Implied volatility term structure and exchange rate predictability

This paper provides empirical evidence of the predictive power of the currency implied volatility term structure (IVTS) for the behavior of the exchange rate from both cross-sectional and time series perspectives. Intriguingly, the direction of the prediction is not the same for developed and emerging markets. For developed markets, a high slope means low future returns, while for emerging markets it means high future returns. We analyze predictability from a cross-sectional perspective by building portfolios based on the slope of the term structure, and thus present a new currency trading strategy. For developed (emerging) currencies, we buy (sell) the two currencies with the lowest slopes and sell (buy) the two with the highest slopes. The proposed strategy performs better than common currency strategies – carry trade, risk reversal, and volatility risk premium (VRP) – based on the Sharpe ratio, considering only currency returns, which supports the exchange rate predictability of the IVTS from a cross-sectional perspective.     

Jump detection with wavelets for high-frequency financial time series

This paper introduces a new nonparametric test to identify jump arrival times in high frequency financial time series data. The asymptotic distribution of the test is derived. We demonstrate that the test is robust for different specifications of price processes and the presence of the microstructure noise. A Monte Carlo simulation is conducted which shows that the test has good size and power. Further, we examine the multi-scale jump dynamics in US equity markets. The main findings are as follows. First, the jump dynamics of equities are sensitive to data sampling frequency with significant underestimation of jump intensities at lower frequencies. Second, although arrival densities of positive jumps and negative jumps are symmetric across different time scales, the magnitude of jumps is distributed asymmetrically at high frequencies. Third, only 20% of jumps occur in the trading session from 9:30 AM to 4:00 PM, suggesting that illiquidity during after-hours trading is a strong determinant of jumps.     

产融结合对制造企业研发投资具有双向调节作用吗

研发投资的高回报吸引着制造企业扩大投资规模，而研发投资的高风险又进一步强化了制造企业融资约束。产融结合是否既能够缓解融资约束调节制造业企业研发投资不足、又能约束投资惯性调节其投资过度呢？以2007—2016年沪深A股制造业上市公司为研究对象的实证研究发现，产融结合对制造企业研发投资具有缓解研发投资不足、加重研发投资过度的单向调节作用。进一步分析产融结合有效缓解研发投资不足、加重研发投资过度的机理，并对如何利用产融结合增强制造企业有效投资提出相关对策建议。〖JP〗     

Predictability of stock markets with disequilibrium trading. A commentary paper

The paper focuses on the problem of predictability of stock market returns with disequilibrium trading. It is shown that the predictability of returns may be the consequence of quantity constraints appearing in the markets due to the imposition of administrative restrictions on trade. A relevant test of predictability for the Warsaw Stock Exchange (WSE) based on information referring to disequilibrium states occurrence is proposed. The empirical results of its application to the WSE on a sample containing session-to-session observations from the period January 1995 to December 1999 strongly support the hypothesis of predictability.     

Losing sight of the trees for the forest? Attention allocation and anomalies

This paper tests asset pricing implications of the investor attention shift hypothesis proposed in theoretical work. We create a novel proxy for the dynamics of inattention towards firm-specific information and explore its impact on prominent return anomalies. As hypothesized and with all else equal, the proxy positively predicts the post-earnings announcement drift as well as the profitability of pairs trading, and negatively predicts the success of momentum strategies. Taken together, our findings highlight the importance of time-varying investor attention allocation for the price discovery process.     

Emerging Equity Market Volatility

Abstract

This paper considers two emerging markets that are under-researched, Kenya and Nigeria. It offers a comprehensive view of four time properties that emerged from the empirical time series literature on asset returns: (1) the predictability of returns from past observations; (2) the auto-regressive behavior of conditional volatility; (3) the asymmetric response of conditional volatility to innovations; and (4) the conditional variance risk premium. Results of the exponential GARCH (EGARCH) model indicate that asymmetric volatility found in the U.S. and other developed markets also characterized the Nigerian stock exchange. In Kenya, however, the asymmetric volatility coefficient is significant and positive, suggesting that positive shocks increase volatility more than negative shocks of an equal magnitude. The Nairobi Stock Exchange (KSE) returns series report negative but insignificant risk-premium parameters. In Nigeria (NSE), return series exhibit a significant and positive time-varying risk premium. The results also show that expected returns are predictable, that the auto-regressive return parameters (? ₁ ) are significant in both Kenya and Nigeria. Finally, the GARCH parameter (b) is statistically significant, indicating that volatility persistence is present in the two emerging markets studied.     

Valuation in US Commercial Real Estate

We consider a log‐linearized version of a discounted rents model to price commercial real estate as an alternative to traditional hedonic models. First, we verify a key implication of the model, namely, that cap rates forecast commercial real estate returns. We do this using two different methodologies: time series regressions of 21 US metropolitan areas and mixed data sampling (MIDAS) regressions with aggregate REIT returns. Both approaches confirm that the cap rate is related to fluctuations in future returns. We also investigate the provenance of the predictability. Based on the model, we decompose fluctuations in the cap rate into three parts: (i) local state variables (demographic and local economic variables); (ii) growth in rents; and (iii) an orthogonal part. About 30% of the fluctuation in the cap rate is explained by the local state variables and the growth in rents. We use the cap rate decomposition into our predictive regression and find a positive relation between fluctuations in economic conditions and future returns. However, a larger and significant part of the cap rate predictability is due to the orthogonal part, which is unrelated to fundamentals. This implies that economic conditions, which are also used in hedonic pricing of real estate, cannot fully account for future movements in returns. We conclude that commercial real estate prices are better modelled as financial assets and that the discounted rent model might be more suitable than traditional hedonic models, at least at an aggregate level.     

Note Short-term predictability of German stock returns

The paper investigates short-horizon individual stock returns; it exhibits statistically and economically significant autocorrelations, which for stock returns have so far been established mainly over long horizons, also for certain daily data, in particular between monday returns and various linear combinations of the previous week's returns.Research supported by Deutsche Forschungsgemeinschaft (DFG); I am grateful to Ralf Runde for preparing the data and to Gerd Ronning and an anonymous referee for helpful criticism and comments.     

A new investor sentiment indicator (ISI) based on artificial intelligence: A powerful return predictor in China

This paper utilizes deep learning approach widely documented in artificial intelligence, and proposes an investor-sentiment indicator (ISI) that is consistent with the purpose of forecasting stock market returns. We find that ISI is positively correlated with future stock market returns at a monthly frequency, but negatively associated with subsequent returns over a longer horizon. Moreover, ISI outperforms other well-recognized predictors both in and out of sample, and can predict cross-sectional stock returns sorted by industry. We also show a positive association between monthly ISI and dividend growth rate, which indicates that investors’ expectations about future cash flows may contribute to the return predictability of ISI.     

The Paradoxical Behavioral Effects of a Directional Goal on Investors' Risk Perceptions and Valuation Judgments

Market participants who evaluate risk often have a preference or goal for positive company performance. The authors test how such a directional goal affects risk perceptions and the relation between risk perceptions and assessments of value in an investment context. Compared with investors without directional goals—who, consistent with prior behavioral research, focus on negative aspects of risk—the authors find that those with directional goals assess risk as being more symmetric (i.e., they are less focused on downside risk). However, investors with directional goals are also less likely to consider risk when assessing value. Taken together, these results suggest that a directional goal reduces one behavioral effect identified in prior literature (the tendency to focus on downside risk), but creates another behavioral effect (ignoring risk in assessing value). The authors discuss implications for standard setters and regulators seeking to communicate risk information to market participants.