Continuous-Time Insider Trading with Risk-Neutral Insider under Imperfect Observation

A model of insider trading in continuous time in which a risk-neutral insider possesses long-lived imperfect information on a risk asset is studied. By conditional expectation theory and filtering theory, we turn it into a model with insider knowing complete information about the asset with a revised risky value and deduce its linear Bayesian equilibrium consisting of optimal insider trading strategy and semistrong pricing rule. It shows that, in the equilibrium, as the degree of insider observing the signal of the risky asset value is more and more accurate, market depth, trading intensity, and residual information are all decreasing and the total expectation profit of the insider is increasing and that the information about the asset value incorporated into the equilibrium price, which has nothing to do with the volatility of noise trades, is increasing as time goes by, but not all information of asset value is incorporated into the price in the final disclosed time due to the incompleteness of insider’s observation, though the market depth is still a time-independent constant. Some simulations are illustrated to show these features. However, it is an open question of how to make maximal profit if the insider is risk-averse.

Leveraging a Long and Tuneful History

In evaluating the success of twenty-first-century applications of surround sound technology, the popular press often fails to take into consideration the powerful role that history plays in their design. Dolby Atmos for Cinema (2012 –) has been marketed as groundbreaking and become a gold standard in cinema sound. Conceived of as a means to create a “platform” that would reach across the movie theatre, home theatre, music, and virtual reality for maximal profit, however, Atmos was always designed to move beyond it. Discussing both Atmos for Cinema and Atmos for Music (2016–), and drawing on first-hand interviews with industry insiders, this chapter situates Dolby’s platform into a longer history of multimedia surround technologies, and argues that its contribution to that history is first, in its reflection of the underrecognized hybridity of surround sound’s past, and second, to think of surround sound as a space to physically move through.

MODEL OF OPTIMAL OF MANUFACTURING AND DELIVERING OF FINAL PRODUCT TO CONSUMERS TAKING INTO ACCOUNT COSTFOR MARKETING

The newtrendsoftheoryandpracticeoflogistics’ developmentarebasedonlogisticaloperatorsandmanagersofeach links of supply chainsaspirations to earn the maximal profit from integral paradigm of logistics application based on more close interaction between logistic and marketing strategies of firms or companies. At present, it is very actual the development and analysis of optimization models which are accounting simultaneously influence of marketing activity of companies and the logistics conception. In the article, on the basis of classical model of multi-nomenclature products optimal planning by an enterprise side by side the optimal planning of finished product transportation to consumers the economic-mathematical model has been developed and analyzed taking into account the marketing activity of enterprise. It is supposed that demand for finished products is a some increasing function of advertising costs. The concrete form of such dependence may be found in result of corresponding market’s analyses for previous period. In more simple case it may be the linear dependence. It is supposed also that expected demand without cost for advertising is known in result of market analyses. This optimization model allows us to findouttheoptimal joint production and transportationplansandoptimal advertising costs maximizing the total profit of enterprise. The experimental calculations show that interaction of marketing and logistics conceptions allows not only to increase the effectiveness of supply chain functioning as a whole but its every link, as well. The approach proposed may be applied for investigation of more general optimization models takingintoaccount the marketdemand fluctuation over the given planning horizon. The results obtained in the article show that above optimization model of integrated supply chain and its possible generalizations has thedefined perspective of further development in the framework of integral paradigm of logistics.Keywords: supply chain, optimization of the production and transportation plans, demand, marketing activity.

A Simple View on the Interval and Fuzzy Portfolio Selection Problems

In this paper, first we show that the variance used in the Markowitz’s mean-variance model for the portfolio selection with its numerous modifications often does not properly present the risk of portfolio. Therefore, we propose another treating of portfolio risk as the measure of possibility to earn unacceptable low profits of portfolio and a simple mathematical formalization of this measure. In a similar way, we treat the criterion of portfolio’s return maximization as the measure of possibility to get a maximal profit. As the result, we formulate the portfolio selection problem as a bicriteria optimization task. Then, we study the properties of the developed approach using critical examples of portfolios with interval and fuzzy valued returns. The α-cuts representation of fuzzy returns was used. To validate the proposed method, we compare the results we got using it with those obtained with the use of fuzzy versions of seven widely reputed methods for portfolio selection. As in our approach we deal with the bicriteria task, the three most popular methods for local criteria aggregation are compared using the known example of fuzzy portfolio consist of five assets. It is shown that the results we got using our approach to the interval and fuzzy portfolio selection reflect better the essence of this task than those obtained by widely reputed traditional methods for portfolio selection in the fuzzy setting.

Evolutionary Analysis for Residential Consumer Participating in Demand Response Considering Irrational Behavior

Demand response (DR) has been recognized as a powerful tool to relieve energy imbalance in the smart grid. Most previous works have ignored the irrational behavior of energy consumers in DR project implementation. Accordingly, in this paper, we focus on solving two questions during the execution of DR. Firstly, considering the bounded rationality of residential users, a population dynamic model is proposed to describe the decision behavior on whether to participate in the DR project, and then the evolutionary process of consumers participating in DR is analyzed. Secondly, for the DR participants, they have to compete dispatching amounts for maximal profit in a day-ahead bidding market, hence, a non-cooperative game model is proposed to describe the competition behavior, and the uniqueness of the Nash equilibrium is analyzed with mathematical proof. Then, the distributed algorithm is designed to search the evolutionary result and the Nash equilibrium. Finally, a case study is performed to show the effectiveness of the formulated models.

Is Factor Investing Sustainable after Price Impact Costs? The Capacity of Factor Investing in Korea

This study investigates whether the profitability of various factor investments is sustainable after costs due to price impact, and estimates the capacity of strategies in the Korean stock market. With various initial amounts invested as of the end of December 2000, we analyze after-cost-returns on factor investing during the period from January 2000 to December 2017, and estimate the break-even fund size and maximal profit fund size. To this end, whenever rebalancing factor-investment portfolios based on trading rules, the number of shares of stocks to be bought and sold is computed and the price impact costs of the transactions are taken into account. This procedure computes the implicit cost of trading of factor investing to produce after-cost-returns for various initial amount invested. While the momentum and value factors perform well before price impact costs, the profitability factor performs better after price impact costs. More specifically, the break-even fund size is estimated to be 1.4 trillion Korean won (KRW), and the maximal profit generating fund size is estimated to be 750 billion KRW which could attain a monthly net profit of 1.9 billion KRW over the sample period.

The Optimal Energy Dispatch of Cogeneration Systems in a Liberty Market

This paper proposes a novel approach toward solving the optimal energy dispatch of cogeneration systems under a liberty market in consideration of power transfer, cost of exhausted carbon, and the operation condition restrictions required to attain maximal profit. This paper investigates the cogeneration systems of industrial users and collects fuel consumption data and data concerning the steam output of boilers. On the basis of the relation between the fuel enthalpy and steam output, the Least Squares Support Vector Machine (LSSVM) is used to derive boiler and turbine Input/Output (I/O) operation models to provide fuel cost functions. The CO2 emission of pollutants generated by various types of units is also calculated. The objective function is formulated as a maximal profit model that includes profit from steam sold, profit from electricity sold, fuel costs, costs of exhausting carbon, wheeling costs, and water costs. By considering Time-of-Use (TOU) and carbon trading prices, the profits of a cogeneration system in different scenarios are evaluated. By integrating the Ant Colony Optimization (ACO) and Genetic Algorithm (GA), an Enhanced ACO (EACO) is proposed to come up with the most efficient model. The EACO uses a crossover and mutation mechanism to alleviate the local optimal solution problem, and to seek a system that offers an overall global solution using competition and selection procedures. Results show that these mechanisms provide a good direction for the energy trading operations of a cogeneration system. This approach also provides a better guide for operation dispatch to use in determining the benefits accounting for both cost and the environment in a liberty market.

Load Aggregator-Based Integrated Demand Response for Residential Smart Energy Hubs

In order to attract more flexible resource to take part in integrated demand response (IDR), this can be realized by introducing load aggregator-based framework. In this paper, based on residential smart energy hubs (S.E. Hubs), a two-level IDR framework is proposed, in which S.E. Hub operators play the role of load aggregators. The framework includes day-ahead bidding and real-time scheduling. In day-ahead bidding, S.E. Hub operators have to compete dispatching amount for maximal profit; hence, noncooperative game approach is formulated to describe the competition behavior among operators. In real-time scheduling, the dispatching model is formulated to minimize the error between real-time scheduling amount and bidding amount. Moreover, in order to reduce the influence of IDR on residential users, 4 categories of users’ flexible loads are modeled according to load consumption characteristic, and then these models are considered as the constraints in real-time scheduling. A case study is designed to validate the effectiveness of the proposed two-level IDR framework. And simulation results confirm that smart grid, S.E. Hub operators, and residential users can benefit simultaneously.

Auctions with Limited Commitment

We study the role of limited commitment in a standard auction environment. In each period, the seller can commit to an auction with a reserve price but not to future reserve prices. We characterize the set of equilibrium profits attainable for the seller as the period length vanishes. An immediate sale by efficient auction is optimal when there are at least three buyers. For many natural distributions two buyers is enough. Otherwise, we give conditions under which the maximal profit is attained through continuously declining reserve prices. (JEL D44, D82)