Convolutional neural network forecasting of European Union allowances futures using a novel unconstrained transformation method
This paper develops an open-high-low-close (OHLC) data forecasting framework to forecast
EUA futures price based on EU ETS data and extended exogenous variables from 2013 to …
EUA futures price based on EU ETS data and extended exogenous variables from 2013 to …
Stock trend prediction using candlestick charting and ensemble machine learning techniques with a novelty feature engineering scheme
Stock market forecasting is a knotty challenging task due to the highly noisy, nonparametric,
complex and chaotic nature of the stock price time series. With a simple eight-trigram feature …
complex and chaotic nature of the stock price time series. With a simple eight-trigram feature …
Encoding candlesticks as images for pattern classification using convolutional neural networks
Candlestick charts display the high, low, opening, and closing prices in a specific period.
Candlestick patterns emerge because human actions and reactions are patterned and …
Candlestick patterns emerge because human actions and reactions are patterned and …
[图书][B] Polska gospodarka w początkowym okresie pandemii COVID-19
Epidemie chorób zakaźnych nękają społeczeństwa od zarania dziejów i to one należą do
głównych przyczyn śmierci ludzi na całym świecie. Ostra choroba układu oddechowego …
głównych przyczyn śmierci ludzi na całym świecie. Ostra choroba układu oddechowego …
Performance of technical analysis in growth and small cap segments of the US equity market
A Shynkevich - Journal of Banking & Finance, 2012 - Elsevier
A large universe of technical trading rules applied to a set of technology industry and small
cap sector portfolios over the 1995–2010 period yields superior predictability after adjusting …
cap sector portfolios over the 1995–2010 period yields superior predictability after adjusting …
Deep reinforcement learning stock market trading, utilizing a CNN with candlestick images
Billions of dollars are traded automatically in the stock market every day, including
algorithms that use neural networks, but there are still questions regarding how neural …
algorithms that use neural networks, but there are still questions regarding how neural …
High frequency momentum trading with cryptocurrencies
Over the past few years, cryptocurrencies have increasingly been discussed as alternatives
to traditional fiat currencies. These digital currencies have garnered significant interest from …
to traditional fiat currencies. These digital currencies have garnered significant interest from …
Price trends and patterns in technical analysis: A theoretical and empirical examination
While many technical trading rules are based upon patterns in asset prices, we lack
convincing explanations of how and why these patterns arise, and why trading rules based …
convincing explanations of how and why these patterns arise, and why trading rules based …
Improving stock trading decisions based on pattern recognition using machine learning technology
PRML, a novel candlestick pattern recognition model using machine learning methods, is
proposed to improve stock trading decisions. Four popular machine learning methods and …
proposed to improve stock trading decisions. Four popular machine learning methods and …
Profitable candlestick trading strategies—The evidence from a new perspective
TH Lu, YM Shiu, TC Liu - Review of Financial Economics, 2012 - Elsevier
This paper aims to investigate the profitability of two-day candlestick patterns by buying on
bullish (bearish) patterns and holding until bearish (bullish) patterns occur. Our data set …
bullish (bearish) patterns and holding until bearish (bullish) patterns occur. Our data set …