A model for unpacking big data analytics in high-frequency trading

This study develops a conceptual model of the 7 V′s of big data analytics to gain a deeper understanding of the strategies and practices of high-frequency trading (HFT) in financial markets. HFT is computerized trading using proprietary algorithms. Empirical data collected from HFT firms and regulators in the US and UK reveals competitive asymmetries between HFTs and low-frequency traders (LFTs) operating more traditional forms of market trading. These findings show that HFT gains extensive market advantages over LFT due to significant investment in advanced technological architecture. Regulators are challenged to keep pace with HFT as different priorities to the 7 V′s are given in pursuit of a short term market strategy. This research has implications for regulators, financial practitioners and investors as the technological arms race is fundamentally changing the nature of global financial markets.     

OPTIMAL EXECUTION HORIZON

Execution traders know that market impact greatly depends on whether their orders lean with or against the market. We introduce the OEH model, which incorporates this fact when determining the optimal trading horizon for an order, an input required by many sophisticated execution strategies. This model exploits the trader's private information about her trade's side and size, and how it will shift the prevailing order flow. From a theoretical perspective, OEH explains why market participants may rationally “dump” their orders in an increasingly illiquid market. We argue that trade side and order imbalance are key variables needed for modeling market impact functions, and their dismissal may be the reason behind the apparent disagreement in the literature regarding the functional form of the market impact function. We show that in terms of its information ratio OEH performs better than participation rate schemes and VWAP strategies. Our backtests suggest that OEH contributes substantial “execution alpha” for a wide variety of futures contracts. An implementation of OEH is provided in Python language.     

Insider Trading 2.0? The Ethics of Information Sales

The sale of faster access to financial market data has recently generated public controversy. NY Attorney General Eric Schneiderman has referred to such fast data feeds as “Insider Trading 2.0”. For example, Thomson Reuters sold the University of Michigan’s Consumer Sentiment Index to computerized trading firms 2 seconds before releasing its data to its other paying clients. This paper explores the ethical issues involved in the sale of such information. Is selling faster access ethically the same as traditional insider trading, which generally involves a breach of fiduciary duty or the use of misappropriated information? Such practices are extremely different from traditional insider trading as there is neither a breach of fiduciary duty nor misappropriation of inside information. The ethical issues are similar to other market segmentation and price discrimination issues, in which different prices are charged to different customers. The ability to price discriminate across segments can actually benefit large segments of the population who may receive lower prices because others, such as the high-speed traders, are paying more. The sale of faster access to information, especially by exchanges, raises additional ethical issues. There may be adverse effects on market quality that must be addressed. The moral distaste for the practice expressed by some stems from the seeming unfairness of a modern market structure that provides advantages to a small group of computerized traders.     

Hong Kong and Singapore exchanges confront high frequency trading

The Hong Kong (HKEx) and Singapore (SGX) exchanges remain conflicted about high frequency trading (HFT), reflecting the environment of private and public sector actors in which the HKEx and SGX operate. Neither exchange has resolved these conflicts, leaving the HFT controversy simmering and limiting the amounts of such trading occurring on their exchanges. Competitor exchanges in Asia, however, are more supportive of HFT. With the aid of technology providers which enable HFT, the HKEx and SGX significantly improved their trading infrastructures. At the same time, these providers developed data centres at other exchanges and built fibre-optic connections which permit low-latency trading across Asia. Traders in Hong Kong and Singapore access these exchanges, potentially undermining the HKEx and SGX.     

Need for speed: Hard information processing in a high‐frequency world

I study the role of high‐frequency traders (HFTs) and non‐high‐frequency traders (nHFTs) in transmitting hard price information from the futures market to the stock market using an index arbitrage strategy. Using intraday transaction data with HFT identification, I find that HFTs process hard information faster and trade on it more aggressively than nHFTs. In terms of liquidity supply, HFTs are better at avoiding adverse selection than nHFTs. Consequently, HFTs enhance the linkage between the futures and stock markets, and significantly contribute to information efficiency in the stock market by reducing the delay between the stock and the futures markets.     

我国现代城市流动商贩的发展与治理研究——基于商贩演化的经济社会学视角

现代流动商贩是在古代商贩数次分化中沉淀下来的包容性最强的底层社会群体。承袭了古代商贩流动谋生的特点,但在“职业”与“身份”、发展的“时间”与“空间”、活动的“集市”与“常市”以及所处的“阶层”和“地位”等方面具有特殊性。尤其是城市化的发展,使商贩从一个概念,发展成一个群体,演变成一种现象,甚至转化为一个“问题”。进城流动商贩问题的形成包括流动性爆发和治理问题两个方面。流动商贩的治理应以民生为导向,以其城市融入为目标,在政府与市场构成的二维坐标内寻求出路。从宏观到微观形成一个“三维九元”的立体治理体系。     

Trader networks and options risk management

We examine the effect of trading partner concentration and a matrix of variables which dictate the relative importance of a trader to the network on a set of large member proprietary traders’ risk. An increased closeness centrality and concentration of trading among network partners are found to reduce price, volatility and rebalancing risk. We further explore the nature of trading concentration established through traders’ recurring trading relationships to find that trading with an established and small network has a positive, yet costly, effect on inventory management. Relationships among market makers are important to managing their portfolio of risk.     

When do informed traders acquire and trade on informational advantage? Evidence from Federal Reserve stress tests

Using Federal Reserve bank stress test announcements, we examine when option traders acquire informational advantage and when they exploit it. We find consistent evidence of informed options trading around announcements. However, when test results are announced in successive weeks we find high abnormal option volume, considerably positive abnormal returns and significant return predictability in the first week, but not the following week. This suggests that informed option traders are able to anticipate upcoming news events and skillfully process public information but it also suggests that trading on acquired information is conditioned on the level of information asymmetry in the market.     

Is it Efficient to Impose Costs on Small-Volume Equity Traders?

A securities market that imposes higher trading costs on small-volume traders may reduce free-riding on information generated by large-volume traders. The reduction in free-riding increases the probability that large-volume traders will invest in socially beneficial information and engage in costly monitoring of managers of firms in their portfolio.V arious mechanisms can be used to impose costs on small-volume traders.We argue that Nasdaq's former treatment of limit orders was one such mechanism. Depending on the market's structure and the nature of the securities traded in the market, a reduction in freeriding activity may improve overall market efficiency despite a potentially negative impact on information dissemination.     

RUNNING FOR THE EXIT: DISTRESSED SELLING AND ENDOGENOUS CORRELATION IN FINANCIAL MARKETS

We propose a simple multiperiod model of price impact from trading in a market with multiple assets, which illustrates how feedback effects due to distressed selling and short selling lead to endogenous correlations between asset classes. We show that distressed selling by investors exiting a fund and short selling of the fund’s positions by traders may have nonnegligible impact on the realized correlations between returns of assets held by the fund. These feedback effects may lead to positive realized correlations between fundamentally uncorrelated assets, as well as an increase in correlations across all asset classes and in the fund’s volatility which is exacerbated in scenarios in which the fund undergoes large losses. By studying the diffusion limit of our discrete time model, we obtain analytical expressions for the realized covariance and show that the realized covariance may be decomposed as the sum of a fundamental covariance and a liquidity‐dependent “excess” covariance. Finally, we examine the impact of these feedback effects on the volatility of other funds. Our results provide insight into the nature of spikes in correlation associated with the failure or liquidation of large funds.     

Electronic Call Market for Commodity Transactions: Design of Computer-Mediated Order Matching System

Commodity exchanges provide potential market structures for electronic trading because commodity products have relatively simple and well-standardized product attributes. Most existing electronic trading systems are introduced for financial exchanges, where qualities of traded products (such as stocks and bonds) are homogeneous, thus taking into account only bid and offer prices for computer-mediated order matching. However, a single commodity market, such as the cotton or grain market, is made up of many heterogeneous goods that are similar to each other but have different product qualities and contract terms. In addition to the price, commodity traders have other pertinent preference ranges over product attributes and delivery conditions. We delineate an electronic call market system for commodity trading, which optimizes the realization of traders' utilities over extended product attributes beyond the price. The electronic call market not only maximizes the total surplus of market participants based on bid and ask prices but also satisfies their qualitative preferences over other attributes, which are difficult to include in the quantitative prices. The trading mechanism of the electronic call market integrates an economic auction model with a social choice model to produce a Pareto-improved transaction. Market simulations are conducted to validate the performance of the proposed electronic call market. The order matching system of the electronic call market is implemented using constraint logic programming.     

Volatility index and the return–volatility relation: Intraday evidence from Chinese options market

We use unique intraday data to investigate the validity of the Shanghai Stock Exchange's the revised Chinese implied volatility index (iVX). We find that iVX is an effective barometer for the underlying exchange-traded fund (ETF) market and can be used as a valid “fear index” when there is anxiety over large drops. Furthermore, we use robust quantile regressions and document the asymmetric relation between returns and iVX changes. We also show that behavioral theories offer better explanations for this asymmetric relation than do fundamental theories. More important, we examine the role of iVX in selecting trading strategies.     

Crypto quanto and inverse options

Over 90% of exchange trading on crypto options has always been on the Deribit platform. This centralized crypto exchange only lists inverse products because they do not accept fiat currency. Likewise, other major crypto options platforms only list crypto–stablecoin trading pairs in so-called direct options, which are similar to the standard crypto options listed by the CME except the US dollar is replaced by a stablecoin version. Until now a clear mathematical exposition of these products has been lacking. We discuss the sources of market incompleteness in direct and inverse options and compare their pricing and hedging characteristics. Then we discuss the useful applications of currency protected “quanto” direct and inverse options for fiat-based traders and describe their pricing and hedging characteristics, all in the Black–Scholes setting.     

What drives informed trading before public releases? Evidence from natural gas inventory announcements

This paper shows evidence of informed trading in the natural gas futures market before gas inventory announcements. We examine whether traders can predict the upcoming announcement by processing public information. The results show that the difference between the median forecast of analysts with high historical forecasting accuracy and the consensus forecast can be used to predict inventory surprises. This predictor explains some of the pre‐announcement price drift, suggesting that informed trading before the announcement is likely to be driven by superior forecasting rather than by information leakage. A simple trading strategy conditioned on the predictor would have generated an annualized Sharpe ratio of 1.26.     

沪港通的绩效增长与反向选择效应——兼论实现高质量增长的资本市场改革路径

本文从金融服务实体企业角度探讨了沪港通对“成分股”绩效增长是否存在激励效应和治理效应,以及沪港通的成分股“选择机制”是否存在“反向选择效应”,并综合运用线性调整、逆概率加权、内生处理效应、异质性处理效应等估计方法,得出如下结论:(1)“沪港通”政策的实施有助于提升成分股企业的绩效水平;(2)沪港通持股水平高更有助于提升企业绩效水平,表明沪港通持股存在治理效应;(3)政策实施过程存在潜在的福利损失——那些在“沪港通”中受益水平较低的企业更大概率地被选入成分股,从而降低了开放政策所能达到的最优福利水平。这表明以“试点”方式进行资本市场开放,会产生因“反向选择”而导致的福利损失。因此,需要加强改革的“强度”和“广度”,适时提升“沪港通”交易份额,并扩大沪港通成分股范围,以提高微观企业增长水平及增长质量。     

Intraday Liquidity Provision by Trader Types in a Limit Order Market: Evidence from Taiwan Index Futures

This study examines the dynamic liquidity provision process by institutional and individual traders in the Taiwan index futures market, which is a pure limit order market. The empirical analysis obtains several interesting empirical results. We find that trader type affects liquidity provision in a number of interesting ways. First, although institutional traders use more limit orders than market orders, foreign institution (individual) traders use a relatively higher percentage of market (limit) orders in the early trading session and then switch to more limit (market) orders for the remainder of the day until close to the end of the trading day. Second, net limit order submissions by both institutional and individual traders are positively related to one‐period lagged transitory volatility and negatively related to informational volatility. Third, net limit order submissions by institutional traders are positively related to one‐period lagged spread. Finally, both the state of limit order book and order size significantly influence all types of traders’ strategy on submission of limit order versus market order during the intraday trading session. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark 34:145–172, 2014     

Liquidity effects of trading frequency

In this paper, we present a discrete‐time modeling framework, in which the shape and dynamics of a Limit Order Book (LOB) arise endogenously from an equilibrium between multiple market participants (agents). We use the proposed modeling framework to analyze the effects of trading frequency on market liquidity in a very general setting. In particular, we demonstrate the dual effect of high trading frequency. On the one hand, the higher frequency increases market efficiency, if the agents choose to provide liquidity in equilibrium. On the other hand, it also makes markets more fragile, in the sense that the agents choose to provide liquidity in equilibrium only if they are market neutral (i.e., their beliefs satisfy certain martingale property). Even a very small deviation from market neutrality may cause the agents to stop providing liquidity, if the trading frequency is sufficiently high, which represents an endogenous liquidity crisis (also known as flash crash) in the market. This framework enables us to provide more insight into how such a liquidity crisis unfolds, connecting it to the so‐called adverse selection effect.     

Learning representation of stock traders and immediate price impacts

We use 239-day trading-level data for a stock on the Shanghai Stock Exchange, including about 440,000 traders and 1.77 million trading relationships, to study the representation of traders in a trading network using the network representation learning method, and to identify different traders' local outlier factor (LOF). Based on the local outlier factors, traders are divided into two categories: novel and normal. The novel traders' orders have smaller immediate price impact. Our method can be used to characterize and discover the behavior of medium-scale trading networks and provide certain decision support for market investors and regulators.     

Resiliency in the E-mini futures market

We study how quickly liquidity is replenished on the order book in E-mini futures. The results show that participants who use patient methods, such as limit orders, are often fast to place new orders, while those using impatient market orders are slow to re-enter the market. These delays are a function of state constants, such as firm types, state conditions, such as whether the order is price improving, and time-varying covariates, such as the volume of trade during the gap. We also find support for the view that certain traders delay providing liquidity during active markets to avoid informed trading.     

What Influences Trader Choice of Electronic versus Intermediated Execution?

We examine the determinants of US equity trader choice of electronic versus intermediated execution. While traders exhibit a strong overall preference for automation, when the market is less liquid at order submission time, traders seek market maker automated and human order‐matching services more often. Traders' overall tendency to choose intermediaries is highly correlated with their demand for liquidity. Market maker participation rates are higher for more active and larger size traders. Traders who choose intermediaries more often trade more stocks, execute orders quicker, price orders more aggressively, and disperse their trading over longer periods of time. Although US stock intermediaries continue to lose market share, our results highlight the important role these firms can play in an increasingly automated, electronically driven marketplace.