Цена внезапного раскрытия инсайдерской информации на фондовом рынке
We consider a discrete model of insider trading in terms of repeated games with incomplete information. The solution of the bidding game of beforehand unlimited duration was obtained by V. Domansky (2007). Insider's optimal strategy in the infinite stage game generates the simple random walk of posterior probabilities over the lattice l/m, l=0,...,m with absorption at the extreme points 0 and 1 and provides the expected gain 1/2 per step to insider. In this paper we calculate insider's profit in the game of any finite duration when he applies the strategy above. It is shown that this strategy is his epsilon-optimal strategy in n-stage game, where epsilon decreases exponentially. This means that the sequence of n-stage game values converges to the value of infinite game at least exponentially. The result obtained is interpreted as the loss of insider in the case of sudden disclosure of his private information. For the special case we compare obtained insider's profit with the exact game value (result of V. Kreps, 2009) and demonstrate that error term in the case of optimal insider's behaviour also decreases exponentially.
The paper considers a game-theoretical model of bidding with asymmetric information. One player has the inside information on the liquidation price of risky asset. The model is formalized with the repeated game with incomplete information on the side of uninformed player. We consider the case of external stopping of the game at the random moment. Insider's expected profit in the game of random duration if she applies the strategy optimal in infinite-stage game is obtained. This result allows to calculate the loss of insider in case of sudden disclosure of his private information.
Adoption of law about inside - very serious step towards formation of the transparent market, without shadow games and gray transactions. The writing, consideration and acceptance of the given statutory act lasted more than 10 years and here, at last, it is accepted. Author tries to analyze, whether it is necessary to wait from it for real results.
In this paper we will lean on the behavioral explanation of return dynamics. The most popular behavioral origin of autocorrelation is gradual information diffusion between equity securities [Badrinath et al., 1995] and different groups of investors [Hong, Stein, 1999]. The first point out, that some piece of information is instantaneously considered to be price-relevant for a certain industry or individual company, but after a while the investors realize, that the information revealed has an effect on valuation of further assets, what induces the prices of these further stocks to follow and thus generate autocorrelation of index returns. The latter argue, that investors perceive different bits of news (even on the same company) and gradually exchange the information they got, until each of them can get together a whole picture from the different parts, similar to children putting a puzzle together. Since each investor gets the same bit of information from a previous investor, he acts on it in the same way (assuming he draws the same conclusions) with a lag, thus inducing serial correlation on single equity and index returns as well.
Until recently in Russia there were only administrative penalties for illegal insider trading, those were rarely used and insider trading was wide-spread. In 2010 the law on insider trading was introduced. It stipulated criminal penalties for illegal insider trading. An identification of cases of suspected insider trading and a comparison of its scale with other markets is a pertinent issue, including for an evaluation of the effectiveness of the adopted law.
The research of insider trading on developed and emerging markets shows that insiders earn positive abnormal return by trading shares before the announcements of important corporate events on average. This abnormal return is higher in emerging markets. Mergers and acquisitions are such type of corporate events. There is a correlations between severity of the law on insider trading and the size of insider trading.
Our research covered 36 M&A deals in the Russian market in 2006–2013. We have found positive average abnormal returns (ACAR) before the announcement of the deals. They reach 15% at the date of an announcement or a first rumor. These numbers are statistically significant starting from date -12 at the 1% confidence level. Two thirds of the ACAR is realized before the announcement of the deal while in the USA only one third is realized before the announcement. Average abnormal trading volume is also positive. A sharp increase of AVV takes place five days before the announcement. AVV grows up to the date of announcement and reaches 382% of the standard volume one day before the announcement. The existence of positive ACAR and AAV is an indication of the fact that the market learned about the deals before the an official announcement and even before public rumors, that is it hints at the existence of the insider trading in the Russian stock market.
We consider certain spaces of functions on the circle, which naturally appear in harmonic analysis, and superposition operators on these spaces. We study the following question: which functions have the property that each their superposition with a homeomorphism of the circle belongs to a given space? We also study the multidimensional case.
We consider the spaces of functions on the m-dimensional torus, whose Fourier transform is p -summable. We obtain estimates for the norms of the exponential functions deformed by a C1 -smooth phase. The results generalize to the multidimensional case the one-dimensional results obtained by the author earlier in “Quantitative estimates in the Beurling—Helson theorem”, Sbornik: Mathematics, 201:12 (2010), 1811 – 1836.
We consider the spaces of function on the circle whose Fourier transform is p-summable. We obtain estimates for the norms of exponential functions deformed by a C1 -smooth phase.