Efficiency of the Turkish Stock Exchange with respect to monetary variables: A cointegration analysis

In this study, we test the semistrong form of the efficient market hypothesis in Turkey by using the recently developed techniques in time series econometrics, namely unit roots and cointegration. The long run relationship between stock prices and inflation is investigated by assuming the possible existence of a proxy effect. Conclusions are made as to the efficiency of the Turkish Stock Exchange and its possible implications for investors. To our knowledge, this is among the pioneering studies conducted in an emerging market that uses an updated econometric methodology to allow for an analysis of long run steady state properties together with short run dynamics.     

Is the predictability of emerging and developed stock markets really exploitable?

A number of recent papers have analyzed the degree of predictability of stock markets. In this paper, we firstly study whether this predictability is really exploitable and secondly, if the economic significance of predictability is higher or lower in the emerging stock markets than in the developed ones. We use a variety of linear and nonlinear – Artificial Neural Networks – models and perform a computationally demanding forecasting experiment to assess the predictability of returns. Since we are interested in comparing the predictability in economic terms we also propose a modification in the nets’ loss function for market trading purposes. In addition, we consider both explicit and implicit trading costs for emerging and developed stock markets. Our conclusions suggest that, in contrast to some previous studies, if we consider total trading costs both the emerging as well as the developed stock returns are clearly nonpredictable. Finally, we find that Artificial Neural Networks do not provide superior performance than the linear models.     

On the optimal spacing of currency denominations

Existing theoretical evidence on optimal currency spacing is fragmentary and, to some extent, contradictory. This note brings together the pieces and tries to solve the puzzle. It shows that if the spacing of denominations is uniform, then the average number of notes and coins exchanged in a transaction can be minimized by spacing denominations apart by a factor of two, even when allowing for overpayment and the return of change.     

On the no-arbitrage condition in option implied trees

The aim of this paper is to discuss the no-arbitrage condition in option implied trees based on forward induction and to propose a no-arbitrage test that rules out the negative probabilities problem and hence enhances the pricing performance. The no-arbitrage condition takes into account two main features: the position of the node in the tree and the relation between the dividend yield and the risk-free rate. The proposed methodology is tested in and out of sample with Italian index options data and findings support a good pricing performance.     

On the impact of low-balling: Experimental results in asymmetric auctions

The paper reports on a series of asymmetric auction experiments with private-independent values and two buyers. Maskin and Riley (2000) showed, under some conditions, that if one buyer has a greater probability than the other of not being able to bid, first-price auctions could yield lower revenues to the seller than second-price auctions. The data rejected this prediction because of an important overbidding when subjects received low values in first-price auctions. In this asymmetric setting, the observed overbidding cannot be explained by the usual risk aversion hypothesis and the detection of a learning pattern indicates that subjects used more an adaptive behaviour than a static one. An ad hoc bidding strategy for the buyers who are the most likely to bid explains the observed low bids better than the risk neutral equilibrium strategy. Finally, as subjects appear to have bid in equilibrium as if there were two other competitors instead of only one, their bidding behaviour can be thought to have displayed an over anxiousness about winning. Received: January 1999/Final version June 2001     

ON THE ROBUSTNESS OF A GENERALIZED PREDICTIVE CONTROLLER

In this paper, we present a quantitative analysis of the robustness of a generalized predictive controller. The result of stability analysis shows that, under a specific bounded modelling error, the closed-loop system is BIBO stable in the presence of unmedelled dynamics.     

On the economics of GPRS networks with Wi-Fi integration

Wi-Fi provides an appealing opportunity for GSM/GPRS operators to enhance their data capability. By integrating both networks, operators are able to provide 3G-like services. However, both networks have different data rates and capacity, which makes economics of the network integration and pricing of services a challenging issue. In this paper we introduce a novel pricing model for GPRS networks integrated with Wi-Fi networks. The model identifies how the integration can play a significant role in increasing operators’ overall revenue and potentially improve the performance of GPRS networks. We identify the optimal GPRS charging rate and Wi-Fi connection fee that yields maximum network revenue. In addition, we conduct a case study of a wireless operator that considers network integration, adopting our pricing model. The investment analysis provides the insightful information for profitable business cases of GPRS networks with Wi-Fi integration.     

On the impact of infrequent trading on the APT systematic risk components — Evidence from a thin security market

The purpose of this note is to analyze the effects of infrequent trading on the APT systematic risk components using Finnish data. Infrequent trading is reported to influence especially the first systematic risk component produced by factor analysis on stock returns.     

On a simple strategy weakly forcing the strong law of large numbers in the bounded forecasting game

In the framework of the game-theoretic probability of Shafer and Vovk it is of basic importance to construct an explicit strategy weakly forcing the strong law of large numbers in the bounded forecasting game. We present a simple finite-memory strategy based on the past average of Reality’s moves, which weakly forces the strong law of large numbers with the convergence rate of ${O(\sqrt{\log n/n})}In the framework of the game-theoretic probability of Shafer and Vovk it is of basic importance to construct an explicit strategy weakly forcing the strong law of large numbers in the bounded forecasting game. We present a simple finite-memory strategy based on the past average of Reality’s moves, which weakly forces the strong law of large numbers with the convergence rate of . Our proof is very simple compared to a corresponding measure-theoretic result of Azuma (T?hoku Mathematical Journal, 19, 357–367, 1967) on bounded martingale differences and this illustrates effectiveness of game-theoretic approach. We also discuss one-sided protocols and extension of results to linear protocols in general dimension.     

On the controversy over tailweight of distributions

Although understanding tail behavior of distributions is important in many areas, such as telecommunications network analysis and finance, there is considerable controversy about distinctions between exponential-type and power-type tails. This paper explains why the distinctions are surprisingly difficult for popular methods in the literature, and why particularly large samples are needed for clear discrimination.     

On the stability of Invariant Capital Stock in a two-dimensional planning model

In this paper, we study the stability of two types of Invariant Capital Stocks which are shown to exist in a two-dimensional planning model. It is shown that, for each type of Invariant Capital Stock, there is a critical discount factor such that when the discount factor falls below it, the corresponding Invariant Capital Stock will become unstable.     

On the negative value of information in informationally inefficient markets: Calculations for large number of traders

In informationally inefficient markets, classical decision theory assumes the value of information to be positive. Recent developments, however, contradict this paradigm. Schredelseker [Schredelseker, K., 2001. Is the usefulness approach useful? Some reflections on the utility of public information. In: McLeay, S., Riccaboni, A. (Eds.), Contemporary Issues in Accounting Regulation, Kluwer Academic Publishers, Boston, pp. 135–153] proposed a simulation model wherein a single security is traded among non-cooperating and asymetrically informed traders. One of the main results was the fact that badly informed traders could expect higher returns than traders with more information. But Schredelseker was able to give exact results for a small number of traders only. The aim of this paper is to give reliable results for a sufficiently large number of traders for both the expected gain and the probability of gain larger than zero. We are using combinatorial methods in order to get exact results for badly informed traders and simulation techniques for results of traders with higher level of information. The exact results are used (error between exact results and simulation results for the first traders) to determine the number of samples which have to be drawn with the simulation algorithm.     

On the existence of solutions to the quadratic mixed-integer mean–variance portfolio selection problem

In the standard mean–variance portfolio selection approach, several operative features are not taken into account. Among these neglected aspects, one of particular interest is the finite divisibility of the (stock) assets, i.e. the obligation to buy/sell only integer quantities of asset lots whose number is pre-established. In order to consider such a feature, we deal with a suitably defined quadratic mixed-integer programming problem. In particular, we formulate this problem in terms of quantities of asset lots (instead of, as usual, in terms of capital per cent quotas). Secondly, we provide necessary and sufficient conditions for the existence of a non-empty mixed-integer feasible set of the considered programming problem. Thirdly, we present some rounding procedures for finding, in a finite number of steps, a feasible mixed-integer solution which is better than the one detected by the necessary and sufficient conditions in terms of the value assumed by the portfolio variance. Finally, we perform an extensive computational experiment by means of which we verify the goodness of our approach.     

On the asymptotic behavior of odd operators

We give quantitative versions of strong convergence results due to Baillon, Bruck and Reich for iterations of nonexpansive odd (and more general) operators in uniformly convex Banach spaces.     

概率准则在投资模型中的应用研究

本文在Black-Scholes金融市场设置下,基于概率准则,研究连续时间金融市场最优动态资产组合的选择问题,导出了最优解的显式表达式,对结论给出了金融学解释,所得结果可以方便地应用于投资决策与管理实践中。     

On the parallel complexity of hierarchical clustering and CC‐complete problems

Complex data sets are often unmanageable unless they can be subdivided and simplified in an intelligent manner. Clustering is a technique that is used in data mining and scientific analysis for partitioning a data set into groups of similar or nearby items. Hierarchical clustering is an important and well‐studied clustering method involving both top‐down and bottom‐up subdivisions of data. In this article we address the parallel complexity of hierarchical clustering. We describe known sequential algorithms for top‐down and bottom‐up hierarchical clustering. The top‐down algorithm can be parallelized, and when there are n points to be clustered, we provide an O(log n)‐time, n²‐processor Crew Pram algorithm that computes the same output as its corresponding sequential algorithm. We define a natural decision problem based on bottom‐up hierarchical clustering, and add this HIERARCHICAL CLUSTERING PROBLEM (HCP) to the slowly growing list of CC‐complete problems, thereby showing that HCP is one of the computationally most difficult problems in the COMPARATOR CIRCUIT VALUE PROBLEM class. This class contains a variety of interesting problems, and now for the first time a problem from data mining as well. By proving that HCP is CC‐complete, we have demonstrated that HCP is very unlikely to have an NC algorithm. This result is in sharp contrast to the NC algorithm which we give for the top‐down sequential approach, and the result surprisingly shows that the parallel complexities of the top‐down and bottom‐up approaches are different, unless CC equals NC. In addition, we provide a compendium of all known CC‐complete problems. © 2008 Wiley Periodicals, Inc. Complexity, 2008     

Calibration of the SABR Model in Illiquid Markets

Recently the SABR model has been developed to manage the option smile which is observed in derivatives markets. Typically, calibration of such models is straightforward as there is adequate data available for robust extraction of the parameters required asinputs to the model. The paper considers calibration of the model in situations where input data is very sparse. Although this will require some creative decision making, the algorithms developed here are remarkably robust and can be used confidently for mark to market and hedging of option portfolios.     

Optimization of component reliability in the design phase of capital goods

We introduce a quantitative model to support the decision on the reliability level of a critical component during its design. We consider an OEM who is responsible for the availability of its systems in the field through service contracts. Upon a failure of a critical part in a system during the exploitation phase, the failed part is replaced by a ready-for-use part from a spare parts inventory. In an out-of-stock situation, a costly emergency procedure is applied. The reliability levels and spare parts inventory levels of the critical components are the two main factors that determine the downtime and corresponding costs of the systems. These two levels are decision variables in our model. We formulate the portions of Life Cycle Costs (LCC) which are affected by a component’s reliability and its spare parts inventory level. These costs consist of design costs, production costs, and maintenance and downtime costs in the exploitation phase. We conduct exact analysis and provide an efficient optimization algorithm. We provide managerial insights through a numerical experiment which is based on real-life data.     

Risk measurement in the presence of background risk

A distortion-type risk measure is constructed, which evaluates the risk of any uncertain position in the context of a portfolio that contains that position and a fixed background risk. The risk measure can also be used to assess the performance of individual risks within a portfolio, allowing for the portfolio’s re-balancing, an area where standard capital allocation methods fail. It is shown that the properties of the risk measure depart from those of coherent distortion measures. In particular, it is shown that the presence of background risk makes risk measurement sensitive to the scale and aggregation of risk. The case of risks following elliptical distributions is examined in more detail and precise characterisations of the risk measure’s aggregation properties are obtained.     

考虑海外代购的品牌商定价模型研究

随着海外代购体量的日趋增大,代购带来的低价威胁对于在不同国家不同市场销售产品的公司来说已经成为一个日益严重的问题。同时,代购渠道中假货的问题也愈发严重。因此,在海外代购背景下探究产品定价模型具有必要性。以往研究普遍认为这种未经授权的销售会削减品牌方的利润,但实则不然。基于这一发现,本研究为在两个不同市场销售相同产品但面临代购低价威胁的公司制定考虑代购的市场定价模型。由公司制定两个市场的价格,消费者选择是否从包括代购在内的三个渠道购买产品。推出两个授权市场的最优价格,分析各参数变化对最优价格的影响,并校验最优价格对消费者需求和总利润的影响。模型分析表明,高价市场中有部分消费者需求转向海外代购,同时低价市场的消费者需求也受到了影响,且在一定条件下,提高高价市场的产品定价能够扩大低价市场的需求,从代购的角度解释了现实中需求曲线向上倾斜的现象。此外,两个独立市场之间的价格差距对代购市场的销售也产生了积极影响,并且在某些条件下,增大价格差距可以提高公司的收益水平。随后讨论了一种极端模型和三种扩展模型,通过模型分析表示,扩展后的定价模型也显示出与基础市场模型相似的灵敏度分析结果,同样得到两个市场的价差扩大会导致代购市场的销售额增加的结论,并且在一定条件下,公司的利润更高,增加了结论的可信度。