Building a Profit Prediction Model for Options Trading Using Newspaper Articles and Online Message Board Posts

Options trading is a type of financial trading that can offer significant profit opportunities depending on market conditions, but its profit and loss structure is complex. Traditional trading decisions are often made based on predictions of market indicators such as price fluctuations and volatility, and improving the predictive accuracy of these indicators may not necessarily lead to increased trading profits. In recent years, there has been growing interest in the use of supplementary information that can reflect the attention, expectations, and psychology of market participants, and it has been reported that text information such as newspaper articles and message board posts is related to short-term price formation and returns. Newspaper articles is useful for understanding events and social conditions that affect the economy and finance, and message board posts are useful for capturing investor interests, opinions, and emotions that cannot be captured by newspaper articles alone. Based on the above, this study proposes a framework for directly predicting profit opportunities in Nikkei 225 options trading using newspaper articles, message board posts, and financial time series, using supervised learning. Furthermore, under the same evaluation period, trading rules, and verification procedures, we systematically compare the forecasting performance and profit characteristics based on trading simulations for each combination of information sources, with and without them. In addition, we implemented a rule-based baseline based on predicting increases in the Nikkei 225 Volatility Index (VI) and a reinforcement learning baseline, and compared their profitability with the proposed model. Experimental results showed that in the options market, classification performance and profit characteristics based on trading simulations change depending on the presence or absence and combination of text information. In particular, when market data was combined with newspaper articles and message board posts, cumulative profits and losses in trading simulations tended to improve and maximum drawdowns tended to be smaller than when market data was used alone. The contribution of the information source also varied depending on the threshold, and it became clear that when market data and message board posts were combined, cumulative profits and losses improved in settings that aimed for high profit opportunities.