Investors In Financial Market Research Articles

Chinese Financial Market Investors Attitudes toward Corporate Social Responsibility: Evidence from Mergers and Acquisitions

As China’s economic development has shifted from quantitative growth to qualitative improvement, stakeholders have enforced stricter corporate social responsibility (CSR) requirements for listed companies. However, few studies have focused on companies and CSR in such developing economies. We used the CSR scoring system from Hexun Finance’s website to group Chinese listed companies according to their CSR scores. By comparing the effects of merger and acquisition (M&A) announcements on different CSR scores, we found that, first, the average abnormal return (AAR) response time of the low-CSR acquirers group was eight trading days, much longer than that of the medium-CSR (three trading days) and the high-CSR group (four trading days). Second, from five trading days before, and 15 trading days after the announcement date, the cumulative AAR (CAAR) of the acquirers in the low-CSR group was 0.270, much higher than those in medium- and high-CSR groups. Third, after considering the CSR scores for the two years prior to the M&A and controlling for other factors affecting the M&A, the CSR performance of the above-mentioned M&As was still negatively correlated with the M&A announcement effect. This point to the need for further studying CSR and M&A announcement effects for Chinese companies.

Pattern Matching Trading System Based on the Dynamic Time Warping Algorithm

The futures market plays a significant role in hedging and speculating by investors. Although various models and instruments are developed for real-time trading, it is difficult to realize profit by processing and trading a vast amount of real-time data. This study proposes a real-time index futures trading strategy that uses the KOSPI 200 index futures time series data. We construct a pattern matching trading system (PMTS) based on a dynamic time warping algorithm that recognizes patterns of market data movement in the morning and determines the afternoon’s clearing strategy. We adopt 13 and 27 representative patterns and conduct simulations with various ranges of parameters to find optimal ones. Our experimental results show that the PMTS provides stable and effective trading strategies with relatively low trading frequencies. Financial market investors are able to make more efficient investment strategies by using the PMTS. In this sense, the system developed in this paper contributes the efficiency of the financial markets and helps to achieve sustained economic growth.

Seeing is Believing: Travel, Familiarity and International Equity Investments

We examine whether international tourism affects financial market investments. Using data for more than 40 countries, we demonstrate that recreational travel between countries is associated with higher levels of foreign equity investments. Increased foreign investments lead to a reduction in home bias and improved diversification. The impact of tourism is stronger for countries that are farther apart or when home country residents are more risk averse. Using predictors of recreational travel as instruments, we show that the relation between foreign travel and foreign equity investments is causal. Collectively, these results suggest that tourism has positive externalities in financial markets.

Modeling volatility of Indian exchange rates under the impact of regime shifts: A study with economic significance analysis

In this paper, we assess the impact of regime shifts on the long memory properties of the Indian exchange rates. We make use of Sanso, Arago and Carrion (2004) Iterated Cumulative Sum of Squares (hereafter referred as AIT-ICSS) algorithm to detect the points of structural breaks in volatility series. Our findings indicate that incorporating the impact of sudden changes in volatility in the model indeed reduces the magnitude of long memory parameter. In the case of INR/JPY, we observe a shift in characteristics from long memory to mean reversion when the impact of regime shifts is included in the volatility model. Our findings also highlight that incorporating the impact of regime shifts in the model also improves the volatility forecast accuracy. Moreover, we implement a trading strategy based on risk-averse investor and find that the volatility forecasts based on the model which incorporate the impact of structural breaks provide substantial gains in return in comparison to volatility models with no structural breaks. These findings have important policy implications for financial market participants, investors and policy makers.

Studying Concepts of the Breakthrough Economic Reforms in Selected Developed and Developing Countries and Regions of the World: Economic and Legal Aspects

The purpose of the present article is to analyze the experience of advanced development of two Asian countries (Japan and China) based on the use of economic breakthrough concepts. The object of study in this article concerns developed and developing countries, as well as transition countries, while research subject involves concepts and models of breakthrough economic reforms in Japan and China. Through the use of several analytical methods (comparative legal and institutional analysis, economic and statistical analysis, and content analysis) we have come up to the following conclusions: economic breakthrough of contemporary developed countries is obviously linked with the technologization as well as modernization of the national production, and economic diversification; developed countries (European Union, North America, and Asia) have established special institutional frameworks (national innovation systems), which allowed creating a competitive product demanded on both the internal and external market, and increasing labor productivity through improving the quality of the workforce (social investment);there are definitely certain similarities in the economic progress of China and Japan (essential involvement of the state in economic processes), however, at the same time these countries are differed by their institutional platforms (in particular, China is open to investment, while Japan focuses on the domestic financial market and the labor market).Results: considering the applicability of economic breakthrough models of Japan and China in relation to Russia, we should note that such models cannot be simply copied to the Russian market without changes (for example, due to the underdeveloped national financial market and insufficient investment attractiveness). Therefore, we suggest in future studies to develop a number of system solutions, which can be used to diversify the Russian raw materials export-based economic model.

Isolating the value-relevant part of advertising spending

PurposeThis paper aims to examine how much importance the financial market attaches to advertising spending’s short-term productivity vis-à-vis its investment component and the impact of important contextual factors (investor mix and analyst coverage) on this trade-off.Design/methodology/approachA stochastic frontier estimation (SFE) approach is used to help disentangle advertising spending. Using a panel internal instruments model and 10,017 firm-year observations from publicly listed US companies over a 13-year period, this study relates aggregated advertising spending and disentangled advertising spending, together with important contextual factors, to Tobin’s q.FindingsThe results do not indicate an effect of aggregated advertising spending on Tobin’s q. However, after advertising spending is disentangled, results show the component with an efficient immediate revenue response to have a positive effect on Tobin’s q, whereas the effect of the remaining investment component is negative. Contextual factors moderate investors’ valuation of the components.Research limitations/implicationsFindings are limited to US publicly listed firms, and are based on secondary, non-experimental data. The results imply that investors reward firms only for short-term advertising productivity, casting doubt on investors’ understanding of the long-term value of marketing.Practical implicationsThe results confirm managers’ belief that not all money spent on advertising creates shareholder value. Managers should use the outlined SFE to benchmark their firms’ short-term advertising productivity against that of industry peer firms.Originality/valueThis study advances a new perspective, suggesting that advertising spending can be decomposed into two distinct parts by considering how financial market investors evaluate advertising spending. Important contextual effects on this evaluation from firms’ investor mix and analyst coverage are also shown for the first time. The findings help in reconciling conflicting prior results, and shed new light on how the financial market evaluates marketing expenditures.

Special Issue: Financial Market Dynamics, Monetary Policy, Investment and Trade. Papers Presented at the Fourth International Symposium in Computational Economics and Finance (Paris, April 14–16, 2016)

Special Issue: Financial Market Dynamics, Monetary Policy, Investment and Trade. Papers Presented at the Fourth International Symposium in Computational Economics and Finance (Paris, April 14–16, 2016)

The Conflict Between Economic and Social Preferences: Social Investing, Social Enterprise, Mind-Sets and Nudges

Investing into the financial markets has become increasingly complex in recent years, with a multitude of investment products and motives. With the rapid growth in social investing and social entrepreneurship, scholars recognise that investors and entrepreneurs often consider a wide range of social factors, in addition to financial return, when making their financial decisions. Behavioural economists argue that it is important to understand the complex economic and behavioural/psychological factors affecting social investors’ decision-making. In this paper, we draw upon lessons from behavioural economics (and in particular, social preference theory) in order to develop neuro-economic tests of investors’ social and financial mind-sets. We focus on two main research questions: a) How heterogeneous are (social-) investors, in terms of the unconscious weightings that they place upon financial and social returns? Can investors’ mind-sets be placed upon a continuum from focussing on social returns, through mixed motivations/weightings, through to focussing on financial returns? b). Can investors be nudged along this continuum? We address these two research questions by means of two neuro-experiments. We employ eye-tracking techniques to examine investors’ attention to, and fixation on, social and financial aspects of financial market investment. In addition, we employ nudges in the form of images relating to positive and negative social behaviour. Our experiments demonstrate that a) investors can indeed be placed on the financial-social motivation continuum (and that there is heterogeneity in social-investors’ motives along this scale), and b) investors can be nudged along the scale. Our experiments thus provide policy implications regarding nudges towards social investment. Practically, we suggest the development of a phone application that integrates real-time stock-tracking with nudges in order to inspire socially responsible investing; banks would play a key role in encouraging its download. Nudges can help to overcome the conflict between social and financial returns.

Which Artificial Intelligence Algorithm Better Predicts the Chinese Stock Market?

Unpredictable stock market factors make it difficult to predict stock index futures. Although efforts to develop an effective prediction method have a long history, recent developments in artificial intelligence and the use of artificial neural networks have increased our success in nonlinear approximation. When we study financial markets, we can now extract features from a big data environment without prior predictive information. We here propose to further improve this predictive performance using a combination of a deep-learning-based stock index futures prediction model, an autoencoder, and a restricted Boltzmann machine. We use high-frequency data to examine the predictive performance of deep learning, and we compare three traditional artificial neural networks: 1) the back propagation neural network; 2) the extreme learning machine; and 3) the radial basis function neural network. We use all of the 1-min high-frequency transaction data of the CSI 300 futures contract (IF1704) in our empirical analysis, and we test three groups of different volume samples to validate our observations. We find that the deep learning method of predicting stock index futures outperforms the back propagation, the extreme learning machine, and the radial basis function neural network in its fitting degree and directional predictive accuracy. We also find that increasing the amount of data increases predictive performance. This indicates that deep learning captures the nonlinear features of transaction data and can serve as a powerful stock index futures prediction tool for financial market investors.

How linkages fuel dependent economic policy initiatives

PurposeWith the globalization and liberalization in terms of increasing financial flows across the countries, the policy makers around the world are not independent in the context of monetary and fiscal policy initiatives. In this regard, this paper aims to attempt to quantify and capture long run, short run as well as time-varying linkages among the two financial stress indices, namely, Kansas City Financial Stress Index (KCFSI) and Indian Financial Stress Index (IFSI) across the monthly period (2004 to 2014).Design/methodology/approachOwing to the non-existence of a standardized financial stress index with regards to the Indian financial system, the study has developed an index/stress indicator using principal component analysis. Furthermore, to comprehend the linkages, the study uses bivariate Johansen cointegration model, vector error correction model, impulse response functions (IRF), variance decomposition analysis (VDA), Toda-Yamamoto’s Granger causality test and, finally, bivariate generalized autoregressive conditional heteroskedastic (BVGARCH) (1,1) model under constant conditional correlation (CCC) framework.FindingsThe results report a stochastic trend among the two indices wherein the US financial system acts as a source of a shock causing disequilibrium in the long run co-movement. About 40 per cent of the adjustments take place in one month and rest in the coming months. Both the IRF and VDA report a greater degree impact of the US financial stress on the Indian financial system. Moreover, there is a uni-directional short run causality running from the stress in the US financial system to the Indian financial stress. Furthermore, the co-movement between the US and Indian financial stress reached to its maximum significant level during the sub-prime crisis even confirmed by the Markov switching model results.Practical implicationsOverall, the results provide an insight to the financial market investors both domestic as well as international in their act of risk management. The financial stress prevailing in an economy further has an impact on different economic factors like foreign exchange rates, interest rates, yield curves, equity market returns and volatility. So, the empirical results support strong implications for the Indian policy makers as well as investors in the Indian financial markets.Originality/valueThe present study contributes to the literature in three senses. First, the study considers indices reflecting financial stress in the Indian as well as US financial system. Second, the study captures long run as well as short run linkages among the financial stress indices relating to a developed and an emerging market. Finally, the study uses CCC-BVGARCH (1,1) model to account for the time-varying co-movement among the financial stress indices. This helps in comprehending time-varying nature of the co-movement of the stress in the financial system prevalent in the respective markets.

Overreaction Market Analysis, Dividend Policy, Firm Size, and Seasonality to Price Reversal Phenomena

Objective - In an efficient capital market, the price of a stock reflects the outstanding and relevant information. However, some studies find that is the capital markets are not always efficient. Sometimes investors put too high a price, good news and vice versa. That's why there are variety of capital market anomalies such as the price reversal. This research, test share return following one day a big change of the share price in the Indonesia capital market. Methodology/Technique - The unit of analysis in this study are the stocks that listed in the Jakarta Islamic Index. Then we used purposive sampling method for sampling and 21 samples obtained shares. These samples, then classified into 11 shares 10 shares winner and a loser. Analysis the user is paired sample t-test and doubled regression. In addition, double regression analysis with market overreaction, dividend policy, firm size and the January effect as independent variables and price reversal as the dependent variable. Findings - Regression test showed that in the group winner stocks, market overreaction, firm size and January effect have an effect on signs of price reversal. And dividend policy has no significant influence. For the group of loser stocks, market overreaction, dividend policy, firm size and January effect affect both simultaneously and partially on price reversal. Novelty - The study contributes decision making of investors in Indonesia financial market with its evidences. Type of Paper: Empirical Keywords: Market Overreaction; Dividend Policy; Firm Size; January Effect; Price Reversal. JEL Classification: G11, G14, M41.

Does hype create irreversibilities? Affective circulation and market investments in digital health

This article draws from two conceptual lenses – the sociology of expectations and market studies – to investigate the relationship between technology hype and market investments: which promises and expectations surround hype and how they come together to shape actors’ investments in an emerging market. We address this question through analysing a contemporary hype in a technology marketing context: digital healthcare. Our aim is to trace how market actors create, support and evaluate a market hype; how hype and market investments are related; and whether hype contributes to irreversibilities in shaping emerging market forms and categories. Our study indicates that hypes contribute tangibly to producing the market, not least by channelling financial, symbolic and material market investments. Furthermore, by highlighting how socio-economic, technological and policy promises become affectively loaded through circulation, we add a novel dimension to existing insights into the socio-cognitive construction of markets. We caution technology marketers, policymakers and investors against blindly following technology hype, especially when it encourages companies to engage in market investment that is unhinged from broader systems and societal, ethical or economic concerns.

Consumption with Unhedgeable Interest Rate Risk

This paper investigates the optimal investment and consumption problem in a continuous-time financial market for investors with power utility on consumption, who face partially hedgeable interest rate risk. With no analytical solution to the optimal strategies, closed-form approximate strategies are derived by solving the same optimization problem in two fictitious complete markets. The approximate solution helps verify the existence and the optimality of the solution to the original optimization problem and provides bounds of the optimal consumption strategy and the approximation error, both in closed form. As the interest rate increases, if the investor's risk aversion is greater than one, the wealth effect dominates the substitution effect, and consumption increases. If risk aversion is less than one, then the substitution effect dominates, and the investor consumes less.

On optimal proportional reinsurance and investment in a hidden Markov financial market

This paper investigates the optimal reinsurance and investment in a hidden Markov financial market consisting of non-risky (bond) and risky (stock) asset. We assume that only the price of the risky asset can be observed from the financial market. Suppose that the insurance company can adopt proportional reinsurance and investment in the hidden Markov financial market to reduce risk or increase profit. Our objective is to maximize the expected exponential utility of the terminal wealth of the surplus of the insurance company. By using the filtering theory, we establish the separation principle and reduce the problem to the complete information case. With the help of Girsanov change of measure and the dynamic programming approach, we characterize the value function as the unique solution of a linear parabolic partial differential equation and obtain the Feynman-Kac representation of the value function.

Dynamics Evolution of Trading Strategies of Investors in Financial Market

This paper analyzes investors’ trading strategies based on the theory of evolutionarily stable strategies and replicator dynamics model. Under the assumptions closer to a real market, we reveal the relationships between the investor’s price anticipation and equilibrium sustained state. If the mean value of price deviation anticipated by investors is a negative value, there is one equilibrium sustained solution. And if the mean value of price deviation anticipated by investors is a positive value, one equilibrium sustained solution or two equilibrium sustained solutions are likely to appear in our models. This research is beneficial to evaluate differences in revenues between rational traders and noise traders, to understand dynamic evolutionary process of trading strategies, and to find equilibrium sustained solution. In addition, financial crisis as an exogenous factor is introduced into the evolutionary model. Based on theoretical analysis and simulation experiment, the results show that case 3 in theoretical analysis does not occur in the simulation after the outbreak of financial crisis, and case 1 and case 2 in theoretical analysis correspond to the different regions of the anticipated price deviation curves. Moreover, the changes of two equilibrium sustained solutions show opposite tendency characteristics with an increasing of the mean value of price deviation of risk asset. Relative to the existing research results, this paper distinguishes the different yield between risk assets and riskless assets, and considers the existence of transaction cost, assumes investors having different risk aversion coefficient, and takes financial crisis as an example to research the impacts of exogenous variables on investors’ trading strategies. Through comparative analysis, the conclusions drawn from simulation experiment are consistent with equilibrium sustained solutions in theoretical analysis.

Financing energy transformation: The role of renewable energy equity indices

ABSTRACTThe support of financial markets for the transformation of the energy system to a low carbon society seems critical for its success. But will they support this transformation on the basis of market incentives alone? This study analyses how equity indices that try to capture renewable energy investments perform compared to conventional benchmark indices. Especially financial market investors—such as pension funds, insurance companies, and mutual funds—use these to assess and guide their renewable energy investments. As such, we take the perspective of financial market participants, which mainly only indirectly invest in renewable energy. We also analyze whether renewable energy indices are to be regarded as an example of market environmentalism. We find that the renewable energy indices’ risk-adjusted return is very poor and suggests renewables is not a financially attractive portfolio investment yet. We also argue that renewable energy equity indices can be regarded as an example of market environmentalism, especially with respect to commodification and frame-shifting.

Influence of Demographic Variables on Saving Behaviour of Rural Households – A Study with Reference to Sriperumpudur, Chennai

Saving is really a good habit particularly for the common layman. With the understanding of the above, a study was conducted in Sriperumpudur near Chennai about the saving behaviour of households and the influence of demographics over them. Objectives: The study was conducted by the authors to know the influence of demographic variables on a whole in saving behaviour and specifically, to know the level of influence of demographic factors in savings, to identify the level of saving of the people from their income and to identify the nature of investors. Analysis: The descriptive research design is adopted by the researchers in this study. They have adopted the non-probabilistic convenience sampling method for the collection of sample and the exact sample size of the study is 457. The respondents are approached with the systematic self-administered questionnaire for data collection. The researcher has used the chi-square test and the cluster analysis for the data analysis and further execution of the study. The study was concentrated on Sriperumpudur town near to Chennai only. Findings: The study has major findings that demographic variables like gender, age, marital status, number of earning members in the family, annual income have influenced annual savings. It is also found that there is an association between different heterogeneous groups of households' investment in financial market and their annual savings. But it has been indentified that there is no association between education and annual savings. Hence it is concluded that the demographic variables are playing vital role in influencing the saving behaviour of the individuals. Applications: The study has contributed for the improvements in the area where saving behaviour can be investigated from the dimension of influence of demographic variables. There are different applications that are made to identify the demographical behaviour of the respondents towards their investment choice. This study can also extensively be applied in the case of classification of demographic and psychographic variables. Improvements: Different educational qualifications of the respondents found in this study and they are considered as School Education, UG, PG, and Professional Education. They have different qualifications and aims in the determination of the investment avenues but at the same time the qualification does not influence them to choose the investment avenue. But all other demographic variables have an influence over the choice of investment avenues and change the behaviour of the investors towards the investment process. It is also found that there are certain developments in the behaviour of the individuals regarding their investment choice by their demographics.

Development and validation of a stock addiction inventory (SAI).

BackgroundInvesting in financial markets is promoted and protected by the government as an essential economic activity, but can turn into a gambling addiction problem. Until now, few scales have widely been used to identify gambling addicts in financial markets. This study aimed to develop a self-rating scale to distinguish them. In addition, the reliability and validity of the stock addiction inventory (SAI) were demonstrated.MethodsA set of questionnaires, including the SAI, south oaks gambling screen (SOGS), and DSM-5 diagnostic criteria, for gambling disorder was completed by 1005 participants. Factor analysis, internal consistency testing, t tests, analysis of variance, and partial correlation analysis were conducted to verify the reliability and validity of SAI.ResultsThe factor analysis results showed the final SAI consisting of two factors and nine items. The internal consistency and concurrent validity of SAI were verified. The Cronbach’s α for the total scale was 0.892, and the SAI and its factors were significantly correlated with SOGS.ConclusionsThis study developed a specific scale for financial market investments or trading; this scale proved to be reliable and valid. Our scale expands the understanding of gambling addiction in financial markets and provides a diagnostic reference.

Проектирование и инвестиционной торговой системы на финансовых рынках

Проектирование и инвестиционной торговой системы на финансовых рынках

Characterizing investor expectations for assets with varying risk

How do financial market investors form expectations about assets with different risk characteristics? We examine this question using Euro-area yield curves for AAA-rated and AAA-with-other bonds. Investors’ conditional forecasts about the yield curves for different assets, at various forecasting horizons, are modeled using a VAR model with time-varying parameters. Two processes are assumed for the evolution of these parameters: a constant-gain learning model and a new endogenous learning technique proposed here. Both these algorithms allow investors to account for structural changes in the data. The endogenous learning mechanism also allows investors to compensate for large deviations in observed coefficients used for forecasting, relative to past data. Daily data is used to estimate the gain parameters for the learning algorithms, and we find that these gains vary across asset types, implying investors form conditional expectations differently for assets with differential risks. For 2005–2015, the investors’ conditional forecasts for the AAA-rated bonds are better described using the endogenous learning mechanism, implying that investors with lower risk preferences are more sensitive to large deviations in the data.