Volatility of Boolean functions

نویسندگان

  • Johan Jonasson
  • Jeffrey E. Steif
چکیده

We study the volatility of the output of a Boolean function when the input bits undergo a natural dynamics. For n = 1, 2, . . ., let fn : {0, 1}mn → {0, 1} be a Boolean function and X(n)(t) = (X1(t), . . . , Xmn(t))t∈[0,∞) be a vector of i.i.d. stationary continuous time Markov chains on {0, 1} that jump from 0 to 1 with rate pn ∈ [0, 1] and from 1 to 0 with rate qn = 1−pn. Our object of study will be Cn which is the number of state changes of fn(X (n)(t)) as a function of t during [0, 1]. We say that the family {fn}n≥1 is volatile if Cn → ∞ in distribution as n → ∞ and say that {fn}n≥1 is tame if {Cn}n≥1 is tight. We study these concepts in and of themselves as well as investigate their relationship with the recent notions of noise sensitivity and noise stability. In addition, we study the question of lameness which means that P(Cn = 0)→ 1 as n→∞. Finally, we investigate these properties for a number of standard Boolean functions such as the majority function, iterated 3-majority, tribes, connectivity of the G(n, p) random graph and percolation on certain trees at various levels of the parameter pn. AMS Subject classification : 60K99

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

ON THE FUZZY SET THEORY AND AGGREGATION FUNCTIONS: HISTORY AND SOME RECENT ADVANCES

Several fuzzy connectives, including those proposed by Lotfi Zadeh, can be seen as linear extensions of the Boolean connectives from the scale ${0,1}$ into the scale $[0,1]$. We discuss these extensions, in particular, we focus on the dualities arising from the Boolean dualities. These dualities allow to transfer the results from some particular class of extended Boolean functions, e.g., from c...

متن کامل

Forecasting Crude Oil prices Volatility and Value at Risk: Single and Switching Regime GARCH Models

Forecasting crude oil price volatility is an important issues in risk management. The historical course of oil price volatility indicates the existence of a cluster pattern. Therefore, GARCH models are used to model and more accurately predict oil price fluctuations. The purpose of this study is to identify the best GARCH model with the best performance in different time horizons. To achieve th...

متن کامل

Modeling Gold Volatility: Realized GARCH Approach

F orecasting the volatility of a financial asset has wide implications in finance. Conditional variance extracted from the GARCH framework could be a suitable proxy of financial asset volatility. Option pricing, portfolio optimization, and risk management are examples of implications of conditional variance forecasting. One of the most recent methods of volatility forecasting is Real...

متن کامل

Comparing the performance of GARCH (p,q) models with different methods of estimation for forecasting crude oil market volatility

The use of GARCH models to characterize crude oil price volatility is widely observed in the empirical literature. In this paper the efficiency of six univariate GARCH models and two methods of estimation the parameters for forecasting oil price volatility are examined and the best method for forecasting crude oil price volatility of Brent market is determined. All the examined models in this p...

متن کامل

Effect of Nominal Exchange Rate Volatility on Output in Iran’s Economy

Volatility of exchange rate while changes from time to time, is expected to affect firm level operations as well as aggregate level outcomes i.e. macroeconomic performance. This paper, investigates the effects of exchange rate volatility on aggregate production in Iran using a Structural Vector Auto Regressive model with Exogenous Variables (SVARX). The model is estimated based on macroeconomic...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2015