Probability Of Positive Returns Research Articles

Does Idiosyncratic Risk Have a Significant Impact on Return Probability? A Case Study of Borsa Istanbul 100 Stocks

Most asset pricing models ignore idiosyncratic risk, or firm-specific risk, while it is one of the most critical determinants of asset pricing and stock returns. In this paper, we investigate the impact of idiosyncratic risk on the returns of stocks traded on the Borsa Istanbul using six different fixed effect panel tobit and four different fixed effect panel logit regression models. The results of logit models suggest that as idiosyncratic risk increases, probability of positive stock returns also increases. Furthermore, an increase in a stock's market sensitivity has a negative effect on the probability of positive returns, while an increase in the market-to-book ratio, firm size, and market return has positive effects on returns. In all models, the explanatory variables, including idiosyncratic risk, market-to-book ratio, firm size, and market return, have a positive effect on returns, except for the model where negative values of dependent variable are censored at zero.

Analysis of Paired Trading Strategies Based on Boll Bands

The development of information technology makes quantitative investment strategy widely used by various investors. Among them, pairing trading strategy has attracted the attention of a large number of investors. In this paper, the validity of paired trading is verified and the validity of Bollinger band signals used for paired trading is tested. To be specific, this paper takes Shanghai and Shenzhen 300 component stocks and China Securities 500 component stocks as data sets. In this paper, the correlation coefficient method is used to match the stocks. This study uses the closing price data of stocks in each pairing group from August 2021 to August 2022 for training, and backtests the training results with trading data from August 2022 to February 2023. From the yield index, the backtest group can get the highest yield of 23.4%. In addition, according to the analysis, the probability of positive returns in the backtest group is up to 80%.

Stock Volatility in Muscat Securities Market

Research studies proved that share prices keep on changing every day in the stock markets. Hence this particular research article is very relevant to analyse the Volatility of Muscat Securities Market over a specified period. Here, six Oil and Gas companies were selected for this research article. The study aimed at analysing the stock market volatility of Regular market players and Parallel market players of Muscat Oil and Gas companies and evaluating their relationship.This research article used GARCH model for measuring the volatility of Muscat Securities Market with special reference to Oil and Gas companies listed in the MSM. The study resulted that highest volatile companies are Shell Oman Marketing from regular market and Oman Oil Market from parallel market. Study also found that National Gas and Shell Oman Marketing companies has the probability of producing positive return and Almaha Petroleum Products Mar. Study also found that positive shock has higher level of impact on conditional variance while connected with negative shock. From the Parallel market it is found that Muscat Gases has the probability of positive return in future. Based on the descriptive result it is found that there are two companies i.e., National Gas and Shell Oman Marketing were expecting positive return in future. Therefore, investors can focus to these companies while they enter into the Muscat stock market, Study found that there is no significant price variation between the three regular market companies.

Framework to support decisions on chemical pest control under uncertainty, applied to aphids and brown rust in winter wheat

An approach is presented for supporting decision making on chemical pest control in an uncertain environment. Timing of chemical control is considered as a decision problem, which is analysed in terms of objectives, strategies, selection criteria, and a model of the system dynamics. Return on expenditure and insurance are considered to be two generally applicable objectives in pest control. These objectives are made operational by defining the profitability of strategy A compared with strategy B as the probability that A results in lower costs than B, and the risk associated with a strategy as the 0.90 quantile of the probability distribution of costs associated with that strategy, respectively. The authors propose to express the performance of relevant strategies in terms of profitability and risk. Risk-neutral damage thresholds where expected costs of no chemical control at any time just exceed those of immediate application of a pesticide, constitute a yardstick for assessing a strategy's performance. The approach is illustrated using a deterministic model of the pathosystem aphid-brown rust-winter wheat. Uncertainty is modelled as random inputs. No control and immediate pesticide application represent the only relevant strategies, as postponing chemical control decreases profitability and increases risk. The decline in risk attributable to pesticide application is larger for brown rust than for aphids. At risk-neutral damage thresholds the probability of positive returns on pesticide application amounts to only 30%. The causes of this bias to chemical control in recommendations for risk-neutral decision makers are discussed. Current recommendations for both aphids and brown rust appear to presume that farmers become more risk-averse as crop development advances.