Sayenzi yeAlgo Kutengeserana: Mhando, Marobhoti Anoshanda uye Matanho 2025

Upfumi hwemazuva ano hahufungidziki pasina kuchinjana uye misika yemari. Kutengeserana panzvimbo idzi kunonzi
kutengeserana . Vatengesi vanoshingairira kushandisa mikana yekombuta tekinoroji kufambisa maitiro ebhizinesi ravo. Kutengeserana uchishandisa masvomhu modhi uye tekinoroji yekombuta inonzi algorithmic trading. Ichi chinyorwa chinotaura nezverudzi urwu rwekutengesa mumisika yemari, marudzi ayo, nzira dzinoshandiswa, zvakanakira nekuipira, software inoshandiswa.

Chii chinonzi algorithmic kutengeserana (algorithmic yekutengesa)

Izwi rekuti “algorithmic trading” kana “algorithmic trading” rine zvirevo zviviri. Muchiitiko chekutanga, izwi iri rinoreva nzira yekuita hurongwa hwakakura pamusika, maererano neinovhurwa zvishoma nezvishoma maererano nemimwe mitemo uye inoparadzaniswa nekazhinji zvidimbu zviduku, izvo zvine mutengo wavo uye huwandu. Odha yega yega inotumirwa kumusika kuti iitwe. Chinangwa che tekinoroji ndechekuita kuti zvive nyore kune vatengesi kuita kutengeserana kukuru kunoda kuitwa nenzira isingaonekwe. Semuenzaniso, unofanirwa kutenga 200,000 shares, uye chinzvimbo chega chega chinosanganisira zvikamu zvina panguva.
Chirevo chechipiri chezwi iri isystem inovhura maodha zvinoenderana neakapihwa algorithm pasina kutora chikamu kwemutengesi. Algorithms akaiswa kuitira kuti awane purofiti kubva otomatiki musika kuongororwa. Aya masisitimu anonzi zvakare ”
kutengesa marobhoti “. Algorithmic kutengeserana uye algorithmic kutengeserana inoshandiswa pakutsinhana, kusanganisira cryptocurrency kuchinjanisa, uye Forex.

Chii chinonzi algorithmic kutengeserana?

Kutengeserana kweAlgo kunosanganisira kuunganidza dhata pane chaiyo asset zvichibva munhoroondo yekuvandudzwa kwayo, kusarudza maalgorithms ekutengeserana uye marobhoti akakodzera ekutengesa. Kuti uone mutengo, dzidziso yemukana inoshandiswa, kukanganisa kwemusika uye mukana wekudzoka kwavo zvakare mune ramangwana zvakatemwa. Kune marudzi matatu ekusarudza. Nemaitiro ekunyora, nyanzvi inoshandisa masvomhu mafomula uye mhando dzemuviri. Iyo genetic maitiro inosanganisira kugadzirwa kwemitemo nemacomputer masisitimu uye nehungwaru hwekugadzira. Otomatiki inogadzirwa nechirongwa chekombuta chakasarudzika chinogadzirisa mitsara yemitemo uye inoiedza.

Ndeapi marudzi ealgorithmic kutengeserana aripo?

Algorithmic kutengeserana inoitwa munzvimbo dzakati wandei:

1. Technical Analysis . Kushandisa kusashanda kwemusika uye kuona maitiro azvino kuburikidza nekirasi yemasvomhu uye kuongorora kwemuviri.
2. Kugadzira musika . Iyi nzira inochengetedza musika liquidity. Vagadziri vemisika vanopihwa mubairo nekutsinhana nekugutsa zvinodiwa, kusanganisira purofiti. Iyo nzira yakavakirwa pa accounting uye nekukurumidza kuyerera kweruzivo kubva kumisika.
3. Kumhanya mberi . Ongororo yehuwandu hwemirairo nechiridzwa uye kusarudzwa kweiyo yakakura kwazvo. Iri zano rinobva pane chokwadi chekuti kurongeka kukuru kuchave nemutengo wakakura uye kukwezva akawanda counter mirairo. Algorithms inoongorora tepi uye kurongeka kwebhuku data uye edza kugadzirisa mafambiro panguva yekutengeserana kukuru nekukurumidza kupfuura vamwe vatori vechikamu.
4. Vaviri uye Basket Trading . Zviridzwa zviviri kana kupfuura zvakabatanidzwa nepamusoro, asi kwete imwe-kune-imwe, kuwirirana. Kutsauka kweimwe yezviridzwa kubva pane yakapiwa kunoreva kuti inowanzodzokera kuboka rayo. Kusarudza kuwirirana kunobatsira kuita kutengeserana kunobatsira.
5. Arbitration . Iyo nzira yakavakirwa pakuenzanisa midziyo ine yakafanana mutengo dynamics. Kufanana uku dzimwe nguva kunotyorwa nekuda kwezvikonzero zvakasiyana. Izvo zvakakosha zve arbitrage kutengeswa kwezvinhu zvinodhura uye kutenga imwe yakachipa. Nekuda kweizvozvo, iyo midziyo ichaenzana mumutengo, uye iyo yakachipa asset ichawedzera mumutengo. Algorithmic yekutengesa masisitimu inoona shanduko yemutengo mumusika uye kuita purofiti arbitrage zvibvumirano.
6. Volatility trading . Mhando yakaoma yekutengesa, iyo inosanganisira kutenga zvakasiyana-siyana zvingasarudzwa. Mutengesi anotarisira kuti kusagadzikana kwemari kunowedzera pakutengesa uye kuderera pakutenga. Iyi mhando yekutengeserana inoda yakakosha midziyo kugona uye nyanzvi dzinokwanisa.

Maitiro ekushanda mualgorithmic kutengeserana, chokwadi chese nezve marobhoti kutengesa: https://youtu.be/eg3s0c_X_ao

Rini uye sei algorithmic kutengeserana kuoneka, sechiitiko

Kutengeserana kwealgorithmic kwakagadzirwa mukutanga kwema1970 nekusikwa kweNASDAQ, yekutanga kuchinjana kushandisa komputa yekutengesa. Mumazuva iwayo, kutengeserana kwealgorithmic kwaingowanikwa kune vatengesi vakuru, vanhuwo zvavo vaisawana tekinoroji yakadaro. Makomputa aive asina kukwana ipapo, uye muna 1987 pakanga paine chikanganiso chehardware chakakonzera kudonha kwemusika weAmerica. Muna 1998, iyo SEC – iyo US Securities Commission yakabvumira zviri pamutemo kushandiswa kwemagetsi ekutengesa mapuratifomu. Gore rino rinofanira kutariswa zuva rekuonekwa kwealgorithmic kutengeserana mune yazvino fomu. Mukutanga kwe2000s, kutengeserana uchishandisa makomputa kwakaitwa mumasekonzi mashoma. Asi mugove wemabhobhoti mumusika waiva pasi pe90%. Pakazosvika 2009, mirairo yekutsinhana yakapedzwa mumamilliseconds, uye
marobhoti ekutengesa akaita 60% yekutengeserana. Pashure pa2012, mamiriro ezvinhu achinja. Kusafungira kwemusika kwakakonzera kukundikana mune yaivepo software. Chikamu chekutengesa chinoitwa otomatiki chakaderedzwa kusvika pa50% yehuwandu. Kuti udzivise zvikanganiso, kuvandudza uye kushandiswa kwehungwaru hwekugadzira kwatanga.

Ko algorithmic yekutengesa yakasiyana sei nealgorithmic yekutengesa?

Pasinei nekufanana kuri pachena kwemazano, munhu anofanira kusiyanisa pakati pepfungwa dze “algorithmic trading” uye “algorithmic trading”. Muchiitiko chekutanga, nzira yekuita hurongwa hwakakura nekuipatsanura kuita zvikamu uye wozoiisa zvinoenderana nemimwe mitemo inoreva, uye mune yechipiri, ivo vanotaura nezve automated system inogadzira mirairo pasina mutengesi maererano neimwe nzira. algorithm. Algorithms in algorithmic trading inoshandiswa kurerutsa kuitwa kwekutengesa kukuru nemutengesi. Mune algorithmic kutengeserana, ivo vanoshandiswa kuongorora musika uye kuvhura zvinzvimbo kuwedzera mari.

Ndeipi software inokodzera algorithmic kutengeserana?

Sezvo algorithmic kutengeserana inosanganisira kushandiswa kwekombuta tekinoroji, iwe unofanirwa kusarudza iyo chaiyo software. Robhoti rekutengesa ndicho chishandiso chikuru chekudzidzira otomatiki kutengeserana. Unogona kuzvigadzira iwe pachako uchishandisa
programming mitauro , kana kushandisa puratifomu kuigadzira.

Chii chinofanira kuyeukwa usati waita algorithmic kutengeserana?

Kutanga, zvakakodzera kutaura kuti algo trader inofanirwa kukwanisa kuronga, nekuti akawanda mapuratifomu anogona kugonekwa nekugona hunyanzvi uhu. Mutauro wechirongwa unoshandiswa pakutengesa algorithmic unofanirwa kuenderana nemapuratifomu ese uye algorithms ari kugadzirwa. Mutauro wakakodzera kwazvo wechirongwa ndiC # (C-inopinza). Inoshandiswa mumapuratifomu akadai seTSLab, StockSharp, WealthLab. Pasina kuziva mutauro wechirongwa, mapurogiramu maviri ekupedzisira anozofanirwa kudzidziswa kwemwedzi yakati wandei.

TSLab ndeimwe yeanonyanya kufarirwa zvirongwa zvekumhanyisa algorithmbots.

Chikuva chekugadzira, kuyedza uye kutanga
kutengesa marobhoti uye masisitimu. Inosanganisira yakanakira yekuona mupepeti muchimiro che cubes, izvo zvinokutendera iwe kugadzira robhoti usingazive mutauro wechirongwa. Iwe unogona kuunganidza yaunoda kutengesa algorithm kubva kuma cubes. Nhoroondo yezviridzwa zvekutengesa zvakaunganidzwa nechirongwa zvinokutendera kuti uwane nekugadzirisa zvikanganiso muzvinyorwa, nepo tekinoroji yekuongorora maturusi achakubatsira iwe kugadzira yakasarudzika mhinduro.

Installation

Kuti uise chikuva, iwe unofanirwa kurodha iyo installer kubva kune yepamutemo webhusaiti. Peji yekurodha inotaura kuti chirongwa chinongoshanda pa64-bit shanduro dzeWindows. Mushure mekurodha, vhura iyo yekuisa faira. Usati waisa, zvichakuita kuti uise shanduro yezvino ye.NET Framework uye Visual C ++ Redistributable Studio.

Kana mavhezheni anodiwa ezvirongwa izvi asipo, iwe unofanirwa kuaisa. Chikuva hachizoshanda pasina ivo. Kana shanduro dzichangoburwa dzezvirongwa izvi dziripo, hwindo rekutanga remuisiri rinovhurika. Tinya “Next”.
Isu tinobvumirana nemitemo yechibvumirano cherezinesi uye tinosarudza nzira iyo chirongwa chichaiswa.

Ipapo iwe unofanirwa kupa mvumo yekuisa uye kumirira kuti ipedze.
Kana kuiswa kwapera, hwindo rinoenderana richavhurwa. Unogona kumhanyisa chirongwa mushure mekuisa.

Kudzidziswa mune algorithmic kutengeserana paTSLab

Supplier setup

Kumisikidza uye kuyedza robhoti rekutengesa, unofanirwa kuve nenhoroondo yemakotesheni. Kuti uwane nhoroondo yemakotesheni, unofanirwa kuseta data provider. Mu “Data” menyu, sarudza chinhu che “Suppliers”.
Tabhu yevatengesi isina chinhu ichavhura. Tinofanira kudzvanya “Add” bhatani. Mubhokisi rebhokisi rinovhura, sarudza “Historical Data”. Panguva ino, iwe unofanirwa kusarudza rudzi rwe data kune makotesheni. Muchiitiko ichi, faira remavara rine makotesheni ane mutengo nhanho ye0.01 inosarudzwa. Dhawunirodha faira rinodiwa kubva kune repository.

Dhaunirodha faira 1.rand.quote.step=0.01_1m.txt.zip. Kana wangodhawunirodha, tsvaga iyo faira mudhawunirodha folda uye woibvisa kubva mudura. Isu tinodzokera kuTSLab uye sarudza chinhu che “Suppliers” mu “Data” menyu.
Iwindo rinoenderana richavhurwa. Iwe unofanirwa kudzvanya bhatani re “Add”.
Window yeAdd Supplier ichavhurwa. Mariri, sarudza chinhu “Historical data”, uye ipapo tinya “Next”.
Muhwindo rinotevera, tsanangura zita uye data rudzi rwemupi. Isa zita racho kuTextData uye rudzi rwe data kuText Files. Isu tinodzvanya “Next”.
Sarudza nzira kune mutengesi. Iyo yakasarudzika nzira ndeye C:ProgramDataTSLabTSLab 2.1ProvidersText. Iwe unogona kudoma imwe nzira nekudzvanya … mubhara renzira. Isu tinogadzirisa nzira yefaira yedu, mushure mezvo tinogadzirisa zvigadziro: 1. Nhamba yenzvimbo dzechisimari ndeye 2. 2. Nhanho yemutengo inotarirwa pakarepo kana iri pasi pe 1. Faira ine nhanho ye0.01 uye inotsanangura 1. saina muzvirongwa zvichasarudza nhanho ye0.1 Dzvanya
kubhatani re “Next”. Muwindo reVanopa, iyo TextData data provider ichaonekwa.

Kugadzira script

Iyo TSLab papuratifomu inobvumidza iwe kuvandudza kutengesa algorithms, kuyedza uye kugadzira marobhoti ekutengesa – vamiririri. Asi usati wagadzira algorithm yekutengesa, unofanirwa kunyora script kwayo. Kuti uite izvi, sarudza “Lab” mumenyu. Sarudza “Scripts” kubva pane yekudonhedza pasi.
Bhokisi rebhokisi richazarura, umo tinodzvanya “Gadzira Nyowani”. Muhwindo rechipiri, isa zita rezvinyorwa uye tinya “OK”.
Tinya kaviri bhatani rekuruboshwe pane chinyorwa chagadzirwa kuti ugadzirise. Tichaona mupepeti wekuona script.

Iyo yebhuruu rectangular block ndiyo “chimbo chinotengeswa”. Grey rectangle “Volume 1” – nhamba yekushanda nesarudzo kana zvibvumirano zveramangwana kune imwe nguva yenguva. Kuvhara “Kuvhara” kunoratidza mutengo wekuvhara webhari. Iyo “Graph panel” block inogadzira iyo inoenderana pani.
Tinya kurudyi. Sarudza “Properties” kubva pane yekudonha-pasi menyu. Sarudza iyo Script tab.
Dzima “Shandisa date kubva”. Sarudza iyo “Source” tab, uye mairi – chishandiso. Dzvanya pandima iyi. Iwindo re “Sarudza securities” richazarura, umo iwe uchada kusarudza TextData data provider uye tsanangura chiridzwa – zvinyorwa zvemashoko efaira 1.rand.quote.step=0.01_1m. Dzvanya “OK” kuti usimbise.

Mushure mekusarudza chishandiso, tebhu ine mufananidzo wechati uye kunyorwa “Kurodha” kuchaonekwa kumusoro kwehwindo. Mushure mekugadzirisa data, zita rechiridzwa chakasarudzwa richaonekwa pane iyi tab – 1.rand.quote.step=0.01_1m

Dzvanya “Chengetedza uye uite” mushure mekuisa data.
Ichi chinyorwa chakagadzirirwa kuratidza chiridzwa chiri pachati. Pakupedzisira, tabhu yegirafu ichavhura. Kutengeserana algorithms uye vatengesi vekutengesa vanomisikidzwa nenzira yakafanana. Sezvauri kuona, algorithmic kutengeserana nerubatsiro rweTSLab inowanikwa kune anenge munhu wese uye haidi kudzidziswa kwekutanga. Mukana mukuru weTSLab nderekuti chero mushandisi anogona kutanga kuunganidza marobhoti ekutengesa mushure memazuva 2-3 ekudzidza papuratifomu. Izvi zvinofambiswa nemupepeti wekuona. Nerubatsiro rwemupepeti, iwe unozodzidza kufunga kunodiwa kunodiwa mualgorithmic yekutengesa. TSLab inotsigira mutauro weC #, kuwedzera hurongwa papuratifomu iyi inogona kuenderera mberi uchishandisa TSLab API. Nekudaro, kuwedzera kunyudzwa mune algorithmic kutengeserana zviri nani kuenderera mberi nezvirongwa zvakaomarara.

stocksharp

Stocksharp iraibhurari yekutengesa marobhoti yakanyorwa muC #. Marobhoti ekutengesa anounganidzwa munzvimbo yeVisual Studio programming. Naizvozvo, usati wanyora robhoti uchishandisa sosi iyi, iwe uchafanirwa kupedza kanenge mwedzi mitanhatu uchidzidza mutauro wechirongwa. Havasi vese vanokwanisa kupedza chidzidzo kusvika kumagumo. Zvisinei, kushandiswa kwepuratifomu iyi kunoruramiswa zvizere mukuita.

WealthLab

WealthLab imwe puratifomu yekuyedza nekugadzira marobhoti ekutengesa uye masisitimu kubva kuFidelity. Kune mavhezheni maviri echirongwa: Pro yevagari vemuUS vane Fidelity account, uye Mugadziri wevamwe vese. WealthLab inokutendera iwe kushandisa tekinoroji yekuongorora maturusi mukuvandudza marobhoti, gamuchira masaini ekupinda nekuvhara chibvumirano uye woaendesa kune terminal. Kana mutengesi asingazivi kuronga, anogona kushandisa mubatsiri (wizard). Ipuratifomu yakavakirwa paC # uye Pascal programming mitauro. Iyi puratifomu inodhirowa machati muchimiro chezvikamu, zvigadziko zvemwenje zveJapan, machati emitsetse, nezvimwe.
Basa guru rechirongwa ndechekugadzirisa uye kuongororwa kwemaitiro anobva pane zvakaitika kare. WealthLab inogona kudzidzwa kwete nekukurumidza seTSLab, asi mumwedzi miviri chete. Iyo yakavakirwa-mukati programming mutauro inopa mikana mikuru mukugadzira purofiti nzira dzekutengesa. Mutengesi anogona kubatanidza chikuva neQuik software package, iyo inobvumira kuisa maodha kunze kwenyika.

Ndeapi marongero anoshandiswa kune algorithmic kutengeserana?

Pakutengesa uchishandisa algorithms kuunza zvinobatika mhedzisiro, iwe unofanirwa kunamatira kune zano rakagadzirirwa mamiriro chaiwo.

1. Kufungidzira Strategy . Inonangana nekuwana iyo yakanyanya kunaka mutengo wekupinda mukutengesa kune inotevera purofiti. Inoshandiswa zvakanyanya nevatengesi vega.
2. data mining . Kutsvaga mapatani matsva ealgorithms matsva. Yakawanda yedata inounganidzwa pane iyi zano risati raedzwa. Ruzivo runotsvakwa nemaitiro emaoko.
3. TWAP ndiyo yenguva-yakayerwa avhareji mutengo. Kuvhura maodha mukati menguva dzakaenzana pamutengo wakanakisa uye mutengo wekupa.
4. VWAP – vhoriyamu-yakayerwa avhareji mutengo. Kuvhura nzvimbo muzvikamu zvakaenzana nevhoriyamu yakafanana kune imwe nguva uye mitengo isingakwiri kupfuura avhareji kukosha.
5. Execution strategy . Nzira inoshandiswa kuwana asset nemutengo wakayerwa weavhareji muhukuru hukuru. Inonyanya kushandiswa nemabroker uye hedge funds.

Maitiro ekudzivirira kurasikirwa kana uchiita algorithmic kutengeserana, njodzi manejimendi

Iko kukanganisa kukuru kutenda kuti algorithmic mutengesi anongoda kugadzira robhoti rekutengesa. Njodzi dzose dzinofanira kudzivirirwa uye kubviswa. Kukanganisa kwemagetsi, kubatana kweInternet uye kukanganisa mukuverenga uye kuronga kunogona kutungamirira mukurasikirwa kukuru uye kukunyima zvachose mari.
Iyo algorithmic yekutengesa zano inogadzirwa sei[/ Caption] Sevha yezvivakwa uko algorithmic kutengeserana inoitwa inogona kungoerekana yatadza kana sisitimu yekushandisa inogona kutangazve pairi. Kuti ubvise matambudziko nesevha, unogona kuhaya sevha kana kusimudza yako. Kana izvi zvisipo, iwe unofanirwa kutora sevha kubva kune yakagadzikana mupi ane hukama hwakanaka. Iyo sisitimu inofanirwa kuve neiyo shoma simba margin ye40-50%. Matambudziko ekubatanidza anogara achiitika zvisingatarisirwi. Iwe unogona kugadzirisa kuwirirana kuitira kuti kuchinjana kuvhare nzvimbo mushure mokunge kubatanidzwa kwarasika. Data packet huori inoteverwa kuburikidza neWatchDog yekutevera algorithms. Mazano ekutengesa anoshandiswa mukutengesa haana kukwana uye kusanganiswa kwavo kunogona kutungamirira kumigumisiro yakasiyana zvachose. Mumaapplication, API zvikanganiso zvinogona kuitwa. Mutengo, vhoriyamu, kukosha kwemijenya inogona kuratidzwa zvisiri izvo. Zvakare, kutengeserana kunogona kuitwa pakupera kwevhiki kana mazororo, nzira yekutengesa kana miganhu yeakaundi inotyorwa.

Kuti ubvise zvikanganiso izvi, zvinodikanwa kutarisa uye kuongorora maodha uye miganhu yemaitiro ekutengesa kuitira kubvisa zvikanganiso zvimiro.

Muchiitiko chemamiriro ezvinhu ekukurumidzira, zvinodikanwa kuti uzivise vose vanofarira nezveizvi kuburikidza neSMS, e-mail, vatumwa pakarepo uye dzimwe nzira dzekukurukurirana. Izvo zvakakosha kunyora kukundikana kwega kwega mumatanda kuitira kudzivirira kudzokorora kwayo mune ramangwana. Maitiro ekugadzira mari yekungoita nealgorithmic yekutengesa: https://youtu.be/UeUANvatDdo

Algo kutengesa: zvakanakira uye zvisingabatsiri

Marobhoti ekutengesa haasi pasi pe “vanhu” zvinhu zvinogona kukanganisa basa ravo: kuneta, kuparara kwepfungwa, nezvimwe. Iyi ndiyo mukana mukuru wealgorithmic kutengeserana. Algorithms anotevera chirongwa chakanyatsotsanangurwa uye usambotsauka kubva pachiri. Algo kutengesa kune zvinoverengeka zvisingabatsiri. Izvi zvinosanganisira, kunyanya, kusawanikwa kweruzivo rwemhando iyi yekutengeserana munharaunda yeruzhinji. Algorithmic mutengesi anofanirwa kuve nehunyanzvi mukuronga, izvo zvakaomera kune vazhinji nyanzvi dzezvemari. Kana musika uchichinja, iwe uchafanirwa kushandura zvachose algorithm. Mukunyora robhoti yekutengesa, kukanganisa kunogona kuitwa kunotungamirira iyo algorithm yose pasi penzira isina kururama, uye izvi zvinotungamirira mukurasikirwa kwemari.
Algorithmic kutengeserana imhando yakaoma yekutsinhana kutengeserana inoda ruzivo kwete mukutengesa chete, asiwo mune masvomhu uye hurongwa. Izvo zvinodikanwa kwete chete kukwanisa kugadzira iyo inodiwa algorithm, asiwo kudzivirira matambudziko ekubatanidza, zvikanganiso mune algorithms uye chirongwa kodhi. Iwe unofanirwa kunyatsofunga usati wafunga kutengesa nenzira iyi. Zvakadaro, achinge azvigona uye nekuishandisa nenzira kwayo mukuita, mutengesi achawana kuwedzera kukuru kwemari uye kuita kuti basa rake rive nyore.