Real Stock Market Research Articles

Stock Trading Using RSPOP: A Novel Rough Set-Based Neuro-Fuzzy Approach

This paper investigates the method of forecasting stock price difference on artificially generated price series data using neuro-fuzzy systems and neural networks. As trading profits is more important to an investor than statistical performance, this paper proposes a novel rough set-based neuro-fuzzy stock trading decision model called stock trading using rough set-based pseudo outer-product (RSPOP) which synergizes the price difference forecast method with a forecast bottleneck free trading decision model. The proposed stock trading with forecast model uses the pseudo outer-product based fuzzy neural network using the compositional rule of inference [POPFNN-CRI(S)] with fuzzy rules identified using the RSPOP algorithm as the underlying predictor model and simple moving average trading rules in the stock trading decision model. Experimental results using the proposed stock trading with RSPOP forecast model on real world stock market data are presented. Trading profits in terms of portfolio end values obtained are benchmarked against stock trading with dynamic evolving neural-fuzzy inference system (DENFIS) forecast model, the stock trading without forecast model and the stock trading with ideal forecast model. Experimental results showed that the proposed model identified rules with greater interpretability and yielded significantly higher profits than the stock trading with DENFIS forecast model and the stock trading without forecast model.

An efficient fuzzy based neuro – genetic algorithm for stock market prediction

Stock market prediction is a complex and tedious task that involves the processing of large amounts of data, that are stored in ever growing databases. The vacillating nature of the stock market requires the use of data mining techniques like clustering for stock market analysis and prediction. Genetic algorithms and neural networks have the ability to handle complex data. In this paper, we propose a fuzzy based neuro-genetic algorithm - Fuzzy based Evolutionary Approach to Self Organizing Map(FEASOM) to cluster stock market data. Genetic algorithms are used to train the Kohonen network for better and effective prediction. The algorithm was tested on real stock market data of companies like Intel, General Motors, Infosys, Wipro, Microsoft, IBM, etc. The algorithm consistently outperformed regression model, backpropagation algorithm and Kohonen network in predicting the stock market values.

A small scale macroeconometric model for the Euro-12 area

In the paper a small scale macroeconometric model for the Euro area is built, relying on cobreaking and fractional cointegration theory. Several linkages relating key macroeconomic variables are found. Firstly, evidence of a common nonlinear deterministic trend driving the long-run evolution of inflation, nominal interest rates and money growth, determined by medium to long term monetary policy management, is found. Both the quantity theory of money and Fisher's theory of nominal interest rate determination are the economic mechanisms explaining how inflation and nominal interest rates are attracted towards their equilibrium values in the long term. Secondly, evidence of two common long memory factors driving the medium-run evolution of the nominal and real variables, related to output and nominal money growth shocks and short term monetary policy management, is also found. The quantity theory of money, the management of the short term rate by the central bank (Taylor rule), term structure linkages and a present value relationship relating output and real stock market prices growth, are the economic mechanisms explaining the evolution of the macroeconomy in the short to medium term. The macroeconometric model has then been employed to assess the monetary policy strategy of the ECB with respect to the achievement of the price stability objective in the medium term, finding full support for its formulation involving two dimensions, i.e. the monetary pillar and economic pillar.

The Risk and Return Profile of Asian Real Estate Stocks

This research examines the risk and return profile of Asian real estate stocks from an American investor’s point of view. Our results indicate that Asian real estate security markets have not produced high levels of compound returns relative to the US REIT and UK real estate stock markets since the 90’s. They have also experienced a higher level of volatility compared to their USA and UK counterparts. Asset allocations using meanvariance optimization are difficult to carry out, as many of the Asian property stock markets are not normally distributed. In addition, Asian real estate stocks have been able to provide diversification benefits in international investing that includes the US and UK security portfolios. However, the case for separate allocations to international real estate is weakened by the high correlations that are found in Asian markets between the real estate stock and broader market indexes.

Stock market political cycles in a small, two-party democracy

Real stock market returns in New Zealand are lower when the left-leaning Labour party is in power than under National party governments, in contrast to the USA where returns are higher under Democratic presidents than under right-leaning Republicans. The difference in real stock market returns between National and Labour is not reversed even when account is taken of the effect of the US political cycle and returns on New Zealand. The results of the study therefore suggest that the presidential puzzle does not transfer directly to other countries with two similar party democracies.

Long-Term Co-Memories and Short-Run Adjustment: Securitized Real Estate and Stock Markets

This study considers whether securitized real estate and stock markets have long-term co-memories and implications for short-term adjustment. Our results offer reasonable support for fractional cointegration (characteristic of a long memory process) between securitized real estate price, stock market price and key macroeconomic factors in some economies. The implication is that where fractional cointegration prevails, securitized real estate and common stocks are substitutable assets over the long run and these assets may not be held together in a portfolio for diversification purpose. Furthermore, short-run analysis indicates that the speed of adjustment towards the long-run equilibrium is faster for fractional integrated vector error correction model (FIVECM) than VECM as the former incorporates a long history of past cointegration residuals. Additional comparisons of the two models’ forecasting accuracy show that incorporating fractional cointegration in a VECM model improves the forecasting performance over conventional VECM models. Our results reinforce the notion that cointegration, fractional cointegration and short-run adjustment dynamics are important in understanding market integration/segmentation.

On the Time‐Series Properties of Real Estate Investment Trust Betas

The relation between real estate investment trust (REIT) returns and stock market returns is of significant importance to investors, practitioners and academics. The temporal properties of this relationship have a critical impact on the usefulness of REIT risk estimates and portfolio allocations to this asset class. Recent studies have suggested a decline in the market betas of equity real estate investment trusts (EREITs). This study applies a rigorous statistical test of the hypothesis that the market betas of EREITs have remained unchanged during the 1972 through 2002 time period. There is weak evidence of a downward trend in EREIT betas using a single‐factor model; however, the hypothesis is not rejected when using a three‐factor model.

A learning market-maker in the Glosten–Milgrom model

This paper develops a model of a learning market-maker by extending the Glosten–Milgrom model of dealer markets. The market-maker tracks the changing true value of a stock in settings with informed traders (with noisy signals) and liquidity traders, and sets bid and ask prices based on its estimate of the true value. We empirically evaluate the performance of the market-maker in markets with different parameter values to demonstrate the effectiveness of the algorithm, and then use the algorithm to derive properties of price processes in simulated markets. When the true value is governed by a jump process, there is a two regime behaviour marked by significant heterogeneity of information and large spreads immediately following a price jump, which is quickly resolved by the market-maker, leading to a rapid return to homogeneity of information and small spreads. We also discuss the similarities and differences between our model and real stock market data in terms of distributional and time series properties of returns.

Corporate Real Estate and Stock Market Performance

An interesting question in corporate real estate literature is whether real estate can improve the stock market performance of “property-intensive” non-real estate firms. Using a data set comprising 75 non-real estate corporations that own at least 20 percent properties, this paper empirically assesses and compares the pair-wise return, total risk, systematic risk and Jensen abnormal return performance of “composite” (with real estate) and hypothetical “business” (without real estate) firms. We employed Morgan Stanley Capital International world equity index instead of a local market index to provide some insights into the performance of the local market relative to the “global” market during the 1997–2001 volatile periods experienced by many Asian countries. Our results suggest the inclusion of real estate in a corporate portfolio appears to be associated with lower return, higher total risk, higher systematic risk and poorer abnormal return performance. It is therefore likely that non-real estate firms own properties for other reasons in addition to seeking improvement in their stock market performance. Further research is needed to explore the main factors contributing to corporate real estate ownership by non-real estate firms.

Inflation Hedging Characteristics of the Chinese Real Estate Market

Executive Summary. The Chinese real estate market has been experiencing rapid growth and transformation over the last few years. This paper tested the short-term inflation hedging characteristics of real estate markets in four major cities in China: Beijing, Chengdu, Shanghai and Shenzhen, using Autoregressive Integrated Moving Average models. The model restriction was relaxed by adding two macroeconomic factors: real GDP growth and real stock market return. The long-term relationship and causality between the real estate returns and inflation were also tested using country-level aggregate data. The results show no evidence of long-term hedging ability. However, the causality test shows that there is a significant unidirectional causality from the inflation to the real estate return.

Corporate Real Estate and Stock Market Performance (Revised)

An interesting question in corporate real estate literature is whether real estate can improve the stock market performance of property-intensive non-real estate firms. Using a data set comprising 75 non-real estate corporations that own at least 20% properties, this paper empirically assesses and compares the pair-wise return, total risk, systematic risk and Jensen abnormal return performance of composite (with real estate) and hypothetical business (without real estate) firms. We employed MSCI world equity index instead of a local market index to provide some insights into the performance of the local market relative to the global market during the 1997-2001 volatile periods experienced by many Asian countries. Our results suggest the inclusion of real estate in a corporate portfolio appears to be associated with lower return, higher total risk, higher systematic risk and poorer abnormal return performance. It is therefore likely that non-real estate firms own properties for other reasons in addition to seeking improvement in their stock market performance. Further research is needed to explore the main factors contributing to corporate real estate ownership by non-real estate firms.

The Connection of Stock Markets Between Germany and the USA - New Evidence from a Co-integration Study

This paper uses an empirical connection between real stock market indices of Germany and the USA for forecasting corresponding returns. We are starting from the random walk as the traditional forecasting model in stock market applications, extending it by co-integration. Since the cointegrating relation considers information about a systematic link between the stock market indices, containing a common stochastic trend of both, differences from the random walk occur particularly in the long run. Thus, the estimation period shows that with increasing forecasting horizon predictability of simple real returns of the German stock market gets more accurate than reflected traditionally.

Historical Results I

Analysis of the very long term in U.S. markets indicates that average real stock market returns have been about 7 percent and average real T-bond and T-bill returns have been about half that figure. Downward bias in the more recent bond returns and upward bias in recent valuations may be skewing the analysis. Valuations have been rising for three possible reasons: declining transaction costs, declining economic risks, and investors learning that stocks have been undervalued on average throughout history. An analysis of the historical relationships among real stock returns, P/Es, earnings growth, and dividend yields and an awareness of the biases justify a future P/E of 20 to 25, an economic growth rate of 3 percent, expected real returns for equities of 4.5–5.5 percent, and an equity risk premium of 2 percent (200 bps).

Relationships between Australian real estate and stock market prices—a case of market inefficiency

AbstractThis paper explores the relationship between the Australian real estate and equity market between 1980 and 1999. The results from this study show three specific outcomes that extend the current literature on real estate finance. First, it is shown that structural shifts in stock and property markets can lead to the emergence of an unstable linear relationship between these markets. That is, full‐sample results support bi‐directional Granger causality between equity and real estate returns, whereas when sub‐samples are chosen that account for structural shifts the results generally show that changes within stock market prices influence real estate market returns, but not vice versa. Second, the results also indicate that non‐linear causality tests show a strong unidirectional relationship running from the stock market to the real estate market. Finally, from this empirical evidence a trading strategy is developed which offers superior performance when compared to adopting a passive strategy for investing in Australian securitized property. These results appear to have important implications for managing property assets in the funds management industry and also for the pricing efficiency within the Australian property market. Copyright © 2002 John Wiley & Sons, Ltd.

Stock Market Developments and Private Consumer Spending in Emerging Markets

Using a panel of 16 emerging markets, the paper finds a small but statistically significant effect of stock market developments on private consumption spending. In the short run, a 10 percent decline in the annual real stock market return is associated with a reduction in real private consumption by around 0.1-0.3 percent on average. There is evidence that the link between stock market fluctuations and private consumption has become stronger during the 1990s as stock markets in emerging economies have broadened and deepened. However, there is no significant evidence that the influence is asymmetric. Stock price declines do not have a different impact on consumption than stock price increases.

Stock Market Developments and Private Consumer Spending in Emerging Markets

Using a panel of 16 emerging markets, the paper finds a small but statistically significant effect of stock market developments on private consumption spending. In the short run, a 10 percent decline in the annual real stock market return is associated with a reduction in real private consumption by around 0.1-0.3 percent on average. There is evidence that the link between stock market fluctuations and private consumption has become stronger during the 1990s as stock markets in emerging economies have broadened and deepened. However, there is no significant evidence that the influence is asymmetric. Stock price declines do not have a different impact on consumption than stock price increases.

Real estate and corporate valuation: an asset pricing perspective

AbstractProperty is a significant asset in the balance sheets of some Singapore industrial/commerce firms and hotel corporations. In this research, we take on the task of examining the relationship between real estate and stock market valuation of these business firms from an asset pricing perspective. Specifically, the real estate sensitivity of ‘property‐intensive’, non‐real estate stocks is investigated in both a three‐index (market, sector and property) of stock returns and in an arbitrage pricing theory (APT) framework. The APT model is further recast as a multivariate non‐linear regression model with across‐equation restrictions. Using weekly returns on ‘property‐intensive’ stocks in the period 1989–1998 and three shorter‐sample periods, iterated non‐linear seemingly regression techniques (ITNSUR) are employed to obtain joint estimates of stock sensitivities and their associated APT risk ‘prices’. The ‘real estate’ sensitivity is found to be systematic and priced in the APT sense of corporations being paid an ex ante premium for bearing property market risk in investing and owning properties in two of the three sample periods (1989–1991, 1992–1994). The empirical results provide some support that property is a factor in corporate valuation, and is broadly consistent with the efficient markets hypothesis. The implications for portfolio and corporate management are examined. Copyright © 2001 John Wiley & Sons, Ltd.

A Swedish real estate stock market index, 1939–19981

This paper presents a new index for Sweden computed using a new time-series of 60 years of monthly returns of real estate stocks from 1939 to the present. The computation of the index is explained along with some general statistics. We find that the financial crisis of 1990-92 and the subsequent economic turmoil had a devastating effect on the real estate stock market. The returns are subject to kurtosis and skewness, especially during the last decade of the period. The Swedish real estate stock market was less sensitive than the Swedish stock market index. This new index offers a valuable data set for future research in financial economics as well as other disciplines.

Who triggered the Asian financial crisis?

The Asian financial crisis was triggered by Japanese commercial banks who reduced their exposure to Asia in response to emerging troubles in Thailand and South Korea. Japanese banks had been severely weakened by the collapse of the real estate and stock market bubble in Japan in 1990. As the largest lenders in Asia and the key creditor in Thailand, Japanese banks signalled the change in sentiment to other foreign commercial banks who also withdrew their loans. These capital outflows triggered a devaluation in Thailand in mid-1997, but not in Korea until late 1997, due to the different exchange rate regimes in these countries. Despite the devaluation and outflow of bank loans, bond investors continued to provide capital to Asian borrowers until November 1997, at spreads which did not reflect the risks involved. By 1998, foreign equity investors were returning to these markets in search of bargains. Rather than rushing to the exits in a herd-like fashion, institutional investors made investment decisions which created off-setting private capital flows. This analysis suggests that more attention should be paid to the incentives facing institutional investors and the design of domestic institutions, rather than to the need for a new financial architecture.

Market Efficiency and Return Statistics: Evidence from Real Estate and Stock Markets Using a Present‐Value Approach

This paper develops a methodology to identify asset price response to news in the framework of the Campbell–Shiller log‐linear present‐value equation. We further show that a slow price adjustment in real estate markets not only induces a high serial autocorrelation in excess returns, but also dampens the return volatility and the correlation with excess returns in other asset markets. Using Hong Kong real estate and stock market data, we find that the quarterly real estate price assimilates only about half the effect of market news, whereas the quarterly stock price incorporates the news fully. Our analysis identifies a cumulative price adjustment that recovers lost information in real estate returns due to market inefficiency and thereby restores the real estate return volatility and the correlation between real estate and stock markets.