Purpose – This paper investigates whether the macroeconomic factors affect the firm stock returns volatility differently depending on their location in different sectors. For this purpose, daily financial time-series data for 683 firms located in nine US sectors for the period of 2000 to 2017 are employed. Research methodology – The GARCH (1,1) model was applied to each firm located in nine US sectors. The four macroeconomic factors, namely, exchange rate, treasury yield spread, oil prices, and market return, are included in both mean and variance equations of GARCH (1,1) model to estimate the effect. Research limitations – This research study is limited to the New York Stock Exchange; therefore, it can be extended to the other economies as well. Further, this study uses one firm feature that is the sectoral location of the firm; it is recommended that some other firm features should be studied to explore the volatility behaviour of firms. In the methodological part, this study does not include the lag effect, since it is recognised in the literature that the investors underreact to public information, so future research can be extended to test the underreaction hypothesis. Practical implications – This study has implications for the investors and policymakers. Since it has emerged from the findings that some sectors are more sensitive than others to macroeconomic changes, so this knowledge will help the investors to diversify their portfolio and policymakers to maintain macroeconomic discipline. Originality/Value – The main contribution of this study is that it undertakes the assumption of heterogeneous nature of firms and conducts a detailed firm level analysis by sector covering a more extended period of time to investigate the impact of four macroeconomic factors, namely, exchange rate, treasury yield spread, oil prices, and market return on firm stock returns, volatility using daily data. Further, this study contributes by including all the macroeconomic factors together as an exogenous variable in mean and conditional variance equations of the GARCH (1,1) model to investigate the effect simultaneously.

Stock market volatility is always been a major concern for investors, regulators, policy makers and academicians. Unfortunately, firm level volatility has not been given the due attention. The studies dealing with the firm level volatility are scarce. Moreover, a common assumption of homogenous nature of firms is used in the aggregate stock market analysis, sectoral level analysis and even in a firm level analysis. This homogenous assumption was objected by several researchers and suggested that firms are heterogeneous even in a narrowly defined sector. Furthermore, firms are different from each other because of possessing different characteristics. Based on that firm’s response to macroeconomic changes would not be the same. Hence, the hypothesis testing ignoring this fact could be spurious. This study proposes five categories in which firms can be classified, such as firm age, firm size, firm nature of business, firm trading nature and the sectoral location of the firm. This study proposes to examine the linkages between the macro economic factors and the firm level stock returns volatility considering the given firm features. It is expected from the empirical testing that the macroeconomic factors effect firm stock returns volatility belonging to different firm features differently, both in terms of magnitude and sign.

This functional exploration inspects the instability smile patters and its determinants for file choices. To survey the determinants that cause the grin design, we utilized Dumas et al. (1998) equation which gave us the best fitted suggested instability. So, it tends to be utilized in three distinct models, for example, Black et al. (1973), Heston (1993) and the MSV model to concentrate on the grin shape. This paper means to summing up the various methodologies in deciding the suggested unpredictability for the choices. Considering point-by-point writing on the guess strategies, a mathematical methodology is made sense of. This paper gives a survey of: (1) the improvement of the choice estimating model by Black et al. (1973), and the resulting changes of this model after 1987 (2) the experimental confirmation of each of the three models; and (3) uses of these models to really look at the examples of grin among various business sectors. We infer that there exists a positive connection between suggested instability and cash ness and the unpredictability grin is less lopsided for call choices. Likewise, the chance to termination for a choice and authentic unpredictability are the significant determinant.