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(1 - 4 of 4)
- Title
- INFORMATION OF MARKET EFFICIENCY, VOLATILITY, VOLUME, AND TREND FROM LIMIT ORDER BOOK
- Creator
- LI, SHOUHAO
- Date
- 2019
- Description
-
This study mainly focuses on a series of topics within high frequency data of aprivate limit order book from NASDAQ. The interest of our...
Show moreThis study mainly focuses on a series of topics within high frequency data of aprivate limit order book from NASDAQ. The interest of our research first comes from thefamous classical theory “Efficient Market Hypothesis (EMH)”. Given the existence of aseparate market in which high frequency traders compete together under today’senvironment, we show that this market is quite adaptive rather than efficient since thestatistical quantity measuring market efficiency will have fluctuating values in differenttime point, confirmed in our study. Then we explore the linkage between high frequency cancelling activity and marketshort-term volatility (quote volatility). The findings for this topic until now are rather notconclusive yet. In our design, we first use Grange Causality test. It turns out realizedvolatility and cancelling activity granger cause each other, and cancelling activitycontributes tremendously to volatility forecasting. Then we fit our data in a generic ofARCH models to establish the predictability of realized volatility by cancellinginformation. Finally, we take advantage of the cancelling activity to predict real timetrading. We use the VIXY which is an ETF of VIX and focuses on short term performance.We find that the ask side of high frequency trading activities has far more significant impactfor both the level of VIXY and return of VIXY, while the bid side seems to be trivial. At last, we analyze the role of traded volume and trend in technical analysis. Theusefulness of technical analysis has been confirmed in the beginning part of this study byrejecting EMH, then a continuing topic for we to discuss is possible variables which couldcontribute to technical analysis. As known to finance literature, volume is frequently takento validify the trend of stock or discover the reversal of the trend. But now there is oppositeopinion maintaining that the role of volume has become trivial. Our findings complementprevious researches and confirm both the usefulness and the fading of such usefulness oftraded volume.
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- Title
- MODELING THE INFORMATION CONTENT OF THE LIMIT ORDER BOOK BY BAGGING
- Creator
- Li, Wenyi
- Date
- 2018
- Description
-
I propose a bagging tree framework to study the information content of the limit order book in U.S. equity market. By measuring the...
Show moreI propose a bagging tree framework to study the information content of the limit order book in U.S. equity market. By measuring the predictability and profitability of the order book data up to 5 levels, I find that the limit orders book is informative. In addition to market orders, limit orders behind the best bid and ask prices also contributes to short-term future price movements. Finally, I design simple strategies to show that this information content can be effectively and consistently translated to economic value. My results may provide important implications for both researchers and market practitioners.
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- Title
- The Impact of High-Frequency Trading on the U.S. Equity Market
- Creator
- Pan, Miaomiao
- Date
- 2018
- Description
-
This dissertation studies the impact of high-frequency trading (HFT) on the U.S equity market. I investigate the trading behavior of high...
Show moreThis dissertation studies the impact of high-frequency trading (HFT) on the U.S equity market. I investigate the trading behavior of high-frequency traders (HFTs) using a massive dataset that contains the NASDAQ ITCH feed messages of all S&P 500 component stocks in year 2012. I identify clusters of extremely high cancellation activity (Blocher et al., 2016) in the order book and use high cancel clusters as a proxy for high-frequency cancellation activity. I examine the change in liquidity measures from one-half second before each cancel cluster starts until after the cancel cluster closes and find that with the presence of high cancel activity, liquidity measures recover to their pre-cluster level faster than in non-cancel clusters. Furthermore, an analysis of 1-minute time intervals finds various HFT proxies to be positively related to liquidity, especially for large-cap stocks and certain sectors. Using the Li criterion (Li et al. 2018), I differentiate trades placed by HFTs versus low-frequency traders (LFTs) and compares the two types of trades under the VAR/VMA framework (Hasbrouck 1991). Evidence shows that HFT trades contribute more to the price discovery process than LFT trades and HFTs impose adverse selection costs on LFTs. This study disambiguates unreliable liquidity and faster price discovery.
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- Title
- MARKETABLE LIMIT ORDERS AND NON-MARKETABLE LIMIT ORDERS ON NASDAQ
- Creator
- ZHANG, DAN
- Date
- 2022
- Description
-
My research includes two parts. In the first part of my research, I classify marketable limit orders into three different types: large...
Show moreMy research includes two parts. In the first part of my research, I classify marketable limit orders into three different types: large marketable order to buy, large marketable order to sell, and small marketable order. I use dummy variance method to research the effect of the three marketable orders on standardized variance, and find that LMOB and LMOS play significant role in variance increase. The second part of my research is about modelling of time to execution and time to cancellation of Non-marketable limit orders. I construct variables and model time to execution for NLO to buy and time to cancellation for NLO to buy and NLO to sell based on exponential distribution with accelerated failure time specification. My research shows that the longer the distance of limit price to buy away from the best bid price, the longer time to execution is. The longer the distance of limit price to buy away from the best bid price or limit price to sell away from the best ask price, the longer the time to cancellation is.
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