Is tick data trustable?

<p id="isPasted">Tick data is generally considered to be a reliable source of market data, but it is important to note that it is not perfect. There are a few things that can make tick data unreliable:</p><ul style="margin-bottom:0cm;" type="disc"><li style="margin-top:0cm;margin-right:0cm;margin-bottom: 7.5pt;margin-left:0cm;line-height:normal;font-size:15px;font-family:&quot;Calibri&quot;,sans-serif;color:#1F1F1F;background:white;">Data corruption:&nbsp;Tick data can be corrupted by technical glitches or by malicious actors. If data is corrupted, it may become inaccurate or incomplete.</li><li style="margin-top:0cm;margin-right:0cm;margin-bottom: 7.5pt;margin-left:0cm;line-height:normal;font-size:15px;font-family:&quot;Calibri&quot;,sans-serif;color:#1F1F1F;background:white;">Data manipulation:&nbsp;Tick data can be manipulated by market participants to create artificial price movements or to mislead other traders.</li><li style="margin-top:0cm;margin-right:0cm;margin-bottom: 7.5pt;margin-left:0cm;line-height:normal;font-size:15px;font-family:&quot;Calibri&quot;,sans-serif;color:#1F1F1F;background:white;">Data quality:&nbsp;The quality of tick data can vary depending on the source. Some data vendors may not have the resources or expertise to provide high-quality data.</li></ul><p>Despite these potential problems, tick data is still a valuable tool for traders and analysts. By being aware of the potential risks and by taking steps to mitigate them, traders and analysts can use tick data to improve their decision-making.</p>

<p id="isPasted">Tick data is the most granular form of market data and, when sourced correctly, is generally considered trustworthy for backtesting and high-frequency analysis, but its reliability is not guaranteed. Its trustworthiness depends heavily on the data provider's quality control, as tick data is highly susceptible to corruption and irregularities due to its massive volume.&nbsp;</p><p id="isPasted"><strong>To ensure your tick data is trustable you may follow these steps:</strong></p><ul><li>Choose a reputable provider: Use established, well-regarded data vendors who have a strong reputation for data quality. Some traders recommend purchasing directly from the exchange if possible.</li><li>Verify the provider's cleaning process: Understand how the vendor handles data corruption, including gaps, outliers, and time stamping issues.</li><li>Cross-reference data: For critical analysis, consider cross-referencing tick data from multiple providers to identify inconsistencies.</li><li>Use advanced tools: Utilize specialized software and programming libraries, such as Python with Pandas, for data cleaning and analysis, as standard spreadsheet programs are inadequate. </li></ul>