Mar
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## Selected Interesting Papers from MFA Conference

I just returned Beijing from the Midwest Finance Association 2016 Annual Meeting in Atlanta, it is my first time in America, and the life there is quite different from that in the British cities... few people in downtown, hard to go out without a car, people are less friendly (at least look like)...

MFA annual conference provides a forum for the interaction of finance academics and practitioners to share scholarly activity and current practice so as to encourage and facilitate the betterment of the profession. Below I select several papers with download links that are of interest to me, it is by no means a list of top quality of the conference though.

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MFA annual conference provides a forum for the interaction of finance academics and practitioners to share scholarly activity and current practice so as to encourage and facilitate the betterment of the profession. Below I select several papers with download links that are of interest to me, it is by no means a list of top quality of the conference though.

**Short-Term Trading Skill: An Analysis of Investor Heterogeneity and Execution Quality**: We examine short-horizon return predictability using a unique, proprietary data set across a large universe of institutional traders with known (masked) identity. We propose a model to estimate an investor-specific short-term trading skill and find that there is pronounced heterogeneity in predicting short-term returns among institutional investors. This suggests that short-term information asymmetry is a significant motivation for trade. Our model illustrates that incorporating short-term predictive ability explains a much higher fraction of short-term asset returns and enables more accurate estimation of price impact. A simple trading strategy exploiting our estimates of skill yields statistically significant abnormal return when benchmarked against a four-factor model. We investigate the source of variation in short-term trading skill and find strong evidence that skilled traders are able to predict short-term returns by following a short-term momentum strategy. Furthermore, we illustrate that the variation in short-term trading skill is statistically dependent on order characteristics such as duration and relative size, that are associated with more urgent and more informed trading. Finally, using both trading skill estimates emerging from our model and proposed skill predictive variables, we show that investor heterogeneity has major implications for quantifying execution quality.paper

**An Empirical Detection of HFT Strategies**: This paper detects empirically the presence of High Frequency Trading strategies from public data and examines their impact on financial markets. The objective is to provide a structured and strategic approach to isolate signal from noise in a high frequency setting. In order to prove the suitability of the proposed approach, several HFT strategies are evaluated on the basis of their market impact, performance and main characteristics.paper

**Financial leverage and cross sectional delta-hedged option returns**: This paper studies how firm's financial decisions affect the expected return of delta-hedged equity options, both theoretically and empirically. I first derive the expected return of the delta-hedged equity option based on a capital structure model, in which the asset value of a firm is driven by a double exponential jump-diffusion process. Empirically I test the implications of the model using cross-sectional equity option data. After controlling for other firm characteristics such as size and asset volatility, the delta-hedged equity option return decreases with the book leverage of the underlying firm. For the same level of book leverage, the return is more negative in a firm where debt is protected by net-worth covenants. The relation is robust across puts, calls, and moneyness levels and especially evident for out-of-the-money options.paper

**Cross-Sectional and Time-Series Tests of Return Predictability: What is the Difference?**: Recent evidence suggests time-series (TS) momentum strategies outperform traditional cross-section (CS) momentum strategies. We show that the TS strategy is effectively a combination of a zero-net investment long/short strategy and a time-varying net-long investment in the equal weighted index, while the CS strategy is a zero-net investment long/short strategy. Empirically, the zero-net investment part of the TS portfolio and the CS portfolio earn about equal returns indicating that their stock selection abilities are similar. The performances of these strategies differs because of the time-varying market investment portion of the TS strategy, which we further break down into risk premium and market timing components. Among TS and CS strategies on financial ratios, stocks selected by the TS approach perform better for profitability ratios but worse for book-to-market ratio.paper

**What the Variance Risk Premium Tells Us About the Expected Market Returns**: Bollerslev, Tauchen and Zhou (2009) find that the variance risk premium performs well in predicting short-term returns. This paper studies how this predictive relation is connected to the `volatility feedback'. This paper finds that the predictive beta is closely related to the beta that explains the contemporaneous relation between the market returns and the variance innovations. They are, in fact, close enough that the beta of this contemporaneous relation is superior to the beta of the historical predictive regression when forecasting out-of-sample. Moreover, the contemporaneous correlation between returns and variance innovations is related to the predictive $R^2$. Thus, we can anticipate the predictive accuracy by observing the strength of volatility feedback.paper

**When Options Markets Disagree**: paper**Volatility and Expected Option Returns**: We analyze the relation between expected option returns and the volatility of the underlying securities. In a Black-Scholes framework, the expected return from holding a call (put) option is a decreasing (increasing) function of the volatility of the underlying. These predictions are strongly supported by the data. In the cross-section of stock option returns, returns on call (put) option portfolios decrease (increase) with underlying stock volatility. This strong negative (positive) relation between call (put) option returns and volatility is not due to cross-sectional variation in expected stock returns. It holds in various option samples with different maturities and moneyness, and it is robust to alternative measures of underlying volatility and different weighting methods. Time-series evidence also supports the predictions from option pricing theory: Future returns on S&P 500 index call (put) options are negatively (positively) related to S&P 500 index volatility.paper

**Forecasting the Term Structure of Implied Volatilities**: Neumann and Skiadopoulos (2013) document that although the implied volatilities are predictable, their economic profits become insignificant once the cost is accounted for. We show that the trading strategies based on the predictability of implied volatilities could generate significant risk-adjusted returns after controlling for the transaction cost. The implied volatility curve information is useful for the out-of-sample forecast of implied volatilities up to one week. Short-maturity implied volatilities tend to be more predictable than long-maturity implied volatilities. Although the long-maturity options are much less traded than the short-maturity options, their implied volatilities provide much more information on the price discovery.paper

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RevTeam

2016/07/15 11:47 [Add/Edit reply] [Clear reply] [Del comment] [Block]

Great! Thank you very much. I was looking something like this paper about Option Returns.

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