Search results

The purpose of this paper is to present a discrete quantitative trading strategy to directly control a portfolio's maximum percentage of drawdown losses while trying to maximize the portfolio's long‐term growth rate.

The loss control target is defined through a Rolling Economic Drawdown (REDD) with a constant look‐back time window. The authors specify risk aversion in the power‐law portfolio wealth utility function as the complement of maximum percentage loss limit and assume long‐term stable Sharpe ratios for asset class indexes while updating volatility estimation in dynamic asset allocation implementation.

Over a test period of the past 20 years (1992‐2011), a risk‐based out‐of‐sample dynamic asset allocation among three broad based indexes (equity, fixed income and commodities) and a risk free asset, is robust against variations in capital market expectation inputs, and out‐performs the in‐the‐sample calibrated model and traditional asset allocation significantly.

The current proposal can lead to a new mathematical framework for portfolio selection. Besides investors' liquidity and behavioural constraints, macroeconomic and market cycle, and the potential of central bank interventions following a market crash, could be additionally considered for a more rigorous dynamic asset allocation model.

Besides the benefit of a clear mandate to construct suitable client portfolios, the portfolio approach can be applied to design invest‐able securities, such as principal‐guaranteed investment products, target risk asset allocation ETFs, and target‐date mutual funds with a glide path, etc. The formulation can also be implemented as a managed futures hedge fund portfolio.

The paper introduces the Rolling Economic Drawdown (REDD) concept and specifies risk aversion as the floor of maximum percentage loss tolerance. Dynamic asset allocation is implemented through updating estimation of asset class volatilities.

The purpose of this paper is to compare the profitability of different pairs selection and spread trading methods using the complete data set of commodity futures from Dalian Commodity Exchange, Shanghai Futures Exchange and Zhengzhou Commodity Exchange.

Paris trading methods that are proposed in the literature are compared in terms of the risk-adjusted returns visa in-sample and out-of-sample backtesting and bootstrapping for robustness.

The empirical results show that pairs trading in the Chinese commodity futures market offers high returns, whereas, the profitability of these strategies primarily depends on the identification of suitable pairs. The observed high returns are a compensation for the spread divergence risk during the potentially longer holding periods, which implies that the maximum drawdown is more crucial compared to other risk-adjusted return measures such as the Sharpe ratio.

Complementary to the existing literature, for the Chinese commodity futures market, it is shown that if shorter maximum holding periods are introduced for the spread positions, then the pairs trading profits decreases. Therefore, the returns do not necessarily imply market inefficiency when the higher maximum drawdown associated with the holding period of the spread position is taken into account.

Using data spanning 145 years for Sweden, the authors investigate the benefits of holding multi-family properties for investors who aim to hedge wage growth.

The authors assess the risk-adjusted excess return that results from adding multi-family properties to a mixed-asset portfolio that aims to track wage growth. The authors also analyse the macroeconomic determinants of asset returns. Finally, the authors test whether a causal relationship exists between the growth rate of real wages and that of real net operating income.

The benefits from holding multi-family properties are the greatest for low-risk allocation approaches. For more risky strategies, the role of real estate is more muted, and it varies greatly over time. Holding real estate was most beneficial during the first two decades of the 21st century. Multi-family properties are found to be the only asset class to be positively related to wage growth. The authors show that the net operating income acts as the transmission channel between wages and property returns.

The paper assesses whether the growing interest of pension funds for multi-family properties is warranted in the context of a portfolio that aims to track wage growth.

Using long term data makes it possible to use a rolling windows approach and hence to consider multiple outcomes for an allocation strategy over a typical investment horizon. This permits to assess the dispersion of performance across several periods rather than just one as is commonly done in the literature. The results show that the conclusions that would be drawn from looking at the past two or three decades of data differ substantially from those for earlier time periods.

The existing literature on the Black-Litterman (BL) model does not offer adequate guidance on how to generate investors’ views in an objective manner. Therefore, the purpose of this paper is to establish a generalized multivariate Vector Error Correction Model (VECM)/Vector Auto-Regressive (VAR)-Dynamic Conditional Correlation (DCC)/Asymmetric DCC (ADCC) framework, and applies it to generate objective views to improve the practicality of the BL model.

This paper establishes a generalized VECM/VAR-DCC/ADCC framework that can be utilized to model multivariate financial time series in general, and produce objective views as inputs to the BL model in particular. To test the VECM/VAR-DCC/ADCC preconditioned BL model’s practical utility, it is applied to a six-asset China portfolio (including one risk-free asset).

With dynamically optimized view confidence parameters, the VECM/VAR-DCC/ADCC preconditioned BL model offers clear advantage over the standard mean-variance method, and provides an automated portfolio optimization alternative to the classic BL approach.

The VECM/VAR-DCC/ADCC framework and its application in the BL model proposed by this paper provide an alternative approach to the classic BL method. Since all the view parameters, including estimated mean return vectors, conditional covariance matrices and pick matrices, are generated in the VECM/VAR and DCC/ADCC preconditioning stage, the model improves the objectiveness of the inputs to the BL stage. In conclusion, the proposed model offers a practical choice for automated portfolio balancing and optimization in a China context.

The purpose of this paper is to provide a cohesive review of the major findings in the literature concerning the Global Financial Crisis.

Papers published in top-rated finance and economics journal since the crisis up to the present were reviewed. A large number of these were selected for inclusion, primarily based on the number of citations they had received adjusted for the amount of time elapsed since their publication, but also partly based on how well they fit in with the narrative.

Much has been done to investigate the causes of the Global Financial Crisis, its effects on various aspects of the financial system, and the effectiveness of regulatory measures undertaken to restore the financial system. While more remains to be done, the existing body of research paints an interesting picture of what happened and why it happened, describes the interrelationships between the mortgage markets and financial markets created by the large scale securitization of financial assets, identifies the problems created by these inter-linkages and offers possible solutions, and assesses the effectiveness of the regulatory response to the crisis.

This study summarizes a vast amount of literature using a framework that allows the reader to quickly absorb a large amount of information as well as identify specific works that they may wish to examine more closely. By providing a picture of what has been done, it may also assist the reader in identifying areas that should be the subject of future research.

This paper aims to demonstrate a dynamic cointegration-based pairs trading strategy, including an optimal look-back window framework in the cryptocurrency market and evaluate its return and risk by applying three different scenarios.

This study uses the Engle-Granger methodology, the Kapetanios-Snell-Shin test and the Johansen test as cointegration tests in different scenarios. This study calibrates the mean-reversion speed of the Ornstein-Uhlenbeck process to obtain the half-life used for the asset selection phase and look-back window estimation.

By considering the main limitations in the market microstructure, the strategy of this paper exceeds the naive buy-and-hold approach in the Bitmex exchange. Another significant finding is that this study implements a numerous collection of cryptocurrency coins to formulate the model’s spread, which improves the risk-adjusted profitability of the pairs trading strategy. Besides, the strategy’s maximum drawdown level is reasonably low, which makes it useful to be deployed. The results also indicate that a class of coins has better potential arbitrage opportunities than others.

This research has some noticeable advantages, making it stand out from similar studies in the cryptocurrency market. First is the accuracy of data in which minute-binned data create the signals in the formation period. Besides, to backtest the strategy during the trading period, this study simulates the trading signals using best bid/ask quotes and market trades. This study exclusively takes the order execution into account when the asset size is already available at its quoted price (with one or more period gaps after signal generation). This action makes the backtesting much more realistic.

The purpose of this paper is to explain how the current “crisis” in the UK pension system arose. I argue that it is a result of a combination of changes in government policy and basic instabilities always inherent in the financial system. Policy changes increased the vulnerability of the pension system to those instabilities. The background to these changes and also the frame of reference in terms of which the “crisis” itself is now phrased is broadly neoliberal. Its theoretical roots are in ideas of the efficiency of free markets. Its policy roots are expressed in a series of similar neoliberal policy tendencies in other capitalist states. I further argue that neoliberal solutions to the pension crisis simply offer more of the very matters that created the problems in the first place. Moreover, the very terms of debate, based in markets, financialisation of saving and individualisation of risk, disguise a more basic debate about providing a living retirement income for all. This is a debate that New Labour is simply not prepared to constructively engage with in any concrete fashion.

The purpose of this paper is to utilize a constrained random portfolio-based framework for measuring the skill of a cross-section of Indian mutual fund managers. Specifically, the authors test whether the observed performance implies superior investment skill on the part of mutual fund managers. Additionally, the authors investigate the suitability of mutual fund investments under diverse investor expectations.

The authors use a new skill measurement methodology based on a cross-section of constrained random portfolios (Burns, 2007).

The authors find no evidence of superior investment skill in the sample of Indian equity mutual funds. Using a series of statistical tests, the authors conclude that the mutual funds fail to outperform the random portfolios. Furthermore, mutual funds show no persistence in their performance over time. These results are robust to choice of performance measure and the investment horizon. However, mutual funds provide lower downside risks and may be suitable for investors with high degree of risk aversion.

The authors extend Burns’ (2007) methodology in several aspects, especially by using a much wider range of performance and downside risk measures to address diverse investor expectations. To the best of the authors’ knowledge, this is first study to apply the constrained random portfolios-based skill tests in an emerging market.