Dynamic Asset Allocation with Event Risk

On the relationship between changes in stock prices and bond yields in the G7 countries: Wavelet analysis

Although the prediction of stock prices is a topic that has been studied in several occasions, there are few variables that have been used for this matter outside of dividends such as determinant of prices (Guo, 2022). The results found to date have not been entirely satisfactory. since they do not explain most price movements in the long run. The use of profits such as predictor variable is an alternative that has not been much explored. This research work seeks to answer what is the effect of using profits as a predictor of stock prices in the long run. With the In order to answer this question, a panel regression was performed, controlling for fixed effects, of the effect of the profits on stock prices over the past 30 years for S&P 500 companies. In general, it was not possible to determine if the profits, whether gross, operating or net, have the capacity to predict changes in stock prices. However, it was established that the size of the assets of a company and changes in US GDP have a negative relationship with changes in price. By On the other hand, the change in the price of the SPX index has a positive relationship with the change in the stock price. This finding can generate a great advantage for investors when creating stock portfolios in the long term that seek to maximize profitability with a certain degree of certainty, since it would allow choosing with greater clarity those actions with greater probability of success and returns in the long

A company's financial statements provide information that is useful in making economic decisions. This may include information about the company's financial performance, financial position and cash flows. Valuation of financial instruments at fair value can have a significant impact on bank share prices. Banks that use fair value accounting for financial instruments may experience greater variability in their share prices than banks that do not use this method. The purpose of this research is to investigate the relationship between accounting valuation of financial instruments at fair value and changes in bank stock prices. The research aims to determine whether and to what extent there is a relationship between the fair value of financial instruments and changes in stock prices. Research may also aim to identify any factors that may influence this relationship and provide information and recommendations for stakeholders such as investors, regulators and financial institutions. Based on the results achieved, the need for optimal and accurate use of fair value indicators due to their impact on the company's performance, as well as clearer compliance by banks with international financial reporting standards regarding the fair value assessment of financial instruments, was investigated. And thus, it can lead to increased accuracy of forecasts and increased confidence of users of financial statements in making economic decisions. The findings of the study can contribute to the existing scientific literature on the impact of fair value accounting on stock prices and provide further understanding of this issue. The results of the research can be used by banks to assess the potential impact of the implementation of fair value accounting for financial instruments on the share price.

Investment Analysis and Strategy for COVID-19

This paper considers variance bounds for stock price changes in a general setting that allows for ex-dividend stock prices, risk averse investors, and exponentially-growing dividends. I show that providing investors with more information about future dividends can either increase or decrease the variance of stock price changes, depending on some key parameters, namely, those governing the properties of dividends and the stochastic discount factor. This finding contrasts with the results of Engel (2005) who shows that news about future dividends will always decrease the variance of stock price changes in a specialized setting with cum-dividend stock prices and risk neutral investors.

Financial Performance of Pakistani Banks after the Implementation of Reforms: A Post-Global-Crisis Study

Dynamic Asset Allocation Under Inflation

One major technical analysis of stock price fluctuation is the use of candlestick charts. This paper proposes a model with six parameters to retrieve similar candlestick patters to improve accuracy of stock price predictions. Because criteria that trigger reversing trade largely affect gains and losses, we examine two criteria; one based on sum of negative stock price changes and the other on sum of negative 5-day average differences. The proposed retrieval algorithm and criteria are evaluated through simulations in terms of gains and losses using NASDAQ's daily stock data. The results of simulations indicate that the proposed method leads to a trade decision that opportunities of successful stock trades are effectively above that of failure ones with several percentage of gains. Simulations also show that high risks deliver high returns. The results are examined statistically by the regression analysis suggesting the significant capabilities of the proposed method to predict stock price fluctuations.

In this paper the distribution of stock price differences is studied. Starting from Bachelier's hypothesis regarding the independence of stock price changes a model based on price differences taken across transactions, rather than differences obtained across time periods, is investigated. Using this model the distributions of price changes for a sample of 10 stocks were studied. In contrast to the fat tailed, excessively peaked distributions obtained by differencing across time periods, the distributions obtained by differencing across transactions did not have an excessive number of extreme events, although the center classes continued to be overcrowded. As the number of transactions over which the price differences were taken increased from 1 to n where n is equal to the largest number of transactions over which the price has remained unchanged, the distribution of the ΔP's approached the normal distribution. Thus we conclude that stock price changes are not independent across single transactions, and that stock prices should be differenced across blocks of transactions, rather than time intervals.

Earning the right premium on the right factor in portfolio planning

How Much Does the Fed Care About Stock Prices?

This paper investigates the interactions between changes in stock prices and monetary policy regimes in four emerging Asian countries—Korea, Malaysia, Singapore, and Thailand—using a Markov regime-switching autoregressive conditional heteroskedasticity (MS-ARCH) model. To connect the stability of monetary policy to stock market volatility, the authors assume that monetary policy and stock price regimes are governed by the same fundamental: the state of the economy. They find that there exists an asymmetric relationship between the volatility of stock prices and the stability of monetary policy regimes. Most of their findings are consistent with real world observations.

The stock price is one indicator that represents the economic performance in a country. Changes in stock prices, including various factors, as an example, is the exchange rate changes as the representation from the foreign exchange market. The fluctuating exchange rate price also influences the volatility of the stock price. Furthermore, volatility has different high and low regime stages that will cause a disparate impact on the outcome of the relationship changes. This study aims to examine the presence of asymmetric volatility and its effects on the volatility of LQ45 stock returns, as well as the changes in exchange rates of Rupiah against USD from 1997 to 2017. Using the Augmented Markov Switching EGARCH approach, the results of this study indicate an asymmetric behavior in the volatility of LQ45 stock returns. High volatility regimes are more dependent and more unstable than low volatility regimes, and low volatility regimes dominate the duration compared to the high volatility regime. The good and bad news give different impact on LQ45 stock return volatility and exchange rate changes. Moreover, the unstable economies will respond faster than the stable economies in terms of facing the exchange rate changes.

The impact of capacity expansion on the market value of the firm

During an inflationary period, changes to the last in, first out (LIFO) method of inventory valuation generally result in reduction of reported earnings and in deferment of tax payments. If the investors rely on the reported earnings, the stock price of the firms which change to the LIFO method will decrease and if they rely on the economic value of the firms, the stock price will increase. Several studies of the relationship between accounting changes and stock price behavior have been conducted by using a research design, as of April 1975. The design involves the use of the market model to isolate the stock price changes associated with specific events from the market-wide price changes. The article attempts to measure the association between the accounting and price changes by abstracting the effect of risk changes. This is accomplished by estimating the time path of the relative risk of stocks during the months surrounding the date of accounting change. The problem of estimating the relative risk of stocks when it is not constant is considered in another section of the article. Conclusions of the study about the relationship between stock price behavior and accounting changes are presented in the last section.