Traditional factors known to affect feeder cattle prices, such as corn prices, have been questioned recently given the volatile nature of agricultural markets and some recent research findings. This work utilizes two very current and unique datasets to examine feeder cattle pricing relationships from Kentucky internet auctions and Certified Preconditioned for Health (CPH) sales. In addition to examining traditional pricing factors, factors that affect feeder cattle basis were also examined. Basis questions are of great interest in the southeast as transportation costs to major cattle feeding areas have been impacted by rising fuel prices and increased market volatility. Finally, price premiums were examined for cattle selling as age and source verified and natural. Results suggested that traditional factors were still found to influence feeder cattle prices, with some evidence that the magnitude of these effects may be smaller. Basis factors were found to be relevant; specifically fuel price was found to have a negative effect on basis in internet sales. This finding was also consistent with weaker basis in areas further away from the Midwest. Finally, premiums for age and source verification were moderate, roughly $11 per head for age and source verified calves, $17 per head for natural calves, and about $32 per head for cattle with both attributes.

The first empirical chapter examines the existence of a 'net equity issuance' (NEI) effect in the UK stock market. Net Equity Issuance (NEI) refers to the change in a firm's shares outstanding due to events such as SEOs, acquisitions financed by share issues, issues to staff and share repurchases. The NEI effect is the ability of share issuance by firms to predict their subsequent stock returns. My results mainly suggest that there is an NEI effect in the UK. However, a discrepancy exists between the UK results and those found in the US. In the UK market, negative-NEI stocks tend to show negative subsequent returns while zero-NEI stocks have the highest subsequent returns. I also find that the abnormal returns from the NEI effect disappear when transaction costs are taken into account. Furthermore, the asset pricing test results suggest that the new factor models partially explain the NEI effect in the UK. The second empirical chapter evaluates the information content of new asset pricing factors in the UK. I find that two new risk factors, the investment factor and the profitability factor, improve the factor model's performance in the UK while both the size factor 'small minus big' (SMB) and the value factor 'high minus low' (HML) are redundant. There is also evidence that factor construction methods matter to the information content of the profitability factor. The most informative profitability factor in the UK among the possible candidates is constructed using income before extraordinary items scaled by book equity. The third empirical chapter explores the information content of the two new factors by linking them to the state variables which predict future investment opportunities. By doing this, I find confirmative evidence that the two new risk factors may proxy for state variables that capture time variations in the investment opportunity set. I find empirical evidence which confirms that the investment factor predicts future economic growth, proxied by GDP growth, investment growth and consumption growth. In addition, the investment factor is found to be related to dividend yield shocks, whereas the profitability factor is related to inflation shocks. In addition, the pricing significance of macroeconomic variable shocks disappears when loadings on the two new factors are presented in the model. The evidence therefore provides economic interpretation to the information content of the new asset pricing factors in the UK market.

No / We examine the short-term price reaction of 424 UK stocks to large one-day price changes. Using the GJR-GARCH(1,1), we find no statistical difference amongst the cumulative abnormal returns (CARs) of the Single Index, the Fama–French and the Carhart–Fama–French models. Shocks ⩾5% are followed by a significant one-day CAR of 1% for all the models. Whilst shocks ⩽−5% are followed by a significant one-day CAR of −0.43% for the Single Index, the CARs are around −0.34% for the other two models. Positive shocks of all sizes and negative shocks ⩽−5% are followed by return continuations, whilst the market is efficient following larger negative shocks. The price reaction to shocks is unaffected when we estimate the CARs using the conditional covariances of the pricing variables.

Управление рыночной стоимостью аварийного жилищного фонда с учетом добавления коэффициента на износ здания при расчете оценки, а также применение новых ценообразующих факторов. / Management of the market value of the dilapidated housing stock, taking into account the addition of the depreciation coefficient of the building when calculating the assessment, as well as the use of new pricing factors.