High-frequency trading
Pairs trade
See Also
Intraday Trading – 10 Best Intraday Trading Strategies & Tips for Beginners | FinschoolIs Day Trading Profitable? How To Get StartedWhy do most of the retail traders (~90%) lose money? And how they can be more successful?Day Trader Demographics and Statistics [2024]: Number Of Day Traders In The USAlternative trading system
Electronic trading
Stock exchange
Best insight from top research papers
The most profitable proven trading strategy appears to be momentum investing, which has consistently earned non-zero returns over time . This strategy involves selecting stocks based on their past performance over a specific time period, such as two to twelve months. It has been observed to earn average monthly returns of 1.57% over the period from 1965 to 2014, and even larger returns of 2.27% in the most recent ten-year period . However, it is important to note that the profitability of this strategy may be affected by transaction costs, especially when trading in smaller stocks . Nevertheless, a strategy that focuses only on the winner portfolio and avoids trading the loser portfolio has been found to earn strong and persistently abnormal profits, even after accounting for transaction costs .
Related Questions
What is the most profitable trading strategy?4 answersAmong the various strategies studied, momentum investing appears to be the most profitable trading strategy. It consistently earns non-zero returns over a long time period, with an average monthly return of 1.57% from 1965 to 2014. In recent years, the return has been even larger at 2.27% per month. However, profitability net of transaction costs is weak due to trading in small stocks with high transaction costs, especially for the loser portfolio. To overcome this, a strategy that focuses only on the winner portfolio and avoids selling the costly loser portfolio can still earn strong and persistently abnormal profits, even after transaction costs.What is the best strategy to trade Bitcoin?4 answersThe best strategy to trade Bitcoin is to use machine learning models for prediction and apply trading strategies based on the predicted results. Wang and Yansuggest using traditional machine learning regression models to predict the changes in Bitcoin price and then transforming the regression results into classification analysis for higher accuracy. They also construct a Machine Learning Trading Strategy that outperforms the traditional Double Moving Average Strategy. Gao and Houcompare the application effect of arbitrage strategy and trend strategy in machine learning on Bitcoin and find that both strategies have potential. Additionally, Cohenexplores algorithmic trading strategies for Bitcoin and finds that the moving average convergence divergence (MACD) and pivot reversal (PR) strategies outperform the buy and hold strategy. These findings indicate that using machine learning models and algorithmic trading strategies can be effective for trading Bitcoin.What are the most profitable trading strategies?4 answersAmong the various strategies studied, momentum investing appears to be the most profitable trading strategy. The classical momentum strategy, based on performance over the previous 2-12 months, has consistently earned positive returns over the period from 1965 to 2014, with an average monthly return of 1.57%. In the most recent 10-year period, this return increased to 2.27% per month. However, profitability net of transaction costs is weak due to trading in small stocks with high transaction costs, especially for the loser portfolio. A strategy that focuses only on the winner portfolio, avoiding the costly loser portfolio, has shown strong and persistently abnormal profits, even after transaction costs. Additionally, a trading rule of buying (selling) aggregate market portfolios with the highest positive (negative) return predictability statistic in the past 24 months has generated statistically significant positive returns in the subsequent 3 to 12 months.Which trading strategy is more profitable in daytrading on cryptocurrency exchange?5 answersPairs trading and moving average trading strategies have been studied for day trading on cryptocurrency exchanges. The results show mixed performance for these strategies. Pairs trading strategies, which exploit mean reversion in prices, underperform classical benchmarks in backtests. However, higher-frequency trading with the distance method shows significantly better performance, indicating the inefficiency of cryptocurrency markets. On the other hand, moving average trading strategies, specifically using the 20-day moving average, generate excess returns after controlling for the average market return. These results suggest that cryptocurrency markets are inefficient and that a variable moving average strategy can be successful in day trading.What are the most stable and effective trading strategies?5 answersThere are several trading strategies mentioned in the abstracts that can be considered stable and effective. One paper discusses the use of technical analysis and trading rules based on historical market data to identify trends and make investment decisions. Another paper explores the effectiveness of trading strategies in the Taiwan stock market and finds that none of the 21 strategies tested were effective, supporting the efficient market hypothesis. Additionally, a paper on radio resource management proposes a novel approach of radio spectrum trading via derivatives contracts to address short-term demands for spectrum while ensuring quality of service requirements are met. These papers provide insights into different trading strategies and their effectiveness in various contexts.What are the most efficient mev trading strategies?5 answersEfficient trading strategies in the field of MEV (minimum extractable value) can be identified from the abstracts provided. One approach is to use machine learning techniques to predict the stock market, which has shown promise in stable market conditions. Another strategy involves applying updated trading rules and risk-tolerance-based strategies to energy ETFs, which have outperformed the buy-and-hold strategy. Additionally, a portfolio trading strategy that minimizes market impact and risk can optimize performance against arrival prices. Furthermore, utilizing forecasts from multivariate linear regression analysis and employing a dynamic programming approach can lead to optimal trading strategies in the foreign exchange market. These findings suggest that combining machine learning, risk-tolerance-based strategies, portfolio optimization, and regression analysis can contribute to efficient MEV trading strategies.
