Yield Higher Returns Research Articles

Stock prediction using Bi-LSTM and RoBERTa sentiment analysis

Stock price forecasting is a widespread research issue in the field of finance. Stock price prediction can give investors more accurate advice and yield higher returns. With the popularity of social media, more and more people choose to express their opinions, and more and more media outlets published news on social media. This paper mainly conducts stock analysis and prediction by presenting the RoBERTa-BiLSTM model with the Bahdanau attention mechanism. It consists of two existing models: the RoBERTa and bidirectional LSTM models. The experimental results show that this model is more accurate in predicting stock prices than the Multi-Layer Perception (MLP) and LSTM models. Inputs to the model include historical AAPL stock price data and sentiment data analysed by news and Twitter tweet sentiment. In this paper, the high-precision RoBERTa-BiLSTM model for stock prediction was proposed, which provides a solution for stock prediction. The practical applications and the typical problem of most studies about stock prediction called the time-shifted problem, are provided in this paper and also have research value.

A Theory on Pre-ICO Venture Capital Involvement

We study the trade-off venture capitalists encounter in a financing framework under moral hazard. The venture capitalist has the option to supply funds either within a revenue-sharing contract or via equity but faces a hidden effort problem. While projects with a low degree of moral hazard yield higher returns to the venture capitalist when financed by equity, revenue-sharing contracts become superior as moral hazard increases. At high moral hazard levels, revenue sharing becomes the sole financing option and hence can raise welfare. We apply our model in the context of initial coin offerings as a modern form of revenue sharing.

Are extreme negative returns priced in the Indian stock market?

Given some recent empirical evidence showing the predictive ability of maximum daily returns (MAX) in the cross-section of stock returns, we examine the relationship between minimum daily returns (MIN) and subsequent monthly returns in the emerging stock market of India during the period 1999–2014. Our findings suggest that stocks with higher MIN in a month yield higher returns in the subsequent month with some caveats. This MIN effect is present primarily among stocks with lower market capitalization, higher illiquidity, and stocks with low institutional holdings. Furthermore, the application of quantile regression reveals that the relation between MIN and future stock returns is dynamic and quantile dependent.

A Study of Seasonality on the SAFEX Wheat Market

This paper examines seasonality in returns and volatilities in the South African Futures Exchange (SAFEX) wheat futures contract in order to seek market inefficiencies that can be exploited for financial gain. Non-parametric and parametric-based techniques are used to study sample regimes before and after the peak in wheat prices that occurred during the global economic crisis in 2008. Findings of the study indicate that wheat returns on Mondays and Kansas City Board of Trade (KCBT) holidays are significant and positive while Tuesday returns are negative and significant. These seasonal patterns occur largely in the second sample of the wheat dataset. Furthermore, it is observed that volatility diminished after the global financial crisis. Finally, based on the return seasonality detected and by applying Monte Carlo simulation in an out-of-sample period, some trading rules are developed that yield higher returns than any trading approach based on chance.

A Study of Seasonality on the Safex Wheat Market

ABSTRACTThis paper examines seasonality in returns and volatilities in the South African Futures Exchange (SAFEX) wheat futures contract in order to seek market inefficiencies that can be exploited for financial gain. Non-parametric and parametric-based techniques are used to study sample regimes before and after the peak in wheat prices that occurred during the global economic crisis in 2008. Findings of the study indicate that wheat returns on Mondays and Kansas City Board of Trade (KCBT) holidays are significant and positive while Tuesday returns are negative and significant. These seasonal patterns occur largely in the second sample of the wheat dataset. Furthermore, it is observed that volatility diminished after the global financial crisis. Finally, based on the return seasonality detected and by applying Monte Carlo simulation in an out-of-sample period, some trading rules are developed that yield higher returns than any trading approach based on chance.

How does the Occurrence of Stock Price Reversals Following End-of-the day Price Moves Differ in Bull and Bear Markets?

This paper uses intraday price data for 326 individual firms to examine how the occurrence of interday stock price reversals differs in bull and bear markets. We find that price reversals following the previous day’s larger high-to-close (low-to-close) price differences are more likely to occur in a bull (bear) market. Based on these findings, we find that the portfolios based on larger high-to-close price differences in the bull market, and portfolios based on smaller low-toclose price differences both in bull and bear markets are profitable investment strategies. In particularly, in bull markets, the portfolios based on smaller low-to-close price differences in the Mining and Service industries yield higher returns; in bear markets, portfolios based on smaller low-to-close price differences in Construction, Finance and Retail Trade yield higher returns

Foreign exchange market efficiency and profitability of trading rules: Evidence from a developing country

This paper empirically investigates market efficiency and trading rule profitability of the Ugandan foreign exchange market for the period January 1994 to June 2012. We test for market efficiency using a battery of variance ratio tests with superior size and power properties. We find that the Ugandan foreign exchange market is characterised by pricing inefficiency, except for a few brief episodes of efficiency. We also find that the Buy signals outperform the Sell signals in correctly predicting exchange rate movements, and yield higher returns. Investors can earn excess returns over a buy-and-hold strategy using trading rules but these returns diminish substantially after accounting for transaction costs. We conclude that the Ugandan foreign exchange market is generally characterised by weak-form inefficiency. However, market participants are unable to consistently exploit pricing inefficiencies due to transaction costs and time variation in the inefficiencies under changing market conditions. Our finding of time variation in market efficiency is consistent with the adaptive market hypothesis of Lo (2004).