Machine learning models have demonstrated remarkable efficacy and efficiency in a wide range of stock forecasting tasks. However, the inherent challenges of data scarcity, including low signal-to-noise ratio (SNR) and data homogeneity, pose significant obstacles to accurate forecasting. To address this issue, we propose a novel approach that utilizes artificial intelligence-generated samples (AIGS) to enhance the training procedures. In our work, we introduce the Diffusion Model to generate stock factors with Transformer architecture (DiffsFormer). DiffsFormer is initially trained on a large-scale source domain, incorporating conditional guidance so as to capture global joint distribution. When presented with a specific downstream task, we employ DiffsFormer to augment the training procedure by editing existing samples. This editing step allows us to control the strength of the editing process, determining the extent to which the generated data deviates from the target domain. To evaluate the effectiveness of DiffsFormer augmented training, we conduct experiments on the CSI300 and CSI800 datasets, employing eight commonly used machine learning models. The proposed method achieves relative improvements of 7.2% and 27.8% in annualized return ratio for the respective datasets. Furthermore, we perform extensive experiments to gain insights into the functionality of DiffsFormer and its constituent components, elucidating how they address the challenges of data scarcity and enhance the overall model performance. Our research demonstrates the efficacy of leveraging AIGS and the DiffsFormer architecture to mitigate data scarcity in stock forecasting tasks.

The US dollar had an event-heavy week to start off June. The US dollar surged early last week as the uncertainty about the Euro arose due to political events happened in Europe and the volatility in Asian markets driven by threats of an immediate trade war between the US and China. On Thursday (May 31), the Euro rebounded as Italy's politicians seemed to have found a resolution to their struggles in forming a new government. In the same day, the Trump administration announced it was putting tariffs on steel and aluminum imports from Canada, Mexico and Europe, strengthening fears over the trade war and making the US dollar suffer a slump. The US labor indicators highlighted the fundamental strength of the country's economy and made the US dollar extend gains amid the Europe geopolitical turmoil.