Reduction of the trend on the profitability and risk of trading. concludes this work and highlights potential future directions. 1. This work offers both academic and practical contributions to the fields of low-latency programming and high-frequency HFT trading. The research provides comprehensive information on low frequencies. This article analyzes the impact of high-frequency trading with respect to the main parameters affecting market quality: volatility, transaction costs, liquidity, price discovery, penalizing slower traders, and impact on sudden financial crises. the famous flash crashes. As often happens within the financial community, different points of view, HFT high-frequency trading uses computer algorithms to make trading decisions in short time frames, for example at the second level, which is widely used in the securities market. cryptocurrencies, for example Bitcoin. RL reinforcement learning in financial research has shown exceptional performance on many quantitative trading tasks. However, Summary. High-frequency trading has become a dominant force in the US capital market, accounting for dollar trading volume. This study examines the implication of high-frequency trading on stock price volatility and price discovery. I find that high-frequency trading is positively correlated with subsequent stock price volatility. We examine the role of HFT high-frequency traders in price discovery and price efficiency. Overall, HFTs facilitate pricing efficiency by trading in the direction of permanent price changes and in the opposite direction of transient pricing errors, both on average and on days of highest volatility. This is done thanks to their liquidity. We examine the robustness of high-frequency trading HFT proxies that are largely defined in limit order book LOB information. We use a unique TRTH Thomson Reuters Tick History, timestamped intraday trades in milliseconds, and a dataset enriched with highly fragmented LSE LOB depth message levels. Statistical arbitrage is a popular trading strategy used by hedge funds and proprietary trading desks, built on the statistical notion of cointegration to identify profitable trading opportunities. Given the revolutionary change in the markets represented by HFT high-frequency trading, it is not surprising that the risks and rewards have changed.