"Uncertainty, Conventional Behavior, and Economic Sociology"

This paper addresses the problem of the conceptualization of social structure and its relationship to human agency in economic sociology. The background is provided by John Maynard KeynesÕs observations on the effects of uncertainty and conventional behavior on the stock market; the analysis consists of a comparison of the social ontologies of the French Intersubjectivist School and the Economics as Social Theory Project in the light of these observations. The theoretical argument is followed by concrete examples drawn from a prominent recent study of the stock market boom of the 1990s.

Uncertainty, Conventional Behavior, and Economic Sociology

This paper addresses the problem of the conceptualization of social structure and its relationship to human agency in economic sociology. The background is provided by John Maynard Keynes's observations on the effects of uncertainty and conventional behavior on the stock market; the analysis consists of a comparison of the social ontologies of the French Intersubjectivist School and the Economics as Social Theory Project in the light of these observations. The theoretical argument is followed by concrete examples drawn from a prominent recent study of the stock market boom of the 1990s.

Digital Subjectivation and Financial Markets: Criticizing Social Studies of Finance with Lazzarato

The recently rising field of Critical Data Studies is still facing fundamental questions. Among these is the enigma of digital subjectivation. Who are the subjects of Big Data? A field where this question is particularly pressing is finance. Since the 1990s traders have been steadily integrated into computerized data assemblages, which calls for an ontology that eliminates the distinction between human sovereign subjects and non-human instrumental objects. The latter subjectivize traders in pre-conscious ways, because human consciousness runs too slow to follow the volatility of the market. In response to this conundrum Social Studies of Finance has drawn on Actor-Network Theory to interpret financial markets as technically constructed networks of human and non-human actors. I argue that in order to develop an explicitly critical data study it might be advantageous to refer to Maurizio Lazzarato’s theory of machinic subjugation instead. Although both accounts describe financial digital subjectivation similarly, Lazzarato has the advantage of coupling his description to a clear critique of and resistance to finance

Self-referential behaviour, overreaction and conventions in financial markets

We study a generic model for self-referential behaviour in financial markets, where agents attempt to use some (possibly fictitious) causal correlations between a certain quantitative information and the price itself. This correlation is estimated using the past history itself, and is used by a fraction of agents to devise active trading strategies. The impact of these strategies on the price modify the observed correlations. A potentially unstable feedback loop appears and destabilizes the market from an efficient behaviour. For large enough feedbacks, we find a `phase transition' beyond which non trivial correlations spontaneously set in and where the market switches between two long lived states, that we call conventions. This mechanism leads to overreaction and excess volatility, which may be considerable in the convention phase. A particularly relevant case is when the source of information is the price itself. The two conventions then correspond then to either a trend following regime or to a contrarian (mean reverting) regime. We provide some empirical evidence for the existence of these conventions in real markets, that can last for several decades.Comment: 15 pages, 12 .eps figure

Investment Discrimination and the Proliferation of Preferential Trade Agreements

The proliferation of bilateral and regional trade agreements has arguably been the main change to the international trading system since the end of the Uruguay Round in the mid- 1990s. We argue that investment discrimination plays a major role in this development. Preferential trade agreements can lead to investment discrimination because of tariff differentials on intermediary products and as result of provisions that relax investment rules for the parties to the agreement. Excluded countries are sensitive to the costs that this investment discrimination imposes on domestic firms and react by signing a trade agreement that aims at leveling the playing field. We test our argument using a spatial econometric model and a newly compiled dataset that includes 166 countries and covers a period of 18 years (1990-2007). Our findings strongly support the argument that investment discrimination is a major driver of the proliferation of trade agreements

Sentiment Analysis of Twitter Data for Predicting Stock Market Movements

Predicting stock market movements is a well-known problem of interest. Now-a-days social media is perfectly representing the public sentiment and opinion about current events. Especially, twitter has attracted a lot of attention from researchers for studying the public sentiments. Stock market prediction on the basis of public sentiments expressed on twitter has been an intriguing field of research. Previous studies have concluded that the aggregate public mood collected from twitter may well be correlated with Dow Jones Industrial Average Index (DJIA). The thesis of this work is to observe how well the changes in stock prices of a company, the rises and falls, are correlated with the public opinions being expressed in tweets about that company. Understanding author's opinion from a piece of text is the objective of sentiment analysis. The present paper have employed two different textual representations, Word2vec and N-gram, for analyzing the public sentiments in tweets. In this paper, we have applied sentiment analysis and supervised machine learning principles to the tweets extracted from twitter and analyze the correlation between stock market movements of a company and sentiments in tweets. In an elaborate way, positive news and tweets in social media about a company would definitely encourage people to invest in the stocks of that company and as a result the stock price of that company would increase. At the end of the paper, it is shown that a strong correlation exists between the rise and falls in stock prices with the public sentiments in tweets.Comment: 6 pages 4 figures Conference Pape

Paths to Fisheries Subsidies Reform: Creating Sustainable Fisheries Through Trade and Economics

The world depends on the oceans for food and livelihood. More than a billion people worldwide depend on fish as a source of protein, including some of the poorest populations on earth. According to the United Nations Food and Agriculture Organization (FAO), the world must produce 70 percent more food to meet coming hunger needs.Fishing activities support coastal communities and hundreds of millions of people who depend on fishing for all or part of their income. Of the world's fishers, more than 95 percent engage in small-scale and artisanal activity and catch nearly the same amount of fish for human consumption as the highly capitalized industrial sector. Small-scale and artisanal fishing produces a greater return than industrial operations by unit of input, investment in catch, and number of people employed.Today, overfishing and other destructive fishing practices have severely decreased the world's fish populations. The FAO estimates that 90 percent of marine fisheries worldwide are now overexploited, fully exploited, significantly depleted, or recovering from overexploitation

At the Water’s Hedge: International Insider-Trading Enforcement After Morrison

From copy rooms to boardrooms, many Americans have succumbed to the siren song of insider trading. As U.S. companies have gone international, so too have corporate secrets ripe for exploitation. With the growth of overseas derivatives based on U.S. stock, foreigners are able to engage in insider trading to a similar extent as Americans. But in Morrison v. National Australia Bank, the Supreme Court limited the reach of the statutory insider-trading prohibition to transactions taking place in U.S. territory or transactions in securities listed on U.S. exchanges. Neither condition applies to overseas insider trading using derivatives. However, courts have reasoned that when the trader’s broker hedges by buying stock on a U.S. exchange, that transaction can be attributed to the trader, thus bringing the scheme within Morrison. This hedging theory depends on the acts of third parties—the brokers—to create insider-trading liability, thus giving arbitrary windfalls to blameworthy traders and creating both evidentiary and legal hurdles for U.S. enforcement. Because Morrison has backed courts into this unworkable corner, it should not govern in insider-trading cases. There is a fix: the Dodd-Frank Wall Street Reform and Consumer Protection Act abrogated Morrison for enforcement actions, albeit imperfectly. By abandoning the theory in favor of Dodd-Frank’s pragmatic standard, courts can more nimbly and forcefully protect U.S. markets from foreign fraud

PRODUCT COMPLEXITY, QUALITY OF INSTITUTIONS AND THE PRO-TRADE EFFECT OF IMMIGRANTS

The paper assesses the trade-creating impact of foreign-born residents on the international imports and exports of the French regions where they are settled. The pro-trade effect of immigrants is investigated along two intertwined dimensions: the complexity of traded goods and the quality of institutions in partner countries. The trade-enhancing impact of immigrants is, on average, more salient when they come from a country with weak institutions. However, this positive impact is especially large on the imports of simple products. When we turn to complex goods, for which the information channel conveyed by immigrants is the most valuable, immigration enhances imports regardless of the quality of institutions in the partner country. Regarding exports, immigrants substitute for weak institutions on both simple and complex goods.MAUP; concentration; agglomeration; wage equations; gravity