1.
오랜만에 금융관련 학회 자료입니다. RSS로 구독하는 Quant News에 올라왔던 Selected Interesting Papers from MFA Conference에서 소개한 행사입니다. ‘미국 중서부 금융학회’라고 할 수 있는 행사 프로그램입니다. 무척 많은 논문들을 발표하였습니다.
Midwest Finance Association 2016 Annual Meeting
발표자중 익수한 분이 있습니다. Mehmet Saglam입니다. High Frequency Traders: Taking Advantage of Speed와 The Cost of Latency in High-Frequency Trading을 쓴 분입니다. 발표논문의 요지는
“일중 거래데이타를 1)트레이덩의 단기적으로 매매시점을 판단하는 능력(a investorspecific “trading skill” component)과 시장충격(a market impact or price impact component)으로 나누어 분석하니 숙련된 트레이더가 비숙련된 트레이더에 비해 단기실적이 좋다”는 내용입니다. 기관투자가가 알고리즘으로 대량주문을 낼 때 시장충격만을 고려하여 주문분할조건만을 고려하는데 트레이더의 short-term predictive ability까지 고려한 모델을 도입하자는 주장을 합니다.
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.
Short-Term Trading Skill: An Analysis of Investor Heterogeneity and Execution Quality중에서
2.
An Empirical Detection of HFT Strategies은 제목처럼 거래데이타을 이용하여 HFT의 전략중 Quote Stuffing과 Momentum Ignition에 의한 주문을 추출하는 모형(방법론)을 제시합니다.
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.
기타 관심이 가는 논문들입니다.
Anomalies Enhanced: The Value of Higher Frequency Information
Cross-Sectional and Time-Series Tests of Return Predictability: What is the Difference
