Theoretical and empirical analysis of trading activity

被引:1
|
作者
Pohl, Mathias [1 ]
Ristig, Alexander [1 ,2 ]
Schachermayer, Walter [2 ]
Tangpi, Ludovic [3 ]
机构
[1] Univ Vienna, Fac Business Econ & Stat, Oskar Morgenstern Pl 1, A-1090 Vienna, Austria
[2] Univ Vienna, Fac Math, Oskar Morgenstern Pl 1, A-1090 Vienna, Austria
[3] Princeton Univ, Dept Operat Res & Financial Engn, Sherrerd Hall 203, Princeton, NJ 08544 USA
基金
奥地利科学基金会;
关键词
91G80; PRICE CHANGES; VOLUME; VOLATILITY; MODEL; MIXTURE; IMPACT; NOISE; FLOW;
D O I
10.1007/s10107-018-1341-x
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Understanding the structure of financial markets deals with suitably determining the functional relation between financial variables. In this respect, important variables are the trading activity, defined here as the number of tradesN, the traded volumeV, the asset priceP, the squared volatility sigma 2 the bid-ask spreadSand the cost of tradingC. Different reasonings result in simple proportionality relations ("scaling laws") between these variables. A basic proportionality is established between the trading activity and the squared volatility, i.e.,N similar to sigma 2 More sophisticated relations are the so called 3/2-lawN3/2 similar to sigma PV/Cand the intriguing scalingN similar to(sigma P/S)2 We prove that these "scaling laws" are the only possible relations for considered sets of variables by means of a well-known argument from physics: dimensional analysis. Moreover, we provide empirical evidence based on data from the NASDAQ stock exchange showing that the sophisticated relations hold with a certain degree of universality. Finally, we discuss the time scaling of the volatility sigma which turns out to be more subtle than one might naively expect.
引用
收藏
页码:405 / 434
页数:30
相关论文
共 50 条
  • [1] Theoretical and empirical analysis of trading activity
    Mathias Pohl
    Alexander Ristig
    Walter Schachermayer
    Ludovic Tangpi
    Mathematical Programming, 2020, 181 : 405 - 434
  • [2] Adverse selection costs, trading activity and price discovery in the NYSE: An empirical analysis
    Pascual, R
    Escribano, A
    Tapia, M
    JOURNAL OF BANKING & FINANCE, 2004, 28 (01) : 107 - 128
  • [3] An empirical analysis of NYSE specialist trading
    Madhavan, A
    Sofianos, G
    JOURNAL OF FINANCIAL ECONOMICS, 1998, 48 (02) : 189 - 210
  • [4] The impact of informed trading on dividend signaling: a theoretical and empirical examination
    Fuller, KP
    JOURNAL OF CORPORATE FINANCE, 2003, 9 (04) : 385 - 407
  • [5] Applying Routine Activity Theory to Cybercrime: A Theoretical and Empirical Analysis
    Leukfeldt, Eric Rutger
    Yar, Majid
    DEVIANT BEHAVIOR, 2016, 37 (03) : 263 - 280
  • [6] An empirical examination of information, differences of opinion, and trading activity
    Bessembinder, H
    Chan, K
    Seguin, PJ
    JOURNAL OF FINANCIAL ECONOMICS, 1996, 40 (01) : 105 - 134
  • [7] Investors' trading activity: A behavioural perspective and empirical results
    Kourtidis, Dimitrios
    Sevic, Zeljko
    Chatzoglou, Prodromos
    JOURNAL OF SOCIO-ECONOMICS, 2011, 40 (05): : 548 - 557
  • [8] The impact of the carbon trading market on corporate employment: Theoretical and empirical evidence
    Wang, Xing
    Li, Pengyu
    Yuan, Yangguang
    Zhang, Qianxiang
    ENERGY, 2025, 320
  • [9] Algorithmic Trading Using Markov Chains: Comparing Empirical and Theoretical Yields
    Svoboda, Milan
    Rihova, Pavla
    EUROPEAN FINANCIAL SYSTEM 2016: PROCEEDINGS OF THE 13TH INTERNATIONAL SCIENTIFIC CONFERENCE, 2016, : 787 - 793
  • [10] An empirical analysis of corporate insiders' trading performance
    Lei, Qin
    Rajan, Murli
    Wang, Xuewu
    CHINA FINANCE REVIEW INTERNATIONAL, 2012, 2 (03) : 246 - 264