scholarly journals Leakage of rank-dependent functionally generated trading strategies

2020 ◽  
Vol 16 (4) ◽  
pp. 573-591
Author(s):  
Kangjianan Xie

AbstractThis paper investigates the so-called leakage effect of trading strategies generated functionally from rank-dependent portfolio generating functions. This effect measures the loss in wealth of trading strategies due to renewing the portfolio constituent stocks. Theoretically, the leakage effect of a trading strategy is expressed explicitly by a finite-variation term. The computation of the leakage is different from what previous research has suggested. The method to estimate leakage in discrete time is then introduced with some practical considerations. An empirical example illustrates the leakage of the corresponding trading strategies under different constituent list sizes.

In this article, we introduce a new methodology to empirically identify the primary strategies used by a trader using only post-trade fill data. To do this, we apply a well-established statistical clustering technique called k-means to a sample of progress charts, representing the portion of the order completed by each point in the day as a measure of a trade’s aggressiveness. Our methodology identifies the primary strategies used by a trader and determines which strategy the trader used for each order in the sample. Having identified the strategy used for each order, trading cost analysis can be performed by strategy. We also discuss ways to exploit this technique to characterize trader behavior, assess trader performance, and suggest the appropriate benchmarks for each distinct trading strategy.


2019 ◽  
Vol 29 (1) ◽  
pp. 135-144
Author(s):  
James Kim ◽  
Mohan Chaudhry ◽  
Abdalla Mansur

This paper introduces a simplified solution to determine the asymptotic results for the renewal density. It also offers the asymptotic results for the first and second moments of the number of renewals for the discrete-time bulk-renewal process. The methodology adopted makes this study distinguishable compared to those previously published where the constant term in the second moment is generated. In similar studies published in the literature, the constant term is either missing or not clear how it was obtained. The problem was partially solved in the study by Chaudhry and Fisher where they provided a asymptotic results for the non-bulk renewal density and for both the first and second moments using the generating functions. The objective of this work is to extend their results to the bulk-renewal process in discrete-time, including some numerical results, give an elegant derivation of the asymptotic results and derive continuous-time results as a limit of the discrete-time results.


2009 ◽  
Vol 46 (04) ◽  
pp. 993-1004
Author(s):  
S. Ma ◽  
M. Molina

We introduce a class of discrete-time two-sex branching processes where the offspring probability distribution and the mating function are governed by an environmental process. It is assumed that the environmental process is formed by independent but not necessarily identically distributed random vectors. For such a class, we determine some relationships among the probability generating functions involved in the mathematical model and derive expressions for the main moments. Also, by considering different probabilistic approaches we establish several results concerning the extinction probability. A simulated example is presented as an illustration.


2019 ◽  
Vol 67 ◽  
pp. 06001 ◽  
Author(s):  
George Abuselidze ◽  
Olga Mohylevska ◽  
Nina Merezhko ◽  
Nadiia Reznik ◽  
Anna Slobodianyk

The article reveals the essence and features of the development of the stock market in Ukraine. It was established that the vigorous activity of countries in the world financial markets means that they also face a risk of global financial turmoil (the so-called “domino effect”). It is determined that the impact of global financial instability on the country depends on the openness of its economy that will lead to significant external “shocks”. The possibility of providing effective influence on domestic stock market activity with taking into account the changing world situation, development of perfect trading strategies for each participant is substantiated. The conducted analysis of the world market conditions of stock markets in recent years has made it possible to assess the real risks for new participants in the stock market and become the basis for the development of an appropriate effective trading strategy. The practical significance of the results is that they allow for a measurable approach to assessing the existing risk when choosing one or another trading strategy to move to the world stock market.


Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-20 ◽  
Author(s):  
Taewook Kim ◽  
Ha Young Kim

Many researchers have tried to optimize pairs trading as the numbers of opportunities for arbitrage profit have gradually decreased. Pairs trading is a market-neutral strategy; it profits if the given condition is satisfied within a given trading window, and if not, there is a risk of loss. In this study, we propose an optimized pairs-trading strategy using deep reinforcement learning—particularly with the deep Q-network—utilizing various trading and stop-loss boundaries. More specifically, if spreads hit trading thresholds and reverse to the mean, the agent receives a positive reward. However, if spreads hit stop-loss thresholds or fail to reverse to the mean after hitting the trading thresholds, the agent receives a negative reward. The agent is trained to select the optimum level of discretized trading and stop-loss boundaries given a spread to maximize the expected sum of discounted future profits. Pairs are selected from stocks on the S&P 500 Index using a cointegration test. We compared our proposed method with traditional pairs-trading strategies which use constant trading and stop-loss boundaries. We find that our proposed model is trained well and outperforms traditional pairs-trading strategies.


2015 ◽  
Vol 16 (3) ◽  
pp. 33-36
Author(s):  
Janet M. Angstadt ◽  
Michael T. Foley ◽  
Ross Pazzol ◽  
James D. Van De Graaff

Purpose – To analyze FINRA’s proposal that would require registration with FINRA of associated persons of FINRA-member firms who are primarily responsible for the design, development or significant modification of an algorithmic trading strategy. Design/methodology/approach – This article discusses the rationale and details of the proposed requirements. Findings – If adopted in its current form, the proposed rule-making, particularly when combined with the SEC’s proposed amendments to Rule 15b9-1 under the Securities and Exchange Act, would result in many various individuals who currently are not subject to a FINRA registration requirement, to pass a qualification examination and register. Originality/value – This article contains valuable information about important FINRA rule making activity.


2008 ◽  
Vol 22 (4) ◽  
pp. 557-585 ◽  
Author(s):  
Iddo Eliazar

The discrete-time G/GI/∞ queue model is explored. Jobs arrive to an infinite-server queuing system following an arbitrary input process X; job sizes are general independent and identically distributed random variables. The system's output process Y (of job departures) and queue process N (tracking the number of jobs present in the system) are analyzed. Various statistics of the stochastic maps X↦ Y and X↦ N are explicitly obtained, including means, variances, autocovariances, cross-covariances, and multidimensional probability generating functions. In the case of stationary inputs, we further compute the spectral densities of the stochastic maps, characterize the fixed points (in the L2 sense) of the input–output map, precisely determine when the output and queue processes display either short-ranged or long-ranged temporal dependencies, and prove a decomposition result regarding the intrinsic L2 structure of general stationary G/GI/∞ systems.


2020 ◽  
Vol 17 (2) ◽  
pp. 169-182
Author(s):  
Asheesh Pandey ◽  
Vandana Bhama ◽  
Amiya Kumar Mohapatra

The efficient market hypothesis states that in the efficient markets, participants cannot make extra-normal returns by exploiting any publicly available information. However, traders are constantly looking to exploit publicly available information to generate abnormal returns for themselves and their clients. One such event is share buyback announcement, which traders can utilize to create profitable trading strategies. The authors undertake the present study to examine if share buyback announcements provide profitable trading strategies to traders. Event study methodology has been adopted to analyze buyback announcements by Indian companies from January 2012 to December 2018. Forty-one (41) day window period comprising of 20 days pre-event, an announcement day, and 20 days post-event period is created to analyze the risk-adjusted average abnormal returns. The empirical findings suggest that there are negligible trading opportunities available for investors post announcements. However, significant risk-adjusted returns are found in the pre-event window, indicating that if investors can predict buyback announcements, they may earn extra-normal returns. The study confirms that Indian stock markets are in the semi-strong form of efficiency. The study also provides a profitable trading strategy for investors in the pre-event window. Finally, it also draws the regulators’ attention to see if insider trading could be the reason for abnormal returns in the pre-event window. The authors conclude the results by confirming that Indian markets are semi-strong in market efficiency and by indicating regulatory interventions to control insider trading. AcknowledgementThe infrastructural support provided by FORE School of Management, New Delhi in completing this paper is gratefully acknowledged.


2018 ◽  
Vol 5 (2) ◽  
pp. 175
Author(s):  
QiaoXu Qin ◽  
GengJian Zhou ◽  
WeiZhou Lin

The purpose of this paper is to establish a futures quantitative trading strategy based on the characteristics of capital flows in the futures market and the factors that influence the Futures rate of return. Firstly, PCA and logistic regression are used as the theoretical basis to analyze the characteristics of future futures with high turnover rate and futures yield in the future, and summarize the characteristics of rotation, continuity and similarity of the capital flow in the futures market. Then combining with the characteristics of the flow of futures funds and the idea of taking profit and stop loss, we establish the quantitative trading strategy of futures. Using the partial futures data from 2014-2015 for back testing, the strategy returns better and provides a new investment perspective for the futures market investors.


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