A Critical Review of the Effects of Stock Returns and Market Timing on Capital Structure

Capital structure is regarded as the combination of debt and equity firms used to finance operations and investments.The choice of capital structure significantly impacts a company’s cost of capital,profitability,and risk profile.Among a series of factors that affect capital structure,this paper focuses on stock returns and market timing.In this review,an array of papers is analyzed to summarize what current research claims regarding the influence of stock returns and market timing on capital structure.This paper centers on the stock return and market timing theories and also discusses other theories like the trade-off theory,the pecking order theory,and the signaling theory.

Does Market Timing Affect Capital Structure？： Evidence for Chinese Firms

This paper investigates the market timing hypothesis of capital structure using a sample of 1,077 Chinese firms for the period 1992 to 2007. We find that market timing plays a significant role in capital structure decisions. However, market timing effects are not persistent and disappear within three years. The results suggest the prominent role played by the government in timing of security issues.

Intrinsic Value and Market Timing of Initial Public Offerings

To avoid debates on the interpretation problem of market-to-book, the residual income model is employed to calculate the intrinsic value and estimate the extent of mis-pricing by market. Using a sample of Chinese listed companies from 1998 to 2003, the empirical evidence supports that equity market mis-pricing plays a significant role in decision making on the initial public offering. Our evidence verifies that the market timing theory can be applied to the analysis of financing behavior of Chinese listed companies, but the long-lasting effect is insignificant.

FUZZY GENETIC HYBRID ALGORITHM FOR MARKET TIMING PREDICTION OF STOCK INVESTMENT

Market timing prediction of stock investment is an important decision problem with uncertainty and risk in the financial activity.An algorithm for market timing prediction of stock investment is proposed in this paper.Considering the close relationship in the stock market and the economic data,we find the correlation of synthetical economic data and the equity returns with the help of the combination of fuzzy logic and genetic algorithm.Finally,the application of stock market is included to test the effectiveness of the algorithm.

Study on the roles and acting mechanism of the real estate brokerage in China second-hand housing market

As China housing reform deepens, the second-hand housing transactions become more and more popular and real estate brokerages, as an intermediary of the transactions, become an undeniable important part of this market. This article mainly explores the roles and the acting mechanism of real estate brokerages in the second-hand housing market. The results show that the participation of real estate brokers in the second-hand housing market may have positive and negative influences. On one side, brokers ease the housing transaction process and benefits buyers and sellers by shortening the sale time on the market. On the other side, if brokers are the only participants in the housing transaction, acting as buyer and seller like some firms do, housing prices will increase and this negative effect will become even stronger as the participation of many more brokers increases. Therefore, the regulation and management of the industry is vital for the long and healthy development of the housing market in China.

PERFORMANCE EVALUATION OF CHINESE NEW FUNDS

The performance of Chinese investment funds was empirically analyzed using the following models, i.e. Jensen model, Treynor Mazuy (T M) model amd Merton Henriksson model. The results show that T M model is fitted to Chinese investment funds best among these three. But none of them can perfectly interpret the new funds’ performance. So, the idea suggested by Jagannathan, Korajczyk (J K) to extend the test was adopted in this paper, and the results show that J K model augmented from the M H can explain the source of excess return of fund Anxin.

Debt Rating Initiations： Natural Evolution or Opportunistic Behavior？

The authors examine a firm＇s decision to begin issuing debt in public bond markets and find that it is a function of both life cycle influences and opportunistic timing. Defining life cycle factors to encompass both a firm＇s age in years and its underlying characteristics, the authors confirm that bond market participation is generally restricted to large, mature firms. Summary statistics show that finns obtain their initial bond ratings on average 9.5 years after their equity initial public offering （IPO） and 11.8 years after initiating dividend payments. Growth rates, capital expenditures, and cash flow volatility all decline as the firm accesses public debt markets, consistent with entry into the mature phase of its life cycle. With respect to opportunistic timing, it is asked whether entry into public bond markets follows strong performance （or precedes weak performance） at both the firm and market levels. At the firm level, the authors find that the debt IPO occurs following periods of strong operating performance and high excess stock returns. At the market level, entry coincides with favorable interest rates and default spreads. The benefits of careful timing result in firms receiving initial bond ratings that are stronger than what would be predicted; however, there is no evidence of abnormal numbers of downgrades for these firms in subsequent years.

Trading Strategies for All Stock Programs

Market traders buy and sell volatile assets frequently,with a goal to maximize their total return.There is usually a commission for each purchase and sale.Two such assets are gold and bitcoin.In order to solve the existing issues of purchases between gold and bitcoin,given that we have 1,000 USD,what strategies should we take to maximize our profits?In this article,the authors established seven models to predict the value of gold and bitcoins and how you should buy them,as the trends of value fluctuate,our models must be accurate enough to avoid being influenced.Targeted at that,the content is divided into three parts.For part 1:The authors selected several indicators that feature how the stock runs.For instance,price of gold and profit of gold to build first two models,which are the risk of investment model and the judgment on bull-or-bear market model.Then we use these models to evaluate whether it is safe to invest.The models are as follows:bear-bull market judgment model,risk of investment evaluation model,prediction model,trade model.For part 2:Based on the data concerned,the authors established the time series model to predict the way the market fluctuates.Meanwhile,the result of this model can be applied in correcting the results of former two models so as to make it more accurate.For part 3:The authors combined models above to give the best trading strategy.In addition,we improved the models by adding more indicators to make it more precise.We hope that by applying our models and strategies,you can successfully maximize your profit.

Determinants of Housing Liquidity in Chinese Cities:Does Market Maturity Matter?

Housing liquidity measures the ability to convert housing to cash as an important characteristic of housing stock. A simple model of buyer offers＇ distributions was used to theoretically explore the determinants of housing liquidity in a search process. An empirical ordinary least squares model of the time-on-market was developed using data collected in four Chinese cities （Beijing, Shanghai, Guangzhou, and Shenzhen）. The results show that in these four Chinese cities, market maturity dominates the variation of housing liquidity, with the effects of housing characteristics, seller＇s search cost, search strategy, and market conditions being less significant to the time-on-market equation. These empirical results indicate that the slow turn-over of housing stock may constrain the overall level of housing liquidity in major Chinese cities.

UNCOVERING BENEFITS AND RISKS OF INTEGRATED PRODUCT SERVICE OFFERINGS-USING A CASE OF TECHNOLOGY ENCAPSULATION

The objective of this article is to uncover benefits and risks of Integrated Product Service Offering （IPSO） in a systematic manner. To do so, it adopts an explorative longitudinal in-depth case study （development of an IPSO based on a new technology） and adds insights to the existing literature. The article first proposes a theoretical and generic framework termed the PCP （Provider - Customer - Product） triangle with associated information flow and uncertainty. Second, various types of benefits and risks are presented based on the framework. Among others, the benefit of keeping IPR （Intellectual Property Rights） with the provider and the risk of regulation change are new findings from the case study. In addition, the case study reveals that IPSO is regarded as a positive contributor to innovation. Applying the framework and classification of benefits and risks as norms to other cases has yet to be done for verification. However, the framework contributes scientifically to a better understanding of the benefits and risks of IPSO. In addition, this framework is advantageous with its easiness to understand, which contributes practically to the dissemination of IPS0 insight to industry.