Pair trading based on quantile forecasting of smooth transition GARCH models

Pair trading is a statistical arbitrage strategy used on similar assets with dissimilar valuations. We utilize smooth transition heteroskedastic models with a second-order logistic function to generate trading entry and exit signals and suggest two pair trading strategies: the first uses the upper and lower threshold values in the proposed model as trading entry and exit signals, while the second strategy instead takes one-step-ahead quantile forecasts obtained from the same model. We employ Bayesian Markov chain Monte Carlo sampling methods for updating the estimates and quantile forecasts. As an illustration, we conduct a simulation study and empirical analysis of the daily stock returns of 36 stocks from U.S. stock markets. We use the minimum square distance method to select ten stock pairs, choose additional five pairs consisting of two companies in the same industrial sector, and then finally consider pair trading profits for two out-of-sample periods in 2014 within a six-month time frame as well as for the entire year. The proposed strategies yield average annualized returns of at least 35.5% without a transaction cost and at least 18.4% with a transaction cost.     

Non-linear,hybrid exchange rate modeling and trading profitability in the foreign exchange market

A neuro-fuzzy decision-making technology is designed and implemented to obtain the optimal daily currency trading rule. It is found that a non-linear, artificial neural network exchange rate microstructure (hybrid) model combined with a fuzzy logic controller generates a set of trading strategies that earn a higher rate of return compared to the simple buy-and-hold strategy. After accounting for realistic transaction costs, the gains from utilizing a dynamic, neuro-fuzzy model are still present.     

Housing appreciation, mortgage interest rates, and homeowner mobility

This paper presents a model of the optimal timing of tradeup, which considers consumption and investment motives of homeownership. Households determine the optimal timing of trading up so as to maximize their intertemporal utility of both housing and nonhousing consumption. First we consider current homeowners, who already own a house and expect that they trade up to a more valuable house at some point in the future. Housing appreciation tends to induce an earlier optimal timing of trading up. Moreover, housing appreciation makes current homeowners better off in terms of welfare. However, current homeowners suffer from a rise in mortgage interest rates. Second, we consider first-time home buyers, who have decided to buy a house and expect to trade up to a more valuable house in the future. Their initial housing consumption is determined by an initial downpayment constraint. In this case, the effect of housing appreciation on the optimal timing of trading up is ambiguous and, unlike current homeowners, first-time home buyers suffer from housing appreciation. Moreover, as current homeowners, first-time home buyers suffer from a rise in mortgage interest rates. Most of the theoretical analytic results are ambiguous. Accordingly, we perform numerical simulations based on the theoretical model in order to determine the most likely comparative effects for a stylized set of parameters.As is apparent, the model captures the recent observations on homewner mobility and suggests that macroeconomic variables such as housing appreciation and mortgage interest rates effect the optimal timing of trading up and homeowner's welfare. Nevertheless, the model in this paper has several shortcomings, which should be the subject of future research. First, transaction costs are ignored. If transaction costs are incorporated, the lock-in effect from a rise in mortgage interest rates is well explained. However, the general analysis above is not altered in any essential way. Second, multiple moves are not considered in this model. Therefore, we concentrate on the timing of one tradeup as opposed to the timing and frequency of trading up. In a different vein, it would be interesting to test empirically the importance of the effects of macroeconomic variables on trading up by using microdata.     

Transaction Costs in the Trading System of Cashew Nuts in the North of Benin: A Field Study

Cashew nut trading is an activity with growing economic importance in the north of Benin. Among the cost categories supported by the trading actors are transaction costs to which rare empirical studies have been devoted. Therefore, based on the theoretical concept this article empirically analyzes the importance of the transaction costs generated by cashew nut trading in the north of Benin. The empirical data were collected in two villages. Using a paired‐sample T test this study shows that the transaction costs are relatively important, but are not the major cost category. The average “production cost” is higher than the average transaction cost incurred by the trading actors. Although the transaction costs are on average lower than the other costs category, they are viewed by most actors (82 percent) as a serious constraint in the trading system due to moral hazard problems arising from the existence of these costs. By analyzing the specific factors that influence the magnitude of the transaction costs borne by the actors, the article shows that some socio‐cultural and environmental characteristics of the actors are determinant of the level of transaction costs incurred.     

Causes of cross-autocorrelation in security returns: Transaction costs versus information quality

We examine empirically the role of transaction costs and information quality as causes of cross-autocorrelations in security returns. Nonsynchronous trading influences are addressed by forming weekly returns based on averages of closing inside bid and ask quotations for NMS securities. Stock return volatility scaled by the bid-ask spread is employed as a proxy for transaction costs and trading volume is used as a measure of information quality. We find evidence that both transaction costs and information quality may contribute to cross-autocorrelations, but that information quality dominates transaction costs in explaining cross-autocorrelations after controlling for autocorrelation influences.     

Model Selection for Monetary Policy Analysis: How Important is Empirical Validity?*

We investigate the economic significance of trading off empirical validity of models against other desirable model properties. Our investigation is based on three alternative econometric systems of the supply side, in a model that can be used to discuss optimal monetary policy in Norway. Our results caution against compromising empirical validity when selecting a model for policy analysis. We also find large costs from basing policies on the robust model, or on a suite of models, even when it contains the valid model. This confirms an important role for econometric modelling and evaluation in model choice for policy analysis.     

The international business cycle and gold-price fluctuations

Drawing on recent empirical research, we study whether the international business cycle, as measured in terms of the output gaps of the G7 countries, has out-of-sample predictive power for gold-price fluctuations. To this end, we use a real-time forecasting approach that accounts for model uncertainty and model instability. We find some evidence that the international business cycle has predictive power for gold-price fluctuations. After accounting for transaction costs, a simple trading rule that builds on real-time out-of-sample forecasts does not lead to a superior performance relative to a buy-and-hold strategy. We also suggest a behavioral-finance approach to study the quality of out-of-sample forecasts from the perspective of forecasters with potentially asymmetric loss functions.     

S&P Global Sector survivals: Momentum effects in sector indices underlying iShares

This study investigates survival of the momentum effects in S&P Global 1200 Sector index returns which are underlying indices for iShares, by employing a methodology which allows analyzing the momentum effect without being dependant on zero-investment portfolios. We design a trading strategy based on momentum survival time for 10 S&P Global 1200 Sectors and show that for most of the sectors, long, short and long/short momentum strategies are profitable at the realistic level of transaction costs, generating substantially higher Sharpe ratios than buy and hold sector index strategy.     

Mobility and optimal tenure choice

In this paper, we offer a dynamic model of the optimal tenure behavior of an individual who faces the possibility of moving multiple times during his lifetime. We also investigate the lifetime effects of such factors as income tax, property tax, transaction costs, and mortgage rates on the household’s tenure choice. The agents in the model utilize a genetic algorithm, a probabilistic search approach, to determine their optimal lifetime tenure choice path. The agents are forward looking in that they anticipate such possible events as changes in jobs, marital status, household size, or dissatisfaction with current residence. Our results suggest several housing policy implications and explain some of the empirical findings in the literature.     

装备采办效益优化研究:一个交易费用理论视角

交易费用理论指出,交易成本是制度的运行成本,其大小取决于交易形式与其制度的匹配程度,两者越匹配则其交易成本越小。从交易费用理论入手,通过分析装备采办成本的构成及决定因素,指出装备采办效益优化的关键在于选择和建立合理的制度以尽可能地降低采办的交易成本,即制度因素是我国装备采办低效的症结。在此思路下,探究了我国装备采办制度的不合理之处,并提出相应的政策建议。     

Mortgage Valuation with Optimal Intertemporal Refinancing Strategies

This article extends previous work on mortgage valuation in two ways. First, I identify the prepayment boundary by solving for the borrower's optimal prepayment strategy over the expected tenure in the house. Previous work has treated the prepayment decision as a one-time decision, not as an element of a multiperiod strategy. Second, the model incorporates borrower heterogeneity in terms of expected tenure in the house. The results show that the optimal refinancing strategy differs significantly from a sequence of one-time decisions. A borrower following the optimal strategy is less aggressive in refinancing and pays more interest and less transaction costs than does a borrower following a myopic strategy. Estimated mortgage values are higher and interest rate sensitivity is lower when compared to values calculated using the traditional approach.     

The Foreign Exchange Exposure Management Practices of Finnish Industrial Firms

This study employs questionnaire survey and financial accounting data to extend earlier empirical work on the foreign exchange (FX) exposure management practices of Finnish industrial firms. The paper concentrates on: (i) the form that FX corporate hedging policy takes; (ii) the control of FX procedures and trading; and, (iii) our respondents' perceptions about their ability to predict FX rate changes for hedging decisions. Our results indicate that the extent to which firms hedge FX exposure depends on the type of exposure and the form that FX hedging policy takes. Also, a significant number of the firms pursue FX hedging strategies on the expectation of attaining trading profits and this strategy appears to be accommodated within their FX policies. This feature is not explicitly demonstrated in previous studies. Finnish firms hedge a much higher proportion of both transaction and translation exposures compared to economic exposure. We partly attribute this emphasis to the requirements of the Finnish Accounting Act, which came into effect in 1993. The organisational, historical and financial settings of the firms also have significant impacts on exposure management practices. The overall implication of those results is that firms respond to changes in the financial, economic and regulatory environments in which they operate.     

存在交易成本的权证避险策略实证研究

权证发行人在存在交易成本时对冲风险,若按照B—S理论进行动态连续避险操作,将造成巨大的交易成本,致使B-S动态连续避险不可行。因此存在交易成本时,对避险的操作都采用间断性避险。本文在统一均值方差框架下,系统全面的比较了存在交易成本的五种避险策略。在比例交易成本情形下,Whalley—Wilmott避险策略优于其他所有策略,当避险误差的标准差相同时该策略的交易成本最小;其次分别是delta固定避险带避险策略,基于标的资产价格变化的避险策略,Leland避险模型和间断的B—S避险策略。随着波动率σ上升,无风险利率γ下降,基于变动的避险策略相对于基于时间的策略优势更大。     

粤港物流成本优化决策分析——广东港资企业物流成本优化研究

广东是我国重要的制造业基地和对外开放的南大门，其物流业的发展对中国其他地区起着极大的带动和示范作用。因此．研究粤港物流成本的优化控制对促进粤港两地的经济发展和我国的对外贸易有着深远的意义。本文先对粤港物流运输成本和仓储成本进行了深入分析，然后构建了粤港物流成本优化控制的非线性规划模型，最后以实证研究方法对粤港物流成本控制进行了优化规划，并得出了优化规划的一些基本结论。     

Transaction costs and a redundant security: divergence of individual and social relevance

This paper shows that, in markets with transaction costs, even if a redundant security does not even save individual investors' total costs for their security trading, the prices of the other securities may well be different were it to not be available for trade, resulting in a different equilibrium consumption allocation. In this sense, a redundant security may give rise to the divergence of individual and social relevance in markets with transaction costs. We then show that this divergence may also be a robust phenomenon with respect to perturbations in utility functions, initial endowments, and transaction costs.     

Option pricing and replication with transaction costs and dividends

This paper derives optimal perfect hedging portfolios in the presence of transaction costs within the binomial model of stock returns, for a market maker that establishes bid and ask prices for American call options on stocks paying dividends prior to expiration. It is shown that, while the option holder's optimal exercise policy at the ex-dividend date varies according to the stock price, there are intervals of values for such a price where the optimal policy would depend on the holder's preferences. Nonetheless, the perfect hedging assumption still allows the derivation of optimal hedging portfolios for both long and short positions of a market maker on the option.     

Trading cost expectations: Evidence from S&P 500 index replacement stock announcements

This paper tests the effect on stock value of an expected change in future trading costs. The capitalized value of a reduction in trading costs is hypothesized to increase the stock value, a trading cost effect. Improved liquidity reduces trading costs. Inclusion as an S&P 500 Index replacement stock is an event hypothesized to increase liquidity. We use 114 observations between January 1, 1983 and October 12, 1989 of stocks added to the Index as replacements for stocks removed. The abnormal return of each stock is regressed against the ratio of the bidask spread to the price of the stock, the change in trading volume of the stock, and the open interest in the Index futures contracts at the close of the month prior to the replacement announcement. We find that the positive abnormal returns for replacement stocks are related to increased daily trading volume after inclusion in the Index. Further, the trading cost effect is proportional to percentage bid-ask spreads prior to inclusion. The trading cost effect increases as trading in derivatives of the Index increases. The volume and stock price changes after replacement are not transitory, indicating an improvement in liquidity. Three alternate hypotheses suggested in prior research to explain the abnormal returns for replacement stocks are tested. Testing each of the three models previously considered: price pressure, inelastic demand curves, and information, we find that none can be accepted with statistical confidence. The abnormal returns of Index replacement stocks are consistent with rational pricing of an anticipated reduction in future transaction costs. This anticipated reduction is capitalized in the value of the stock at the time of the replacement announcement. These results are consistent with a trading cost effect.     

Supply chain decisions and coordination in the presence of an imperfect spot market

This study considers a supply chain consisting of a commodity supplier and a final product manufacturer with uncertain demand. In addition to purchasing from the supplier through a forward contract, the manufacturer can adjust their inventory by trading the commodity in an online spot market after observing the actual demand. However, the spot market is imperfect in that transactions cannot be certainly realized and come with additional transaction costs. Furthermore, the spot price is volatile such that overly relying on the spot market is unwise. To investigate how the spot market affects the decisions and coordination in a supply chain, we develop a game-theoretical model incorporating spot trading. We derive the optimal ordering decision in a centralized supply chain, as well as the supplier's and manufacturer's equilibrium pricing and ordering decisions in a decentralized supply chain. The impact of the imperfect spot market on the optimal decisions and profits is analyzed. This study also demonstrates how the supply chain can be coordinated in the presence of an imperfect spot market. Finally, a numerical analysis is performed to examine the analytical results. Our results indicate that the spot market can generally improve the performance of the centralized supply chain and benefit the manufacturer in the decentralized one. However, it can be detrimental to the supplier. The supply chain can be coordinated by a revenue-sharing contract, and both parties' profits can be improved. Our findings suggest that the manufacturer could take advantage of the spot market, and the supplier should attempt to integrate or coordinate the supply chain to share the benefits of spot trading.     

Optimal impulse control for cash management¶with quadratic holding-penalty costs

This paper studies optimal control for an infinite horizon cash management problem where the cash fund fluctuates as a Brownian motion. Holding-penalty costs are assumed to be a quadratic function of the cash level and there are fixed and proportional transaction costs. Using the “impulse technique”, we prove that optimal control exists and takes the form of a control band policy. Received: 4 January 2001 / Accepted: 5 June 2001     

Learning strategic cooperative behavior in industrial symbiosis: A game‐theoretic approach integrated with agent‐based simulation

This paper investigates the negotiation phase of industrial symbiosis relationships, where companies exchanging wastes for inputs need to develop strategies on how to share the additional costs to operate the industrial symbiosis business. The business behavior is approached as a “coopetition” problem where companies need to cooperate to reduce waste discharge costs and traditional input purchase costs and dive into competition to pay a minimum share of additional costs (i.e., waste treatment, waste transportation, and transaction costs) of operating industrial symbiosis. A noncooperative game‐theoretical model for sharing the additional costs is proposed that highlights the two strategies that companies can adopt aimed at sharing costs: a fair strategy and an opportunistic strategy. Then, an agent‐based model is used to simulate the game iterated over time and investigate how the players can adapt their strategies according to their past experience. Simulation results show that players learn that playing the fair strategy is beneficial in the long period, despite in the short period they can gain more benefit by playing the opportunistic strategy. Findings of the paper are critically important to reduce the business and managerial barriers against the formation of industrial symbiosis networks and to stimulate innovative thinking of company managers to foster the development of the circular economy. The paper proposes theoretical, managerial, and policy implications, which are discussed in detail in a comparative manner between linear and circular economy.