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In today’s world scenario, paper currency is economical in the sense that its face value is greater than intrinsic value. It is also more elastic and stable, paper currency can be counted quickly, it is easy to move and safe to store. These all are the main reasons because of which counterfeit currency recognition is crucial. Fake currency cannot be identified by human vision and due to this recognition of forged currency notes has become crucial problem because counterfeiters are using new and improved methods. The methods currently existing to determine whether the notes are real cannot be accessed by the common people and are also complex hardware based methods. There are no applications or devices available through which fake currencies can be detected and identified easily by common people. The main purpose of the project is to identify Indian paper currency with a new methodical approach using Generative Adversarial Networks(GAN). In this system, the Indian currency note features would be primarily extracted using Convolutional Neural Networks (CNNs).The processed image data are then fed to a Generative Adversarial Network which helps to classify the currency as either real or fake. GAN consists of two main modules – Generator and Discriminator. The Generator generates fake currency images and the Discriminator identifies and labels the real and fake images.

With the development of digital economy and big data technology, data resources owned by enterprises have become one of the important production factors in the era of digital economy. Via data empowerment, enterprises analyze the intrinsic value of data, and then realize their own business transformation and innovation and development. After more than ten years of rapid development, China is now the world’s largest automobile production country. Behind the huge automobile market, there are a lot of data resources related to the market and products. However, due to the problems of scattered data sources, inconsistent statistical caliber and untimely updating, it brings great inconvenience to the researchers engaged in automobile industry. This paper proposes a set of passenger car product data governance framework, which aims to provide high-quality passenger car product database for enterprises in the process of studying the market and technology of passenger car products, mining the value of data assets, and assisting managers in decision-making.

This exploratory study examines which investing characteristics determine success in an equity market. Based on data from 403 respondents, exploratory factor analysis results in 13 factors: middle/long time horizon, qualitative analyst, open-minded/disciplined, organized, emotional stability, naive, growth stock, concentrated portfolio, contrarian, value stock, globalized, intrinsic value, and price-independent. Multiple linear regression of individual investors' excess return on these factors show statistically significant relationship. These results deepen our knowledge on what sort of investing characteristics are required to survive in equity markets.

The research on forecasting Ethereum STORJ token has not been widely studied compared to forecasting Bitcoin. The objective of this paper is threefold: apply existing Bitcoin price forecasting models to the Ethereum STORJ token price; evaluate the dynamics of the model predictive utility across three time horizons (h=5 days, h=20 days and h=50 days); and determine if Ethereum STORJ token clustering coefficients impact the effectiveness of the forecasting model. We choose Bitcoin forecasting models of: ARIMA, ARMA-GARCH, VAR, alpha-Sutte Indicator and NNAR. Model effectiveness is analyzed using RMSE, MAE and MAPE. We find that VAR outperforms all models in the short and mid-term horizons (h=5 and h=20 days) and NNAR outperforms all models in the long-term horizon (h=50 days). Non-linearity, the intrinsic value that Neural Network has, may strongly effect the forecast accuracy result. When adding the clustering coefficient to ARIMA, we find that the variable is significant but only marginally improves the forecasting of the Ethereum STORJ token. The VAR model, which includes the clustering coefficient is shown to better forecast Ethereum STORJ prices in the short and mid-term forecasting horizons. The NNAR model is a better model for the long-term forecasting horizon.

We demonstrate a machine learning and artificial intelligence method, i.e., lexical link analysis (LLA) to discover high-value information from big data. In this paper, high-value information refers to the information that has the potential to grow its value over time. LLA is a unsupervised learning method that does not require manually labeled training data. New value metrics are defined based on a game-theoretic framework for LLA. In this paper, we show the value metrics generated from LLA in a use case of analyzing business news. We show the results from LLA are validated and correlated with the ground truth. We show that by using game theory, the high-value information selected by LLA reaches a Nash equilibrium by superpositioning popular and anomalous information, and at the same time generates high social welfare, therefore, contains higher intrinsic value.

The proposed model is intended to assessment of company's operation effectiveness, which is an important factor at investment decisions making. There are compared indicators of the growth rate, profitability and risk for shares placed on various stock exchanges with an assessment of the intrinsic value and management efficiency of company. The information received is useful for investors and company managers for operating on stock markets.

This study aimed to assess the enterprise value of tourism industry. Data of financial statement from 2009 to 2013 was analyzed with the base date on 31 December, 2013. Sensitivity Analysis Method was conducted to convey the effect of each value driver on the promotion of enterprise value. This study found that the fundamental value of Lion Travel agent was NT$ 71.25 while the stock price at the evaluated date was NT$ 126, and the fundamental value of the Phoenix Tours agent is NT$ 45.55 while the stock price at the evaluated date was NT$ 57.7. In addition, the important rankings of the key value drivers of the tourism industry were gross profit margin, change of capital expenditure, revenue growth ratio, capital expenditure ratio, and credit policy, respectively. Therefore, this study suggested that the management should pay more attention to the key value drivers of gross profit margin and change of capital expenditure in the tourism industry.

Most of the methods for estimating the monetary value of patents can be categorized into one of the three conventional discounted cash flow-based approaches, which exhibit two major pitfalls. Firstly, the patent cash flows could not be estimated precisely due to the poor transparency in and the illiquidity of the patent market. Secondly, the value of managerial flexibility which stems from a patent proprietor's right to choose among different patent exploitation strategies could not be systematically revealed through the discounted cash flow analysis. This paper proposes a fuzzy binomial model which is capable of not only assessing the value of a given patent under a fuzzy environment, but revealing the economic value of its inherent managerial flexibility, such as the embedded licensing opportunity.

This study aimed to assess the firm value of TTET Union Corporation. Data from 2007 to 2012 were analyzed, and the evaluation-base date was on 31 December, 2012. Conclusions were as follows: (1) The evaluated firm value of the sample firm by the discounted cash flow method was NT 45.24, (2) The most significant value drivers of TTET Union Corporation were listed in sequence: gross profit margin, revenue growth rate, capital expenditure and capital cost. Managers should concentrate more resources on those value drivers to boost their firm value. Then, the goal of the corporation maximizing the shareholders' wealth might be achieved.

According to the Signaling Theory, excellent auditors have excellent auditing quality. The quality of accounting information from a listed company that hired an excellent auditor for its IPO auditing is more secure, hence favored by investors. This paper uses data from Growth Enterprises Market (GEM) listed companies as a sample, and establish an OLS multiple linear regression model to analyze the impact of auditor reputation and the IPO pricing of GEM listed companies. The results show that hiring a reputable auditors can improve the company's IPO issue price but cannot significantly affect underpricing of IPO. Overall, the auditor's reputation will have an important but relatively limited effect on the stock pricing. Thus, auditor's reputation needs further improvement. This paper empirically examines the relationship between auditor's reputation and IPO issue price as well as underpricing in China's GEM listed companies. It also enriches the scope of IPO study, which has a practical significance in reducing the current high-rate of IPO underpricing.

This essay takes 199 listed companies between October 23, 2009 and December 31, 2011 as samples to study the relationship among intrinsic value of the company, investor sentiment and the IPO under-pricing in the growth enterprise market. Results show that the intrinsic value of the company, investor sentiment and corporate governance is the main factor to affect GEM IPO under-pricing, while industry has no effect on IPO under-pricing.

Option's time value is often deemed as positive by some scholars. Could the time value of option be negative? The paper makes profound analysis and gives a definite answer. Given the time value is positive, should the option be exercised? The answer is NO, for selling option may be better than exercising it. However, for some reasons, selling option is unavailable. As long as the time value is less than the expected intrinsic value loss, exercising option is wise. For American option, its time value disappears at the expiration date while existing intrinsic value can be obtained. The other circumstance is that if underlying assets are going through cash distribution, the value of American option would be higher than European option. Vice versa, if stock price falls, option carriers still have to bear the loss. Therefore, if the time value when you exercise option is less than the dividend or bonus, it would be better for carriers of American option to exercise option before payment of the dividend or bonus.

As the founder of the theory of emergy, more and more scholars use the theory to quantitative analysis human nature, macro-regional environmental resources and the relationship between social and economic value, but for small environmental assessment is still relatively little study. As a study case, Chongqing green space system is analyzed. The results showed that: in 2009, the monetary value of total investment is 36.41×105$, in which the value of renewable energy to the monetary value is 36.41×105$, the value of non-renewable energy sources to the monetary value is 0.16×108$, the value of social investment to the currency value is 12.61×108$. the currency value of total output is 13.8×108$. It can be seen from the data that the total output value of green space system slightly larger than the total value of inputs.

The enterprise market value includes the fair value of net assets, the fair value of residual income, and the impact of Non-Economic Factors on share prices. In addition to the fair value of net assets, the measurement of enterprise excess profitability (Self-created Goodwill) could revise the differences between the fair value of financial statements' items and the stock value, and help the fair value to regain the value relevance. The Non-Economic Factors should be considered not only during the value relevance test, but also when to explain the results.

This paper focus on the behavior option of majority stockholders in private placement of assets-injecting. This research based on the market timing theory. I find that the majority stockholders prefer to issue shares and inject assets when the benchmark price under the intrinsic value and the company's earnings before issue lower than the overall industry earnings. In order to manipulate the benchmark price, they will use the way of choosing pricing base day, opposite earning management and delist. Except that, I also discover that the majority stockholders prefer to issue stocks and inject assets under the background of bull market expectation and in accordance with equity division reform. But the conclusions above also should be verified by empirical research.

This paper classed the investors in the primary market to arbitragers and noise traders, then analyzed the return of the investors from the primary market under the system of cash rationing in China. The results suggest that the arbitragers can work with changing their demand, but the effect of the arbitragers is limited by the demand of the noise traders. When the noise demand is less than the issue volume, the quantity arbitrage is perfect and the offering price is underpriced, but the investors can just earn the normal return and the rule of restricted price has no effect. When the noise demand is more than the issue volume, the quantity arbitrage is limited and the offering price may be overpriced, and the investors will get a negative abnormal return if the offering price is lower than the given value which is lower than the intrinsic value.

Based on monthly data of dual-listed companies in A share and H share markets from November 2006 to November 2009, this paper provides an explanation for A-H share premium by introducing two behavioral factors: heterogeneous beliefs and investor sentiment. The results show that, under the short-sales constraints of A share market, the stronger the heterogeneous beliefs, the higher the A-H premium rate. The higher the investor sentiment of A share market, the higher the A-H premium rate. Under higher investor sentiment, A shares of stocks whose intrinsic value is difficult to estimate are more likely to be overpriced, leading to a higher A-H premium rate. Moreover, higher investor sentiment can strengthen the effect of heterogeneous beliefs on AH premium rate. Overall, theories on heterogeneous beliefs and investor sentiment can well explain the irrational phenomenon of A-H share premium.

IPO's abnormal initial return is very high in the Chinese stock market, which has seriously affected the stock market resource allocation efficiency. This paper empirical analyses abnormal initial returns of 540 new-issued A-shares which issued after the reform of split share structure from January 1st, 2006 to June 30th, 2010. It is found that the noise traders make IPO price away from its intrinsic value; in all circulated shares issue, abnormal initial return does not reduce; investor sentiment remains high, IPO price changes are closely related with the investor sentiment. Comparing IPO initial return and investor sentiment indicators before and after the financial crisis, we can see the first-day initial return has a significant difference, but no big change in investor sentiment.

Based on the MDH theory, a new deterministic delay difference system is proposed combined with a deterministic delay difference model which is suggested by Jan Melecky for time series of closing stock price and intrinsic value of the stock. The merit is that describing the trend of the stock's closing price from intrinsic value and volume of the stock. Therefore, it avoids the non-measurability of other state variables and has more advantages to the application in practical stock market. Based on that, the root of this system is discussed, determination of the intrinsic value of the stock and selection range of some parameters are showed, besides, the system is stably analyzed and the results of numerical simulation shows that trading volume contains the valuable information of the absolute change in future price in conjunction with the data of the Shanghai A shares

Economic Valued Added (EVA) has led an evolution of corporate finance in many well-known abroad enterprises but be paid little attention in China. The empirically analytical results on the SSE 50 sample companies showed that 86% of these companies had no profitability in 2008 from the view of EVA comparing to 2% from the view of accounting profits. The potential reason may be (1) the leading shareholder of most of the SSE 50 samples is the state; (2) the owner's equity often be considered to be “self-owned” by the samples while not by the stockholder; (3) most stockholders speculate but not to invest on the intrinsic value of stock; so their ignore companies' profits, nevertheless EVA;(4)the concept of EVA is based on the opportunity cast of capital, but in China the average investors lack of opportunity to invest their money rather than stock market. In order to be popularized, EVA idea had to be obliged to be used in assessing CEO and his team members' performance. The calculation of the EVA should be standardized and the index of EVA as well as other related index should be added in the Mandatory Information Disclosure System. Thus investors will have chance to know, to understand this index then to make decisions based on it.

The traditional net present value methods didn't do well in the evaluation of power construction projects, which are characterized by large scale of investment, long construction period, and many complex uncertainties, as it is difficult for those methods to calculate the relevant cash flow, internal rate of return and other key indicators. In this paper, we make use of real options to deal with uncertainty in power construction project investment analysis and decision-making, regard risk factors rationally and excavate its option value, thus reflecting the true value of the investment project. Moreover, the paper examined the option value of a power plant with the B-S model. The result reflects that, compared to NPV method, more value would be excavated when considering its flexibility value due to the uncertainty.

In recent years there has been a wide discussion in S&T policy fora on the intrinsic value of countries defining S&T priorities. This paper addresses the international situation with regard to these issues, by comparing a group of 27 different countries. An empirical exploration of data regarding S&T activities in those 27 countries is carried out, in order to infer through cluster analysis different ‘types’ or ‘models’ of S&T priority setting. The analysis shows that two major patterns of scientific publication exist, with some countries concentrating on “engineering and technology” publications while others concentrate on “health-related” themes. A second important aspect is that some countries tend to select R&D areas targeting ”socio-economic objectives” to be financed by public funds while others give priority to a more blue-sky research. Larger countries, namely those that have stronger military interests, tend to be part of the first group. Finally, it is shown that providing less earmarked funds does not necessarily mean lower private participation in national R&D activities. By illuminating what are the existing models of research priority setting the paper intends to have a practical value for both policy-makers and analysts.

The result of value appraisal decides whether an enterprise acquires target or not. Discounted Cash Flow is a theoretical, widely applied method of value appraisal. However, it predicts cash flow by linear model, static appraisal and ignores integration cost. This paper tries to amend the flaws through combining games and Discounted Cash Flow method, considering integration cost. The amendment optimizes Discounted Cash Flow method, increases its practicability and science. Its improvement is available to reduce the risk of value appraisal and complete integration successfully.

This paper constructs a model to analyze the equilibrium of shareholder's interests in the non-public offerings and asset injection, and takes empirical test of 50 listed companies in China's stock market. The model shows whether non-public offering price equals intrinsic value is the critical condition to realize the equilibrium of shareholders' interests. However, the empirical results reveal there is not a close relationship between the two, and exist significant difference in statistics. The average offering price is notably lower than the intrinsic value, which shows major shareholders are likely to seize the interests of minor shareholders. Moreover, the phenomenon is more common in good companies than in bad companies.

After the human society has entered into the 21st century, one new economic form-experience economy followed service economy appeared, which is a new stage of economic development since 1990s. As the experience economy is forming, consumers? attention on the garment products has been changing from their inherent function to pleasant emotion experience which would help to quiet human?s soul. That is, the pure inclination towards rational demand has developed into individuation demand to pursue self-fulfillment. At the same time, the connotation of garment design also changed in terms of this trend. The product would not only have the value of inherent function, but also have the intrinsic value of culture and spirit. Based on experience economy, experience designing and experience, the paper analyzes the main features of garment design in experience economy times, illustrates the related methods and principles of experiencing garment design and tries to offer an instructive thought to experiencing garment design.

The result of value appraisal decides whether an enterprise acquires target or not. Discounted cash flow is a theoretical, widely applied method of value appraisal. However, there are flaws of the theory in predicting cash flow by linear model, static appraisal and ignoring integration cost. This paper tries to amend the flaws in predicting cash flow by genetic neural network, combining games and discounted cash flow method, considering integration cost. The amendment optimizes discounted cash flow method, increases the practicability and science of the method. The improvement of model is available to reduce the risk of value appraisal and complete integration successfully.

As we all know, "sustainable development" idea is spread all over the world. Pollutant control regulations is not only related with the optimization of power resources and environment protection, but also related with the development of electricity market and power structure in the future. How to resolve externality of electricity market is becoming the focus world widely. This article analyzes two key questions of emission trading including allocation and pricing of emission permits. This article also makes economic analysis of pricing of emission trading and set up pricing model for emission permits based on shadow price theory. With these researches, the article verifies that shadow price can be used to reveal the intrinsic value of emission permits resource and realize the optimization allocation and utilization of emission permits among all the electricity generation enterprises. The article also verifies that shadow pricing model could promote total amount control of environment pollution.

Since venture investment can be deferred or not in practices, venture investment projects are classified into exclusiveness ones and competitiveness ones in this paper. With reference to Option-Game theory, the authors analyze their intrinsic value respectively and develop a decision model for each so as to determine deferability of these two types of projects.

To get the over-100-year sustainability, the intrinsic value of renewable energy is the most important. According to this understanding, some projections are provided concerning future PV capability from world energy demand side. A stable, sustainable scenario is proposed up to 2100 in this discussion. To seek for this future state, typical key technologies are also suggested toward the last half of 21st century. In addition, recently in May 2004, Japan set up a long-term roadmap called "PV2030" Assuming that the domestic PV installation will reach around 100 GW up to 2030 and cost targets for 2010, 2020 and 2030 were specified as 23 JPY/kWh, 14 JPY/kWh and 7 JPY/kWh respectively. These levels correspond to present average single-family electricity price, industrial price and whole sale price.

Many authors have studied probabilistic cash flows in recent years. They have introduced analytical methods which determine the probability distribution function of the net present value and internal rate of return of a series of random discrete cash flows; considered serially correlated cash flows and the uncertainty of future capital investment and reinvestment rates; and presented formulas for benefit-cost ratio for probabilistic cash flows. Others have studied the arithmetic of inflation corrections in evaluating real present values. Here, the expected value and the variance of a probabilistic cash flow are obtained by means of moments. Assuming that cash flows are probabilistic because only future discount rates (involving inflation, risk and other factors) are uncertain, we calculate the mean level of future discount rates equivalent to the risk degree in probabilistic cash flows. A numerical example is given.