Abstract: The authors suggest a methodology that involves conducting a preliminary analysis of inertia in financial time series. Inertia here means the manifestation of some kind of long-term memory. Such effects may take place in complex processes of a stochastic kind. If the decision is negative, they do not recommend using predictive management strategies based on trend analysis. The study uses computational schemes to detect and confirm trends in financial market data. The effectiveness of these schemes is evaluated by analyzing the frequency of trend confirmation over different time intervals and with different levels of trend confirmation. Furthermore, the study highlights the limitations of using smoothed curves for trend analysis due to the lag in the dynamics of the curve, emphasizing the importance of considering real-time data in trend analysis for more accurate predictions.
Keywords: electronic trading, stochastic processes, local trends, inertia of a process, immersion environment.
Keywords: electronic trading, stochastic processes, local trends, inertia of a process, immersion environment.
Link to work
DOI: https://doi.org/10.3390/computation11110209
DOI: https://doi.org/10.3390/computation11110209