Novel and topical business news and their impact on stock market activities

We propose an indicator to measure the degree to which a particular news article is novel, as well as an indicator to measure the degree to which a particular news item attracts attention from investors. The novelty measure is obtained by comparing the extent to which a particular news article is similar to earlier news articles, and an article is regarded as novel if there was no similar article before it. On the other hand, we say a news item receives a lot of attention and thus is highly topical if it is simultaneously reported by many news agencies and read by many investors who receive news from those agencies. The topicality measure for a news item is obtained by counting the number of news articles whose content is similar to an original news article but which are delivered by other news agencies. To check the performance of the indicators, we empirically examine how these indicators are correlated with intraday financial market indicators such as the number of transactions and price volatility. Specifically, we use a dataset consisting of over 90 million business news articles reported in English and a dataset consisting of minute-by-minute stock prices on the New York Stock Exchange and the NASDAQ Stock Market from 2003 to 2014, and show that stock prices and transaction volumes exhibited a significant response to a news article when it is novel and topical.Comment: 8 pages, 6 figures, 2 table

Emergence of power laws with different power-law exponents from reversal quasi-symmetry and Gibrat’s law

To explore the emergence of power laws in social and economic phenomena, the authors discuss the mechanism whereby reversal quasi-symmetry and Gibrat’s law lead to power laws with different powerlaw exponents. Reversal quasi-symmetry is invariance under the exchange of variables in the joint PDF (probability density function). Gibrat’s law means that the conditional PDF of the exchange rate of variables does not depend on the initial value. By employing empirical worldwide data for firm size, from categories such as plant assets K, the number of employees L, and sales Y in the same year, reversal quasi-symmetry, Gibrat’s laws, and power-law distributions were observed. We note that relations between power-law exponents and the parameter of reversal quasi-symmetry in the same year were first confirmed. Reversal quasi-symmetry not only of two variables but also of three variables was considered. The authors claim the following. There is a plane in 3-dimensional space (log K, log L, log Y ) with respect to which the joint PDF PJ (K,L, Y ) is invariant under the exchange of variables. The plane accurately fits empirical data (K,L, Y ) that follow power-law distributions. This plane is known as the Cobb-Douglas production function, Y = AKαLβ which is frequently hypothesized in economics.

Power laws in real estate prices during bubble periods

How can we detect real estate bubbles? In this paper, we propose making use of information on the cross-sectional dispersion of real estate prices. During bubble periods, prices tend to go up considerably for some properties, but less so for others, so that price inequality across properties increases. In other words, a key characteristic of real estate bubbles is not the rapid price hike itself but a rise in price dispersion. Given this, the purpose of this paper is to examine whether developments in the dispersion in real estate prices can be used to detect bubbles in property markets as they arise, using data from Japan and the U.S. First, we show that the land price distribution in Tokyo had a power-law tail during the bubble period in the late 1980s, while it was very close to a lognormal before and after the bubble period. Second, in the U.S. data we find that the tail of the house price distribution tends to be heavier in those states which experienced a housing bubble. We also provide evidence suggesting that the power-law tail observed during bubble periods arises due to the lack of price arbitrage across regions.Econophysics, Power law, Bubbles, House prices, Land prices, Price dispersion

POWER LAWS IN REAL ESTATE PRICES DURING BUBBLE PERIODS

How can we detect real estate bubbles? In this paper, we propose making use of information on the cross-sectional dispersion of real estate prices. During bubble periods, prices tend to go up considerably for some properties, but less so for others, so that price inequality across properties increases. In other words, a key characteristic of real estate bubbles is not the rapid price hike itself but a rise in price dispersion. Given this, the purpose of this paper is to examine whether developments in the dispersion in real estate prices can be used to detect bubbles in property markets as they arise, using data from Japan and the U.S. First, we show that the land price distribution in Tokyo had a power-law tail during the bubble period in the late 1980s, while it was very close to a lognormal before and after the bubble period. Second, in the U.S. data we find that the tail of the house price distribution tends to be heavier in those states which experienced a housing bubble. We also provide evidence suggesting that the power-law tail observed during bubble periods arises due to the lack of price arbitrage across regions.

Temporal and Cross Correlations in Business News

We empirically investigated temporal and cross correlations in the frequency of news reports on companies using a unique dataset with more than 100 million news articles reported in English by around 500 press agencies worldwide for the period 2003-2009. Our main findings are as follows. First, the frequency of news reports on a company does not follow a Poisson process; instead, it is characterized by long memory with a positive autocorrelation for more than a year. Second, there exist significant correlations in the frequency of news across companies. Specifically, on a daily or longer time scale, the frequency of news is governed by external dynamics such as an increase in the number of news due to, for example, the outbreak of an economic crisis, while it is governed by internal dynamics on a time scale of minutes. These two findings indicate that the frequency of news on companies has similar statistical properties as trading activities, measured by trading volumes or price volatility, in stock markets, suggesting that the flow of information through news on companies plays an important role in price dynamics in stock markets.

High quality topic extraction from business news explains abnormal financial market volatility

Understanding the mutual relationships between information flows and social activity in society today is one of the cornerstones of the social sciences. In financial economics, the key issue in this regard is understanding and quantifying how news of all possible types (geopolitical, environmental, social, financial, economic, etc.) affect trading and the pricing of firms in organized stock markets. In this article, we seek to address this issue by performing an analysis of more than 24 million news records provided by Thompson Reuters and of their relationship with trading activity for 206 major stocks in the S&P US stock index. We show that the whole landscape of news that affect stock price movements can be automatically summarized via simple regularized regressions between trading activity and news information pieces decomposed, with the help of simple topic modeling techniques, into their "thematic" features. Using these methods, we are able to estimate and quantify the impacts of news on trading. We introduce network-based visualization techniques to represent the whole landscape of news information associated with a basket of stocks. The examination of the words that are representative of the topic distributions confirms that our method is able to extract the significant pieces of information influencing the stock market. Our results show that one of the most puzzling stylized fact in financial economies, namely that at certain times trading volumes appear to be "abnormally large," can be partially explained by the flow of news. In this sense, our results prove that there is no "excess trading," when restricting to times when news are genuinely novel and provide relevant financial information.Comment: The previous version of this article included an error. This is a revised versio

Proposal of a Wireless Power Transfer Technique for Low-Power Multireceiver Applications

In this paper, we proposed and verified the feasibility of a unique wireless power transfer structure called a rail transformer to drive multiple low-power devices such as electronic shelf label (ESL) devices. The rail transformer is composed of a rectangular, circular-shaped transmitting yoke and two transmitting coils to provide wireless power. Multiple receiving yokes coupled with receiving coils are installed across the elongated edge of the transmitting yoke. It can be driven by low-frequency ac power at 50/60 Hz. In our prototype, the transmitting yoke is 900 mm long and 15 mm wide. We obtained the minimal induced wireless power, and the voltage was similar to 61 mW and 3.5 V, which is sufficient to drive a typical ESL device. By designing a nonuniform gap thickness between the transmitting and the receiving yokes at the specific locations, we improved the uniformity of the induced power for multiple ESL devices.ArticleIEEE TRANSACTIONS ON MAGNETICS. 51(11):8402904 (2015)journal articl

Improvement in Efficiency of Wireless Power Transfer of Magnetic Resonant Coupling Using Magnetoplated Wire

Wireless power transfer is expected in the use of an electric vehicle and a chip card. However, it requires a high efficiency and takes a long distance. In this paper, we propose the use of a magnetoplated wire (MPW), which is a copper wire (COW) whose circumference is plated with a magnetic thin film to improve transmission efficiency. The MPW can reduce resistances due to the proximity effect comparison with the COW. The inner diameter of COW and MPW coils is d(i) = 37 mm and their number of turns is n = 10. As a result, the resistances of the COW and MPW at the frequency f = 12 MHz are 6.8 and 4.1 Omega, respectively, which show a reduction of 40%. The quality factors of the COW and MPW at the frequency f = 12 MHz are 83 and 138, respectively, which show an increase of 66%. The efficiencies of the COW and MPW at a transmission distance of 10 mm are 69.8% and 77.7%, respectively, which show an increase of 7.9%.ArticleIEEE TRANSACTIONS ON MAGNETICS. 47(10):4445-4448 (2011)journal articl

On the Evolution of the House Price Distribution

Is the cross-sectional distribution of house prices close to a (log) normal distribution, as is often assumed in empirical studies on house price indexes? How does the distribution evolve over time? To address these questions, we investigate the cross-sectional distribution of house prices in the Greater Tokyo Area for the period 1986 to 2009. We find that size-adjusted house prices follow a lognormal distribution except for the period of the housing bubble and its collapse in Tokyo, for which the price distribution has a substantially heavier right tail than that of a lognormal distribution. In addition, we find that, during the bubble era, the sharp price movements were concentrated in particular areas, and this spatial heterogeneity is the source of the fat upper tail. These findings suggest that the shape of the size-adjusted price distribution, especially the shape of the tail part, may contain information useful for the detection of housing bubbles. Specifically, the presence of a bubble can be safely ruled out if recent price observations are found to follow a lognormal distribution. On the other hand, if there are many outliers, especially near the upper tail, this may indicate the presence of a bubble, since such price observations are unlikely to occur if they follow a lognormal distribution. This method of identifying bubbles is quite different from conventional ones based on aggregate measures of housing prices, and therefore should be a useful tool to supplement existing methods