Explanation of changes in real estate stock market

The aim of this study is to explain the changes in the real estate prices as well as in the real estate stock market prices, using some macro-economic explanatory variables, such as the gross domestic product (GDP), the real interest rate and the unemployment rate. Several regressions have been carried out in order to express some types of incremental and absolute deflated real estate lock market indexes in terms of the macro-economic variables. The analyses are applied to the Swedish economy. The period under study is 1984-1994. Time series on monthly data are used. i.e. the number of data-points is 132. If time leads/lags are introduced in the e regressions, significant improvements in the already high correlations are achieved. The signs of the coefficients for IR, UE and GDP are all what one would expect to see from an economic point of view: those for GDP are all positive, those for both IR and UE are negative. All the regressions have high R2 values. Both markets anticipate change in the unemployment rate by 6 to 9 months, which seems reasonable because such change can be forecast quite reliably. But, on the contrary, there is no reason why they should anticipate by 3-6 months changes in the interest rate that can hardly be reliably forecast so far in advance.

Book-prices current : a record of prices at which books have been sold at auction.

Report year irregular.

A note on information seasonality and the disappearance of the weekend effect in the UK stock market

The weekend effect in UK stock prices has disappeared in the 1990s. Beneath the surface however there remain systematic day-of-the-week effects only visible when returns are partitioned by the direction of the market. A systematic pattern of market-wide news arrivals into the UK stock market is discovered and found to provide an explanation for these day-of-the-week effects.

The effects of ownership and stock liquidity on the timing of repurchase transactions

We analyze detailed monthly data on U.S. open market stock repurchases (OMRs) that recently became available following stricter disclosure requirements. We find evidence that OMRs are timed to benefit non-selling shareholders. We present evidence that the profits to companies from timing repurchases are significantly related to ownership structure. Institutional ownership reduces companies' opportunities to repurchase stock at bargain prices. At low levels, insider ownership increases timing profits and at high levels it reduces them. Stock liquidity increases profits from timing OMRs.

Cojumps in stock prices:empirical evidence

We examine contemporaneous jumps (cojumps) among individual stocks and a proxy for the market portfolio. We show, through a Monte Carlo study, that using intraday jump tests and a coexceedance criterion to detect cojumps has a power similar to the cojump test proposed by Bollerslev et al. (2008). However, we also show that we should not expect to detect all common jumps comprising a cojump when using such coexceedance based detection methods. Empirically, we provide evidence of an association between jumps in the market portfolio and cojumps in the underlying stocks. Consistent with our Monte Carlo evidence, moderate numbers of stocks are often detected to be involved in these (systematic) cojumps. Importantly, the results suggest that market-level news is able to generate simultaneous large jumps in individual stocks. We also find evidence of an association between systematic cojumps and Federal Funds Target Rate announcements. © 2013 Elsevier B.V.

A study of stock market fluctuations and their relation to business conditions

Most research on stock prices is based on the present value model or the more general consumption-based model. When applied to real economic data, both of them are found unable to account for both the stock price level and its volatility. Three essays here attempt to both build a more realistic model, and to check whether there is still room for bubbles in explaining fluctuations in stock prices. In the second chapter, several innovations are simultaneously incorporated into the traditional present value model in order to produce more accurate model-based fundamental prices. These innovations comprise replacing with broad dividends the more narrow traditional dividends that are more commonly used, a nonlinear artificial neural network (ANN) forecasting procedure for these broad dividends instead of the more common linear forecasting models for narrow traditional dividends, and a stochastic discount rate in place of the constant discount rate. Empirical results show that the model described above predicts fundamental prices better, compared with alternative models using linear forecasting process, narrow dividends, or a constant discount factor. Nonetheless, actual prices are still largely detached from fundamental prices. The bubblelike deviations are found to coincide with business cycles. The third chapter examines possible cointegration of stock prices with fundamentals and non-fundamentals. The output gap is introduced to form the nonfundamental part of stock prices. I use a trivariate Vector Autoregression (TVAR) model and a single equation model to run cointegration tests between these three variables. Neither of the cointegration tests shows strong evidence of explosive behavior in the DJIA and S&P 500 data. Then, I applied a sup augmented Dickey-Fuller test to check for the existence of periodically collapsing bubbles in stock prices. Such bubbles are found in S&P data during the late 1990s. Employing econometric tests from the third chapter, I continue in the fourth chapter to examine whether bubbles exist in stock prices of conventional economic sectors on the New York Stock Exchange. The ‘old economy’ as a whole is not found to have bubbles. But, periodically collapsing bubbles are found in Material and Telecommunication Services sectors, and the Real Estate industry group.

Three essays on the microstructure of exchange traded funds

Exchange traded funds (ETFs) have increased significantly in popularity since they were first introduced in 1993. However, there is still much that is unknown about ETFs in the extant literature. This dissertation attempts to fill gaps in the ETF literature by using three related essays. In these three essays, we compare ETFs to closed ended mutual funds (CEFs) by decomposing the bid-ask spread into its three components; we look at the intraday shape of ETFs and compare it to the intraday shape of equities as well as examine the co-integration factor between ETFs on the London Stock Exchange and the New York Stock Exchange; we also examine the differences between leveraged ETFs and unleveraged ETFs by analyzing the impact of liquidity and volatility. These three essays are presented in Chapters 1, 2, and 3, respectively. ^ Chapter one uses the Huang and Stoll (1997) model to decompose the bid-ask spread in CEFs and ETFs for two distinct periods—a normal and a volatile period. We show a higher adverse selection component for CEFs than for ETFs without regard to volatility. However, both ETFs and CEFs increased in magnitude of the adverse selection component in the period of high volatility. Chapter two uses a mix of the Werner and Kleidon (1993) and the Hupperets and Menkveld (2002) methods to get the intraday shape of ETFs and analyze co-integration between London and New York trading. We find two different shapes for New York and London ETFs. There also appears to be evidence of co-integration in the overlapping two-hour trading period but not over the entire trading day for the two locations. The third chapter discusses the new class of ETFs called leveraged ETFs. We examine the liquidity and depth differences between unleveraged and leveraged ETFs at the aggregate level and when the leveraged ETFs are classified by the leveraged multiples of -3, -2, -1, 2, and 3, both for a normal and a volatile period. We find distinct differences between leveraged and unleveraged ETFs at the aggregate level, with leveraged ETFs having larger spreads than unleveraged ETFs. Furthermore, while both leveraged and unleveraged ETFs have larger spreads in high volatility, for the leveraged ETFs the change in magnitude is significantly larger than for the unleveraged ETFs. Among the multiples, the -2 leveraged ETF is the most pronounced in its liquidity characteristics, more so in volatile times. ^

A Study of Stock Market Fluctuations and their Relations to Business Conditions

Most research on stock prices is based on the present value model or the more general consumption-based model. When applied to real economic data, both of them are found unable to account for both the stock price level and its volatility. Three essays here attempt to both build a more realistic model, and to check whether there is still room for bubbles in explaining fluctuations in stock prices. In the second chapter, several innovations are simultaneously incorporated into the traditional present value model in order to produce more accurate model-based fundamental prices. These innovations comprise replacing with broad dividends the more narrow traditional dividends that are more commonly used, a nonlinear artificial neural network (ANN) forecasting procedure for these broad dividends instead of the more common linear forecasting models for narrow traditional dividends, and a stochastic discount rate in place of the constant discount rate. Empirical results show that the model described above predicts fundamental prices better, compared with alternative models using linear forecasting process, narrow dividends, or a constant discount factor. Nonetheless, actual prices are still largely detached from fundamental prices. The bubble-like deviations are found to coincide with business cycles. The third chapter examines possible cointegration of stock prices with fundamentals and non-fundamentals. The output gap is introduced to form the non-fundamental part of stock prices. I use a trivariate Vector Autoregression (TVAR) model and a single equation model to run cointegration tests between these three variables. Neither of the cointegration tests shows strong evidence of explosive behavior in the DJIA and S&P 500 data. Then, I applied a sup augmented Dickey-Fuller test to check for the existence of periodically collapsing bubbles in stock prices. Such bubbles are found in S&P data during the late 1990s. Employing econometric tests from the third chapter, I continue in the fourth chapter to examine whether bubbles exist in stock prices of conventional economic sectors on the New York Stock Exchange. The ‘old economy’ as a whole is not found to have bubbles. But, periodically collapsing bubbles are found in Material and Telecommunication Services sectors, and the Real Estate industry group.

What Moved Share Prices in the Nineteenth-Century London Stock Market?

Using a new weekly blue-chip index, this paper investigates the causes of stock price movements on the London market between 1823 and 1870. We find that economic fundamentals explain about 15 per cent of weekly and 34 per cent of monthly variation in share prices. Contemporary press reporting from the London Stock Exchange is used to ascertain what market participants thought were causing the largest movements on the market. The vast majority of large movements were attributed by the press to geopolitical, monetary, railway-sector, and financial-crisis news. Investigating the stock price changes on an independent list of events reaffirms these findings, suggesting that the most important specific events which moved markets were wars involving European powers.

Stock price and volume effects associated with changes in the composition of the FTSE Bursa Malaysian KLCI

We examine the stock price and volume effects associated with changes in the composition of the FTSE Bursa Malaysia Kuala Lumpur Composite Index (KLCI), over the time period of 2005–2012. We find evidence to support the price pressure hypothesis for both additions to and deletions from the KLCI. This is because significant stock price and trading volume effects in the pre index revision period are entirely reversed after the announcement of the news. Our empirical findings can be explained by the market microstructure literature. Significant changes in liquidity cause trading volume and stock prices to reverse back to their original level before the index revisions took place.

Is the Australian wool futures market efficient as a predictor of spot prices?

Giles and Goss (1980) have suggested that, if a futures market provides a forward pricing function, then it is an efficient market. In this article a simple test for whether the Australian Wool Futures market is efficient is proposed. The test is based on applying cointegration techniques to test the Law of One Price over a three, six, nine, and twelve month spread of futures prices. We found that the futures market is efficient for up to a six-month spread, but no further into the future. Because futures market prices can be used to predict spot prices up to six months in advance, woolgrowers can use the futures price to assess when they market their clip, but not for longer-term production planning decisions. (C) 1999 John Wiley & Sons, Inc.

Movement and stock structure of narrow-barred Spanish mackerel as indicated by parasites

Data from permanent parasites (juvenile trypanorhynchs and anisakids) indicated that Spanish mackerel Scomberomorus commerson from four sites on the west coast of Australia, Abrolhos, Shark Bay, Exmouth and Onslow, intermingled and were probably all drawn from the same stock. Fish from Broome, Kupang (Indonesia), Groote Eylandt-Torres Strait and the cast coast of Australia had distinct faunas of permanent parasites and probably each belonged to a different stock. There was evidence of movement of fish between Broome and the west coast. Abundances of temporary parasites (gill copepods and monogeneans) suggested that males and females on the west coast migrated separately because in several cases the parasite fauna of one sex was more similar to that of fish in an adjacent area than to the opposite sex in the same area. (C) 2001 The Fisheries Society of the British Isles.