Fractal modeling of volatility dynamics in financial time series (Copyright Reserved)

Econophysics is an interdisciplinary research field, applying theories and methods originally developed by physicists in order to solve problems in economics, usually those including uncertainty or stochastic elements and nonlinear dynamics [1,2]. Its application to the study of financial markets has also been termed statistical finance referring to its roots in statistical physics [3].

A financial market is a mechanism that allows people to easily buy and sell (trade) financial securities (such as stocks and bonds), commodities (such as precious metals or agricultural goods), and other fungible items of value at low transaction costs and at prices that reflect the efficient market hypothesis [4-6]. In finance, financial markets facilitate:
(i) raising of capital in the capital markets,
(ii) transfer of risk in the derivatives markets,
(iii) international trade in the currency markets.

Long-range dependence (LRD) in financial time series has been widely studied [10-13]. It has been argued that the LRD may well be due to the time-varying trend. LRD can be defined in terms of the decay rates of long-lag autocorrelation C(t)~t--H ,as t®¥ for 0<> 0: step fi upwards,
fi <>> sx (5)
respectively. Meanwhile, for the case of long-range dependence (LRD) processes, one observes
with 0 < γ < 1 (6)

(7)

The fractional Brownian motion (FBM), BH(t) is one of the simplest stochastic model that can be used to model financial stocks or any time series with long-range memory (LRD) [21]. FBM is a Gaussian process defined in moving average representation as [16]
(8)
with the self-similar Hurst exponent 0 < H < 1 and B( ) is the Brownian motion. A general notation for the multiplicative constants VH and K, where VH = Г(2H+1) sin(πH) is the normalizing factor such that E[(BH,K (1) – BH,K (0))2] = K2, with K is the scale factor. The process is said to be a standard FBM, BH (t) when K = 1 and has zero mean with covariance
(9)

In addition, FBM is H-self-similar that is {BH(t)} and {a -H BH(at)} are equivalent in their joint distribution for all real a and 0 < H < 1. The discrete version of the increment processes or the fractional Gaussian noise WH(t) ≡ BH(t+1) – BH(t) is a stationary Gaussian process with zero mean and covariance
(10)
and as the lag k®¥,
(11)
where H = ½ which is refer to the Brownian motion. In general, for ½ < H < 1, WH(t) is said to be LRD or persistent. Meanwhile for 0 < H < 1, WH(t) is said to indicate short-range dependence (SRD) or antipersistent. These are the three different correlation behaviors.

Multifractional Brownian motion (MBM) is the generalization of fractional Brownian motion with the constant Hurst exponent H changed to Hurst function H(t) [13]. Using the time varying Hurst exponent one can model the stylized effects in time series based on the variation in their sample path irregularities.

Problems in economy and finance have attracted the interest of statistical physicists all over the world. Statistical physics concepts such as stochastic dynamics, short- and long-range correlations, self-similarity and scaling permit an understanding of the global behavior of economic systems without first having to work out a detailed microscopic description of the same system. Fundamental problems pertain to the existence or not of long-, medium- or/and short-range power-law correlations in various economic systems, to the presence of financial cycles and on economic considerations, including economic policy. A method like the detrended fluctuation analysis (DFA) is recalled emphasizing its value in sorting out correlation ranges, thereby leading to predictability at short horizon [7-8]. A well-known financial analysis technique, the so-called moving average, is shown to raise questions to physicists about fractional Brownian motion (FBM) properties [8].
In order to probe the extent of universality in the dynamic of complex behavior in financial markets and to provide a basic and appropriate framework for emerging economies, we focus in the international trade (foreign exchange) time series of certain emerging economies in East Asia namely Malaysia, Singapore, Indonesia, Thailand, and South Korea by studying and analyses the dynamical properties in the foreign currency exchange, such as volatility, scaling behavior [9]. These time series are then modeled using fractional Brownian Motion (FBM), fractional Gaussian noise (FGN), fractionally integrated ARFIMA (0,d,0). The focus parameters (LRD parameters) are the price, returns, absolute returns and volatility [10].

[1] H.E. Stanley, R. Mantegna, An Introduction to Econophysics, Cambridge University Press, Cambridge (2000)
[2] Joseph McCauley, Dynamics of Markets, Econophysics and Finance, Cambridge University Press, Cambridge (2004)
[3] M. Ausloos, Statistical physics in foreign exchange currency and stock markets, Physica A285 (2000)
[4] T.E. Copeland and J.F. Weston, Financial Theory and Corporate Policy, Addison-Wesley, West Sussex (1988)
[5] Fama, Eugene, Efficient Capital Markets: A Review of Theory and Empirical Work, Journal of Finance 25: 383–417 (1970)
[6] Burton G. Malkiel, "efficient market hypothesis," The New Palgrave: A Dictionary of Economics, v. 2, pp. 120-23 (1987)
[7] Peng, C.K, et al, On the mosaic organization of DNA sequences, Physical Review, E49, 1685-1689 (1994)
[8] Bunde A. and Havlin S., Multifractal fluctuations in the dynamics of disordered systems, Physica A194, 288-297 (1993)
[9] H.E. Stanley, et al, Self-organized complexity in economics and finance, Boston University, PNAS vol.99, 2561-2565 (2002)
[10] Muniandy, S.V. & Uning, R., Characterization of exchange rate regimes based on scaling and correlation properties of volatility for ASEAN-5 countries. Physica A371, 585-598 (2006)
[11] Whitcher, B and Jensen, M.J., Wavelet estimation of a local long memory parameter, Geophysics 31, 94-103 (2000)
[12] Wang, Y., et al, Self-similarity index estimation via wavelets for locally self-similar processes, Journal of Statistical Planning and Inference, 99,91-110 (2001)
[13] Muniandy, S.V and Lim, S.C., Modeling of locally self-similar processes using multifractional Brownian motion of Riemann-Liouville type, Physical Review, E63, 046104-7 (2001)
[14] Bayraktar, et al, Estimating the fractal dimension of the S&P 500 index using wavelet analysis, International Journal of Theoretical and Applied Finance, 7(5), 615-643 (2004)
[15] Chan, Z, et al, Effect of nonstationarities on detrended fluctuation analysis, Physical Review E65, 041107-041122 (2002)
[16] S.V. Muniandy, M.F. Mak, W.A.T Wan Abdullah, Characterization of Foreign Exchange Regimes of East Asian Emerging Economies Using Time-Varying Scaling Exponents, Preprint (2008)
[17] Hurst, E, Long-term storage capacity of reservoirs, Transactions of American Society of Civil Engineers, 116, 770-808 (1951)
[18] Z.Ding, et al, A long memory property of stock market returns and a new model, J. Empirical Finance 1, 83-106 (1983)
[19] P.Grau-Carles, Empirical evidence of long-rang correlation in stock returns, Physica A 287, 396-404 (2000)
[20] R. Degennaro and R. Shrieves, Public information releases, private information arrival and volatility in the foreign exchange market, J. Empirical Finance 4, 295-315 (1997)
[21] Bianchi, S., Pathwise identification of the memory function of multi-fractional Brownian motion with application to finance, International Journal of Theoretical and Applied Finance, 8(2), 255-281 (2005)

DJ US Stocks Down As Financial Worries, Spike In Oil Weigh

NEW YORK (Dow Jones)--Another sell-off in the financial sector pushed U.S. stocks down Thursday as oil prices gained on a weakened dollar and tensions between the U.S. and Russia.
With more wild swings for shares of mortgage buyers Fannie and Freddie Thursday morning, investors are grappling with what the markets and economy may look like after a potential wipeout of their stock-market value.
Shares of Freddie recently gained 4% to $3.38, rebounding after hitting $2.26, their lowest mark of the crisis, earlier. Fannie Mae rose 7% to $4.72, up from its low of $3.53. The Wall Street Journal said the fate of the two, which own or guarantee about half of all U.S. home loans, hinges on whether they can repay bonds due at the end of September.
"The stock market appears to be discounting a doomsday scenario" for Freddie and Fannie, said Kevin Kruszenski, director of equity trading for KeyBanc Capital Markets. "I would say in terms of cost of credit in general, if you have a failure of this magnitude it's going to cause everyone to reprice risk."
Adding fuel to the fire, Citigroup lowered its fiscal third-quarter earnings estimates for Goldman Sachs, Lehman Brothers and Morgan Stanley due to asset write-downs, weaker client flows and a seasonal slowdown.
Despite the flurry of bad news, investors do not seem to be reacting like they have in the past, when indexes saw steep drops and the issues in the financial sector weighed more heavily across the broader market.
The Dow Jones Industrial Average fell 38 points, or 0.3%, to 11378. The broad Standard & Poor's 500 index declined 2.9 points to 1271, and the technology-oriented Nasdaq Composite dropped 17 points to 2371.
"The Fannie, Freddie news would have been a market disaster 60, 90 days ago, but now the market is taking it in stride and we're not free-falling. Volume has remained summer-like anemic," said Jim Paulsen, chief investment strategists at Well Capital Management. "I think the market would be making a much bigger move upwards if we didn't have the spike in oil."
On the New York Mercantile Exchange, crude oil futures shot $6.01, or 5.2%, higher to $121.57 a barrel, hitting a 17-day high, as the dollar weakened and relations between the U.S. and Russia deteriorated following Russia's conflict with Georgia.
The news weighed on consumer stocks as rising oil prices are seen to weigh on cash-strapped consumers' ability to spend.
Also at issue was data from the Labor Department indicating initial claims for jobless benefits fell 13,000 to a seasonally adjusted 432,000 in the week ended Aug. 16.
The four-week average of new claims, a figure used to smooth the effects of weekly volatility in the data, rose 7,250 to 445,750 from the previous week's revised average of 438,500. The new figure is the highest since December 2001 and above the 400,000 mark typically seen as recession territory.
A new unemployment insurance program may have given claims an upward bias for the last four weeks, said Zach Pandl, an economist at Lehman Brothers Holdings.
"The question remains if fundamental deterioration is happening underneath this bias, and we're just going to have to wait for the August payrolls report," Pandl said.
Whether the U.S. is in recession is an "academic question" at this point, the economist added, saying any recovery is likely "to be a drawn-out process."
Separately, The Wall Street Journal reported that the Federal Reserve investigated a rumor that Credit Suisse Group pulled a Lehman credit line. The newspaper said the Fed was told by the Swiss bank that the rumor was false. The Financial Times reported that a recent effort by Lehman to sell about half of the firm to overseas investors failed. Shares of Lehman, the smallest of the four major Wall Street brokers, fell 5.4% to $12.99. The Financial Select Sector SPDR, a basket of financial stocks, fell 1.7% to $20.
Markets overseas generally lost ground Thursday, with the Nikkei 225 falling 0.8% in Tokyo.

Newbie Analyser

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