Payout policy as a steering mechanism towards optimal capital structure - Elo, Tuomas (fi=Turun yliopisto. Turun kauppakorkeakoulu|en=University of Turku. Turku School of Economics|, 2016)
This thesis examines the relationship between the capital structure and payout policy of a firm. Both of these theories are popular research topics and in the latest studies their interdepency has been noted. This thesis aims to investigate the topic by examining if the firms that are theoretically underleveraged and overleveraged have clear similarities or differences in their payout methods. First, an extensive literature review of the main theories and their current states are presented. This is followed by the empirical part of this thesis. A statistical model, which is widely used in the academia, is used to determine optimal capital structures for a sample of firms. These optimal capital structures are then compared to their actual capital structures that are observed from their balance sheets. This will reveal, if the firms are overleveraged or underleveraged. These firms and their payouts are then examined in detail to see, if clear patterns of underleveraged and overleveraged firms and payouts are found. The findings of the empirical part of this thesis reveal that the sign of the deviation from optimal capital structure does not have a clear effect on the payout policy. However, it is observed that firms that deviate much from their optimal capital structures clearly execute less payouts that their less deviating counterparts. The thesis considered share repurchases and dividends as payouts. Unfortunately, the amount of share repurchases in the sample was too little, so statistically significant results were nearly absent. However, dividends yielded significant results. The main finding of this thesis, that the firms that operate close to their theoretical optimal capital structure execute payouts more likely, was mostly based on the dividend data. However, the results were promising. With a better sample and especially wider share repurchase data, the results could have been much more useful.