arXiv · arXiv q-fin · 2026
Traditional moving average convergence divergence (MACD) trading rules are often constrained by signal lag and susceptibility to false signals. To address these limitations, this study develops a volume-price-adjusted MACD (VP-MACD) framework that incorporates volume, volatility, and intraday price structure into the conventional indicator, and introduces a sensitivity parameter to allow earlier trade entry and impro…
Luyun Lin, Lixing Lin, Zhen Zhang, Moxuan Zheng, Yiqing Wang
arXiv · arXiv q-fin · 2025
This paper develops a rigorous functional-analytic framework for the MACD (Moving Average Convergence Divergence) indicator, a classical tool in technical analysis. We show that MACD, commonly defined as the difference between two moving averages, can be precisely interpreted as a phase-corrected, smoothed derivative operator. By analyzing nested and recursive moving averages, we establish that MACD is structurally e…
Yuelong Li
arXiv · arXiv q-fin · 2022
In recent years, more and more investors use technical analysis methods in their own trading. Evaluating the effectiveness of technical analysis has become more feasible due to increasing computing capability and blooming public data, which indie investors can perform stock analysis and backtest their own trading strategy conveniently. The Moving Average Convergence Divergence (MACD) indicator is one of the popular t…
Pat Tong Chio
arXiv · arXiv q-fin · 2020
There is a great number of factors to take into account when building and managing an investment portfolio. It is widely believed that a proper set-up of the portfolio combined with a good, robust management strategy is the key to successful investment. In this paper, we aim at an analysis of two aspects that may have an impact on investment performance: diversity of assets and inclusion of cash in the portfolio. We …
Jarosław Gruszka, Janusz Szwabiński
arXiv · arXiv q-fin · 2026
The intricate behavior patterns of financial markets are influenced by fundamental, technical, and psychological factors. During times of high volatility and regime shifts causes many traditional strategies like trend-following or mean-reversion to fail. This paper proposes a hybrid AI-based trading strategy that combines (1) trend-following and directional momentum capture via EMA and MACD, (2) detection of price no…
Varun Narayan Kannan Pillai, Akshay Ajith, Sumesh K J
arXiv · arXiv q-fin · 2026
We consider a class of partial-information portfolio optimization problems in which the drift of a risky asset is driven by two latent stochastic factors evolving at distinct time scales. We show that the filtered estimate of the latent mean-reversion level is driven by the difference between fast and slow exponential moving average (EMA)-type processes of the trailing price history, yielding a Moving Average Converg…
Dannin J. Eccles, Roger Lee
arXiv · arXiv q-fin · 2025
Deep neural networks (DNNs) have transformed fields such as computer vision and natural language processing by employing architectures aligned with domain-specific structural patterns. In algorithmic trading, however, there remains a lack of architectures that directly incorporate the logic of traditional technical indicators. This study introduces Technical Indicator Networks (TINs), a structured neural design that …
Longfei Lu
arXiv · arXiv q-fin · 2025
In this note, we compare Bitcoin trading performance using two machine learning models-Light Gradient Boosting Machine (LightGBM) and Long Short-Term Memory (LSTM)-and two technical analysis-based strategies: Exponential Moving Average (EMA) crossover and a combination of Moving Average Convergence/Divergence with the Average Directional Index (MACD+ADX). The objective is to evaluate how trading signals can be used t…
José Ángel Islas Anguiano, Andrés García-Medina
arXiv · arXiv q-fin · 2025
We examine the predictive power of a novel hybrid A3T-GCN architecture for forecasting closing stock prices of FTSE100 constituents. The dataset comprises 79 companies and 375,329 daily observations from 2007 to 2024, with node features including technical indicators (RSI, MACD), normalized and log returns, and annualized log returns over multiple windows (ALR1W, ALR2W, ALR1M, ALR2M). Graphs are constructed based on …
A. L. Paredes
arXiv · arXiv q-fin · 2020
In this note we discuss the mathematical tools to define trend indicators which are used to describe market trends. We explain the relation between averages and moving averages on the one hand and the so called exponential moving average (EMA) on the other hand. We present a lot of examples and give the definition of the most frequently used trend indicator, the MACD, and discuss its properties.
Frank Klinker
arXiv · arXiv q-fin · 2019
Stock prediction has always been attractive area for researchers and investors since the financial gains can be substantial. However, stock prediction can be a challenging task since stocks are influenced by a multitude of factors whose influence vary rapidly through time. This paper proposes a novel approach (Word2Vec) for stock trend prediction combining NLP and Japanese candlesticks. First, we create a simple lang…
Marko Poženel, Dejan Lavbič
arXiv · arXiv q-fin · 2019
The purpose of this research is to apply technical analysis of Sutte Indicator in stock trading which will assist in the investment decision making process i.e. buying or selling shares. This research takes data of "A" on the Indonesia Stock Exchange(IDX or BEI) 29 November 2006 until 20 September 2016 period. To see the performance of Sutte Indicator, other technical analysis are used as a comparison, Simple Moving …
Ansari Saleh Ahmar