB R973|TAB A101|TAB A103|TAB A104|TAB A104.2|R105BK|M713G|A972BK|TAB A971|TAB R974.2|TAB R104|TAB R83.3|TAB A1042",ModecomTablet:"FreeTAB 9000|FreeTAB 7.4|FreeTAB 7004|FreeTAB 7800|FreeTAB 2096|FreeTAB 7.5|FreeTAB 1014|FreeTAB 1001 |FreeTAB 8001|FreeTAB 9706|FreeTAB 9702|FreeTAB 7003|FreeTAB 7002|FreeTAB 1002|FreeTAB 7801|FreeTAB 1331|FreeTAB 1004|FreeTAB 8002|FreeTAB 8014|FreeTAB 9704|FreeTAB 1003",VoninoTablet:"\\b(Argus[ _]?S|Diamond[ _]?79HD|Emerald[ _]?78E|Luna[ _]?70C|Onyx[ _]?S|Onyx[ _]?Z|Orin[ _]?HD|Orin[ _]?S|Otis[ _]?S|SpeedStar[ _]?S|Magnet[ _]?M9|Primus[ _]?94[ _]?3G|Primus[ _]?94HD|Primus[ _]?QS|Android.*\\bQ8\\b|Sirius[ _]?EVO[ _]?QS|Sirius[ _]?QS|Spirit[ _]?S)\\b",ECSTablet:"V07OT2|TM105A|S10OT1|TR10CS1",StorexTablet:"eZee[_']?(Tab|Go)[0-9]+|TabLC7|Looney Tunes Tab",VodafoneTablet:"SmartTab([ ]+)?[0-9]+|SmartTabII10|SmartTabII7|VF-1497|VFD 1400",EssentielBTablet:"Smart[ ']?TAB[ ]+?[0-9]+|Family[ ']?TAB2",RossMoorTablet:"RM-790|RM-997|RMD-878G|RMD-974R|RMT-705A|RMT-701|RME-601|RMT-501|RMT-711",iMobileTablet:"i-mobile i-note",TolinoTablet:"tolino tab [0-9.]+|tolino shine",AudioSonicTablet:"\\bC-22Q|T7-QC|T-17B|T-17P\\b",AMPETablet:"Android.* A78 ",SkkTablet:"Android.* (SKYPAD|PHOENIX|CYCLOPS)",TecnoTablet:"TECNO P9|TECNO DP8D",JXDTablet:"Android.* \\b(F3000|A3300|JXD5000|JXD3000|JXD2000|JXD300B|JXD300|S5800|S7800|S602b|S5110b|S7300|S5300|S602|S603|S5100|S5110|S601|S7100a|P3000F|P3000s|P101|P200s|P1000m|P200m|P9100|P1000s|S6600b|S908|P1000|P300|S18|S6600|S9100)\\b",iJoyTablet:"Tablet (Spirit 7|Essentia|Galatea|Fusion|Onix 7|Landa|Titan|Scooby|Deox|Stella|Themis|Argon|Unique 7|Sygnus|Hexen|Finity 7|Cream|Cream X2|Jade|Neon 7|Neron 7|Kandy|Scape|Saphyr 7|Rebel|Biox|Rebel|Rebel 8GB|Myst|Draco 7|Myst|Tab7-004|Myst|Tadeo Jones|Tablet Boing|Arrow|Draco Dual Cam|Aurix|Mint|Amity|Revolution|Finity 9|Neon 9|T9w|Amity 4GB Dual Cam|Stone 4GB|Stone 8GB|Andromeda|Silken|X2|Andromeda II|Halley|Flame|Saphyr 9,7|Touch 8|Planet|Triton|Unique 10|Hexen 10|Memphis 4GB|Memphis 8GB|Onix 10)",FX2Tablet:"FX2 PAD7|FX2 PAD10",XoroTablet:"KidsPAD 701|PAD[ ]?712|PAD[ ]?714|PAD[ ]?716|PAD[ ]?717|PAD[ ]?718|PAD[ ]?720|PAD[ ]?721|PAD[ ]?722|PAD[ ]?790|PAD[ ]?792|PAD[ ]?900|PAD[ ]?9715D|PAD[ ]?9716DR|PAD[ ]?9718DR|PAD[ ]?9719QR|PAD[ ]?9720QR|TelePAD1030|Telepad1032|TelePAD730|TelePAD731|TelePAD732|TelePAD735Q|TelePAD830|TelePAD9730|TelePAD795|MegaPAD 1331|MegaPAD 1851|MegaPAD 2151",ViewsonicTablet:"ViewPad 10pi|ViewPad 10e|ViewPad 10s|ViewPad E72|ViewPad7|ViewPad E100|ViewPad 7e|ViewSonic VB733|VB100a",VerizonTablet:"QTAQZ3|QTAIR7|QTAQTZ3|QTASUN1|QTASUN2|QTAXIA1",OdysTablet:"LOOX|XENO10|ODYS[ -](Space|EVO|Xpress|NOON)|\\bXELIO\\b|Xelio10Pro|XELIO7PHONETAB|XELIO10EXTREME|XELIOPT2|NEO_QUAD10",CaptivaTablet:"CAPTIVA PAD",IconbitTablet:"NetTAB|NT-3702|NT-3702S|NT-3702S|NT-3603P|NT-3603P|NT-0704S|NT-0704S|NT-3805C|NT-3805C|NT-0806C|NT-0806C|NT-0909T|NT-0909T|NT-0907S|NT-0907S|NT-0902S|NT-0902S",TeclastTablet:"T98 4G|\\bP80\\b|\\bX90HD\\b|X98 Air|X98 Air 3G|\\bX89\\b|P80 3G|\\bX80h\\b|P98 Air|\\bX89HD\\b|P98 3G|\\bP90HD\\b|P89 3G|X98 3G|\\bP70h\\b|P79HD 3G|G18d 3G|\\bP79HD\\b|\\bP89s\\b|\\bA88\\b|\\bP10HD\\b|\\bP19HD\\b|G18 3G|\\bP78HD\\b|\\bA78\\b|\\bP75\\b|G17s 3G|G17h 3G|\\bP85t\\b|\\bP90\\b|\\bP11\\b|\\bP98t\\b|\\bP98HD\\b|\\bG18d\\b|\\bP85s\\b|\\bP11HD\\b|\\bP88s\\b|\\bA80HD\\b|\\bA80se\\b|\\bA10h\\b|\\bP89\\b|\\bP78s\\b|\\bG18\\b|\\bP85\\b|\\bA70h\\b|\\bA70\\b|\\bG17\\b|\\bP18\\b|\\bA80s\\b|\\bA11s\\b|\\bP88HD\\b|\\bA80h\\b|\\bP76s\\b|\\bP76h\\b|\\bP98\\b|\\bA10HD\\b|\\bP78\\b|\\bP88\\b|\\bA11\\b|\\bA10t\\b|\\bP76a\\b|\\bP76t\\b|\\bP76e\\b|\\bP85HD\\b|\\bP85a\\b|\\bP86\\b|\\bP75HD\\b|\\bP76v\\b|\\bA12\\b|\\bP75a\\b|\\bA15\\b|\\bP76Ti\\b|\\bP81HD\\b|\\bA10\\b|\\bT760VE\\b|\\bT720HD\\b|\\bP76\\b|\\bP73\\b|\\bP71\\b|\\bP72\\b|\\bT720SE\\b|\\bC520Ti\\b|\\bT760\\b|\\bT720VE\\b|T720-3GE|T720-WiFi",OndaTablet:"\\b(V975i|Vi30|VX530|V701|Vi60|V701s|Vi50|V801s|V719|Vx610w|VX610W|V819i|Vi10|VX580W|Vi10|V711s|V813|V811|V820w|V820|Vi20|V711|VI30W|V712|V891w|V972|V819w|V820w|Vi60|V820w|V711|V813s|V801|V819|V975s|V801|V819|V819|V818|V811|V712|V975m|V101w|V961w|V812|V818|V971|V971s|V919|V989|V116w|V102w|V973|Vi40)\\b[\\s]+|V10 \\b4G\\b",JaytechTablet:"TPC-PA762",BlaupunktTablet:"Endeavour 800NG|Endeavour 1010",DigmaTablet:"\\b(iDx10|iDx9|iDx8|iDx7|iDxD7|iDxD8|iDsQ8|iDsQ7|iDsQ8|iDsD10|iDnD7|3TS804H|iDsQ11|iDj7|iDs10)\\b",EvolioTablet:"ARIA_Mini_wifi|Aria[ _]Mini|Evolio X10|Evolio X7|Evolio X8|\\bEvotab\\b|\\bNeura\\b",LavaTablet:"QPAD E704|\\bIvoryS\\b|E-TAB IVORY|\\bE-TAB\\b",AocTablet:"MW0811|MW0812|MW0922|MTK8382|MW1031|MW0831|MW0821|MW0931|MW0712",MpmanTablet:"MP11 OCTA|MP10 OCTA|MPQC1114|MPQC1004|MPQC994|MPQC974|MPQC973|MPQC804|MPQC784|MPQC780|\\bMPG7\\b|MPDCG75|MPDCG71|MPDC1006|MP101DC|MPDC9000|MPDC905|MPDC706HD|MPDC706|MPDC705|MPDC110|MPDC100|MPDC99|MPDC97|MPDC88|MPDC8|MPDC77|MP709|MID701|MID711|MID170|MPDC703|MPQC1010",CelkonTablet:"CT695|CT888|CT[\\s]?910|CT7 Tab|CT9 Tab|CT3 Tab|CT2 Tab|CT1 Tab|C820|C720|\\bCT-1\\b",WolderTablet:"miTab \\b(DIAMOND|SPACE|BROOKLYN|NEO|FLY|MANHATTAN|FUNK|EVOLUTION|SKY|GOCAR|IRON|GENIUS|POP|MINT|EPSILON|BROADWAY|JUMP|HOP|LEGEND|NEW AGE|LINE|ADVANCE|FEEL|FOLLOW|LIKE|LINK|LIVE|THINK|FREEDOM|CHICAGO|CLEVELAND|BALTIMORE-GH|IOWA|BOSTON|SEATTLE|PHOENIX|DALLAS|IN 101|MasterChef)\\b",MediacomTablet:"M-MPI10C3G|M-SP10EG|M-SP10EGP|M-SP10HXAH|M-SP7HXAH|M-SP10HXBH|M-SP8HXAH|M-SP8MXA",MiTablet:"\\bMI PAD\\b|\\bHM NOTE 1W\\b",NibiruTablet:"Nibiru M1|Nibiru Jupiter One",NexoTablet:"NEXO NOVA|NEXO 10|NEXO AVIO|NEXO FREE|NEXO GO|NEXO EVO|NEXO 3G|NEXO SMART|NEXO KIDDO|NEXO MOBI",LeaderTablet:"TBLT10Q|TBLT10I|TBL-10WDKB|TBL-10WDKBO2013|TBL-W230V2|TBL-W450|TBL-W500|SV572|TBLT7I|TBA-AC7-8G|TBLT79|TBL-8W16|TBL-10W32|TBL-10WKB|TBL-W100",UbislateTablet:"UbiSlate[\\s]?7C",PocketBookTablet:"Pocketbook",KocasoTablet:"\\b(TB-1207)\\b",HisenseTablet:"\\b(F5281|E2371)\\b",Hudl:"Hudl HT7S3|Hudl 2",TelstraTablet:"T-Hub2",GenericTablet:"Android.*\\b97D\\b|Tablet(?!.*PC)|BNTV250A|MID-WCDMA|LogicPD Zoom2|\\bA7EB\\b|CatNova8|A1_07|CT704|CT1002|\\bM721\\b|rk30sdk|\\bEVOTAB\\b|M758A|ET904|ALUMIUM10|Smartfren Tab|Endeavour 1010|Tablet-PC-4|Tagi Tab|\\bM6pro\\b|CT1020W|arc 10HD|\\bTP750\\b|\\bQTAQZ3\\b|WVT101|TM1088|KT107"},oss:{AndroidOS:"Android",BlackBerryOS:"blackberry|\\bBB10\\b|rim tablet os",PalmOS:"PalmOS|avantgo|blazer|elaine|hiptop|palm|plucker|xiino",SymbianOS:"Symbian|SymbOS|Series60|Series40|SYB-[0-9]+|\\bS60\\b",WindowsMobileOS:"Windows CE.*(PPC|Smartphone|Mobile|[0-9]{3}x[0-9]{3})|Windows Mobile|Windows Phone [0-9.]+|WCE;",WindowsPhoneOS:"Windows Phone 10.0|Windows Phone 8.1|Windows Phone 8.0|Windows Phone OS|XBLWP7|ZuneWP7|Windows NT 6.[23]; ARM;",iOS:"\\biPhone.*Mobile|\\biPod|\\biPad|AppleCoreMedia",iPadOS:"CPU OS 13",SailfishOS:"Sailfish",MeeGoOS:"MeeGo",MaemoOS:"Maemo",JavaOS:"J2ME/|\\bMIDP\\b|\\bCLDC\\b",webOS:"webOS|hpwOS",badaOS:"\\bBada\\b",BREWOS:"BREW"},uas:{Chrome:"\\bCrMo\\b|CriOS|Android.*Chrome/[.0-9]* (Mobile)?",Dolfin:"\\bDolfin\\b",Opera:"Opera.*Mini|Opera.*Mobi|Android.*Opera|Mobile.*OPR/[0-9.]+$|Coast/[0-9.]+",Skyfire:"Skyfire",Edge:"\\bEdgiOS\\b|Mobile Safari/[.0-9]* Edge",IE:"IEMobile|MSIEMobile",Firefox:"fennec|firefox.*maemo|(Mobile|Tablet).*Firefox|Firefox.*Mobile|FxiOS",Bolt:"bolt",TeaShark:"teashark",Blazer:"Blazer",Safari:"Version((?!\\bEdgiOS\\b).)*Mobile.*Safari|Safari.*Mobile|MobileSafari",WeChat:"\\bMicroMessenger\\b",UCBrowser:"UC.*Browser|UCWEB",baiduboxapp:"baiduboxapp",baidubrowser:"baidubrowser",DiigoBrowser:"DiigoBrowser",Mercury:"\\bMercury\\b",ObigoBrowser:"Obigo",NetFront:"NF-Browser",GenericBrowser:"NokiaBrowser|OviBrowser|OneBrowser|TwonkyBeamBrowser|SEMC.*Browser|FlyFlow|Minimo|NetFront|Novarra-Vision|MQQBrowser|MicroMessenger",PaleMoon:"Android.*PaleMoon|Mobile.*PaleMoon"},props:{Mobile:"Mobile/[VER]",Build:"Build/[VER]",Version:"Version/[VER]",VendorID:"VendorID/[VER]",iPad:"iPad.*CPU[a-z ]+[VER]",iPhone:"iPhone.*CPU[a-z ]+[VER]",iPod:"iPod.*CPU[a-z ]+[VER]",Kindle:"Kindle/[VER]",Chrome:["Chrome/[VER]","CriOS/[VER]","CrMo/[VER]"],Coast:["Coast/[VER]"],Dolfin:"Dolfin/[VER]",Firefox:["Firefox/[VER]","FxiOS/[VER]"],Fennec:"Fennec/[VER]",Edge:"Edge/[VER]",IE:["IEMobile/[VER];","IEMobile [VER]","MSIE [VER];","Trident/[0-9.]+;.*rv:[VER]"],NetFront:"NetFront/[VER]",NokiaBrowser:"NokiaBrowser/[VER]",Opera:[" OPR/[VER]","Opera Mini/[VER]","Version/[VER]"],"Opera Mini":"Opera Mini/[VER]","Opera Mobi":"Version/[VER]",UCBrowser:["UCWEB[VER]","UC.*Browser/[VER]"],MQQBrowser:"MQQBrowser/[VER]",MicroMessenger:"MicroMessenger/[VER]",baiduboxapp:"baiduboxapp/[VER]",baidubrowser:"baidubrowser/[VER]",SamsungBrowser:"SamsungBrowser/[VER]",Iron:"Iron/[VER]",Safari:["Version/[VER]","Safari/[VER]"],Skyfire:"Skyfire/[VER]",Tizen:"Tizen/[VER]",Webkit:"webkit[ /][VER]",PaleMoon:"PaleMoon/[VER]",SailfishBrowser:"SailfishBrowser/[VER]",Gecko:"Gecko/[VER]",Trident:"Trident/[VER]",Presto:"Presto/[VER]",Goanna:"Goanna/[VER]",iOS:" \\bi?OS\\b [VER][ ;]{1}",Android:"Android [VER]",Sailfish:"Sailfish [VER]",BlackBerry:["BlackBerry[\\w]+/[VER]","BlackBerry.*Version/[VER]","Version/[VER]"],BREW:"BREW [VER]",Java:"Java/[VER]","Windows Phone OS":["Windows Phone OS [VER]","Windows Phone [VER]"],"Windows Phone":"Windows Phone [VER]","Windows CE":"Windows CE/[VER]","Windows NT":"Windows NT [VER]",Symbian:["SymbianOS/[VER]","Symbian/[VER]"],webOS:["webOS/[VER]","hpwOS/[VER];"]},utils:{Bot:"Googlebot|facebookexternalhit|Google-AMPHTML|s~amp-validator|AdsBot-Google|Google Keyword Suggestion|Facebot|YandexBot|YandexMobileBot|bingbot|ia_archiver|AhrefsBot|Ezooms|GSLFbot|WBSearchBot|Twitterbot|TweetmemeBot|Twikle|PaperLiBot|Wotbox|UnwindFetchor|Exabot|MJ12bot|YandexImages|TurnitinBot|Pingdom|contentkingapp|AspiegelBot",MobileBot:"Googlebot-Mobile|AdsBot-Google-Mobile|YahooSeeker/M1A1-R2D2",DesktopMode:"WPDesktop",TV:"SonyDTV|HbbTV",WebKit:"(webkit)[ /]([\\w.]+)",Console:"\\b(Nintendo|Nintendo WiiU|Nintendo 3DS|Nintendo Switch|PLAYSTATION|Xbox)\\b",Watch:"SM-V700"}},g.detectMobileBrowsers={fullPattern:/(android|bb\d+|meego).+mobile|avantgo|bada\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\/|plucker|pocket|psp|series(4|6)0|symbian|treo|up\.(browser|link)|vodafone|wap|windows ce|xda|xiino/i, shortPattern:/1207|6310|6590|3gso|4thp|50[1-6]i|770s|802s|a wa|abac|ac(er|oo|s\-)|ai(ko|rn)|al(av|ca|co)|amoi|an(ex|ny|yw)|aptu|ar(ch|go)|as(te|us)|attw|au(di|\-m|r |s )|avan|be(ck|ll|nq)|bi(lb|rd)|bl(ac|az)|br(e|v)w|bumb|bw\-(n|u)|c55\/|capi|ccwa|cdm\-|cell|chtm|cldc|cmd\-|co(mp|nd)|craw|da(it|ll|ng)|dbte|dc\-s|devi|dica|dmob|do(c|p)o|ds(12|\-d)|el(49|ai)|em(l2|ul)|er(ic|k0)|esl8|ez([4-7]0|os|wa|ze)|fetc|fly(\-|_)|g1 u|g560|gene|gf\-5|g\-mo|go(\.w|od)|gr(ad|un)|haie|hcit|hd\-(m|p|t)|hei\-|hi(pt|ta)|hp( i|ip)|hs\-c|ht(c(\-| |_|a|g|p|s|t)|tp)|hu(aw|tc)|i\-(20|go|ma)|i230|iac( |\-|\/)|ibro|idea|ig01|ikom|im1k|inno|ipaq|iris|ja(t|v)a|jbro|jemu|jigs|kddi|keji|kgt( |\/)|klon|kpt |kwc\-|kyo(c|k)|le(no|xi)|lg( g|\/(k|l|u)|50|54|\-[a-w])|libw|lynx|m1\-w|m3ga|m50\/|ma(te|ui|xo)|mc(01|21|ca)|m\-cr|me(rc|ri)|mi(o8|oa|ts)|mmef|mo(01|02|bi|de|do|t(\-| |o|v)|zz)|mt(50|p1|v )|mwbp|mywa|n10[0-2]|n20[2-3]|n30(0|2)|n50(0|2|5)|n7(0(0|1)|10)|ne((c|m)\-|on|tf|wf|wg|wt)|nok(6|i)|nzph|o2im|op(ti|wv)|oran|owg1|p800|pan(a|d|t)|pdxg|pg(13|\-([1-8]|c))|phil|pire|pl(ay|uc)|pn\-2|po(ck|rt|se)|prox|psio|pt\-g|qa\-a|qc(07|12|21|32|60|\-[2-7]|i\-)|qtek|r380|r600|raks|rim9|ro(ve|zo)|s55\/|sa(ge|ma|mm|ms|ny|va)|sc(01|h\-|oo|p\-)|sdk\/|se(c(\-|0|1)|47|mc|nd|ri)|sgh\-|shar|sie(\-|m)|sk\-0|sl(45|id)|sm(al|ar|b3|it|t5)|so(ft|ny)|sp(01|h\-|v\-|v )|sy(01|mb)|t2(18|50)|t6(00|10|18)|ta(gt|lk)|tcl\-|tdg\-|tel(i|m)|tim\-|t\-mo|to(pl|sh)|ts(70|m\-|m3|m5)|tx\-9|up(\.b|g1|si)|utst|v400|v750|veri|vi(rg|te)|vk(40|5[0-3]|\-v)|vm40|voda|vulc|vx(52|53|60|61|70|80|81|83|85|98)|w3c(\-| )|webc|whit|wi(g |nc|nw)|wmlb|wonu|x700|yas\-|your|zeto|zte\-/i,tabletPattern:/android|ipad|playbook|silk/i};var h,i=Object.prototype.hasOwnProperty;return g.FALLBACK_PHONE="UnknownPhone",g.FALLBACK_TABLET="UnknownTablet",g.FALLBACK_MOBILE="UnknownMobile",h="isArray"in Array?Array.isArray:function(a){return"[object Array]"===Object.prototype.toString.call(a)},function(){var a,b,c,e,f,j,k=g.mobileDetectRules;for(a in k.props)if(i.call(k.props,a)){for(b=k.props[a],h(b)||(b=[b]),f=b.length,e=0;e<f;++e)c=b[e],j=c.indexOf("[VER]"),j>=0&&(c=c.substring(0,j)+"([\\w._\\+]+)"+c.substring(j+5)),b[e]=new RegExp(c,"i");k.props[a]=b}d(k.oss),d(k.phones),d(k.tablets),d(k.uas),d(k.utils),k.oss0={WindowsPhoneOS:k.oss.WindowsPhoneOS,WindowsMobileOS:k.oss.WindowsMobileOS}}(),g.findMatch=function(a,b){for(var c in a)if(i.call(a,c)&&a[c].test(b))return c;return null},g.findMatches=function(a,b){var c=[];for(var d in a)i.call(a,d)&&a[d].test(b)&&c.push(d);return c},g.getVersionStr=function(a,b){var c,d,e,f,h=g.mobileDetectRules.props;if(i.call(h,a))for(c=h[a],e=c.length,d=0;d<e;++d)if(f=c[d].exec(b),null!==f)return f[1];return null},g.getVersion=function(a,b){var c=g.getVersionStr(a,b);return c?g.prepareVersionNo(c):NaN},g.prepareVersionNo=function(a){var b;return b=a.split(/[a-z._ \/\-]/i),1===b.length&&(a=b[0]),b.length>1&&(a=b[0]+".",b.shift(),a+=b.join("")),Number(a)},g.isMobileFallback=function(a){return g.detectMobileBrowsers.fullPattern.test(a)||g.detectMobileBrowsers.shortPattern.test(a.substr(0,4))},g.isTabletFallback=function(a){return g.detectMobileBrowsers.tabletPattern.test(a)},g.prepareDetectionCache=function(a,c,d){if(a.mobile===b){var e,h,i;return(h=g.findMatch(g.mobileDetectRules.tablets,c))?(a.mobile=a.tablet=h,void(a.phone=null)):(e=g.findMatch(g.mobileDetectRules.phones,c))?(a.mobile=a.phone=e,void(a.tablet=null)):void(g.isMobileFallback(c)?(i=f.isPhoneSized(d),i===b?(a.mobile=g.FALLBACK_MOBILE,a.tablet=a.phone=null):i?(a.mobile=a.phone=g.FALLBACK_PHONE,a.tablet=null):(a.mobile=a.tablet=g.FALLBACK_TABLET,a.phone=null)):g.isTabletFallback(c)?(a.mobile=a.tablet=g.FALLBACK_TABLET,a.phone=null):a.mobile=a.tablet=a.phone=null)}},g.mobileGrade=function(a){var b=null!==a.mobile();return a.os("iOS")&&a.version("iPad")>=4.3||a.os("iOS")&&a.version("iPhone")>=3.1||a.os("iOS")&&a.version("iPod")>=3.1||a.version("Android")>2.1&&a.is("Webkit")||a.version("Windows Phone 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