Jia Miao

Trading foreign exchange portfolios with volatility filters: the carry model revisited

The rejection of the simple risk-neutral efficient market hypothesis in the foreign exchange (FX) market opens the possibility of the profitable use of a carry model taking full advantage of interest rate differentials to trade currencies. A first motivation for this paper is to study whether a simple passive carry model can outperform a typical currency fund manager replicated by dynamic technical moving average convergence and divergence (MACD) models as in Lequeux and Acar (1998). Secondly, we study whether the addition of volatility filters can further improve the carry model performance. We consider the period starting from the introduction of the Euro (EUR) on 4 January 1999 to 31 March 2005 (1620 datapoints). To assess the consistency of the carry model performance on a portfolio of the nine most heavily traded exchange rates, the whole review period is further split into two sub-periods. Our results show that in the three periods considered and after inclusion of transaction costs, the simple carry model performs much better than the benchmark MACD model in terms of annualized return, risk-adjusted return and maximum potential loss, while a combined carry/MACD model has the lowest trading volatility. Moreover, the addition of two volatility filters adds significant value to the performance of the three models studied.

Volatility filters for dynamic portfolio optimization

It is well known that volatilities and correlations of international stock markets tend to increase in times of financial instability. A dynamic rebalancing scheme is proposed where the underlying market volatility functions as a timing device and portfolio is only rebalanced when the underlying volatility regime changes. In addition, the traditional Markowitz mean variance (MV) optimization can lead to an ‘inefficient frontier’ with wrong expected returns. A risk-adjusted expected return (RAER) approach is proposed where expected returns are expressed as a linear function of the risk incurred through a risk-aversion coefficient. The results show that the addition of volatility filters adds value to the portfolio performance in terms of annualized return, maximum drawdown, risk-adjusted Sharpe ratio in the whole out-of-sample period as well as all the sub-periods. Moreover, the proposed RAER approach produces most consistent performance with and without the constraint on short-selling compared to other dynamic rebalancing approaches and a constant equally weighted portfolio.

The post‐investment relationship between a venture capitalist and its investee companies

Purpose – The purpose of this paper is to identify the key characteristics of the post‐investment relationship between the venture capital firm and its investee companies.Design/methodology/approach – The research is a case study of a major UK venture capital firm using qualitative research to determine the key characteristics of the post‐investment relationship. The study is based on interviews with parties on both sides of the relationship.Findings – While the results reflect the findings of the entrepreneurship and venture capital literature they also point to the importance of network growth and development for organizational learning in the venture capital industry, professionalization of investee firms and as a context in which the selection of the entrepreneur and the post investment relationship are set.Research limitations/implications – The research has the limitation of most case studies that the results cannot readily be generalized, in this case to the wider population of venture capital firm...

Profitability of a simple pairs trading strategy : recent evidences from a global context

Pairs trading strategy is a popular investment strategy, where traders long one stock and short the other stock. The trading profits are expected to be “immune” to any market conditions: being uptrend, downtrend, or sideways, instead the performance is determined by the relative performance of the pair. Following Gatev et al. [(1999) Pairs Trading: Performance of a Relative-Value Arbitrage Rule. Working Paper, Yale School of Management; (2006) Pairs trading: Performance of a relative-value arbitrage rule, The Review of Financial Study, 19, 797–827] and Do & Faff [(2010) Does simple pairs trading still work? Financial Analyst Journal, 66, 1–12], we examine whether the simple pairs trading rule is also profitable in markets outside of the US. We also examine whether the trading rule performs consistently during bull and bear markets, including the recent period of market turbulence. Our results show that in most countries, the strategy generates positive returns, without evidence of under performance during bear markets. Unlike prior research, we do not find that the trading profits diminish over recent years. The pairs trading strategy generates positive returns even after transaction costs. However, the returns deteriorate significantly at a higher level of transaction costs. It is also found that the correlation between the returns on our pairs trading portfolios and the returns on the corresponding stock market indexes is low, confirming its role as a diversifier to the traditional long only investments.

The Long-Run Effects of the Fed’s Monetary Policy on the Dynamics among Major Asset Classes

Abstract It is well known that government monetary policies significantly impact financial markets. There have been numerous studies examining the relationship between monetary policy and the prices of financial assets, including equities and bonds. Little, however, has been done to explore the impact of major financial assets on changes in monetary policies. This study examines the impacts of the Federal Reserve’s monetary policy on the dynamics of major financial assets in the U. S. For this purpose, cointegration was tested for between equities, bonds and real estate markets in the period 1980 to 2014, whereas the U. S. monetary base M2 was used as an exogenous variable. Our cointegration tests suggest that the exogenous component of the U. S. M2 significantly affected the interaction among major U. S. financial assets. These findings have implications for both policymakers and market practitioners in terms of portfolio allocation rules.

Volatility filters for FX portfolios trading: the impact of alternative volatility models

Dunis and Miao (2005) find that the addition of volatility filters with RiskMetrics forecasts can improve the performance of moving average convergence and divergence (MACD) models that replicate typical currency fund managers introduced as in Lequeux and Acar (1998). The motivation of this paper is to test whether alternative volatility models forecasts can further improve the models’ performance with such filters. The two alternative volatility forecast models used in this paper are GARCH model as in Bollerslev (1986) and stochastic volatility model with Markov switching (MS) based on Hamilton (1994) and Roche and Rockinger (2003). Our results show that volatility filters using alternative volatility models fail to enhance the performance of the simpler filters using RiskMetrics forecasts in terms of annualized return and Sharpe ratio.