Common-Stock Transaction Sequences and the Random-Walk Model

Simmons, Donald M.

doi:10.1287/opre.19.4.845

Cited by 10 publications

(4 citation statements)

References 5 publications

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“…There is also direct evidence from previous studies of systematic patterns in successive transactions (Working [25], Neiderhoffer and Osborne [13], Simmons [16], Garbade and Lieber [8]). This has been interpreted as reflecting *…”

Section: Hypothesesmentioning

confidence: 54%

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Continuous Versus Intermittent Trading on Auction Markets

Smidt¹

1979

The Journal of Financial and Quantitative Analysis

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Section: Hypothesesmentioning

confidence: 54%

“…Some or all of these transactions may represent movements from one side to the other of the spread when the spread is larger than 1/8. (Simmons [16].) The methodology we are "using does not easily permit identification of temporary variations in the spread.…”

Section: Analysis Of Transaction Datamentioning

confidence: 99%

Continuous Versus Intermittent Trading on Auction Markets

Smidt¹

1979

The Journal of Financial and Quantitative Analysis

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“…the us(' of random ualk thinking for such spwifiv purposes as the study of the aggrcgatc. tiyo-party votc in the USA (Stokes & Ivcrscn, I Y W ) , or the behavior of the stock market (Simmons, 1971), to m mtion only two cxamplrs. Rather it has put general implications arid questions of r(Lsearch strategy in thc center, and the discussion has thereforr bwn conductt.d on a somctvhat abstract lrvcl.…”

Section: Discussionmentioning

confidence: 99%

Random walk effects in behavioral data

Carlsson

1972

Syst. Res.

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IZtrnk of Sweden ?'el centenary Fund and Uni7,ersity o j StokholttlThis paper deals with random walk models and their possible application to psychological and sociological data. Such data may present a combination of apparent regularity and great difficulty of causal explanation. Random walk, implying the summation of individually small shocks or effects could account for both properties. A s a special case a binary structure consisting of two interacting entities, each also influenced by an exogenous factor, is considered and ways of looking a t the behavior of such systems suggested. Conventional techniques of analyzing variability rely heavily on stratification, e.g.. by social class, as a means of determining the effects of environment. This method often performs rather poorly, and the outcome is put in the same perspective, and related to different conceptions of environment. Finally, developmental data and developmental correlations are examined from the same point of view. Gy3 APPEARANCE OF ORDERm G E ASU +mall units alike often >how a L high degr ( b e of stability and therefore predictability in some behavior judged agaiiiit the variation observed among units. This i i trur iri psychological research when individual diffcwmces are itudied and fitted into dcvclopmcrital patterns, arid no less true in sociological research in so far a\ it dcah \\ ith aggregate bchavior and largescdc manifcdations of pcrsiitenw and change. Thw Durkheim (1952, 51) noting the distinctive, and criduririg character of suividc rates cwnrluded that tlicir i t ability (through timc) and variability (among units) slionc,d that they spring from a ''unified and definite" causal em, \$how prrniaiwtiw I T ould ot2icriviic bc incxplicablc.Hcw arc phmomeria that sccm natural targets for a psyrhologi5t or soc*iologist \\ ho has set his heart on systematic. thcory. Ytlt, cvery behavioral irirntiit i5 also a\rztrc of the limited degrccb of i u (~e s i that hah follo~vcd vc.nturcs into hard thcory. Why is there this strange combination of opaquciie+ with the appearance of la\\ fulness arid predic.tability? To give a cwmpletc a n s w r is clcarlj. beyond anvoric's reach but it is p o 4 b l c to invoke a i a partial explanation a qirnpl(1 t j pe of stochastic process, random \\ allr. \Iore specifically, this nil1 wrv(' two purpo5cs. The first is the usual one, to provide a (*ompart scheme into \\ hich observational data can be fitted. The serond is less eomrnoii and borders on a mctathcwrctical function. This i i to use the> itatistical liypothrsis as a gcncml assumption about tlic true structurr underlying thc class of phenomcna one is invchtigating, and t h m to aik what light cuhtomary resvarch mrthods I \ ill shed on the structure. It will be >howl that the random walk model fits some of the known facts in bcliavioral rcscarc*h reasonably well and explains fiiidirigs of apparrnt regularity arid also their stubborn r to cfforts at causal interpretation.Random w d k is a udl-knon n clemcwt in the thcory of probability and stochastic procchs...

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“…Nearly a century ago, Bachelier (see Cootner [6]) suggested that the first differences of the prices should be normally distributed with zero mean. Simmons [20] tested the model…”

Section: Model With Uncertain Capital Gainsmentioning

confidence: 99%

Optimal cash management under uncertainty

Bensoussan

Chutani

Sethi

2009

Operations Research Letters

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The problem of optimal investment in two types of assets over time is formulated as a stochastic optimal control problem. The two assets considered are a bank account and stock. The earnings derived from stock consist of dividends and capital gains. The randomness in the return on stock is modeled using a standard Brownian motion. Using a stochastic maximum principle, an explicit decision rule of the bang-bang type is derived for optimal management of cash.

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Common-Stock Transaction Sequences and the Random-Walk Model

Cited by 10 publications

References 5 publications

Continuous Versus Intermittent Trading on Auction Markets

Continuous Versus Intermittent Trading on Auction Markets

Random walk effects in behavioral data

Optimal cash management under uncertainty

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