Portfolio Trading Research Articles

Novel Automatic Food Trading System Using Consortium Blockchain

Conventional food trading platforms face several issues, such as quickly to find trading objects and protect the reliability of transaction information. With e-commerce developing rapidly, food trading has also recently shifted to the online domain. Blockchain has changed many industries owing to its robustness, decentralization and end-to-end credibility. This paper proposes a novel Food Trading System with COnsortium blockchaiN (FTSCON) to improve trust and security issues in transactions. It uses consortium blockchain technology to set permission and authentication for different roles in food transaction, which meet the challenge of the privacy protection of multi-stakeholders. The algorithm of optimized transaction combination is designed for the purpose of helping users find suitable transaction objects. It can choose the optimized trading portfolio for buyers. The online double auction mechanism is used to eliminate competition. And the improved PBFT (iPBFT) is used to enhance efficiency of system. Moreover, a smart-contract life- cycle management method is introduced, and security analysis shows that FTSCON improves transaction security and privacy protection. Experiment results based on a series of data indicate that the proposed algorithm can achieve profit improvement of merchants.

Assessing Market Efficiency And Volatility Of Exchange Rates in South Africa and United Kingdom: Analysis Using Hurst Exponent

The possibility of random walk movements in the log-returns of exchange rate series as well as the characterization of returns by periods of tranquility and volatility is of interest in financial time series modelling. These features make the analysis of exchange rates to be important in the design of policy, portfolio and risk management whenever international trade and finance is discussed. This paper investigated the level of exchange rates market efficiency and volatility at three market phases of US Dollar-South African Rands and US Dollars-British Pounds exchange rates for the daily periods from 2 January 1995 to 8 June 2016. This paper applied the modified Hurst exponent' and volatility modelling techniques on the series log-returns, absolute and squared log-returns used as proxies to volatility. The results of the modified Hurst exponent techniques on the log-returns and squared log-returns show that the future path of the exchange rates returns in these markets are not governed by their immediate past in the second and third identified phases. Thus, the two markets have been in the state of weak form of efficiency since 2001 to the current transition, with UK exchange rate market more efficient than South African exchange rate market. Using the efficiency and volatility indices to classify the two exchange rate markets as well as the market phases, we observe similar transition in the level of market efficiency in these markets, this which is as a result of trade partnership between the two countries. In terms of market volatility, we cannot make a clearer judgement between the two economies. This paper has repositioned the stability foreign exchange rates of South Africa, a member of Group of 20 (G20) countries, with that of a member of the G7 countries, that is, the UK. To the government, risk and portfolio managers, the findings emanating from this paper indicated that the South Africa's Rand is also stable like the British Pound, and thus, can be traded on the international currency market without fear of excessive loss/gain.

Dynamic Portfolio Allocation in Goals-Based Wealth Management

Given any set of exogenously provided efficient portfolios, we develop a dynamic programming algorithm that constructs an optimal portfolio trading strategy to maximize the probability of attaining an investor’s specified goal wealth at the end of a designated timeframe. Our algorithm can also accommodate periodic infusions or withdrawals of any size with no degradation in runtime performance. We explore how the terminal wealth distribution is sensitive to restrictions on the segment of the portfolio’s efficient frontier made available to the investor. Because our algorithm’s optimal strategy is on the efficient frontier, allowed to depend on the investor’s wealth, and allowed to depend on the investor’s individual goals and specifications, we show that it soundly beats the performance of target date funds for attaining investors’ goals. These optimal goals-based wealth management strategies are useful for modern day FinTech offerings, both advisor-driven or robo-driven.

THE YIELD OF THE CARRY TRADE STRATEGY

The article analyzes the carry trade strategy in which, according to common definition, traders borrow a currency that has a low-interest rate and use the funds to buy a different currency that is paying a higher interest rate. The aim of this work is to form the optimal strategies and carry trade portfolio. The task of our study was to study the interdependence between the yield of the carry trade strategy and the USA stock market on the basis of a mathematical approach and offer a portfolio of currencies with the highest historical yield over the past five years. The author used the model of relative risk aversion. We analyzed data on exchange rates, forward premium and real exchange rates for the Eurozone, as well as for countries of the Organization for Economic Cooperation and Development (OECD) such as Australia, Brazil, China, Japan, New Zealand, Russia, Switzerland, the United Kingdom and the United States of America. Carry trade’s yield is not tied to standard risk factors. Popular funding currency — the yen has experienced a strong jump of volatility as a result of the 2008–2009 crisis. A possible explanation for this reversal is investors’ appetite for risk. The author concluded that the most common carry trade strategies in the period from 2009 to 2014 were formed on the basis of two financing currencies (Japanese yen and the US dollar) and three investment currencies (Australian dollar, New Zealand dollar and Chinese yuan). After 2014, the US dollar ceases to be the funding currency, giving way to the Euro. The optimal carry trade strategy is borrowing in the currencies of developed countries (EUR, JPY) and investing in the currencies of energy producing countries (RUB, BRL). There is a negative relationship between the volume of transactions based on the carry trade strategy and the yield of shares in the financing country. There is also a significant link between the yield of the carry trade strategy and the profitability of the USA stock market.

Structured Factor Model and Its Applications on Market Risk Management

The aims of this paper are twofold. First, we develop a new algorithm to fit a structured factor model for high-dimensional data analysis. The algorithm fits to the covariances of observable variables and has several advantages: it overcomes the curse of dimensionality that arises usually in analyzing high-dimensional data and converges effectively; it produces a unique solution of factor loadings that preserve the layer structure of observable variables; it properly captures the idiosyncratic components of the structured factor model and thus become particular useful for the applications in the risk management where idiosyncratic component represent a part of the specific risk and might be too significant to be treated as an estimation errors. Secondly, as an application, we provide a model to decompose market risk and simulate the shocks of the market variables relevant to the trading portfolio as part of a large bank's VaR based risk measure framework. The model is capable of capturing not only the covariances and the marginal volatilities of the market variables, but also can be enhanced to include some desired features about the target loss distributions. The model is scalable so that it works effectively with virtually no limit to the size of the portfolio. We also discuss how the model can be used to simulate shocks of illiquid market variables. The case study on SP500 suggests that the model is capable of providing a satisfactory performance with a simple and transparent setting.

Spectral Backtests of Forecast Distributions with Application to Risk Management

We study a class of backtests for forecast distributions in which the test statistic is a spectral transformation that weights exceedance events by a function of the modeled probability level. The choice of the kernel function makes explicit the user's priorities for model performance. The class of spectral backtests includes tests of unconditional coverage and tests of conditional coverage. We show how the class embeds a wide variety of backtests in the existing literature, and propose novel variants as well. In an empirical application, we backtest forecast distributions for the overnight P&L of ten bank trading portfolios. For some portfolios, test results depend materially on the choice of kernel.

Dispersion in macroeconomic volatility between the core and periphery of the international trade network

At the country level, macroeconomic volatility tends to correlate with trade openness although the direction of correlation is not stable across samples. Higher openness allows for greater diversification opportunities, but provides lesser immunity from outside shocks. Here I consider trade network as a composite of all pairwise trade linkages to emphasize that different linkages contribute differently to the transmission or mitigation of shocks, and show that volatility is inversely related to centrality, a summary measure of strength of the linkages specific to a country. I study a dynamic multi-country, multi-sector model subject to idiosyncratic liquidity shocks, and characterize volatility as an explicit function of centrality, diversification and the Herfindahl of the trade network in equilibrium. With sufficient skewness in the trade linkages across countries, similar shocks generate substantially different levels of repercussions across the network. The conventional effect of diversification holds true that countries with better diversified trade portfolio fluctuate less. Centrality directly contributes to higher resilience to exogenous shocks, thus reducing volatility. Combined effect of these two mechanisms dominates the opposite effect that a more central country is also more exposed to shocks, which increases volatility. The model calibrated to the EU generates and closely replicates the negative relationship between centrality and volatility. The theoretical model is then extended to capture preference shocks and sparseness of the trade networks.

Does the Assumption on Innovation Process Play an Important Role for Filtered Historical Simulation Model?

Most of the financial institutions compute the Value-at-Risk (VaR) of their trading portfolios using historical simulation-based methods. In this paper, we examine the Filtered Historical Simulation (FHS) model introduced by Barone-Adesi et al. (1999) theoretically and empirically. The main goal of this study is to find an answer for the following question: “Does the assumption on innovation process play an important role for the Filtered Historical Simulation model?”. For this goal, we investigate the performance of FHS model with skewed and fat-tailed innovations distributions such as normal, skew normal, Student’s-t, skew-T, generalized error, and skewed generalized error distributions. The performances of FHS models are evaluated by means of unconditional and conditional likelihood ratio tests and loss functions. Based on the empirical results, we conclude that the FHS models with generalized error and skew-T distributions produce more accurate VaR forecasts.

Cross-Sectional Variation of Intraday Liquidity, Cross-Impact, and Their Effect on Portfolio Execution

The composition of natural liquidity has been changing over time. An analysis of intraday volumes for the SP and, to the increased trading intensity of such strategies towards the end of the trading session, e.g., due to execution of mutual fund inflows/outflows that are benchmarked to the closing price on each day. In this paper, we investigate the consequences of such portfolio liquidity on price impact and portfolio execution. We derive a linear cross-asset market impact from a stylized model that explicitly captures the fact that a certain fraction of natural liquidity providers only trade portfolios of stocks whenever they choose to execute. We find that due to cross-impact and its intraday variation, it is optimal for a risk-neutral, cost minimizing liquidator to execute a portfolio of orders in a coupled manner, as opposed to a separable VWAP-like execution that is often assumed. The optimal schedule couples the execution of the various orders so as to be able to take advantage of increased portfolio liquidity towards the end of the day. A worst case analysis shows that the potential cost reduction from this optimized execution schedule over the separable approach can be as high as 6% for plausible model parameters. Finally, we discuss how to estimate cross-sectional price impact if one had a dataset of realized portfolio transaction records that exploits the low-rank structure of its coefficient matrix suggested by our analysis.

Regressed Profits on Total Trades, Winners, Size, and Intraday Drawdown of Commodities, Equities, Fixed Income, and Trade Duration Exit Days

This paper describes Business Intelligence Systems and Engineering of Profits from trading. This paper discusses a system (The System) that includes regressed profits on Total Trades, Winners, Size, and Intraday drawdown of Commodities, Equities, Fixed Income, and Trade duration Exit Days. The System uses the SP including a variety of traded securities. The System applies trading portfolio theories, such as asset diversification, and extends these theories to human resource management diversification. The System integrates an Automated Trading System (ATS), of algorithmic trading, with a Simple Moving Average (SMA) trading strategy. This paper also tests several null hypotheses on predictor independent variables and their coefficient of determination; rejecting the null hypotheses that these determinations are equal to zero. Furthermore, this paper links constructs to SMA and Trend-Following Ordinary Least Square (OLS), to the World Wide Web (WWW), and to High Frequency Trading (HTF). Additionally, this paper discusses topping the WWW’s Search Engine Results page (SERP) and discusses Search Engine Optimization (SEO). The System includes Mobile Phones (smart phones and tablets), Audit Counter Party Audio/Video (AV), a surveillance approach to IP (Internet Protocol) both fixed and mobile, and wired and wireless AV cameras. The System also includes wearable cameras; such as Google-Glass. Additionally, The System includes screen-sharing broadcasting, archiving shots, and webcams. The System also implements Google Plus’s Hangouts on Air (G+ HOA), as well as Voice over IP (VOIP) phone video conferencing, which is similar to Skype. Software robots (BOTs) and classroom Instructor’s Lecture Videos, which are recorded with the instructor’s tablet, supplement The System. Furthermore, The System deals with Quantitative Robotic Algorithmic Automated Securities (e.g., Stocks, Equities, Treasuries, Commodities, and Futures). Additionally The System includes Trading System Strategy, internet security, forensic accounting, and expert witness testimony, point of view (POV) surveillance, fraud examination, and web programming. The System helps identify misinformation such as “cooking the books” from Toxic Paper Sub-Prime Mortgages, CDS, and CSOs Material Misstatements of the Financial Services Industry; such as the Crisis Challenges and counterparty surveillance of collateralized debt obligations.

From Carry Trades to Curvy Trades

Traditional carry trade strategies are based on differences in short-term interest rates, neglecting any other information embedded in yield curves. We derive return distributions of carry trade portfolios among G10 currencies, where the signals to buy and sell currencies are based on summary measures of the yield curve, the Nelson-Siegel factors. We find that a strategy based on the relative curvature factor, the curvy trade, yields higher Sharpe ratios and a smaller return skewness than traditional carry trade strategies. Curvy trades build less upon the typical carry currencies, like the Japanese yen and the Swiss franc, and are hence less susceptible to crash risk. In line with that, standard pricing factors of traditional carry trade returns, such as exchange rate volatility, fail to explain curvy trade returns in a linear asset pricing framework. Our findings are in line with recent interpretations of the curvature factor. A relatively high curvature signals a relatively higher path of future short-term rates over the medium-term putting upward pressure on the currency. JEL Classification: C23, C53, G11

The Next Generation ETF Student-Managed Investment Program

Exchange-traded funds (ETFs) are well suited for trading in student-managed investment funds (SMIFs). Unlike other forms of security selection, ETF trading provides efficient trading of portfolios by asset classes, subclasses, investment style, countries, regions, and sectors. The learning experience from trading ETFs based on global macroeconomic themes enhances the learning experience of economics students by requiring application of macroeconomics, industrial organization, international economics, and econometrics. This article presents the structure, tools, and results of an ETF trading program implemented by the economics and finance departments at the University of Richmond. Although this SMIF example uses ETF funds as a learning medium for undergraduates, the investment process with ETFs is also well suited to small individual investors.

Self-Attribution Bias and Overconfidence Among Nonprofessional Traders

Abstract We investigate consequences of the self-attribution bias for nonprofessional traders. By applying a textual analysis of more than 44,000 public comments on a large social trading platform, we contribute to empirical literature on investment and trading behavior in three ways: First, we show that one component of the self-attribution bias, the self-enhancement bias, leads to subsequent underperformance. Second, results support the theory that traders become overconfident due to biased self-enhancement. Third, we find that traders’ social trading portfolios attract higher investment flows from investors when showing self-enhancement biased behavior.

Aid for trade and ecologically sustainable development in Australia’s international aid program

ABSTRACTIn September 2015, Australia, along with 193 member states of the United Nations, signed the United Nations Sustainable Development Goals. The facilitation of international trade and increasing foreign aid for developing countries were emphasised as crucial means for achieving the Sustainable Development Goals. An important role was assigned to the international Aid for Trade initiative, which is about stimulating economic growth in developing countries through removing constraints to trade. Australia has been a strong supporter of the Aid for Trade initiative since it was launched at the World Trade Organization’s Ministerial Conference in Hong Kong in 2005. Aid for trade has become a central plank of the ‘new development paradigm’ of Australia’s international aid program. This article analyses the conceptualisation and practice of aid for trade in Australia’s aid, with a focus on how it links to ecologically sustainable development. It argues that Australia’s aid for trade is reinforcing the neo-liberal development paradigm in which environmental dimensions are overall neglected and private sector development and free trade are prioritised. In order to achieve international and national development goals of poverty reduction and sustainable development, environmental sustainability needs to be fully integrated into the growing aid for trade portfolio of Australia’s international aid.

A stacked generalization system for automated FOREX portfolio trading

Abstract Multiple FOREX time series forecasting is a hot research topic in the literature of portfolio trading. To this end, a large variety of machine learning algorithms have been examined. However, it is now widely understood that, in real-world trading settings, no single machine learning model can consistently outperform the alternatives. In this work, we examine the efficacy and the feasibility of developing a stacked generalization system, intelligently combining the predictions of diverse machine learning models. Our approach establishes a novel inferential framework that comprises the following levels of data processing: (i) We model the dependence patterns between major currency pairs via a diverse set of commonly used machine learning algorithms, namely support vector machines (SVMs), random forests (RFs), Bayesian autoregressive trees (BART), dense-layer neural networks (NNs), and naive Bayes (NB) classifiers. (ii) We generate implied signals of exchange rate fluctuation, based on the output of these models, as well as appropriate side information obtained by analyzing the correlations across currency pairs in our training datasets. (iii) We finally combine these implied signals into an aggregate predictive waveform, by leveraging majority voting, genetic algorithm optimization, and regression weighting techniques. We thoroughly test our framework in real-world trading scenarios; we show that our system leads to significantly better trading performance than the considered benchmarks. Thus, it represents an attractive solution for financial firms and corporations that perform foreign exchange portfolio management and daily trading. Our system can be used as an integrated part in international commercial trade activities or in a quantitative investing framework for algorithmic trading and carry-trade speculation.

Portfolio Size and Profitability of Moving Average Timing Strategy

Using popular technical trading rule of moving averages, this study documents the profitability of technical analysis for equal weighted random portfolios from Australian Securities Exchange (ASX) and New Zealand Exchange (NZX) equity markets. The findings confirm prior evidence on the profitability of technical analysis for portfolio trading in relatively illiquid financial markets that are part of small open economies. This study contributes to the technical analysis literature regarding the number of stocks in a portfolio (hereafter “portfolio size”) that a trader must hold to outperform a passive benchmark strategy. Precisely, the findings suggest that an investor can consistently outperform buy and hold strategy return by applying MA timing strategy to a portfolio that contains 80 or more random stocks. In addition, the study identifies market volatility and short-term market trend as major determinants of moving average strategy’s success.

Global Hedging through Post-Decision State Variables

Unlike delta-hedging or similar methods based on Greeks, global hedging is an approach that optimizes some terminal criterion that depends on the difference between the value of a derivative security and that of its hedging portfolio at maturity or exercise. Global hedging methods in discrete time can be implemented using dynamic programming. They provide optimal strategies at all rebalancing dates for all possible states of the world, and can easily accommodate transaction fees and other frictions. However, considering transaction fees in the dynamic programming model requires the inclusion of an additional state variable, which translates into a significant increase of the computational burden. In this short note, we show how a decomposition technique based on the concept of post-decision state variables can be used to reduce the complexity of the computations to the level of a problem without transaction fees. The latter complexity reduction allows for substantial gains in terms of computing time and should therefore contribute to increasing the applicability of global hedging schemes in practice where the timely execution of portfolio rebalancing trades is crucial.

Behavior of fund managers in Malaysian investment management industry

PurposeThis paper aims to explore the relevance of bounded rationality to the practice of institutional investors in Malaysia. Understanding institutional investor behavior is important, as it can determine the asset prices and consequently the market behavior.Design/methodology/approachA set of questionnaires is used to solicit information regarding the understanding and practical application of behavioral finance theories and strategies among fund managers in the Malaysian investment management practice. In the process, bounded rational theory is aimed to be validated. Fund managers’ possible bounded rational behavior is assessed with reference to their investment management approaches and strategies right from individual beliefs and acquisition of information, as well as investment management and strategies used.FindingsThe findings lend support to the notion that institutional investors too, being normal human beings, are expected to think and behave in a boundedly rational manner as postulated in bounded rational theory. The sources of bounded rationality are individual, institutional and social forces. Thus, portfolio trading and investment management strategies are exposed to wide varieties of behavioral risks. Despite the notions that behavioral risks are real and the impact on fund performance could be pervasive, fund managers’ self-awareness regarding control and institutional readiness to govern behavioral risks in investment practices is still low.Research limitations/implicationsEmpirical evidence drawn in the current paper is subjected to small sample size and specific focus on Malaysian context. Despite this limitation, the sample is statistically sufficient and provides a fair representation, as well as quality opinions, of fund manager’s investment management behavior in Malaysia. This research provides valuable implications to practitioners (fund managers) and regulators (investment management and capital market policymakers). In practice, the current study draws some practical ideas, especially for buy-side institutional investors, on the source and impact of behavioral biases on fund management practices and performance. For regulators, this research highlighted the needs and possible ways to regulate these behavioral risks.Originality/valueThe current paper provides new insights on the theory and practice of the institutional investor. In theory, this research provides evidence of bounded rationality of institutional investor behavior, practicing in the asset management industry in the emerging markets of Malaysia. This evidence lends support to the validity of the bounded rationality theory in explaining institutional investor behavior. In practice, thisresearch provides new insights on the relevance of behavioral finance perspectives and strategies in the asset management industry practice and policy.

What Drives Investment Flows into Social Trading Portfolios?

What Drives Investment Flows into Social Trading Portfolios?

Optimal portfolio trading subject to stochastic dominance constraints under second‐order autoregressive price dynamics

AbstractThis paper studies the optimal portfolio trading problem under the generalized second‐order autoregressive execution price model. The problem of minimizing expected execution cost under the proposed price model is formulated as a quadratic programming (QP) problem. For a risk‐averse trader, problem formulation under the second‐order stochastic dominance constraints results in a quadratically constrained QP problem. Under some conditions on the execution price model, it is proved that the portfolio trading problems for risk‐neutral and risk‐averse traders become convex programming problems, which have many theoretical and computational advantages over the general class of optimization problems. Extensive numerical illustrations are provided, which render the practical significance of the proposed execution price model and the portfolio trading problems.