Friday, December 27, 2013

stoch Process^random Variable - not same thing

I feel a "random walk" and "random variable" are sometimes treated as interchangeable concepts. Watch out. Fundamentally different!

If a variable follows a stoch process (i.e. a type of random walk) then its Future [2] value at any Future time has a Probability  distribution. If this PD is normal, then mean and stdev will depend on (characteristics of) that process, but also depend on the  distance in time from the last Observation/revelation.

Let's look at those characteristics -- In many simple models, the drift/volatility of the Process are assumed unvarying[3]. I'm not familiar with the more complicated, real-world models, but suffice to say volatility of the Process is actually time-varying. It can even follow a stoch Process of its own.

Let's look at the last Observation -- an important point in the Process. Any uncertainty or randomness before that moment is  irrelevant. The last Observation (with a value and its timestamp) is basically the diffusion-start or the random-walk-start. Recall Polya's urn.

[2] Future is uncertain - probability. Statistics on the other hand is about past.
[3] and can be estimated using historical observations

Random walk isn't always symmetrical -- Suppose the random walk has an upward trend, then PD at a given future time won't be a nice  bell centered around the last observation. Now let's compare 2 important random walks -- Brownian Motion (BM) vs GBM.
F) BM - If the process is BM i.e. Wiener Process,
** then the variable at a future time has a Normal distribution, whose stdev is proportional to sqrt(t)
** Important scenario for theoretical study, but how useful is this model in practice? Not sure.
G) GBM - If the process is GBM,
** then the variable at a future time has a Lognormal distribution
** this model is extremely important in practice.

No comments:

Total Pageviews

my favorite topics (labels)

_fuxi (302) _misLabel (13) _orig? (3) _rm (2) _vague (2) clarified (58) cpp (39) cpp_const (22) cpp_real (76) cpp/java/c# (101) cppBig4 (54) cppSmartPtr (35) cppSTL (33) cppSTL_itr (27) cppSTL_real (26) cppTemplate (28) creditMkt (14) db (65) db_sybase (43) deepUnder (31) dotnet (20) ECN (27) econ/bank` (36) fin/sys_misc (43) finGreek (34) finReal (45) finRisk (30) finTechDesign (46) finTechMisc (32) finVol (66) FixedIncom (28) fMath (7) fMathOption (33) fMathStoch (67) forex (39) gr8IV_Q (46) GTD_skill (15) GUI_event (30) inMemDB (42) intuit_math (41) intuitFinance (57) javaMisc (68) javaServerSide (13) lambda/delegate (22) marketData (28) math (10) mathStat (55) memIssue (8) memMgmt (66) metaProgram` (6) OO_Design (84) original_content (749) polymorphic/vptr (40) productive (21) ptr/ref (48) py (28) reflect (8) script`/unix (82) socket/stream (39) subquery/join (30) subvert (13) swing/wpf (9) sysProgram` (16) thread (164) thread_CAS (15) thread_cpp (28) Thread* (22) timeSaver (80) transactional (23) tune (24) tuneDB (40) tuneLatency (30) z_ajax (9) z_algoDataStruct (41) z_arch (26) z_arch_job (27) z_automateTest (17) z_autoTrad` (19) z_bestPractice (39) z_bold (83) z_bondMath (35) z_book (18) z_boost (19) z_byRef^Val (32) z_c#GUI (43) z_c#misc (80) z_cast/convert (28) z_container (67) z_cStr/arr (39) z_Favorite* (8) z_FIX (15) z_forex (48) z_fwd_Deal (18) z_gz=job (33) z_gzBig20 (13) z_gzMgr (13) z_gzPain (20) z_gzThreat (19) z_hib (19) z_IDE (52) z_ikm (5) z_IR_misc (36) z_IRS (26) z_javaWeb (28) z_jdbc (10) z_jobFinTech (46) z_jobHunt (20) z_jobRealXp (10) z_jobStrength (15) z_jobUS^asia (27) z_letter (42) z_linq (10) z_memberHid` (11) z_MOM (54) z_nestedClass (5) z_oq (24) z_PCP (12) z_pearl (1) z_php (20) z_prodSupport (7) z_py (31) z_quant (14) z_regex (8) z_rv (38) z_skillist (48) z_slic`Problem (6) z_SOA (14) z_spring (25) z_src_code (8) z_swingMisc (50) z_swingTable (26) z_unpublish (2) z_VBA/Excel (8) z_windoz (17) z_wpfCommand (9)

About Me

New York (Time Square), NY, United States
http://www.linkedin.com/in/tanbin