In this thesis, I study whether stock returns are predictable. Specifically, I study whether the focal firm's linked partners or linked peers can forecast its future returns. The literature of return predictability has found that a lot of forecasting variables, which are mainly constructed by the focal firm's own characteristics, can predict its future returns, but the predictive power from explicitly or implicitly linked firms is not fully explored and understood. The study of interfirm return predictability has become an interesting and important research field, since it challenges current asset pricing theory and models. In this thesis, my research questions are whether inter-firm return predictability exists in the ownership network (namely one new "explicit" network) and whether it exists in the similar employee satisfaction network (namely one new "implicit" network). The overall contribution of the thesis is to find new evidence of return predictability in the inter-firm networks. These new inter-firm return predictabilities are not only an interesting practical fact with implications for investing and hedging, but also have essential implications for new asset pricing factors. In Chapter 2 and Chapter 3, I find the subsidiary-parent return predictability and parent-subsidiary return predictability in a global sample and different regional samples. In Chapter 4, I find that the returns of similar employeesatisfaction-linked firm peers have predictive power over focal firm returns. These results have important implications to call for a new asset pricing model that explicitly incorporates value-relevant information from various inter-firm networks.