Time series momentum

We document significant “time series momentum” in equity index, currency, commodity, and bond futures for each of the 58 liquid instruments we consider. We find persistence in returns for one to 12 months that partially reverses over longer horizons, consistent with sentiment theories of initial under-reaction and delayed over-reaction. A diversified portfolio of time series momentum strategies across all asset classes delivers substantial abnormal returns with little exposure to standard asset pricing factors and performs best during extreme markets. Examining the trading activities of speculators and hedgers, we find that speculators profit from time series momentum at the expense of hedgers.     

Risk-managed 52-week high industry momentum,momentum crashes and hedging macroeconomic risk

This is the first study to investigate the profitability of Barroso and Santa-Clara’s [J. Financial Econ., 2015, 116, 111–120] risk-managing approach for George and Hwang’s [J. Finance, 2004, 59, 2145–2176] 52-week high momentum strategy in an industrial portfolio setting. The findings indicate that risk-managing adds value as the Sharpe ratio increases, and the downside risk decreases notably. Even after controlling for the spread of the traditional 52-week high industry momentum strategy in association with standard risk factors, the risk-managed version generates economically and statistically significant pay-offs. Notably, the risk-managed strategy is partially explained by changes in cross-sectional return dispersion, whereas the traditional strategy does not appear to be exposed to such economic risks.     

Time series momentum and moving average trading rules

We compare and contrast time series momentum (TSMOM) and moving average (MA) trading rules so as to better understand the sources of their profitability. These rules are closely related; however, there are important differences. TSMOM signals occur at points that coincide with a MA direction change, whereas MA buy (sell) signals only require price to move above (below) a MA. Our empirical results show MA rules frequently give earlier signals leading to meaningful return gains. Both rules perform best outside of large stock series which may explain the puzzle of their popularity with investors, yet lack of supportive evidence in academic studies.     

Time series momentum trading strategy and autocorrelation amplification

This paper investigates why general Moving Average (MA) trading rules are widely used by technical analysts and others. We assume general stationary processes for prices and we derive the autocorrelation function for an MA trading rule. Based on our results, we conjecture that autocorrelation amplification is one of the reasons why such trading rules are popular. Using simulated results, we show that the MA rule may be popular because it can identify price momentum and is a simple way of assessing and exploiting the price autocorrelation structure without necessarily knowing its precise structure. This paper then, provides empirical evidence of autocorrelation amplification using 15-year daily price data for 11 major international stock indices.     

Asymmetry,tail risk and time series momentum

In this paper, we investigate how to improve the time series momentum strategy by using partial moments. We find that reversals of time series momentum can be partly predicted by tail-distributed upper and lower partial moments derived from daily returns of commodity futures. Based on such information, we propose rule-based approaches to improve the trading signals suggested by the time series momentum strategy. The empirical results based on Chinese commodity futures document statistically significant improvements of the Sharpe ratio in the out-of-sample period. These improvements are robust to different look-back windows.     

Profitability of time series momentum

We propose a continuous-time heterogeneous agent model consisting of fundamental, momentum, and contrarian traders to explain the significant time series momentum. We show that the performance of momentum strategy is determined by both time horizon and the market dominance of momentum traders. Specifically, when momentum traders are more active in the market, momentum strategies with short (long) time horizons stabilize (destabilize) the market, and meanwhile the market under-reacts (over-reacts) in short-run (long-run). This provides profit opportunity for time series momentum strategies with short horizons and reversal with long horizons. When momentum traders are less active in the market, they always lose. The results provide an insight into the profitability of time series momentum documented in recent empirical studies.     

Capital structure,credit risk,and macroeconomic conditions

This paper develops a framework for analyzing the impact of macroeconomic conditions on credit risk and dynamic capital structure choice. We begin by observing that when cash flows depend on current economic conditions, there will be a benefit for firms to adapt their default and financing policies to the position of the economy in the business cycle phase. We then demonstrate that this simple observation has a wide range of empirical implications for corporations. Notably, we show that our model can replicate observed debt levels and the countercyclicality of leverage ratios. We also demonstrate that it can reproduce the observed term structure of credit spreads and generate strictly positive credit spreads for debt contracts with very short maturities. Finally, we characterize the impact of macroeconomic conditions on the pace and size of capital structure changes, and debt capacity.     

Trend following,risk parity and momentum in commodity futures

We show that combining momentum and trend following strategies for individual commodity futures can lead to portfolios which offer attractive risk adjusted returns which are superior to simple momentum strategies; when we expose these returns to a wide array of sources of systematic risk we find that robust alpha survives. Experimenting with risk parity portfolio weightings has limited impact on our results though in particular is beneficial to long–short strategies; the marginal impact of applying trend following methods far outweighs momentum and risk parity adjustments in terms of risk-adjusted returns and limiting downside risk. Overall this leads to an attractive strategy for investing in commodity futures and emphasises the importance of trend following as an investment strategy in the commodity futures context.     

经济已陷"风险三角"宏观经济政策空间收缩

对2017年全球经济有两个基本的看法:第一,2017年全球的经济形势还是有很大的不确定性.第二, 2017年从全球来看,经济增长似乎还是比较疲软.在这两个前提下,还碰到一个比较大的问题,从政策的角度来说,就是所谓的风险三角,风险三角是2016年国际清算银行在一个报告当中提出来的,我们现在很多国家都面对一个困境,我觉得这个困境确实是普遍存在,在中国也存在.所谓的"风险三角":一是生产率不断下降.二是杠杆率不断上升.     

Time series patterns in credit ratings

This article offers a substitute setting to simulate credit rating migrations. The internal correlations model tracks time-series movements within credit rating entries, rather than cross-ratings correlations. The proposed nonhomogeneous process is authenticated through the likelihood ratio Dickey–Fuller test, and is found to be statistically and economically significant, by better fitting observed cumulative default rates. Several nonlinear regression models assist to better identify these time-related patterns. The economic structure underlying the time dependency often corresponds to changes in GDP, business cycles, and market risk. Furthermore, significant positive autocorrelation is detected mostly among downgrade probabilities.     

Time series reversal in trend-following strategies

This paper empirically studies the reversal pattern following the formation of trend-following signals in the time series context. This reversal pattern is statistically significant and usually occurs between 12 and 24 months after the formation of trend-following signals. Employing a universe of 55 liquid futures, we find that instruments with sell signals in the trend-following portfolio (‘losers’) contribute to this type of reversal, even if their profits are not realised. The instruments with buy signals in the trend-following portfolio (‘winners’) contribute much less. A double-sorted investment strategy based on both return continuation and reversal yields to portfolio gains which are significantly higher than that of the corresponding trend-following strategy.     

Bank systemic risk and macroeconomic shocks: Canadian and U.S. evidence

This paper investigates how banks, as a group, react to macroeconomic risk and uncertainty; more specifically, it examines the relationship between bank systemic risk and changes and disruptions in economic conditions. Adopting the methodology of Beaudry et al. (2001), we introduce a new estimation procedure based on EGARCH to refine the framework developed by Baum et al., 2002, Baum et al., 2004, Baum et al., 2009 and Quagliariello, 2007, Quagliariello, 2009, and we analyze the relationship in the current industry context—i.e., in the context of market-based banking. Our results confirm that banks tend to behave more homogeneously vis-à-vis macroeconomic uncertainty. In particular, we find that both the cross-sectional dispersion of loans-to-assets and the cross-sectional dispersion of non-interest income share shrink during slow growth episodes, and particularly during financial crises, when the resilience of the banking system is at its lowest. More importantly, our main findings indicate that the cross-sectional dispersion of loans-to-assets has increased in the last decade, whereas the cross-sectional dispersion of non-interest income share appears to be more volatile and sensitive to macroeconomic shocks.     

Growth options,macroeconomic conditions,and the cross section of credit risk

This paper develops a structural equilibrium model with intertemporal macroeconomic risk, incorporating the fact that firms are heterogeneous in their asset composition. Compared with firms that are mainly composed of invested assets, firms with growth options have higher costs of debt because they are more volatile and have a greater tendency to default during recession when marginal utility is high and recovery rates are low. Our model matches empirical facts regarding credit spreads, default probabilities, leverage ratios, equity premiums, and investment clustering. Importantly, it also makes predictions about the cross section of all these features.     

Risk-managed industry momentum and momentum crashes

This paper investigates Barroso and Santa-Clara’s [J. Financ. Econ., 2008, 116, 111–120] risk-managed momentum strategy in an industry momentum setting. We investigate several traditional momentum strategies including that recently proposed by Novy-Marx [J. Financ. Econ., 2012, 103, 429–453]. We moreover examine the impact of different variance forecast horizons on average pay-offs and also Daniel and Moskowitz’s [J. Financ. Econ., 2016, 122, 221–247] optionality effects. Our results show in general that neither plain industry momentum strategies nor the risk-managed industry momentum strategies are subject to optionality effects, implying that these strategies have no time-varying beta. Moreover, the benefits of risk management are robust across volatility estimators, momentum strategies and subsamples. Finally, the ‘echo effect’ in industries is not robust in subsamples as the strategy works only during the most recent subsample.     

Time series analysis for financial market meltdowns

There appears to be a consensus that the recent instability in global financial markets may be attributable in part to the failure of financial modeling. More specifically, it is alleged that current risk models have failed to properly assess the risks associated with large adverse stock price behavior. In this paper, we first discuss the limitations of classical time series models for forecasting financial market meltdowns. Then we set forth a framework capable of forecasting both extreme events and highly volatile markets. Based on the empirical evidence presented in this paper, our framework offers an improvement over prevailing models for evaluating stock market risk exposure during distressed market periods.     

Finance and growth: Time series evidence on causality

This paper re-examines the empirical relationship between financial and economic development while (i) taking into account their dynamics and (ii) differentiating between stock market and banking sector development. We study the cointegration and causality between finance and growth for 22 advanced economies. Our time series analysis suggests that causality patterns depend on whether countries’ financial development stems from the stock market or the banking sector. We show that stock market development tends to cause economic development, while a reverse causality is mostly present between banking sector development and output growth. These findings indicate that the direction of causality between finance and growth is likely to be different at high levels of development.     

Misintermediation and macroeconomic fluctuations

Individuals plan consumption and production for different point in the future, using interest rates of various maturities as a guide. However, the financial intermediaries individuals work through traditionally do not match the maturity structure of their assets and liabilities. As a result, aggregate production plans and aggregate consumption plans for each period in the future need not coincide. The resulting discrepancy will eventually appear as a recession or boom, involving an unanticipated change in interest rates and production inside the original intertemporal production possibilities frontier. Maturity transformation is therefore not an essential function of financial intermediation, but rather a misfunction, one which we call ‘misintermediation’.     

Does the debt market assess large banks, risk? : Time series evidence from money center CDs

Uninsured bank liabilities should offer a promised yield that compensates depositors for their expected default losses. However, the conjectural, guarantees available to large U.S. banking firms makes it questionable whether large depositors should or do feel themselves exposed to credit risk. Prior papers have evaluated the determinants of bank risk premia using cross-sectional data, with relatively inconclusive results. This paper investigates the same issue in a methodologically independent fashion: using time series data on specific banks' daily offering rates during the period May 1982 through July 1988. We find that CD rates paid by large money center banks include significant default risk premia.