Determinants and Impacts of the Relative Use of Depository Receipts and Euro Convertible Bonds by High-tech Corporations: An Empirical Study

This paper adopts Taiwan's high-tech companies as the sample to address and examine four new determinants of various foreign financing instruments and test their impacts on the issuing firms. Our empirical findings are consistent with the following notions. First, the firms with higher foreign holding and foreign investment will be likely to adopt foreign financing policy. Moreover, the firms with higher stock dividend payment in Taiwan will adopt both of ECB (Euro convertible bond) and DR (depository receipt). Firm managers with better education background will prefer DR. Second, the use of DR can effectively decrease the volatility of stock returns but also pronounce a negative influence on the mean of stock returns. In contrast, the use of ECB can effectively increase the mean but can not significantly decrease the volatility.

Revisiting the problem of audio-based hit song prediction using convolutional neural networks

Being able to predict whether a song can be a hit has impor- tant applications in the music industry. Although it is true that the popularity of a song can be greatly affected by exter- nal factors such as social and commercial influences, to which degree audio features computed from musical signals (whom we regard as internal factors) can predict song popularity is an interesting research question on its own. Motivated by the recent success of deep learning techniques, we attempt to ex- tend previous work on hit song prediction by jointly learning the audio features and prediction models using deep learning. Specifically, we experiment with a convolutional neural net- work model that takes the primitive mel-spectrogram as the input for feature learning, a more advanced JYnet model that uses an external song dataset for supervised pre-training and auto-tagging, and the combination of these two models. We also consider the inception model to characterize audio infor- mation in different scales. Our experiments suggest that deep structures are indeed more accurate than shallow structures in predicting the popularity of either Chinese or Western Pop songs in Taiwan. We also use the tags predicted by JYnet to gain insights into the result of different models.Comment: To appear in the proceedings of 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP