Brownian model of financial markets

The Brownian motion models for financial markets are based on the work of Robert C. Merton and Paul A. Samuelson, as extensions to the one-period market models of Harold Markowitz and William F. Sharpe, and are concerned with defining the concepts of financial assets and markets, portfolios, gains and wealth in terms of continuous-time stochastic processes.

Under this model, these assets have continuous prices evolving continuously in time and are driven by Brownian motion processes.[1] This model requires an assumption of perfectly divisible assets and a frictionless market (i.e. that no transaction costs occur either for buying or selling). Another assumption is that asset prices have no jumps, that is there are no surprises in the market. This last assumption is removed in jump diffusion models.

Financial market processes

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Consider a financial market consisting of   financial assets, where one of these assets, called a bond or money market, is risk free while the remaining   assets, called stocks, are risky.

Definition

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A financial market is defined as   that satisfies the following:

  1. A probability space  .
  2. A time interval  .
  3. A  -dimensional Brownian process   where   adapted to the augmented filtration  .
  4. A measurable risk-free money market rate process  .
  5. A measurable mean rate of return process  .
  6. A measurable dividend rate of return process  .
  7. A measurable volatility process  , such that  .
  8. A measurable, finite variation, singularly continuous stochastic  .
  9. The initial conditions given by  .

The augmented filtration

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Let   be a probability space, and a   be D-dimensional Brownian motion stochastic process, with the natural filtration:

 

If   are the measure 0 (i.e. null under measure  ) subsets of  , then define the augmented filtration:

 

The difference between   and   is that the latter is both left-continuous, in the sense that:

 

and right-continuous, such that:

 

while the former is only left-continuous.[2]

Bond

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A share of a bond (money market) has price   at time   with  , is continuous,   adapted, and has finite variation. Because it has finite variation, it can be decomposed into an absolutely continuous part   and a singularly continuous part  , by Lebesgue's decomposition theorem. Define:

  and
 

resulting in the SDE:

 

which gives:

 

Thus, it can be easily seen that if   is absolutely continuous (i.e.  ), then the price of the bond evolves like the value of a risk-free savings account with instantaneous interest rate  , which is random, time-dependent and   measurable.

Stocks

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Stock prices are modeled as being similar to that of bonds, except with a randomly fluctuating component (called its volatility). As a premium for the risk originating from these random fluctuations, the mean rate of return of a stock is higher than that of a bond.

Let   be the strictly positive prices per share of the   stocks, which are continuous stochastic processes satisfying:

 

Here,   gives the volatility of the  -th stock, while   is its mean rate of return.

In order for an arbitrage-free pricing scenario,   must be as defined above. The solution to this is:

 

and the discounted stock prices are:

 

Note that the contribution due to the discontinuities in the bond price   does not appear in this equation.

Dividend rate

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Each stock may have an associated dividend rate process   giving the rate of dividend payment per unit price of the stock at time  . Accounting for this in the model, gives the yield process  :

 

Portfolio and gain processes

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Definition

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Consider a financial market  .

A portfolio process   for this market is an   measurable,   valued process such that:

 , almost surely,
 , almost surely, and
 , almost surely.

The gains process for this portfolio is:

 

We say that the portfolio is self-financed if:

 .

It turns out that for a self-financed portfolio, the appropriate value of   is determined from   and therefore sometimes   is referred to as the portfolio process. Also,   implies borrowing money from the money-market, while   implies taking a short position on the stock.

The term   in the SDE of   is the risk premium process, and it is the compensation received in return for investing in the  -th stock.

Motivation

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Consider time intervals  , and let   be the number of shares of asset  , held in a portfolio during time interval at time  . To avoid the case of insider trading (i.e. foreknowledge of the future), it is required that   is   measurable.

Therefore, the incremental gains at each trading interval from such a portfolio is:

 
 

and   is the total gain over time  , while the total value of the portfolio is  .

Define  , let the time partition go to zero, and substitute for   as defined earlier, to get the corresponding SDE for the gains process. Here   denotes the dollar amount invested in asset   at time  , not the number of shares held.

Income and wealth processes

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Definition

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Given a financial market  , then a cumulative income process   is a semimartingale and represents the income accumulated over time  , due to sources other than the investments in the   assets of the financial market.

A wealth process   is then defined as:

 

and represents the total wealth of an investor at time  . The portfolio is said to be  -financed if:

 

The corresponding SDE for the wealth process, through appropriate substitutions, becomes:

 .

Note, that again in this case, the value of   can be determined from  .

Viable markets

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The standard theory of mathematical finance is restricted to viable financial markets, i.e. those in which there are no opportunities for arbitrage. If such opportunities exists, it implies the possibility of making an arbitrarily large risk-free profit.

Definition

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In a financial market  , a self-financed portfolio process   is considered to be an arbitrage opportunity if the associated gains process  , almost surely and   strictly. A market   in which no such portfolio exists is said to be viable.

Implications

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In a viable market  , there exists a   adapted process   such that for almost every  :

 .

This   is called the market price of risk and relates the premium for the  -the stock with its volatility  .

Conversely, if there exists a D-dimensional process   such that it satisfies the above requirement, and:

 
 ,

then the market is viable.

Also, a viable market   can have only one money-market (bond) and hence only one risk-free rate. Therefore, if the  -th stock entails no risk (i.e.  ) and pays no dividend (i.e. ), then its rate of return is equal to the money market rate (i.e.  ) and its price tracks that of the bond (i.e.  ).

Standard financial market

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Definition

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A financial market   is said to be standard if:

(i) It is viable.
(ii) The number of stocks   is not greater than the dimension   of the underlying Brownian motion process  .
(iii) The market price of risk process   satisfies:
 , almost surely.
(iv) The positive process   is a martingale.

Comments

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In case the number of stocks   is greater than the dimension  , in violation of point (ii), from linear algebra, it can be seen that there are   stocks whose volatilities (given by the vector  ) are linear combination of the volatilities of   other stocks (because the rank of   is  ). Therefore, the   stocks can be replaced by   equivalent mutual funds.

The standard martingale measure   on   for the standard market, is defined as:

 .

Note that   and   are absolutely continuous with respect to each other, i.e. they are equivalent. Also, according to Girsanov's theorem,

 ,

is a  -dimensional Brownian motion process on the filtration   with respect to  .

Complete financial markets

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A complete financial market is one that allows effective hedging of the risk inherent in any investment strategy.

Definition

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Let   be a standard financial market, and   be an  -measurable random variable, such that:

 .
 ,

The market   is said to be complete if every such   is financeable, i.e. if there is an  -financed portfolio process  , such that its associated wealth process   satisfies

 , almost surely.

Motivation

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If a particular investment strategy calls for a payment   at time  , the amount of which is unknown at time  , then a conservative strategy would be to set aside an amount   in order to cover the payment. However, in a complete market it is possible to set aside less capital (viz.  ) and invest it so that at time   it has grown to match the size of  .

Corollary

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A standard financial market   is complete if and only if  , and the   volatility process   is non-singular for almost every  , with respect to the Lebesgue measure.

See also

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Notes

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  1. ^ Tsekov, Roumen (2013). "Brownian Markets". Chin. Phys. Lett. 30 (8): 088901. arXiv:1010.2061. Bibcode:2013ChPhL..30h8901T. doi:10.1088/0256-307X/30/8/088901. S2CID 18675919.
  2. ^ Karatzas, Ioannis; Shreve, Steven E. (1991). Brownian motion and stochastic calculus. New York: Springer-Verlag. ISBN 0-387-97655-8.

References

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Karatzas, Ioannis; Shreve, Steven E. (1998). Methods of mathematical finance. New York: Springer. ISBN 0-387-94839-2.

Korn, Ralf; Korn, Elke (2001). Option pricing and portfolio optimization: modern methods of financial mathematics. Providence, R.I.: American Mathematical Society. ISBN 0-8218-2123-7.

Merton, R. C. (1 August 1969). "Lifetime Portfolio Selection under Uncertainty: the Continuous-Time Case" (PDF). The Review of Economics and Statistics. 51 (3): 247–257. doi:10.2307/1926560. ISSN 0034-6535. JSTOR 1926560. S2CID 8863885. Archived from the original (PDF) on 12 November 2019.

Merton, R.C. (1970). "Optimum consumption and portfolio rules in a continuous-time model". Journal of Economic Theory. 3 (4): 373–413. doi:10.1016/0022-0531(71)90038-x. hdl:1721.1/63980.