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suite43 · 3 years

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PS Neither the egg fic nor the vegan freak have anything to do with M/gastar before you try it. That's all pure Starscream stanning, baby. And one of them is St/rop, the supposedly ""good""" ship LOL.

List of female Transformers Main Complete list Following is a thorough list of the various female Transformers in canon thus far. Many of these characters were Japan-exclusive, featured only in fiction, or exist as limited-run exclusive toys. Female characters who had multiple toys are listed only once. Generation 1 (Numbers indicate order of appearance.) Chromia (1) Moonracer (2) Firestar (3) Elita One (4) Greenlight (5) Lancer (6) Arcee (7) Beta (8) An Autobot rebel (9) Paradron Medic (11) Nancy (12) Minerva (13) Clipper (14) Karmen (18) Glyph (20) Road Rage (21) Discharge[1] (22) Windy[1] (23) Vibes (24) Roulette (25) Flareup (32) Flip Sides (34) Rosanna (35) Windrazor (38) Thunderblast (46) Cassiopeia (47) Nautica (51) Windblade (52) Victorion (61) Velocity (63) Javelin (62) Proxima (64) Roadmaster (65) Acceleron (66) Override (69) Rust Dust (70) Pyra Magna (71) Skyburst (72) Stormclash (73) Jumpstream (74) Dust Up (75) Scorpia[1] (76) Eos (80) Lifeline (83) Quickslinger (84) Hotwire[2] (98) Strongarm (99) Slide[2] (104) Crush Bull[2] (107) Oiler[2] (108) Broadside[2] (109) Sky High[2] (110) Circuit[2] (116) Pyra Ignatia Spark[2] (118) Scorchfire (122) Orthia (126) Smashdown[2] (128) Esmeral (15) Lyzack (16) Clio (17) Nightracer (19) Shadow Striker (26) Howlback (31) Flamewar (33) Flip Sides (34) Crasher (39) Freezon[1] (44) Nightracer (49) Slipstream (50) Twirl (54) Nickel (60) Swift (77) Killjoy (79) Blackout[2] (81) Spaceshot[2] (82) Crash Test (85) Trickdiamond (92) Moonheart (93) Megaempress (94) Flowspade (95) Lunaclub (96) Megatronia (100) Buckethead[1] (103) Diveplane[1] (112) Seawave[1] (113) Mindgame (114) Tracer[2] (115) Devastator[2] (117) Cindersaur[2] (125) Shadow Striker (127) Nova Storm[2] (129) Termagax (133) Kaskade (135) Heavywait (138) Tyrannocon Rex (139) Cheesecake robot (10) Roulette and Shadow Striker's sister (27) Path Finder (28) Small Foot (29) Devcon's galpal (30) One of Optimus Prime's rescuees (36) Angela (37) Four members of the Kaon upperclass (40-43) Ma-Grrr (45) Red waitress Transformer (48) Windshear (53) Solus Prime (55) Female protester (56) Lightbright (57) Strafe (58) Mistress of Flame (59) Exocet (67) Vertex (68) Aileron (78) Gnash (86) Slice (87) Thrashclaw (88) Shred (89) A pair of Devisen twins (90-91) Maxima (97) Sieg[3] (101) Kari (102) Anode (105) Lug (106) X-Throttle (111) Rum-Maj (119) Praesidia Magna (120) Fastbreak (121) Crash Test (122) Stardrive (123) Magrada (124) Leviathan (130) Codexa (131) Gauge (132) Lodestar (134) Shutter (136) Sharpclaw (137) Cargohold (140) Half-qualifiers: Alana, turned into a Transformer for a short time. Aunty, female Cybertronian intelligent computer. Combination granny and attack-dog-bots, human-sized drones supposedly based on Transformer technology. One of Maccadam's bartenders Nightbird Overlord, has a female side to him. Some of the "Teletraan" computers like 15 and 10 are female. There appears to be a female design among a group of old generics. Bayonet, the fake female Decepticon disguise of Britt. In the French dub of The Transformers: The Movie, Shrapnel and Starscream are considered female. Shrapnel is also female in the Russian dub. Beast Era (Numbers indicate order of appearance.) Airazor (2) Kitte Shūshū (5) Rage (6) Botanica (7) Sonar[1] (13) Crystal Widow (14) Crossblades (15) Stiletto (16) Transmutate[1] (18) Binary (19) Wedge Shape[1] (24) Aura (25) Legend Convoy[1] (26) Stockade[2] (28) Rav (29) Hammerstrike[2] (31) Triceradon[2] (35) Skimmer (36) Nyx (44) Blackarachnia (1) Scylla (3) Antagony (4) Strika (8) Manta Ray[1] (17) Ser-Ket (20) Dead-End[2] (27) Jai-Alai (30) Max-B[2] (32) Gaidora (33) Soundbyte/Soundbite (34) Liftoff (37) Freefall (38) Snarl-blast[2] (39) Vertebreak (43) Skold (45) Libras (9) Virgol (10) Cancix[1] (11) Possibly Sagittarii (12) Dipole (21) Vamp (22) Plasma[2] (23) Deep Blue (40) At least two bridge officers of the Terrastar (41-42) Half-qualifiers: NAVI-ko, female Cybertronian intelligent computer NAVI (Yukikaze), female Cybertronian intelligent computer NAVI (Gung Ho), female Cybertronian

intelligent computer DNAVI, female Cybertronian intelligent computer Medusa, an Intruder-built robot modified with Cybertronian technology Robots in Disguise (2001) (Numbers indicate order of appearance.) Optimus Prime[2] (1) Nightcruz[1] (3) Scourge[2] (2) Half-qualifiers: T-AI, female Cybertronian intelligent computer. Unicron Trilogy (Numbers indicate order of appearance.) Airazor (5) Arcee (9) Autobot nurses (10) Two Velocitronian band members (11-12) Override[4] (13) Joyride[4] (15) Quickslinger (16) Crystal Widow (24) Treadbolt (33) Chromia (34) Thunderblast (14) Spacewarp (30) Sureshock (1) Combusta (2) Falcia (3) Twirl (4) Sunburn (6) Cliffjumper[1] (7) Ironhide[1] (8) Spiral[1] (9) Offshoot[1] (17) Breakage[1] (18) Kickflip[1] (19) Mudbath[1] (20) Heavy Metal[1] (21) "Disco ball" (22) Road Rebel[1] (23) Guardian Speed[1] (25) Mugen[1] (26) Bingo/Triac[1] (27) Wedge Shape[1] (28) Sprite (29) Boom Tube (31) Windrazor (32) Rán (33) Half-qualifiers: A possible scooterformer Dark Nitro Convoy, evil clone of a character whose gender was switched in translation Red Alert, minimally-altered release of a toy that was female in Japan Midnight Express, unaltered release of a toy that was female in Japan Hourglass, a female character who might be a Cybertronian Bombshell, a female character who might be a Cybertronian Carillon, a female character who might be a Cybertronian Vector Prime, the former multiversal entity who was female in some universes Movie continuity family (Numbers indicate order of appearance.) Arcee (1) Elita-One (2) Chromia (4) Perihelion (8) HMS Alliance (9) Windblade (13) Fracture (3) Alice (5) Shadow Striker (6) Override[3] (7) Diabla (10) Howlback (11) Shatter (12) Nightbird Airazor Half-qualifiersJetfire claims to have a mother who may or may not have been a Transformer. Animated (Numbers indicate order of appearance.) Sari Sumdac (2) Arcee (3) Elita-1 (4) Red Alert (6) Botanica (8) Flareup (10) Rosanna (11) Glyph (12) Lickety-Split (13) Lightbright (14) Chromia (16) Clipper (17) Quickslinger (18) Kappa Supreme (19) Override Prime (20) Windy (21) Road Rage (25) Flashpoint (26) Minerva (27) Sureshock (28) Nightbeat (29) Sunstreaker (30) Blackarachnia (1) Slipstream (5) Strika (7) Flip Sides (9) Antagony (15) Wingthing (22) Beta (23) Drag Strip (24) Half-qualifiers: Teletran-1, female Cybertronian intelligent computer TransTech (Numbers indicate order of appearance.) Blackarachnia (5) Strika (3) Unnamed medic (1) Andromeda (2) Cyclis (4) Sonar (6) Hammerstrike (7) Scorpia (8) Proxima (9) Half-qualifiers: Axiom Nexus News Editor, a 'bot with one male and one female personality Shattered Glass (Numbers indicate order of appearance.) Crasher (1) Esmeral (6) Howlback (7) Arcee (2) Andromeda (3) Elita-One (4) Strongarm (8) Windblade (9) Nautica (10) Beta (5) Half-qualifiers: Teletraan-X, female Cybertronian intelligent computer. Aligned continuity family (Numbers indicate order of appearance.) Akiba Prime Arc Arcee Arcee Blade Assault Star Brushfire Cameo Catapult Chevalier Chromia Deep Blue Ether Walker Firestar Galaxy Flare Galaxy 'Questrian Glow Matronly Docent Quickshadow Rocket Plume Solus Prime Strongarm Tempest Spin Thunderclap Upkeep Windblade Airachnid Astraea Aurora Speeder Balewing Coldstar Crimson Phantom Cyberwarp Cyclone Dancer Diabla Duststorm Fallen Angel Filch Flamewar Flash Runner Glowstrike Hoverbolt Helter-Skelter Hurricane Hunter Ida Lensflare Metal Thunder Nebula Ripper Night Dancer Overhead Retrofit Rollcage Scatterspike Skyjack Slink Slipstream Spiral Zealot Supernova Flame Variable Star Void Pulse Zizza Ser-Ket Ripclaw Azimuth Cogwheel Elita One Mercury Moonracer Nightra Override Bot Shots (Numbers indicate order of appearance.) Buzzclaw (1) Kre-O (Numbers indicate order of appearance.) Chromia (1) Arcee (3) Strika (4) Minerva (5) Windblade (6) Paradron Medic (10) Strongarm (12) Skimmer[1] (13) Airachnid (2) Thunderblast (7) Blackarachnia (8) Slipstrike (9) Ida (11) Liftoff[1] (14) Freefall[1] (15) Angry Birds Transformers (Numbers indicate order of appearance.) Stella as:Arcee

(1) Airachnid (2) Chromia (4) Novastar (10) Moonracer (11) Greenlight (12) Silver as:Windblade (3) Energon Windblade (5) Elita-One (8) Matilda as:Energon Nautica (6) Nautica (7) Strongarm (9) Zeta as:Nightbird (13) Rosanna (15) Zeta as:Slipstream (14) Cyberverse (Numbers indicate order of appearance.) Arcee Chromia Clobber Jazz[3] Windblade Alpha Strike Nova Storm Shadow Striker Skywarp Slipstream Blackarachnia Cosmos Operatus Solus Prime Half-qualifiers: In the Japanese dub of Cyberverse, Thrust was female, and went by the name Red Wing. Acid Storm fluctuates between the male and female Seeker body types in show. Mae Catt would explain this on Twitter as this being "just something Acid Storm likes to do" and that pronouns are "up to Acid Storm". This would imply Acid Storm is non-binary gender fluid, thus they semi-qualify for the list. BotBots (Numbers indicate order of appearance.) Aday Angry Cheese Arctic Guzzlerush Bankshot Big Cantuna Bok Bok Bok-O Bonz-Eye Bot-T-Builder Bottocorrect Bratworst Brock Head Chef Nada Clawsome Crabby Grabby Cuddletooth Dingledeedoo Disaster Master Disgusto Desserto DJ Fudgey Fresh Doctor Flicker Drama Sauce Drillit Yaself Face Ace Fail Polish Fit Ness Monster Flare Devil Flood Jug Fomo Frohawk Frostfetti Frostyface Glam Glare Fancy Flare Glitch Face Goggly Spy P.I. Gold Dexter Goldface Goldiebites Goldie Terrortwirl Goldito Favrito Goldpin Baller Gold Punch Grampiano Grandma Crinkles Grave Rave The Great Mumbo Bumblo Greeny Rex Grrr'illa Grimes Halloween Knight Handy Dandy Hashtagz Hawt Diggity Hawt Mess Highroller Hiptoast Ice Sight Javasaurus Rex Jet Setter Knotzel Latte Spice Whirl Leafmeat Alone Loadoutsky Lolly Licks Lolly Mints Miss Mixed Movie Munchster Ms. Take Must Turd Nanny McBag Nomaste Nope Soap Ol' Tic Toc Ollie Bite Outta Order Overpack Pop N. Lock Pop O' Gold Pressure Punk Professor Scope Rebugnant Roarista Sandy Shades Scribby Sheriff Sugarfeet Shifty Gifty Sippyberry Sippy Slurps Skippy Dippy Disc Slappyhappy Smooth Shaker Smore N' More Sour Wing Starscope Sticky McGee Sugar Saddle Super Bubs Sweet Cheat Technotic Sonic Terror Tale Torch Tidy Trunksky Tricitrustops Tropic Guzzlerush Tutu Puffz Twerple Burple Unilla Icequeencone Venus Frogtrap Vigitente Waddlepop Wasabi Breath Whirlderful Whoopsie Cushion Wristocrat

#really long post #red.reply #spamguy

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thenationview · 2 years

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Maarten Heijmans wins Willem Wilmink Award for Best Children's Song

Maarten Heijmans wins Willem Wilmink Award for Best Children’s Song

song give me skin, sung by actor Maarten Heijmans, among others, was voted the best children’s song. The song won the Willem Wilmink Award in the Grote Kerk in Enschede on Sunday evening. Written by Jurrian van Dongen give me skin and Keez Groenteman composed the song. Heijmans sings the song together with Rop Verheijen and Jesse Mensah. The song was one of 77 works for the prize, and according…

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orange1896 · 3 years

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5261376 CRANKSHAFT FOTON TRUCK SPARE PARTS

5261376 CRANKSHAFT FOTON TRUCK SPARE PARTS

705269365 XCMG F481CACA101005-400软管总成 705223593 XCMG 600FN.7.1-3转向泵吸油胶管 252803374 XCMG 胶管总成F781C91C252512-1790(备件) 803415040 XCMG FG28XFCACE222212-665-PG/170胶管 6800302 252807739 XCMG O型圈78K4(变速箱8421H)(备件) 201304552 XCMG 640-1201060消声器垫片 276610620 XCMG 2BS280.875-1.8机罩 9508689 252913192 XCMG FS1240油水分离器(108454)(专用备件) 860115389 XCMG XD132OS.2.84L-1上轴 253005908 XCMG LW180KVBR.6.2.1摆动架 7V1702 705218216 XCMG 0-360°万能角度尺放大镜（删除） 803681075 XCMG CW61802016L=77分油环 705232007 XCMG 继电器-马达连接线ZL50.14-13(备件) 803166677 XCMG RP903S.1.1.10右立柱 226302010 XCMG 679-10.7.1刀槽 803163839 XCMG RP1356.08.9电加热系统 705257017 XCMG R6.13.6.1Ⅱ右挡板 803166045 XCMG 700KN.5前车架系统 281200741 XCMG WA2211Z4装配连接毂 251810407 XCMG TZ3A.08.1.1.3-2弯板Ⅱ 705207519 XCMG X670.030-02-1700支承座Ⅲ 803607684 XCMG 800K(LNG)II.12.2-8(L)挡板 9346570 228900632 XCMG J6.2-4进水管I 7E3111 803382869 XCMG XT550K.6.1B.2-2筋板 Z00360305 276401292 XCMG XAP320.09.6-1压型板 840101766 XCMG XS122Ⅲ.07.2.3.1操纵箱线束 253105584 XCMG LQC240B.01.1.1.1前片 Z00250300 276401031 XCMG 废弃物料 230503039 XCMG LW180KVII.12.1.4-2降噪材料 407002578 251708836 XCMG XS202JVII.1.3.2-1X1箱罩 252102321 XCMG DL210KL.5前车架系统 840103932 XCMG HZS180.12-1徐工集团标牌 253205852 XCMG T.4.3A联轴节总成 860151791 XCMG DT12A.6.4I左0.25米振捣总成标准件 229602302 XCMG 主减(肥城新式)520F(备件) 251900704 XCMG 550FV.605-1550FV前车架阀支座划线样板 251807551 XCMG Z5G.12.3-18后支架 250100448 XCMG XT870.8.3.4-5加强板 705235260 XCMG YL16.5.5-2盖板0.03kg 102176 860137422 XCMG YZ16JS.1Ⅱ.1.1轴架 227300401 XCMG 500FV.10A.1-2打印机支架 252913785 XCMG XS122V.5.4燃油系统 859917249 XCMG NJZH181.1.6筛网 705204452 XCMG F481CACA282816-750胶管 228700717 XCMG 800K.030-8.11.1.-3板 201319284 XCMG 500FNV.6.1.2-1上面板 252113148 XCMG 600KVM.32X.1-3斗侧板 9372479 200900293 XCMG 液压油散XGYS01-19(备件)=803004090 230200111 XCMG JB/T8406-2001胶管B38×470 859936377 XCMG LW180K.10.1.1-6后玻璃上粘接边 251809766 XCMG HZS120-新疆（铸本）增加件 A0-0290 822736160 XCMG RP13.07.14-2钢管φ10X1L=1500 9359251 860117828 XCMG 300FS.7.1.9X液压油箱 "WHATSAPP/WECHAT:0086-1525 4934 126 Email:[email protected]" 252109350 XCMG E340.1.3.2-2后挡板 253100402 XCMG 500K.7.1.4.1A-5支板 410402610 XCMG 胶管(删除) 252807806 XCMG XSH060J.030-01-7垫圈 GH2219 201309117 XCMG LW500K装载机-再制造整机-1500KDL118315 860130871 XCMG 400KV.22.1.5工作泵吸油胶管组件 226000204 XCMG LW150FV.38.5A-10加强板 270100120 XCMG RP752.840-02划线样板 252900474 XCMG 接头I10LG3/8ED Z00200107 251808621 XCMG 912-31.1挂件工装 705209988 XCMG EW-PP-M10/P7波纹管 9502419 201302733 XCMG RT0404000-T46V特康密封圈 404202735 XCMG GB5625.2-198510# 401003893 XCMG WZ30.12-1后挡风玻璃 251500260 XCMG WZ30.06B-2管夹 860138047 XCMG LQC240A.16.3.1废料仓体 "WHATSAPP/WECHAT:0086-1525 4934 126 Email:[email protected]" 705215152 XCMG BYPT-1弯板 705207250 XCMG XC990.10II.1.1.1.3-1后安装板 705229400 XCMG 049677密封包(卡拉罗)（特机备件） 253206633 XCMG TWZ180.10.5.2-2挡头 33771536 705217701 XCMG ZL50G安装暖风机与风扇 705202730 XCMG 948.10.1.3.1-1右窗玻璃 705259054 XCMG TZ3S.15.4-2支板 705101851 XCMG HZS180I.5.8.1WH水箱支架 200400279 XCMG 600KIII.6.1.1发动机前支撑 253203548 XCMG 05A2214-20-39卡箍 705106991 XCMG 679-6A-2卡板2 705218634 XCMG R8.1.1.8-1Ⅱ前板 252604241 XCMG 轴承77204/30204 251805159 XCMG GE16SMEDOMDCF接头 705242676 XCMG Z5GS.3-2水管胶管B(8)-φ10L=1030 226802706 XCMG XD122III.14A-1弯座 705221377 XCMG LWJ350K(DC)夹钳装载机+东康发动机+先导+ROPS+电控箱 201000758 XCMG 902-892A.1-16面板 253600102 XCMG F481CACA151506-3000软管总成 252612235 XCMG 600KNVKII.1.3.5-1弯板 253004388 XCMG Z3080变速油缸3轴 705267250 XCMG LQC240A.08.7.2.1.7-2上弯板 200600457 XCMG M250SG.15Ⅱ.1.2.1.3小滑道 201303964 XCMG F381CACA121206-4800软管总成 24024925 252100630 XCMG 1000K.030-8.1-3把手 802138576 XCMG 木箱1400×1000×780(备件) 860115174 XCMG 1200K.1.8.1-3板III 362400996 XCMG RP952.732-03.1-1模板 253300565 XCMG RP953.9Ⅱ.1-5板 400404890 XCMG HZS120T.6.4.1排料连接管 9502801 802149569 XCMG 700K.030-14-2垫块 "WHATSAPP/WECHAT:0086-1525 4934 126 Email:[email protected]" 253304254 XCMG 0637842509接头(杭齿4WG180)(备件) 253402985 XCMG 300KNV.1.7-5胶管 239900229 XCMG 300F.4A.3.1-1矩管 253009592 XCMG YZC12G.01III.2-2筋板 820100334 XCMG TZ3S.06.2-3分隔板1 9365982 252119102 XCMG 500F.10II.1.5X车门挡板 252115965 XCMG 575.7.3.1-7垫 231401771 XCMG 500F.030-113.2-3垫块 839900232 XCMG 400K.6.1.6发动机支腿 803604970 XCMG XC958.030-3.2.1-9横梁9 228101577 XCMG 500KG.1.3.1-9安装板 U006612 705110364 XCMG 500F.10II.1.1.7前灯支架III 250100437 XCMG XGYS01-27双变油散 9364167 803165112 XCMG J300FV(TD)潍柴+杭齿箱+干式桥+三联+暖风+三联臂+1.8斗齿斗 391078 201308504 XCMG 800K(LNG)V.11.3后车架线束 9330912 201303318 XCMG RP952.4Ⅳ.1前支腿 200900501 XCMG XT870L.14.1-7耳板 253009022 XCMG Z5G.741-7.1底座 803086766 XCMG WJ04.9Ⅱ.5-8钢管 252903853 XCMG 50GV.W5ADGK-000潍柴+行星箱+干桥+大高卸+空调+大配重 Read the full article

#crankshaft #FOTON

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stock-filter · 3 years

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Stock daily Filter Report for 2021/07/08 05-40-12

*******************Part 1.0 Big Cap Industry Overiew********************* big_industry_uptrending_count tickers industry Basic Materials 3 Communication Services 18 Consumer Cyclical 13 Consumer Defensive 4 Energy 2 Financial Services 9 Healthcare 31 Industrials 12 Real Estate 6 Technology 52 Utilities 3 **************************************** big_industry_downtrending_count tickers industry Basic Materials 8 Communication Services 8 Consumer Cyclical 13 Consumer Defensive 10 Energy 1 Financial Services 22 Healthcare 8 Industrials 9 Real Estate 2 Technology 4 Utilities 8 *******************Part 1.1 Big Cap Long Entry SPAN MACD********************* big_long_signal_entry_span_macd Symbol Day Return Market Cap Long/Short score MACD Signal Count Market Value Span Signal Count industry 115 AWK 1 0.0 big-cap Long NaN 1.0 1.413273e+08 3.0 Utilities Mean Return: nan Mean Day/Week: inf Accuracy:nan *******************Part 1.2 Big Cap Short Entry SPAN MACD********************* big_short_signal_entry_span_macd Symbol Day Return Market Cap Long/Short score MACD Signal Count Market Value Span Signal Count industry 10 PDD 1 0.0 big-cap Short NaN -1.0 8.504009e+08 -5.0 Consumer Cyclical Mean Return: nan Mean Day/Week: inf Accuracy:nan *******************Part 1.3 Big Cap Long Entry SPAN********************* big_long_signal_entry_span Symbol Day Return Market Cap Long/Short score MACD Signal Count Market Value Span Signal Count industry 115 AWK 1 0.0 big-cap Long NaN 1.0 1.413273e+08 3.0 Utilities Mean Return: nan Mean Day/Week: inf Accuracy:nan *******************Part 1.4 Big Cap Short Entry SPAN********************* big_short_signal_entry_span Symbol Day Return Market Cap Long/Short score MACD Signal Count Market Value Span Signal Count industry 10 PDD 1 0.00 big-cap Short NaN -1.0 8.504009e+08 -5.0 Consumer Cyclical 76 STZ 2 -1.04 big-cap Short NaN -39.0 2.445756e+08 -3.0 Consumer Defensive Mean Return: -1.04 Mean Day/Week: 3.0 Accuracy:1.0 *******************Part 1.5 Big Cap Long Entry MACD********************* big_long_signal_entry_macd Symbol Day Return Market Cap Long/Short score MACD Signal Count Market Value Span Signal Count industry 3 GOOGL 2 0.23 big-cap Long NaN 2.0 3.036378e+09 77.0 Communication Services 8 CMCSA 2 0.88 big-cap Long NaN 2.0 7.426283e+08 9.0 Communication Services 27 AMT 3 1.93 big-cap Long NaN 3.0 4.680756e+08 74.0 Real Estate 20 BMY 2 0.74 big-cap Long NaN 2.0 4.649235e+08 20.0 Healthcare 91 JCI 4 0.77 big-cap Long NaN 4.0 3.232801e+08 77.0 Industrials 33 GILD 5 -0.72 big-cap Long NaN 5.0 3.153007e+08 44.0 Healthcare 135 ANET 1 0.00 big-cap Long NaN 1.0 2.298231e+08 64.0 Technology 43 ADP 1 0.00 big-cap Long NaN 1.0 2.173194e+08 77.0 Industrials 111 SBAC 2 1.41 big-cap Long NaN 2.0 1.963169e+08 75.0 Real Estate 203 IT 3 1.31 big-cap Long NaN 3.0 1.688201e+08 77.0 Technology 115 AWK 1 0.00 big-cap Long NaN 1.0 1.413273e+08 3.0 Utilities 161 ALB 4 -1.15 big-cap Long NaN 4.0 1.217255e+08 42.0 Basic Materials 177 BR 1 0.00 big-cap Long NaN 3.0 9.177683e+07 9.0 Technology 144 GRMN 3 0.57 big-cap Long NaN 3.0 7.758592e+07 77.0 Technology 167 TRU 2 1.06 big-cap Long NaN 2.0 6.013670e+07 67.0 Industrials 18 NVO 1 0.00 big-cap Long NaN 1.0 5.979819e+07 56.0 Healthcare 217 OSH 1 0.00 big-cap Long NaN 1.0 3.199691e+07 12.0 Healthcare 188 BIP 4 -0.69 big-cap Long NaN 4.0 1.984324e+07 7.0 Utilities 244 RDY 1 0.00 big-cap Long NaN 1.0 1.859484e+07 58.0 Healthcare 59 RELX 2 0.69 big-cap Long NaN 2.0 1.180848e+07 66.0 Communication Services Mean Return: 0.5407692307692309 Mean Day/Week: 3.4615384615384617 Accuracy:0.7692307692307693 *******************Part 1.6 Big Cap Short Entry MACD********************* big_short_signal_entry_macd Symbol Day Return Market Cap Long/Short score MACD Signal Count Market Value Span Signal Count industry 10 PDD 1 0.00 big-cap Short NaN -1.0 8.504009e+08 -5.0 Consumer Cyclical 42 BEKE 2 -7.61 big-cap Short NaN -2.0 4.365734e+08 -136.0 Real Estate 123 BBY 1 0.00 big-cap Short NaN -1.0 2.222004e+08 -20.0 Consumer Cyclical 223 KC 2 -1.99 big-cap Short NaN -2.0 6.071088e+07 -136.0 Technology 69 LU 3 -2.87 big-cap Short NaN -4.0 3.065707e+07 -136.0 Financial Services 212 YSG 1 0.00 big-cap Short NaN -1.0 1.289004e+07 -136.0 Consumer Cyclical 239 BCH 2 0.70 big-cap Short NaN -2.0 1.652749e+06 -42.0 Financial Services Mean Return: -2.9425000000000003 Mean Day/Week: 3.0 Accuracy:0.75 *******************Part 1.7 Big Cap Long Maintainance********************* big_long_signal_maintainance Symbol Day Return Market Cap Long/Short score MACD Signal Count Market Value Span Signal Count industry 6 NVDA 30 27.01 big-cap Long NaN 30.0 8.387002e+09 64.0 Technology 1 MSFT 18 8.28 big-cap Long NaN 19.0 6.225574e+09 77.0 Technology 4 FB 9 2.23 big-cap Long NaN 9.0 4.926883e+09 77.0 Communication Services 26 AMD 6 1.35 big-cap Long NaN 30.0 4.650501e+09 14.0 Technology 21 SHOP 16 14.47 big-cap Long NaN 33.0 2.510731e+09 34.0 Technology 7 PYPL 14 6.70 big-cap Long NaN 28.0 1.972162e+09 33.0 Financial Services 55 ROKU 11 4.22 big-cap Long NaN 32.0 1.416142e+09 14.0 Communication Services 9 ADBE 19 12.49 big-cap Long NaN 23.0 1.216333e+09 67.0 Technology 32 SNAP 13 3.45 big-cap Long NaN 30.0 1.127114e+09 31.0 Communication Services 49 MRNA 12 6.97 big-cap Long NaN 29.0 1.082567e+09 59.0 Healthcare 11 CRM 27 4.41 big-cap Long NaN 30.0 1.063722e+09 33.0 Technology 60 CRWD 15 13.88 big-cap Long NaN 32.0 9.223594e+08 33.0 Technology 65 DOCU 15 13.58 big-cap Long NaN 27.0 8.846687e+08 23.0 Technology 5 V 11 1.75 big-cap Long NaN 11.0 8.622096e+08 75.0 Financial Services 19 COST 8 2.57 big-cap Long NaN 8.0 8.251267e+08 64.0 Consumer Defensive 25 ZM 13 5.34 big-cap Long NaN 35.0 7.899979e+08 23.0 Communication Services 70 PTON 7 -2.68 big-cap Long NaN 35.0 7.854215e+08 14.0 Consumer Cyclical 14 LLY 9 1.24 big-cap Long NaN 44.0 7.285926e+08 34.0 Healthcare 88 TTD 8 2.30 big-cap Long NaN 27.0 7.069985e+08 11.0 Technology 13 MRK 18 3.86 big-cap Long NaN 18.0 6.461290e+08 19.0 Healthcare 16 ACN 8 4.99 big-cap Long NaN 8.0 5.796738e+08 77.0 Technology 40 ZTS 19 8.15 big-cap Long NaN 19.0 5.127571e+08 61.0 Healthcare 15 DHR 9 4.15 big-cap Long NaN 12.0 5.095228e+08 61.0 Healthcare 29 TGT 12 5.76 big-cap Long NaN 33.0 5.038875e+08 76.0 Consumer Defensive 138 ENPH 8 3.98 big-cap Long NaN 32.0 4.822315e+08 15.0 Technology 30 ISRG 17 9.03 big-cap Long NaN 17.0 4.691767e+08 62.0 Healthcare 120 LI 14 4.68 big-cap Long NaN 36.0 4.554165e+08 28.0 Consumer Cyclical 28 INTU 35 19.51 big-cap Long NaN 35.0 4.432913e+08 40.0 Technology 24 CHTR 9 4.28 big-cap Long NaN 9.0 4.308797e+08 58.0 Communication Services 81 EBAY 12 8.55 big-cap Long NaN 25.0 4.217288e+08 44.0 Consumer Cyclical 54 REGN 20 11.78 big-cap Long NaN 23.0 4.107382e+08 52.0 Healthcare 90 DXCM 8 3.95 big-cap Long NaN 25.0 4.104345e+08 25.0 Healthcare 22 AZN 7 -0.50 big-cap Long NaN 7.0 3.822148e+08 58.0 Healthcare 105 XLNX 6 -1.32 big-cap Long NaN 30.0 3.756844e+08 11.0 Technology 89 A 19 4.58 big-cap Long NaN 27.0 3.303484e+08 66.0 Healthcare 181 GNRC 16 18.09 big-cap Long NaN 27.0 3.208548e+08 29.0 Industrials 68 LULU 17 11.38 big-cap Long NaN 29.0 3.121821e+08 57.0 Consumer Cyclical 78 PSA 23 7.28 big-cap Long NaN 23.0 3.097922e+08 77.0 Real Estate 93 MRVL 15 4.83 big-cap Long NaN 31.0 3.063310e+08 33.0 Technology 46 ILMN 18 4.46 big-cap Long NaN 32.0 2.969829e+08 28.0 Healthcare 37 SPGI 17 5.71 big-cap Long NaN 17.0 2.947554e+08 77.0 Financial Services 131 NET 22 23.82 big-cap Long NaN 30.0 2.893582e+08 35.0 Technology 64 CVNA 10 0.81 big-cap Long NaN 28.0 2.833307e+08 18.0 Consumer Cyclical 75 IDXX 30 18.26 big-cap Long NaN 30.0 2.761535e+08 38.0 Healthcare 87 APTV 9 -0.66 big-cap Long NaN 28.0 2.718117e+08 28.0 Consumer Cyclical 133 FTNT 28 16.09 big-cap Long NaN 28.0 2.671649e+08 77.0 Technology 57 EW 31 12.46 big-cap Long NaN 31.0 2.663597e+08 62.0 Healthcare 107 ORLY 6 3.52 big-cap Long NaN 8.0 2.579987e+08 77.0 Consumer Cyclical 51 DASH 12 6.95 big-cap Long NaN 34.0 2.490669e+08 19.0 Communication Services 83 MTCH 10 -2.34 big-cap Long NaN 19.0 2.253147e+08 14.0 Communication Services 184 ULTA 11 1.66 big-cap Long NaN 11.0 2.244035e+08 29.0 Consumer Cyclical 232 BILL 13 6.18 big-cap Long NaN 27.0 2.179794e+08 22.0 Technology 189 EXR 24 11.67 big-cap Long NaN 24.0 2.145630e+08 77.0 Real Estate 53 TEAM 15 8.22 big-cap Long NaN 30.0 2.122391e+08 23.0 Technology 192 DPZ 20 7.99 big-cap Long NaN 20.0 2.066044e+08 65.0 Consumer Cyclical 130 WELL 24 10.28 big-cap Long NaN 25.0 2.039531e+08 77.0 Real Estate 104 CARR 7 1.99 big-cap Long NaN 7.0 1.990241e+08 77.0 Industrials 71 VEEV 20 11.34 big-cap Long NaN 29.0 1.973193e+08 29.0 Healthcare 77 ROP 9 4.31 big-cap Long NaN 9.0 1.969979e+08 67.0 Industrials 106 PAYX 9 5.20 big-cap Long NaN 9.0 1.935525e+08 77.0 Industrials 119 ROK 12 4.13 big-cap Long NaN 24.0 1.874491e+08 32.0 Industrials 129 CPRT 12 5.25 big-cap Long NaN 12.0 1.799250e+08 63.0 Industrials 114 RMD 20 17.68 big-cap Long NaN 31.0 1.772092e+08 46.0 Healthcare 58 MCO 17 8.13 big-cap Long NaN 17.0 1.763471e+08 77.0 Financial Services 235 FSLR 7 -1.53 big-cap Long NaN 30.0 1.732452e+08 10.0 Technology 164 HUBS 14 6.75 big-cap Long NaN 17.0 1.700945e+08 23.0 Technology 94 TROW 8 4.10 big-cap Long NaN 8.0 1.697389e+08 77.0 Financial Services 110 DDOG 14 5.47 big-cap Long NaN 34.0 1.526938e+08 33.0 Technology 80 SNPS 10 4.07 big-cap Long NaN 31.0 1.522545e+08 33.0 Technology 162 APO 8 2.78 big-cap Long NaN 8.0 1.478602e+08 58.0 Financial Services 122 MTD 17 6.14 big-cap Long NaN 17.0 1.450287e+08 65.0 Healthcare 241 AAP 6 2.03 big-cap Long NaN 8.0 1.432779e+08 77.0 Consumer Cyclical 179 WAT 20 10.93 big-cap Long NaN 20.0 1.398470e+08 72.0 Healthcare 102 MSCI 17 12.57 big-cap Long NaN 17.0 1.356062e+08 68.0 Financial Services 97 INFO 16 5.29 big-cap Long NaN 16.0 1.353610e+08 77.0 Industrials 193 POOL 8 3.19 big-cap Long NaN 8.0 1.334585e+08 65.0 Consumer Cyclical 146 WST 13 5.66 big-cap Long NaN 13.0 1.302540e+08 64.0 Healthcare 219 CABO 13 3.27 big-cap Long NaN 33.0 1.234734e+08 14.0 Communication Services 149 ZBRA 7 3.67 big-cap Long NaN 7.0 1.228612e+08 34.0 Technology 127 KEYS 9 1.73 big-cap Long NaN 25.0 1.225073e+08 33.0 Technology 142 KKR 10 0.06 big-cap Long NaN 10.0 1.176383e+08 77.0 Financial Services 145 YNDX 10 3.68 big-cap Long NaN 49.0 1.174322e+08 31.0 Communication Services 103 CTAS 12 7.21 big-cap Long NaN 15.0 1.164427e+08 71.0 Industrials 206 CRL 19 7.78 big-cap Long NaN 19.0 1.163469e+08 77.0 Healthcare 185 BPY 7 -0.72 big-cap Long NaN 7.0 1.112345e+08 77.0 Real Estate 99 LBRDK 9 5.28 big-cap Long NaN 9.0 1.053335e+08 58.0 Communication Services 207 BKI 8 4.34 big-cap Long NaN 67.0 1.046839e+08 18.0 Technology 113 MSI 12 6.06 big-cap Long NaN 41.0 1.030843e+08 77.0 Technology 220 DT 10 5.91 big-cap Long NaN 29.0 1.025638e+08 22.0 Technology 209 TECH 19 6.38 big-cap Long NaN 19.0 1.013383e+08 77.0 Healthcare 172 AVTR 19 6.67 big-cap Long NaN 19.0 9.649130e+07 67.0 Basic Materials 199 IFF 11 0.33 big-cap Long NaN 19.0 8.684385e+07 38.0 Basic Materials 210 AVLR 11 3.41 big-cap Long NaN 29.0 8.469607e+07 18.0 Technology 143 VRSN 10 2.87 big-cap Long NaN 10.0 7.605276e+07 67.0 Technology 175 PKI 19 6.00 big-cap Long NaN 19.0 7.536903e+07 44.0 Healthcare 39 INFY 21 8.44 big-cap Long NaN 32.0 6.951884e+07 29.0 Technology 225 CG 10 4.31 big-cap Long NaN 10.0 6.374826e+07 77.0 Financial Services 165 ALNY 20 9.61 big-cap Long NaN 35.0 6.166088e+07 28.0 Healthcare 205 ESTC 13 3.63 big-cap Long NaN 32.0 5.567562e+07 24.0 Technology 174 PAGS 12 3.19 big-cap Long NaN 33.0 4.803255e+07 27.0 Technology 198 CDAY 7 -0.16 big-cap Long NaN 14.0 3.971503e+07 14.0 Technology 233 AXON 10 5.87 big-cap Long NaN 26.0 3.481056e+07 22.0 Industrials 236 PEGA 9 -0.49 big-cap Long NaN 22.0 1.962446e+07 22.0 Technology 215 OTEX 9 2.25 big-cap Long NaN 25.0 1.651609e+07 22.0 Technology 100 LBRDA 8 2.76 big-cap Long NaN 8.0 1.570532e+07 58.0 Communication Services 141 RCI 10 1.75 big-cap Long NaN 10.0 9.711365e+06 65.0 Communication Services 134 EC 10 9.37 big-cap Long NaN 25.0 8.502079e+06 22.0 Energy 153 CQP 6 3.53 big-cap Long NaN 23.0 5.192716e+06 20.0 Energy Mean Return: 6.065925925925926 Mean Day/Week: 13.675925925925926 Accuracy:0.9166666666666666 *******************Part 1.8 Big Cap Short Maintainance********************* big_short_signal_maintainance Symbol Day Return Market Cap Long/Short score MACD Signal Count Market Value Span Signal Count industry 132 DAL 18 -8.72 big-cap Short NaN -18.0 5.037903e+08 -26.0 Industrials 128 LUV 14 -7.71 big-cap Short NaN -59.0 4.644246e+08 -24.0 Industrials 66 MET 12 -1.33 big-cap Short NaN -39.0 4.568518e+08 -14.0 Financial Services 73 WBA 9 -8.96 big-cap Short NaN -58.0 3.497407e+08 -15.0 Healthcare 86 LVS 24 -10.68 big-cap Short NaN -24.0 2.520518e+08 -45.0 Consumer Cyclical 48 SO 9 1.19 big-cap Short NaN -38.0 1.851535e+08 -15.0 Utilities 150 FLT 22 -5.80 big-cap Short NaN -43.0 1.775638e+08 -40.0 Technology 44 CB 12 1.88 big-cap Short NaN -20.0 1.483648e+08 -14.0 Financial Services 173 MTB 11 -3.77 big-cap Short NaN -30.0 1.364127e+08 -14.0 Financial Services 108 PCAR 13 -0.17 big-cap Short NaN -17.0 1.328094e+08 -22.0 Industrials 136 ED 6 1.79 big-cap Short NaN -35.0 1.323917e+08 -13.0 Utilities 52 D 10 1.50 big-cap Short NaN -42.0 1.235338e+08 -15.0 Utilities 41 CNI 14 0.10 big-cap Short NaN -14.0 1.115108e+08 -40.0 Industrials 139 TSN 9 -1.19 big-cap Short NaN -50.0 1.112338e+08 -16.0 Consumer Defensive 197 FMC 6 -3.09 big-cap Short NaN -34.0 1.068888e+08 -13.0 Basic Materials 216 MPW 13 2.51 big-cap Short NaN -13.0 9.410510e+07 -46.0 Real Estate 147 ABC 6 0.54 big-cap Short NaN -44.0 9.323486e+07 -15.0 Healthcare 117 PEG 6 2.27 big-cap Short NaN -44.0 9.210341e+07 -13.0 Utilities 183 HPE 13 0.01 big-cap Short NaN -65.0 8.735600e+07 -15.0 Technology 158 AEE 6 2.98 big-cap Short NaN -40.0 8.380695e+07 -13.0 Utilities 148 PPL 13 2.03 big-cap Short NaN -15.0 8.286001e+07 -15.0 Utilities 224 CHRW 11 -2.10 big-cap Short NaN -14.0 7.866004e+07 -15.0 Industrials 62 VOD 11 -6.99 big-cap Short NaN -34.0 7.800714e+07 -35.0 Communication Services 95 MFC 18 -5.18 big-cap Short NaN -70.0 7.026888e+07 -34.0 Financial Services 159 QSR 7 0.23 big-cap Short NaN -24.0 6.096194e+07 -14.0 Consumer Cyclical 194 ABCL 22 -30.85 big-cap Short NaN -25.0 5.860149e+07 -29.0 Healthcare 213 SMG 24 -8.34 big-cap Short NaN -57.0 5.693523e+07 -34.0 Basic Materials 196 ATHM 34 -31.16 big-cap Short NaN -34.0 4.827380e+07 -136.0 Communication Services 56 PHG 17 -13.04 big-cap Short NaN -50.0 4.675473e+07 -28.0 Healthcare 222 PLTK 19 -12.42 big-cap Short NaN -19.0 3.924527e+07 -24.0 Communication Services 245 AQN 12 0.82 big-cap Short NaN -12.0 2.479836e+07 -136.0 Utilities 109 ORAN 12 -6.13 big-cap Short NaN -28.0 9.905511e+06 -24.0 Communication Services 137 CAJ 6 -0.78 big-cap Short NaN -46.0 6.723534e+06 -17.0 Technology 72 PUK 12 -5.90 big-cap Short NaN -63.0 6.091644e+06 -15.0 Financial Services 234 CNA 7 -0.63 big-cap Short NaN -73.0 5.820915e+06 -13.0 Financial Services 160 DISCB 9 -11.10 big-cap Short NaN -61.0 6.381646e+05 -38.0 Communication Services 211 ZNH 22 -9.77 big-cap Short NaN -22.0 3.846271e+05 -47.0 Industrials 240 CEA 11 -6.13 big-cap Short NaN -21.0 4.691211e+04 -50.0 Industrials Mean Return: -4.844473684210525 Mean Day/Week: 13.157894736842104 Accuracy:0.6578947368421053 ************************************** ************************************** ************************************** *******************Part 2.0 Small Cap Industry Overiew********************* small_industry_uptrending_count tickers industry Communication Services 3 Consumer Cyclical 2 Consumer Defensive 2 Financial Services 4 Healthcare 11 Industrials 4 Real Estate 5 Technology 12 Utilities 2 unknown 2 **************************************** small_industry_downtrending_count tickers industry Basic Materials 7 Communication Services 2 Consumer Cyclical 12 Consumer Defensive 5 Financial Services 20 Healthcare 5 Industrials 11 Real Estate 4 Technology 4 Utilities 4 *******************Part 2.1 Small Cap Long Entry SPAN MACD********************* small_long_signal_entry_span_macd Empty DataFrame Columns: [Symbol, Day, Return, Market Cap, Long/Short, score, MACD Signal Count, Market Value, Span Signal Count, industry] Index: [] Mean Return: nan Mean Day/Week: nan Accuracy:nan *******************Part 2.2 Small Cap Short Entry SPAN MACD********************* small_short_signal_entry_span_macd Empty DataFrame Columns: [Symbol, Day, Return, Market Cap, Long/Short, score, MACD Signal Count, Market Value, Span Signal Count, industry] Index: [] Mean Return: nan Mean Day/Week: nan Accuracy:nan *******************Part 2.3 Small Cap Long Entry SPAN********************* small_long_signal_entry_span Empty DataFrame Columns: [Symbol, Day, Return, Market Cap, Long/Short, score, MACD Signal Count, Market Value, Span Signal Count, industry] Index: [] Mean Return: nan Mean Day/Week: nan Accuracy:nan *******************Part 2.4 Small Cap Short Entry SPAN********************* small_short_signal_entry_span Symbol Day Return Market Cap Long/Short score MACD Signal Count Market Value Span Signal Count industry 354 PNFP 2 -0.29 small-cap Short NaN -73.0 2.759551e+07 -3.0 Financial Services Mean Return: -0.29 Mean Day/Week: 2.0 Accuracy:1.0 *******************Part 2.5 Small Cap Long Entry MACD********************* small_long_signal_entry_macd Symbol Day Return Market Cap Long/Short score MACD Signal Count Market Value Span Signal Count industry 329 LSI 2 1.03 small-cap Long NaN 2.0 9.310152e+07 77.0 Real Estate 306 CUBE 1 0.00 small-cap Long NaN 1.0 8.970776e+07 77.0 Real Estate 340 TPX 4 -2.27 small-cap Long NaN 4.0 4.666279e+07 8.0 Consumer Cyclical 279 STOR 2 -0.36 small-cap Long NaN 2.0 4.357478e+07 8.0 Real Estate 298 ARCC 3 0.00 small-cap Long NaN 3.0 3.288478e+07 29.0 Financial Services 271 AGNCM 5 0.92 small-cap Long NaN 5.0 1.513663e+05 12.0 Real Estate Mean Return: -0.13599999999999998 Mean Day/Week: 3.4 Accuracy:0.4 *******************Part 2.6 Small Cap Short Entry MACD********************* small_short_signal_entry_macd Symbol Day Return Market Cap Long/Short score MACD Signal Count Market Value Span Signal Count industry 312 KSS 2 -3.92 small-cap Short NaN -2.0 1.351550e+08 -33.0 Consumer Cyclical 283 BLDR 5 0.90 small-cap Short NaN -5.0 1.120707e+08 -27.0 Industrials 319 PLNT 3 -2.14 small-cap Short NaN -3.0 7.845036e+07 -28.0 Consumer Cyclical 291 YY 4 -7.29 small-cap Short NaN -4.0 7.754547e+07 -72.0 Communication Services 296 MLCO 1 0.00 small-cap Short NaN -1.0 7.153496e+07 -48.0 Consumer Cyclical 318 AZEK 2 0.08 small-cap Short NaN -2.0 6.704033e+07 -28.0 Industrials 266 ARMK 2 -1.29 small-cap Short NaN -2.0 2.327148e+07 -7.0 Consumer Cyclical 303 ALLK 2 -1.40 small-cap Short NaN -2.0 2.104975e+07 -136.0 Healthcare 364 TNET 1 0.00 small-cap Short NaN -1.0 1.291928e+07 -41.0 Industrials 305 ANGI 3 -1.96 small-cap Short NaN -3.0 6.742713e+06 -53.0 Communication Services 326 ESLT 5 -0.02 small-cap Short NaN -5.0 4.443781e+06 -31.0 Industrials 363 ENIC 1 0.00 small-cap Short NaN -1.0 2.019581e+06 -136.0 Utilities Mean Return: -1.8933333333333333 Mean Day/Week: 3.4444444444444446 Accuracy:0.7777777777777778 *******************Part 2.7 Small Cap Long Maintaiance********************* small_long_signal_maintainance Symbol Day Return Market Cap Long/Short score MACD Signal Count Market Value Span Signal Count industry 350 BIGC 11 9.34 small-cap Long NaN 31.0 3.960449e+08 22.0 Technology 253 NTRA 9 -2.56 small-cap Long NaN 23.0 2.031572e+08 23.0 Healthcare 246 VST 8 5.60 small-cap Long NaN 33.0 1.867554e+08 21.0 Utilities 256 DBX 20 6.96 small-cap Long NaN 32.0 1.584479e+08 37.0 Technology 339 ASAN 23 56.06 small-cap Long NaN 33.0 1.331060e+08 34.0 Technology 277 DECK 8 2.61 small-cap Long NaN 11.0 1.165992e+08 12.0 Consumer Cyclical 268 SMAR 13 6.59 small-cap Long NaN 31.0 1.028315e+08 18.0 Technology 286 FVRR 9 -2.06 small-cap Long NaN 29.0 9.756933e+07 14.0 Communication Services 345 UPWK 11 3.98 small-cap Long NaN 29.0 6.760952e+07 23.0 Industrials 287 SYNH 7 3.98 small-cap Long NaN 7.0 6.341734e+07 21.0 Healthcare 288 ATH 6 1.56 small-cap Long NaN 6.0 6.302249e+07 77.0 Financial Services 315 VRT 37 15.06 small-cap Long NaN 37.0 5.493410e+07 67.0 Industrials 280 LSPD 14 7.26 small-cap Long NaN 31.0 4.980732e+07 33.0 Technology 337 VRNS 7 0.34 small-cap Long NaN 28.0 4.434852e+07 17.0 Technology 359 OMCL 10 1.66 small-cap Long NaN 22.0 3.794028e+07 35.0 Healthcare 265 BRKR 19 8.19 small-cap Long NaN 20.0 3.713024e+07 77.0 Healthcare 330 GMED 9 9.17 small-cap Long NaN 11.0 3.620138e+07 63.0 Healthcare 336 TNDM 9 3.64 small-cap Long NaN 26.0 3.384105e+07 19.0 Healthcare 314 ARES 9 6.91 small-cap Long NaN 28.0 3.227077e+07 23.0 Financial Services 249 FWONK 9 2.72 small-cap Long NaN 12.0 2.790761e+07 10.0 Communication Services 278 DNLI 25 18.84 small-cap Long NaN 59.0 2.526811e+07 31.0 Healthcare 300 MANH 29 9.03 small-cap Long NaN 29.0 2.353458e+07 50.0 Technology 259 KOF 27 7.13 small-cap Long NaN 41.0 9.457249e+06 65.0 Consumer Defensive 250 FWONA 9 3.59 small-cap Long NaN 10.0 3.276782e+06 12.0 Communication Services 352 DSGX 9 3.50 small-cap Long NaN 23.0 2.366280e+06 23.0 Technology 310 PBCTP 14 2.99 small-cap Long NaN 35.0 1.373439e+06 37.0 Financial Services 313 JSM 27 2.50 small-cap Long NaN 30.0 3.199107e+05 46.0 unknown Mean Return: 7.207037037037037 Mean Day/Week: 14.37037037037037 Accuracy:0.9259259259259259 *******************Part 2.8 Small Cap Short Maintaiance********************* small_short_signal_maintainance Symbol Day Return Market Cap Long/Short score MACD Signal Count Market Value Span Signal Count industry 328 ALK 14 -8.14 small-cap Short NaN -60.0 1.271235e+08 -25.0 Industrials 297 RL 7 -3.19 small-cap Short NaN -33.0 1.035966e+08 -19.0 Consumer Cyclical 258 WU 15 -3.90 small-cap Short NaN -46.0 1.022253e+08 -33.0 Financial Services 349 HBI 12 -5.23 small-cap Short NaN -40.0 7.743727e+07 -27.0 Consumer Cyclical 335 PBCT 9 -4.75 small-cap Short NaN -32.0 7.282169e+07 -14.0 Financial Services 316 PFGC 9 -6.05 small-cap Short NaN -15.0 7.103030e+07 -41.0 Consumer Defensive 262 KGC 8 1.27 small-cap Short NaN -20.0 6.875988e+07 -14.0 Basic Materials 248 AU 6 6.24 small-cap Short NaN -23.0 6.790228e+07 -17.0 Basic Materials 351 VAC 15 -7.99 small-cap Short NaN -73.0 6.582269e+07 -35.0 Consumer Cyclical 308 EXEL 7 -0.19 small-cap Short NaN -34.0 6.265147e+07 -30.0 Healthcare 361 AER 8 -7.85 small-cap Short NaN -60.0 5.115426e+07 -20.0 Industrials 357 BTG 8 -1.88 small-cap Short NaN -24.0 4.981618e+07 -14.0 Basic Materials 293 RS 7 1.42 small-cap Short NaN -34.0 4.873970e+07 -14.0 Basic Materials 321 HTA 7 -0.70 small-cap Short NaN -10.0 4.495896e+07 -15.0 Real Estate 294 PAAS 12 -1.92 small-cap Short NaN -24.0 4.477713e+07 -18.0 Basic Materials 252 GL 13 2.92 small-cap Short NaN -33.0 4.413243e+07 -14.0 Financial Services 344 PSTH 8 -3.56 small-cap Short NaN -22.0 4.412815e+07 -136.0 Financial Services 301 RGA 14 -2.45 small-cap Short NaN -55.0 3.843993e+07 -22.0 Financial Services 343 SNV 12 -4.72 small-cap Short NaN -40.0 3.689986e+07 -14.0 Financial Services 324 CDK 12 -2.00 small-cap Short NaN -16.0 3.353105e+07 -18.0 Technology 309 CASY 18 -6.74 small-cap Short NaN -47.0 3.338822e+07 -20.0 Consumer Defensive 272 ATR 11 -0.42 small-cap Short NaN -35.0 3.100409e+07 -17.0 Consumer Cyclical 322 PB 7 -2.90 small-cap Short NaN -14.0 2.646706e+07 -14.0 Financial Services 282 NLSN 9 -2.76 small-cap Short NaN -30.0 2.628918e+07 -14.0 Industrials 333 TKR 12 -2.29 small-cap Short NaN -32.0 2.486735e+07 -16.0 Industrials 355 BWXT 15 -7.35 small-cap Short NaN -51.0 1.909776e+07 -34.0 Industrials 348 MDU 11 1.13 small-cap Short NaN -39.0 1.904616e+07 -14.0 Basic Materials 289 NFE 8 -7.51 small-cap Short NaN -8.0 1.683777e+07 -136.0 Utilities 342 PRI 7 -3.43 small-cap Short NaN -20.0 1.455663e+07 -14.0 Financial Services 311 GLPG 10 -3.38 small-cap Short NaN -10.0 1.183789e+07 -17.0 Healthcare 353 BOKF 7 -5.53 small-cap Short NaN -20.0 1.175372e+07 -7.0 Financial Services 247 BSAC 8 -9.34 small-cap Short NaN -8.0 1.097463e+07 -42.0 Financial Services 275 AEG 13 -3.29 small-cap Short NaN -31.0 9.973423e+06 -36.0 Financial Services 254 MNSO 11 -16.21 small-cap Short NaN -11.0 9.140457e+06 -30.0 Consumer Cyclical Mean Return: -3.6085294117647058 Mean Day/Week: 10.294117647058824 Accuracy:0.8529411764705882 ************************************** ************************************** ************************************** *******************Part 3.0 Penny Cap Industry Overiew********************* penny_industry_uptrending_count tickers industry Basic Materials 1 Communication Services 4 Consumer Cyclical 11 Consumer Defensive 3 Energy 4 Financial Services 37 Healthcare 27 Industrials 16 Real Estate 10 Technology 32 Utilities 2 unknown 6 **************************************** penny_industry_downtrending_count tickers industry Basic Materials 20 Communication Services 8 Consumer Cyclical 38 Consumer Defensive 15 Energy 6 Financial Services 86 Healthcare 34 Industrials 46 Real Estate 10 Technology 20 Utilities 11 unknown 4 *******************Part 3.1 Penny Cap Long Entry SPAN MACD********************* penny_long_signal_entry_span_macd Symbol Day Return Market Cap Long/Short score MACD Signal Count Market Value Span Signal Count industry 610 SHEN 3 -2.41 penny-cap Long NaN 3.0 6.116809e+07 5.0 Communication Services 773 NMFC 2 -0.89 penny-cap Long NaN 2.0 4.504497e+06 5.0 Financial Services Mean Return: -1.6500000000000001 Mean Day/Week: 2.5 Accuracy:0.0 *******************Part 3.2 Penny Cap Short Entry SPAN MACD********************* penny_short_signal_entry_span_macd Symbol Day Return Market Cap Long/Short score MACD Signal Count Market Value Span Signal Count industry 576 OM 1 0.00 penny-cap Short NaN -2.0 2.828697e+07 -5.0 Healthcare 406 GOCO 3 -2.20 penny-cap Short NaN -3.0 1.298989e+07 -5.0 Financial Services 769 CERS 1 0.00 penny-cap Short NaN -1.0 8.142006e+06 -3.0 Healthcare 605 MFGP 3 -4.81 penny-cap Short NaN -4.0 6.191008e+06 -4.0 Technology Mean Return: -3.505 Mean Day/Week: 4.0 Accuracy:1.0 *******************Part 3.3 Penny Cap Long Entry SPAN********************* penny_long_signal_entry_span Symbol Day Return Market Cap Long/Short score MACD Signal Count Market Value Span Signal Count industry 610 SHEN 3 -2.41 penny-cap Long NaN 3.0 6.116809e+07 5.0 Communication Services 773 NMFC 2 -0.89 penny-cap Long NaN 2.0 4.504497e+06 5.0 Financial Services Mean Return: -1.6500000000000001 Mean Day/Week: 2.5 Accuracy:0.0 *******************Part 3.4 Penny Cap Short Entry SPAN********************* penny_short_signal_entry_span Symbol Day Return Market Cap Long/Short score MACD Signal Count Market Value Span Signal Count industry 576 OM 1 0.00 penny-cap Short NaN -2.0 2.828697e+07 -5.0 Healthcare 450 UMBF 2 -0.34 penny-cap Short NaN -72.0 2.111981e+07 -2.0 Financial Services 406 GOCO 3 -2.20 penny-cap Short NaN -3.0 1.298989e+07 -5.0 Financial Services 717 GWB 1 0.00 penny-cap Short NaN -40.0 1.106132e+07 -3.0 Financial Services 769 CERS 1 0.00 penny-cap Short NaN -1.0 8.142006e+06 -3.0 Healthcare 605 MFGP 3 -4.81 penny-cap Short NaN -4.0 6.191008e+06 -4.0 Technology Mean Return: -2.4499999999999997 Mean Day/Week: 3.6666666666666665 Accuracy:1.0 *******************Part 3.5 Penny Cap Long Entry MACD********************* penny_long_signal_entry_macd Symbol Day Return Market Cap Long/Short score MACD Signal Count Market Value Span Signal Count industry 610 SHEN 3 -2.41 penny-cap Long NaN 3.0 6.116809e+07 5.0 Communication Services 534 KYMR 4 -6.85 penny-cap Long NaN 4.0 3.130641e+07 29.0 Healthcare 454 ALKS 3 0.75 penny-cap Long NaN 3.0 2.892457e+07 52.0 Healthcare 709 TSLX 3 2.01 penny-cap Long NaN 3.0 1.933050e+07 29.0 Financial Services 412 WTS 5 0.03 penny-cap Long NaN 5.0 1.689504e+07 53.0 Industrials 666 CCCC 1 0.00 penny-cap Long NaN 1.0 1.340942e+07 25.0 Healthcare 632 DEA 1 0.00 penny-cap Long NaN 1.0 8.378806e+06 9.0 Real Estate 773 NMFC 2 -0.89 penny-cap Long NaN 2.0 4.504497e+06 5.0 Financial Services 751 NMZ 5 1.04 penny-cap Long NaN 5.0 3.155733e+06 64.0 Financial Services 731 BXMX 3 -0.55 penny-cap Long NaN 3.0 2.150730e+06 77.0 Financial Services 559 NUV 3 -0.77 penny-cap Long NaN 3.0 2.024907e+06 37.0 Financial Services 429 ESGRO 3 -0.35 penny-cap Long NaN 3.0 5.913285e+05 9.0 Financial Services 643 NSS 4 -0.15 penny-cap Long NaN 4.0 5.447360e+05 77.0 unknown Mean Return: -0.7400000000000001 Mean Day/Week: 3.6363636363636362 Accuracy:0.36363636363636365 *******************Part 3.6 Penny Cap Short Entry MACD********************* penny_short_signal_entry_macd Symbol Day Return Market Cap Long/Short score MACD Signal Count Market Value Span Signal Count industry 401 TRIP 2 -2.21 penny-cap Short NaN -2.0 7.022489e+07 -49.0 Consumer Cyclical 405 DOYU 2 -0.90 penny-cap Short NaN -2.0 4.605631e+07 -74.0 Communication Services 456 IRBT 3 -2.13 penny-cap Short NaN -3.0 3.640444e+07 -136.0 Technology 529 NUVA 3 0.20 penny-cap Short NaN -3.0 3.459089e+07 -6.0 Healthcare 576 OM 1 0.00 penny-cap Short NaN -2.0 2.828697e+07 -5.0 Healthcare 672 BALY 1 0.00 penny-cap Short NaN -1.0 2.506207e+07 -56.0 Consumer Cyclical 492 PCRX 2 -1.56 penny-cap Short NaN -2.0 2.430339e+07 -67.0 Healthcare 473 TRTN 1 0.00 penny-cap Short NaN -1.0 2.208495e+07 -48.0 Industrials 733 GNOG 2 -7.66 penny-cap Short NaN -2.0 1.876755e+07 -136.0 Consumer Cyclical 510 AVAV 4 -2.40 penny-cap Short NaN -5.0 1.709780e+07 -8.0 Industrials 455 SLQT 1 0.00 penny-cap Short NaN -1.0 1.707821e+07 -41.0 Financial Services 419 RSI 1 0.00 penny-cap Short NaN -1.0 1.588752e+07 -136.0 Consumer Cyclical 802 WPRT 1 0.00 penny-cap Short NaN -1.0 1.506239e+07 -74.0 Consumer Cyclical 486 AMRN 1 0.00 penny-cap Short NaN -1.0 1.370352e+07 -136.0 Healthcare 406 GOCO 3 -2.20 penny-cap Short NaN -3.0 1.298989e+07 -5.0 Financial Services 698 MASS 3 -2.55 penny-cap Short NaN -3.0 1.109120e+07 -136.0 Healthcare 592 THRM 2 -1.66 penny-cap Short NaN -2.0 1.085126e+07 -17.0 Consumer Cyclical 625 CALM 2 0.37 penny-cap Short NaN -2.0 1.073592e+07 -55.0 Consumer Defensive 399 NEU 1 0.00 penny-cap Short NaN -1.0 1.040462e+07 -136.0 Basic Materials 769 CERS 1 0.00 penny-cap Short NaN -1.0 8.142006e+06 -3.0 Healthcare 706 NRIX 3 -7.91 penny-cap Short NaN -3.0 8.107440e+06 -136.0 Healthcare 678 ATSG 2 -1.30 penny-cap Short NaN -2.0 8.094297e+06 -54.0 Industrials 813 VITL 4 0.61 penny-cap Short NaN -4.0 7.822979e+06 -76.0 Consumer Defensive 785 TCMD 2 -1.66 penny-cap Short NaN -2.0 6.821210e+06 -7.0 Healthcare 605 MFGP 3 -4.81 penny-cap Short NaN -4.0 6.191008e+06 -4.0 Technology 656 ALG 1 0.00 penny-cap Short NaN -1.0 5.884320e+06 -25.0 Industrials 665 ICLK 1 0.00 penny-cap Short NaN -1.0 5.548864e+06 -74.0 Communication Services 708 MRSN 2 0.00 penny-cap Short NaN -2.0 5.313368e+06 -136.0 Healthcare 686 LKFN 1 0.00 penny-cap Short NaN -1.0 5.071069e+06 -50.0 Financial Services 647 FMTX 3 -2.92 penny-cap Short NaN -5.0 4.424297e+06 -20.0 Healthcare 675 ARQT 2 -2.20 penny-cap Short NaN -2.0 3.873791e+06 -40.0 Healthcare 567 ALVR 1 0.00 penny-cap Short NaN -1.0 3.108629e+06 -136.0 Healthcare 649 CLBK 2 0.65 penny-cap Short NaN -2.0 3.045979e+06 -25.0 Financial Services 772 JOUT 2 -0.58 penny-cap Short NaN -2.0 2.648402e+06 -35.0 Consumer Cyclical 759 ATRI 1 0.00 penny-cap Short NaN -1.0 2.458572e+06 -53.0 Healthcare 638 SPNS 5 0.39 penny-cap Short NaN -5.0 1.927410e+06 -45.0 Technology 434 MOR 5 -1.94 penny-cap Short NaN -5.0 1.117870e+06 -136.0 Healthcare Mean Return: -1.9291304347826084 Mean Day/Week: 3.347826086956522 Accuracy:0.7391304347826086 *******************Part 3.7 Penny Cap Long Maintainance********************* penny_long_signal_maintainance Symbol Day Return Market Cap Long/Short score MACD Signal Count Market Value Span Signal Count industry 507 JKS 8 37.38 penny-cap Long NaN 34.0 4.588714e+08 10.0 Technology 413 NTLA 10 66.52 penny-cap Long NaN 26.0 4.092060e+08 31.0 Healthcare 597 RIG 10 5.87 penny-cap Long NaN 10.0 1.409823e+08 26.0 Energy 369 CROX 9 -0.21 penny-cap Long NaN 9.0 9.511519e+07 77.0 Consumer Cyclical 420 CELH 9 -4.13 penny-cap Long NaN 10.0 8.057658e+07 33.0 Consumer Defensive 546 RVLV 15 15.41 penny-cap Long NaN 28.0 7.159957e+07 38.0 Consumer Cyclical 443 SYNA 9 2.68 penny-cap Long NaN 23.0 6.559629e+07 23.0 Technology 661 IRWD 11 -2.05 penny-cap Long NaN 11.0 6.362037e+07 61.0 Healthcare 384 RPD 15 9.50 penny-cap Long NaN 33.0 6.215725e+07 37.0 Technology 552 CLNY 12 15.42 penny-cap Long NaN 13.0 6.041885e+07 66.0 Real Estate 394 JOBS 26 6.29 penny-cap Long NaN 65.0 5.758655e+07 45.0 Industrials 382 IIPR 7 2.97 penny-cap Long NaN 30.0 5.696160e+07 22.0 Real Estate 388 JCOM 19 11.29 penny-cap Long NaN 22.0 5.032561e+07 77.0 Technology 370 WK 15 15.44 penny-cap Long NaN 31.0 4.712893e+07 23.0 Technology 451 APLS 29 28.58 penny-cap Long NaN 59.0 4.473001e+07 36.0 Healthcare 756 RAVN 12 -0.56 penny-cap Long NaN 12.0 4.221503e+07 54.0 Industrials 608 DOMO 24 22.50 penny-cap Long NaN 32.0 3.770337e+07 33.0 Technology 441 OPCH 20 6.09 penny-cap Long NaN 29.0 3.734981e+07 22.0 Healthcare 461 SPT 24 31.56 penny-cap Long NaN 30.0 3.623230e+07 32.0 Technology 400 TRUP 21 20.81 penny-cap Long NaN 59.0 3.614376e+07 29.0 Financial Services 542 NSA 26 12.48 penny-cap Long NaN 26.0 3.517239e+07 77.0 Real Estate 720 PACK 11 0.59 penny-cap Long NaN 12.0 3.514453e+07 36.0 Consumer Cyclical 501 PHR 10 9.09 penny-cap Long NaN 29.0 3.490676e+07 21.0 Healthcare 616 DDS 12 11.69 penny-cap Long NaN 37.0 3.484323e+07 52.0 Consumer Cyclical 495 FRHC 15 9.64 penny-cap Long NaN 27.0 3.297124e+07 26.0 Financial Services 467 KTOS 6 -3.69 penny-cap Long NaN 24.0 3.053336e+07 9.0 Industrials 514 MIME 40 17.14 penny-cap Long NaN 67.0 2.995684e+07 42.0 Technology 554 MXL 10 4.61 penny-cap Long NaN 29.0 2.960982e+07 31.0 Technology 660 BOOT 10 -3.28 penny-cap Long NaN 10.0 2.796167e+07 77.0 Consumer Cyclical 577 MGY 12 2.83 penny-cap Long NaN 28.0 2.620590e+07 29.0 Energy 463 PZZA 17 3.15 penny-cap Long NaN 21.0 2.255367e+07 43.0 Consumer Cyclical 520 SMPL 7 2.12 penny-cap Long NaN 17.0 2.241178e+07 72.0 Consumer Defensive 411 KRNT 17 1.49 penny-cap Long NaN 31.0 2.225810e+07 29.0 Industrials 770 STAR 8 1.32 penny-cap Long NaN 18.0 2.205423e+07 20.0 Real Estate 816 CDMO 25 20.30 penny-cap Long NaN 25.0 2.156381e+07 77.0 Healthcare 368 GSHD 7 -2.73 penny-cap Long NaN 26.0 2.063679e+07 16.0 Financial Services 623 PRFT 61 27.04 penny-cap Long NaN 61.0 2.011220e+07 77.0 Technology 385 HLI 12 5.89 penny-cap Long NaN 39.0 1.992325e+07 39.0 Financial Services 685 CNST 19 0.95 penny-cap Long NaN 51.0 1.984187e+07 25.0 Healthcare 440 SVMK 9 7.59 penny-cap Long NaN 56.0 1.936393e+07 23.0 Technology 755 CRTO 8 2.62 penny-cap Long NaN 8.0 1.930592e+07 77.0 Communication Services 573 RMBS 14 3.89 penny-cap Long NaN 28.0 1.914285e+07 17.0 Technology 396 HCM 9 18.29 penny-cap Long NaN 9.0 1.912233e+07 10.0 Healthcare 732 BLFS 13 12.82 penny-cap Long NaN 33.0 1.895051e+07 16.0 Healthcare 631 TBIO 6 9.67 penny-cap Long NaN 25.0 1.863330e+07 11.0 Healthcare 752 VLRS 15 13.36 penny-cap Long NaN 15.0 1.811516e+07 77.0 Industrials 515 AMRC 24 13.85 penny-cap Long NaN 65.0 1.800896e+07 29.0 Industrials 392 HASI 6 0.84 penny-cap Long NaN 30.0 1.770772e+07 14.0 Real Estate 367 DAVA 35 27.11 penny-cap Long NaN 51.0 1.666022e+07 54.0 Technology 740 QADA 7 -0.39 penny-cap Long NaN 7.0 1.590147e+07 28.0 Technology 758 EVRI 12 3.98 penny-cap Long NaN 51.0 1.582872e+07 54.0 Consumer Cyclical 433 GOOS 6 -3.08 penny-cap Long NaN 10.0 1.393547e+07 9.0 Consumer Cyclical 606 SKY 13 4.89 penny-cap Long NaN 29.0 1.386960e+07 29.0 Consumer Cyclical 535 ATRC 9 3.64 penny-cap Long NaN 9.0 1.343731e+07 77.0 Healthcare 674 SYKE 12 -0.78 penny-cap Long NaN 13.0 1.343565e+07 13.0 Technology 425 SIGI 9 1.45 penny-cap Long NaN 9.0 1.332369e+07 12.0 Financial Services 655 ZUO 11 1.37 penny-cap Long NaN 17.0 1.296969e+07 17.0 Technology 477 CNS 41 15.70 penny-cap Long NaN 84.0 1.242378e+07 52.0 Financial Services 767 LNTH 14 12.77 penny-cap Long NaN 26.0 1.207244e+07 28.0 Healthcare 505 FSKR 12 2.00 penny-cap Long NaN 12.0 1.178254e+07 63.0 Financial Services 431 VICR 9 8.02 penny-cap Long NaN 31.0 1.134694e+07 26.0 Technology 722 FFG 17 0.38 penny-cap Long NaN 17.0 1.006323e+07 17.0 Financial Services 683 BSIG 11 1.63 penny-cap Long NaN 11.0 9.495389e+06 68.0 Financial Services 448 WNS 15 5.57 penny-cap Long NaN 32.0 9.477305e+06 33.0 Industrials 748 PRCH 6 2.06 penny-cap Long NaN 37.0 8.972799e+06 26.0 Technology 403 ALTR 9 -1.40 penny-cap Long NaN 9.0 8.661484e+06 13.0 Technology 783 ZUMZ 9 0.69 penny-cap Long NaN 10.0 8.056395e+06 12.0 Consumer Cyclical 744 INVA 12 1.17 penny-cap Long NaN 12.0 7.818925e+06 41.0 Healthcare 611 CVA 20 2.23 penny-cap Long NaN 20.0 7.805682e+06 47.0 Industrials 421 INOV 20 4.82 penny-cap Long NaN 20.0 6.900728e+06 77.0 Healthcare 644 CSII 12 1.33 penny-cap Long NaN 32.0 6.887880e+06 21.0 Healthcare 651 HSKA 20 12.47 penny-cap Long NaN 20.0 6.862987e+06 37.0 Healthcare 703 VCRA 7 1.43 penny-cap Long NaN 26.0 6.844974e+06 13.0 Technology 734 LASR 7 -1.25 penny-cap Long NaN 31.0 6.834323e+06 12.0 Technology 482 SOGO 7 2.81 penny-cap Long NaN 7.0 6.393488e+06 62.0 Communication Services 636 HLIO 8 3.77 penny-cap Long NaN 11.0 6.255645e+06 26.0 Industrials 488 CCU 8 6.30 penny-cap Long NaN 16.0 5.768695e+06 11.0 Consumer Defensive 511 BSTZ 15 6.16 penny-cap Long NaN 27.0 5.570316e+06 32.0 unknown 633 CRVL 11 8.37 penny-cap Long NaN 11.0 5.555535e+06 65.0 Financial Services 588 VRRM 16 4.00 penny-cap Long NaN 16.0 5.532555e+06 24.0 Industrials 600 EVA 10 1.51 penny-cap Long NaN 11.0 5.490971e+06 12.0 Basic Materials 693 EVV 23 3.13 penny-cap Long NaN 35.0 5.290038e+06 37.0 Financial Services 781 MDXG 6 -2.11 penny-cap Long NaN 27.0 5.041546e+06 18.0 Healthcare 408 NEA 9 1.16 penny-cap Long NaN 30.0 4.870779e+06 64.0 Financial Services 427 MSP 11 1.94 penny-cap Long NaN 11.0 4.141102e+06 37.0 Technology 478 NAD 33 4.13 penny-cap Long NaN 33.0 4.025670e+06 64.0 Financial Services 704 MLAB 8 1.03 penny-cap Long NaN 59.0 3.923717e+06 26.0 Technology 724 HYT 7 -0.31 penny-cap Long NaN 30.0 3.814973e+06 37.0 Financial Services 753 LINX 16 1.81 penny-cap Long NaN 50.0 3.751500e+06 46.0 Technology 680 BBN 21 3.07 penny-cap Long NaN 71.0 3.578820e+06 35.0 Financial Services 811 SPH 6 3.04 penny-cap Long NaN 37.0 3.243839e+06 21.0 Utilities 648 DCBO 12 13.89 penny-cap Long NaN 67.0 2.966008e+06 52.0 Technology 561 NZF 13 1.81 penny-cap Long NaN 27.0 2.726892e+06 64.0 Financial Services 735 NFJ 11 3.14 penny-cap Long NaN 23.0 2.177481e+06 68.0 Financial Services 765 FAX 11 1.15 penny-cap Long NaN 63.0 2.092567e+06 31.0 Financial Services 711 BTZ 10 2.79 penny-cap Long NaN 69.0 2.077513e+06 47.0 Financial Services 580 NAC 6 0.57 penny-cap Long NaN 6.0 2.034119e+06 64.0 Financial Services 791 HQH 10 2.13 penny-cap Long NaN 29.0 2.021043e+06 22.0 Financial Services 621 ADX 7 1.01 penny-cap Long NaN 7.0 2.016785e+06 77.0 Financial Services 730 USAC 6 0.63 penny-cap Long NaN 17.0 1.980762e+06 38.0 Energy 794 EOS 8 1.86 penny-cap Long NaN 20.0 1.978639e+06 33.0 Financial Services 788 CHY 9 0.80 penny-cap Long NaN 26.0 1.687084e+06 65.0 Financial Services 688 VCTR 11 4.94 penny-cap Long NaN 11.0 1.527401e+06 77.0 Financial Services 754 NRK 25 2.26 penny-cap Long NaN 25.0 4.297347e+05 61.0 Financial Services 745 QADB 7 -0.62 penny-cap Long NaN 22.0 1.173233e+05 27.0 Technology Mean Return: 6.560952380952381 Mean Day/Week: 13.80952380952381 Accuracy:0.8571428571428571 *******************Part 3.8 Penny Cap Short Maintainance********************* penny_short_signal_maintainance Symbol Day Return Market Cap Long/Short score MACD Signal Count Market Value Span Signal Count industry 372 NYCB 19 -4.68 penny-cap Short NaN -19.0 1.334982e+08 -45.0 Financial Services 539 SAVE 23 -19.16 penny-cap Short NaN -23.0 1.280830e+08 -41.0 Industrials 397 JBLU 16 -10.94 penny-cap Short NaN -61.0 1.063288e+08 -25.0 Industrials 445 SABR 7 -0.90 penny-cap Short NaN -8.0 9.145210e+07 -11.0 Technology 393 HFC 14 -7.61 penny-cap Short NaN -14.0 8.951360e+07 -45.0 Energy 423 PK 7 -7.04 penny-cap Short NaN -7.0 7.449850e+07 -8.0 Real Estate 462 ADS 11 -1.46 penny-cap Short NaN -35.0 7.412658e+07 -14.0 Financial Services 668 PLAY 18 -13.87 penny-cap Short NaN -18.0 6.448081e+07 -41.0 Consumer Cyclical 547 FLR 15 -10.48 penny-cap Short NaN -38.0 6.222325e+07 -38.0 Industrials 596 CAKE 14 -6.54 penny-cap Short NaN -40.0 6.154034e+07 -19.0 Consumer Cyclical 778 CVM 6 -31.75 penny-cap Short NaN -7.0 5.939462e+07 -7.0 Healthcare 415 KBH 11 -5.73 penny-cap Short NaN -54.0 5.067133e+07 -20.0 Consumer Cyclical 657 EB 16 -16.98 penny-cap Short NaN -71.0 4.670704e+07 -40.0 Technology 544 EAF 6 -1.25 penny-cap Short NaN -26.0 4.315839e+07 -14.0 Industrials 378 AUY 6 1.71 penny-cap Short NaN -18.0 4.198260e+07 -14.0 Basic Materials 471 CBRL 20 -7.60 penny-cap Short NaN -58.0 4.121897e+07 -41.0 Consumer Cyclical 566 FBC 6 0.78 penny-cap Short NaN -19.0 3.941321e+07 -15.0 Financial Services 617 ENDP 11 -18.74 penny-cap Short NaN -11.0 3.828162e+07 -71.0 Healthcare 571 ATI 7 3.89 penny-cap Short NaN -19.0 3.484262e+07 -14.0 Industrials 508 ISBC 7 -5.21 penny-cap Short NaN -73.0 3.342376e+07 -14.0 Financial Services 497 ALGT 25 -15.29 penny-cap Short NaN -74.0 3.106773e+07 -46.0 Industrials 512 COLB 14 -11.61 penny-cap Short NaN -75.0 3.005041e+07 -60.0 Financial Services 398 IDA 6 1.70 penny-cap Short NaN -39.0 2.986315e+07 -13.0 Utilities 437 AVT 12 -0.66 penny-cap Short NaN -46.0 2.889966e+07 -14.0 Technology 506 BXS 18 -11.81 penny-cap Short NaN -18.0 2.685256e+07 -55.0 Financial Services 453 EQC 6 0.88 penny-cap Short NaN -11.0 2.663068e+07 -11.0 Real Estate 410 VLY 7 -2.83 penny-cap Short NaN -70.0 2.626633e+07 -14.0 Financial Services 543 ABM 17 -10.15 penny-cap Short NaN -55.0 2.570632e+07 -27.0 Industrials 428 POR 9 -0.57 penny-cap Short NaN -48.0 2.406084e+07 -14.0 Utilities 414 HAIN 10 -0.90 penny-cap Short NaN -10.0 2.390211e+07 -56.0 Consumer Defensive 598 TSE 14 -0.91 penny-cap Short NaN -34.0 2.386053e+07 -35.0 Basic Materials 635 MDGL 11 -4.50 penny-cap Short NaN -33.0 2.336193e+07 -29.0 Healthcare 662 FSM 14 -11.13 penny-cap Short NaN -14.0 2.197013e+07 -24.0 Basic Materials 524 ASB 11 -6.78 penny-cap Short NaN -30.0 2.169158e+07 -14.0 Financial Services 509 DAN 12 -4.17 penny-cap Short NaN -20.0 2.116138e+07 -14.0 Consumer Cyclical 558 THS 28 -7.70 penny-cap Short NaN -30.0 2.095571e+07 -45.0 Consumer Defensive 374 SAGE 16 -6.81 penny-cap Short NaN -16.0 2.094768e+07 -17.0 Healthcare 522 ONB 14 -7.29 penny-cap Short NaN -72.0 2.083769e+07 -47.0 Financial Services 525 NWE 13 -0.25 penny-cap Short NaN -50.0 2.077946e+07 -30.0 Utilities 389 AL 19 -10.01 penny-cap Short NaN -19.0 2.055539e+07 -42.0 Industrials 615 BCC 11 0.15 penny-cap Short NaN -36.0 2.053144e+07 -17.0 Basic Materials 452 MDC 17 -1.96 penny-cap Short NaN -55.0 2.052934e+07 -26.0 Consumer Cyclical 607 SKYW 23 -12.86 penny-cap Short NaN -74.0 1.908692e+07 -47.0 Industrials 575 FULT 13 0.41 penny-cap Short NaN -73.0 1.886523e+07 -30.0 Financial Services 564 FUN 7 0.67 penny-cap Short NaN -7.0 1.828865e+07 -41.0 Consumer Cyclical 379 MMS 6 -0.16 penny-cap Short NaN -51.0 1.796557e+07 -7.0 Industrials 480 TRN 12 -3.66 penny-cap Short NaN -13.0 1.779841e+07 -14.0 Industrials 523 HMY 8 2.15 penny-cap Short NaN -23.0 1.728011e+07 -17.0 Basic Materials 476 FNB 7 -4.48 penny-cap Short NaN -73.0 1.721933e+07 -14.0 Financial Services 541 AVA 13 -1.41 penny-cap Short NaN -57.0 1.663224e+07 -26.0 Utilities 407 UBSI 7 -5.18 penny-cap Short NaN -30.0 1.586365e+07 -14.0 Financial Services 551 IBOC 12 -10.00 penny-cap Short NaN -34.0 1.539686e+07 -14.0 Financial Services 483 BOH 7 -2.78 penny-cap Short NaN -39.0 1.526595e+07 -41.0 Financial Services 447 HOMB 13 -2.07 penny-cap Short NaN -73.0 1.480371e+07 -20.0 Financial Services 517 UTZ 17 -4.55 penny-cap Short NaN -39.0 1.461875e+07 -38.0 Consumer Defensive 540 UCBI 7 -3.40 penny-cap Short NaN -30.0 1.429298e+07 -14.0 Financial Services 489 PDCO 9 -3.75 penny-cap Short NaN -10.0 1.414339e+07 -10.0 Healthcare 569 MSGE 7 -0.50 penny-cap Short NaN -14.0 1.394761e+07 -75.0 Communication Services 574 IOSP 14 -5.14 penny-cap Short NaN -19.0 1.362245e+07 -20.0 Basic Materials 699 CYTK 6 -6.06 penny-cap Short NaN -6.0 1.284589e+07 -27.0 Healthcare 536 AUB 11 -4.71 penny-cap Short NaN -25.0 1.278439e+07 -14.0 Financial Services 484 AGI 6 5.47 penny-cap Short NaN -21.0 1.277298e+07 -14.0 Basic Materials 553 WWW 14 -4.86 penny-cap Short NaN -39.0 1.274926e+07 -34.0 Consumer Cyclical 619 MTOR 15 -5.71 penny-cap Short NaN -15.0 1.271998e+07 -68.0 Consumer Cyclical 601 CMP 14 -4.66 penny-cap Short NaN -32.0 1.256572e+07 -17.0 Basic Materials 612 FMBI 21 -10.29 penny-cap Short NaN -70.0 1.204175e+07 -35.0 Financial Services 695 PRIM 14 -5.45 penny-cap Short NaN -14.0 1.192907e+07 -53.0 Industrials 459 NJR 6 1.60 penny-cap Short NaN -39.0 1.192800e+07 -11.0 Utilities 380 FTDR 6 -2.18 penny-cap Short NaN -21.0 1.187990e+07 -53.0 Consumer Cyclical 481 SR 11 1.52 penny-cap Short NaN -11.0 1.179107e+07 -11.0 Utilities 799 BJRI 19 -9.15 penny-cap Short NaN -75.0 1.157547e+07 -35.0 Consumer Cyclical 432 PSB 8 0.96 penny-cap Short NaN -15.0 1.103996e+07 -15.0 Real Estate 653 CVI 13 -4.31 penny-cap Short NaN -17.0 1.089405e+07 -66.0 Energy 381 ESGR 8 0.27 penny-cap Short NaN -69.0 1.049382e+07 -26.0 Financial Services 671 PATK 14 -1.98 penny-cap Short NaN -39.0 9.972076e+06 -24.0 Consumer Cyclical 654 LZB 15 -2.95 penny-cap Short NaN -39.0 9.760570e+06 -35.0 Consumer Cyclical 479 GATX 11 -3.99 penny-cap Short NaN -34.0 9.581133e+06 -14.0 Industrials 705 HOPE 13 -3.25 penny-cap Short NaN -70.0 9.413268e+06 -14.0 Financial Services 557 EQX 10 -5.19 penny-cap Short NaN -15.0 9.396215e+06 -14.0 Basic Materials 550 FIBK 20 -9.29 penny-cap Short NaN -74.0 9.391666e+06 -41.0 Financial Services 681 BV 13 1.80 penny-cap Short NaN -47.0 9.326887e+06 -20.0 Industrials 532 CVBF 13 -3.02 penny-cap Short NaN -14.0 9.312522e+06 -14.0 Financial Services 527 CATY 7 -5.67 penny-cap Short NaN -19.0 9.226171e+06 -7.0 Financial Services 663 NWBI 13 0.37 penny-cap Short NaN -13.0 9.110317e+06 -14.0 Financial Services 784 ACRS 21 -7.19 penny-cap Short NaN -60.0 9.056139e+06 -42.0 Healthcare 812 ENTA 7 -4.10 penny-cap Short NaN -42.0 8.891413e+06 -36.0 Healthcare 692 CGEM 13 3.70 penny-cap Short NaN -13.0 8.804253e+06 -124.0 Healthcare 652 SBCF 13 -2.37 penny-cap Short NaN -35.0 8.709068e+06 -14.0 Financial Services 563 RUSHA 14 -4.21 penny-cap Short NaN -55.0 8.704361e+06 -25.0 Consumer Cyclical 696 TBK 13 -2.12 penny-cap Short NaN -52.0 8.478999e+06 -35.0 Financial Services 789 AMSF 12 -1.60 penny-cap Short NaN -33.0 8.401349e+06 -23.0 Financial Services 613 BANF 19 -8.23 penny-cap Short NaN -35.0 8.394247e+06 -31.0 Financial Services 533 SCL 11 -3.51 penny-cap Short NaN -31.0 8.375138e+06 -14.0 Basic Materials 583 AVNS 7 -2.40 penny-cap Short NaN -7.0 8.236448e+06 -136.0 Healthcare 764 PLUS 26 -7.30 penny-cap Short NaN -40.0 8.212635e+06 -34.0 Technology 537 XNCR 7 -3.74 penny-cap Short NaN -7.0 7.601818e+06 -136.0 Healthcare 750 TBPH 8 -9.48 penny-cap Short NaN -8.0 7.448825e+06 -38.0 Healthcare 641 FBK 21 -10.98 penny-cap Short NaN -73.0 7.378468e+06 -50.0 Financial Services 738 EHTH 6 -7.13 penny-cap Short NaN -46.0 7.244602e+06 -24.0 Financial Services 700 NWN 7 -1.58 penny-cap Short NaN -51.0 7.217620e+06 -13.0 Utilities 595 PVG 9 -1.23 penny-cap Short NaN -24.0 7.116775e+06 -21.0 Basic Materials 741 HURN 7 -4.04 penny-cap Short NaN -32.0 6.859041e+06 -17.0 Industrials 687 AMWD 8 -4.67 penny-cap Short NaN -47.0 6.723473e+06 -39.0 Consumer Cyclical 485 NG 8 5.82 penny-cap Short NaN -20.0 6.689454e+06 -15.0 Basic Materials 593 FRME 19 -8.07 penny-cap Short NaN -72.0 6.618244e+06 -31.0 Financial Services 694 NBTB 14 -8.07 penny-cap Short NaN -30.0 6.577094e+06 -30.0 Financial Services 555 MANU 6 -1.77 penny-cap Short NaN -6.0 6.567624e+06 -46.0 Consumer Cyclical 810 PRA 14 -8.04 penny-cap Short NaN -72.0 6.381546e+06 -41.0 Financial Services 504 BVN 6 -0.62 penny-cap Short NaN -18.0 5.717183e+06 -16.0 Basic Materials 646 CFFN 30 -6.61 penny-cap Short NaN -30.0 5.666427e+06 -65.0 Financial Services 639 TRMK 14 -5.35 penny-cap Short NaN -69.0 5.648301e+06 -30.0 Financial Services 629 HTLF 6 -3.58 penny-cap Short NaN -20.0 5.601914e+06 -8.0 Financial Services 729 NXGN 7 -0.14 penny-cap Short NaN -11.0 5.476125e+06 -136.0 Healthcare 723 CVGW 20 -9.80 penny-cap Short NaN -50.0 5.286017e+06 -47.0 Consumer Defensive 614 PRK 14 -8.03 penny-cap Short NaN -20.0 5.275379e+06 -47.0 Financial Services 779 SAFT 13 -2.63 penny-cap Short NaN -30.0 5.210656e+06 -26.0 Financial Services 797 NBHC 13 -1.56 penny-cap Short NaN -73.0 4.877302e+06 -31.0 Financial Services 682 WABC 19 -6.79 penny-cap Short NaN -74.0 4.806169e+06 -31.0 Financial Services 493 ADV 7 -4.78 penny-cap Short NaN -41.0 4.707873e+06 -15.0 Communication Services 790 ORIC 23 -3.16 penny-cap Short NaN -23.0 4.573412e+06 -136.0 Healthcare 684 HTLD 34 -6.59 penny-cap Short NaN -54.0 4.408062e+06 -40.0 Industrials 548 MEOH 14 -0.39 penny-cap Short NaN -32.0 4.337223e+06 -41.0 Basic Materials 801 AKRO 6 -5.90 penny-cap Short NaN -6.0 4.108537e+06 -11.0 Healthcare 775 OCFC 14 -7.39 penny-cap Short NaN -69.0 3.744564e+06 -43.0 Financial Services 727 KROS 9 -8.55 penny-cap Short NaN -9.0 3.638647e+06 -47.0 Healthcare 777 CHCO 7 -2.76 penny-cap Short NaN -71.0 3.454615e+06 -50.0 Financial Services 677 NTB 13 -1.16 penny-cap Short NaN -40.0 3.426176e+06 -31.0 Financial Services 768 TCBK 13 -3.45 penny-cap Short NaN -19.0 3.203457e+06 -14.0 Financial Services 712 TRS 8 -3.93 penny-cap Short NaN -19.0 2.964814e+06 -13.0 Industrials 807 MATW 14 -7.05 penny-cap Short NaN -73.0 2.368581e+06 -31.0 Industrials 659 KRO 12 -5.22 penny-cap Short NaN -38.0 2.079267e+06 -22.0 Basic Materials 793 FOR 18 -4.51 penny-cap Short NaN -43.0 2.017541e+06 -32.0 Real Estate 796 PFC 7 -6.46 penny-cap Short NaN -74.0 1.696843e+06 -49.0 Financial Services 713 WMK 6 0.07 penny-cap Short NaN -6.0 1.612390e+06 -55.0 Consumer Defensive 446 IFS 8 -5.23 penny-cap Short NaN -19.0 1.297286e+06 -22.0 Financial Services 578 CENT 7 -7.70 penny-cap Short NaN -58.0 1.205450e+06 -20.0 Consumer Defensive 562 RUSHB 14 -6.23 penny-cap Short NaN -58.0 7.862662e+05 -25.0 Consumer Cyclical 726 NEXA 15 4.06 penny-cap Short NaN -19.0 7.413513e+05 -20.0 Basic Materials 584 UZC 13 0.04 penny-cap Short NaN -36.0 6.440420e+05 -121.0 unknown 689 MNTK 12 -18.30 penny-cap Short NaN -12.0 3.908661e+05 -115.0 Utilities 502 TCBIL 12 0.12 penny-cap Short NaN -37.0 3.602880e+05 -125.0 unknown 670 SBLKZ 9 0.08 penny-cap Short NaN -9.0 2.905885e+05 -29.0 unknown 624 ITCB 7 -10.38 penny-cap Short NaN -50.0 1.032444e+05 -42.0 Financial Services 586 HWCPL 11 -0.32 penny-cap Short NaN -31.0 4.250000e+04 -33.0 unknown 503 HKIB 13 -7.54 penny-cap Short NaN -54.0 3.135000e+04 -33.0 Financial Services 500 TCBIP 16 -0.10 penny-cap Short NaN -32.0 0.000000e+00 -125.0 Financial Services 658 PRTC 13 -3.81 penny-cap Short NaN -13.0 0.000000e+00 -39.0 Healthcare Mean Return: -4.677278911564627 Mean Day/Week: 12.34013605442177 Accuracy:0.8435374149659864 ************************************** ************************************** ************************************** Error: []

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tovejanssonblogg · 4 years

Text

Mumin: det visuella i Tove Janssons romaner

En sak som skiljer muminböckerna från Toves andra skönlitterära texter är det faktum att romanerna inkluderar teckningar. Svartvita bläckmålningar av trollet, de övriga figurerna och den omgivning de placerats i. Detta kan man kanske se på som tribut till mumintrollets framkomst, det är nämligen så att den första instansen av en muminfigur är den som då kallades ”snorken” och fungerade som Toves signatur. Snorken kunde man återfinna i de konstverk Tove ritat till tidningen Garm (Boel Westin: 1988: s. 77) där den muminlika figuren interagerade med hennes ritade sidor. Snorken var ett svart troll med horn snarare än öron, men bar en mycket liknande profil till vad som senare kom att bli mumins. År 1945 debuterar Tove med boken Småtrollen och den stora översvämningen, en fullt illustrerad barnbok med ett mumintroll som ännu inte ser ut som den gör idag. Trollen (både mumin och mamman) hade längre, smalare nosar som snarare liknade stora näsor – men för övrigt påminner de om den modernare, rundade mumin.

Trots att Småtrollen och den stora översvämningen var Toves första muminbok var hon inte en nybörjare, redan under sin uppväxt skrev hon ett flertal barnböcker och noveller (Boel Westin: 1988: s. 97). Med en kombination av denna inövade författarförmåga, hennes inlära konstnärskap samt kunskap om boktryckning (Sirke Happonen: 2014 a: s. 37) skapades en expertis inom ett område som tangerar såväl ord som bild: bilderboken. I de tryckta böckerna syns det tydligt hur Tove förstår böckernas layout – bilderna är av varierande storlek och position på sidorna, vilket påverkar deras stämning. Och det är just detta Tove uppnår med denna kombination av ord och bild, stämning. Vare sig det är konstrast och skuggor som skapar en mystisk och skrämmande skog (Sirke Happonen: 2014 a: s. 49) eller tecknade dansscener i vilka var och en av figurerna har sin egen rörelse och glädjeyttring (Sirke Happonen: 2011: s. 397).

Särskilt landskapen beskrivs i djupet av kombinationen ord och bild; i sin text om Toves illustrationer ger Sirke Happonen (2014 b: s. 192 – 196) en extensiv analys av den ”sista muminfesten”. I Toves sista muminroman, Sent i november, firas den frånvarande muminfamiljen genom en middag i deras ära. Gästerna (Snusmumriken, Hemulen, Filifjonkan, Onkelskrutten, Mymlan och homsan Toft) sitter alla kring ett bord och utför familjens middagstraditioner, som bäst de kan. Men istället för att skåla i familjens ära tar de istället en tyst minut, och den ritade bilden av scenen tycks för ljus. Allting är upplyst, det finns ingen fokaliseringspunkt, alltså inget egentligt fokus (Happonen: 2014 b: s.194). Med bilden till stöd för detta ofokuserade narrativ inser läsaren att karaktärerna själva upplever sig vara vilsekomna – de vet inte riktigt varför de är där eller vad de håller på med. Samspelet mellan bild och ord förstärker upplevelsen av vilsenhet, detta exempel är bara ett av de många man kan ge i vilka ord och bild vävs samman.

Gällande det visuella är det heller inte enbart teckningar som Tove använder för att skapa stämning och inlevelse, utan man kan även se på textformerna. I boken Hur gick det sen? har exempelvis alla karaktärer sin egen font. Muminmamman talar med kursiv stil, och lilla mys repliker är alla mycket små. Dessutom är texten skriven i versform med lekfulla slutrim, vilket ”lockar läsaren att läsa och tralla dem högt” (Hanna Lähdenperä: 2013: s.134). Detta är ett sätt Tove lekt med texten, men även sidlayout och något så enkelt som mellanslag har stor effekt. I en scen ur Sent i november använder Tove ett utropstecken som full stopp på en mening som tycks vilja fortsätta, jag citerar: ” […] nu slutade Snusmumriken att spela med ett högt rop! och Mymlan skrattade av stolthet” (Sent i november: 1970: s. 127). Meningen fortsätter utan stor bokstav efter utropet, vilket berättar åt läsaren att det inte är en ny mening, utan det var en temporär paus i textens flyt. Detta ger läsaren en upplevelse av att ha hört ett rop, vilket tillfälligtvis framkallat tystnad men senare fortsätter i samma takt.

Det finns givetvis massvis fler intressanta exempel på de gånger ord och bild samverkat för att betona, förstärka eller förtydliga en viss stämning – men jag valde dessa eftersom de tydligast presenterade de olika sätt Tove använder sin kunskap om såväl författarskap, konstnärskap och textbehandling. Denna egenskap att kombinera ord och bild är kanske den Tove hyllats mest för, vilken man kan se i titeln av en av de biografier jag läst om henne – nämligen Tove Jansson - Ord, bild, liv (Boel Westin: 2007). Personligen har jag imponerats mest av Toves figurskrivning och temabehandling, men speciellt i de tidigaste bilderböckerna har teckningarna t.o.m. en central roll. För att avsluta detta inlägg vill jag bifoga en stämningsfull teckning från romanen Trollvinter.

#ToveJansson

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freswe · 4 years

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Rop på hjälp Hej alla mina Gotlands kompisar och vänner . Nu!!! äldre boende på Fältgatan 75/77 (Mitt jobb) behöver ditt stöd eller hjälp . Vi Tänker bygga en eller flera avskärmningsvägg (ar) där anhöriga och boenden kan träffas utan risk av smitta (covid 19 ) så vi behöver att nån skänker eller Säljer för en billig penning några Plexiglas frontplast, eller plastglas samma som man använder som till Gatupratare i olika butiker . Super tacksam med allt hjälp .mvh Äldre boende på Fältgatan 75/77 . Kontakt : 75 huset avd ; 1 tel: 0498204508 Ps : dela gärna vidare (Gotland)❤️ (på/i Fältgatan) https://www.instagram.com/p/CAnBoOgBZgwEbRkpz_Smqz1irFGoCEKWpF9AiI0/?igshid=1fwlpbsfq0h0p

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daydr-eam · 7 years

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“should we know us a little better” tag 📜

RULES: you must answer these 92 statements and tag 20 people maaaan this is long

tagged by @shownud (jasdbasd thanks gurl ilu 🌺🌼💕🌷)

THE LAST:

1. Drink: monsta

2. Phone call: my friend

3. Text message: "why are you taking the birds??”

4. Song you listened to: married to the music - shinee

5. Time you cried: this is embarrassing but last night a tear fell out of my eye as i was looking at kihyun pics

6. Dated someone twice: no

7. Kissed someone and regretted it: yes

8. Been cheated on: no

9. Lost someone special: i guess

10. Been depressed: yes

11. Gotten drunk and thrown up: do not...... eat oreos...... after getting very drunk (you will throw up blackness)

LIST 3 FAVORITE COLORS:

12-14: green, blue, pink

IN THE LAST YEAR HAVE YOU:

15. Made new friends: yes everyone on tumblr 🌷💕

16. Fallen out of love: i doubt it

17. Laughed until you cried: most likely

18. Found out someone was talking about you: yes

19. Met someone who changed you: @moonbebe (for the worse probably)

20. Found out who your friends are: idk dude

21. Kissed someone on your Facebook list: fml

GENERAL:

22. How many of your Facebook friends do you know in real life: almost all of them

23. Do you have any pets: i have leo my kit, i have rosie my doog, i have mango and peach my boods and i have a fat fish named oscar

24. Do you want to change your name: yeah kind of, i hate my name for some reason

25. What did you do for your last Birthday: probably sat in my room alone playing ps1 i usually do that

26. What time did you wake up: like 1:30pm lol rop

27. What were you doing at midnight last night: i’m pretty sure i was making thos bomb ass gifsets

28. Name something you can’t wait for: me and kihyuns inevitable wedding

29. When was the last time you saw your mom: about 2 months ago

30. What is one thing you wish you could change in your life: ill be typing forever ha

31. What are you listening right now: love sick by shinee 🌈 (you can tell what album im listening to during this lfmao)

32. Have you ever talked to a person named Tom: yes???

33. Something that is getting on your nerves: ppl who think veganism is wrong (lmgao die??)

34. Most visited Website: probably tumblr lolol or youtube

35. Mole/s: one on each side of my face, a few on each arm, and one big boi on the side of my left leg... and one next to my left nip lol (its cute)

36. Mark/s: i think the most interesting is the scar in my eyebrow????? i like to tell ppl this story because a lot of people assume i just cut my brow like that to look edgy (like no binch i am edgy naturally).. basically when i was a small child i was in me and my brothers bomb ass games room and i tripped over the nintendo controller cord he was holding, and my face fell onto plastic train tracks on the ground and it cut my eyebrow in half

37. Childhood dream: idk?? probably wanted to be a vet or some shit

38. Hair color: brown

39. Long or short hair: its like medium length now

40. Do you have a crush on someone: k-kihyun

41. What do you like about yourself: my eyebrows are nice??? thats about it

42. Piercings: both ears are stretched, and then i have a conch in my right ear (i used to have more but i fucked up)

43. Bloodtype: O+ lol im a basic bitch

44. Nickname: idk but @moonbebe calls me ashl

45. Relationship status: kihyun

46. Zodiac: saggittarius (and so is my boi)

47. Pronouns: she & her

48. Favorite TV Show: dragon ball z

49. Tattoos: nope but i want some

50. Right or left hand: right

51. Surgery: nope

52. Piercing: yeah wtf this already got answered

53. Sport: no thanks no thanks

55. Vacation: is this asking me if im on one or if ive been on one or if im going on one or ?????

56. Pair of trainers: are trainers sporty shoes? idk

MORE GENERAL:

57. Eating: no im not eating rn???? what is this q

58. Drinking: no???

59. I’m about to: eat soup and watch the next 2 episodes of lookout (kashdhasdsafd my boi kibum)

61. Waiting for: death

62. Want: death

63. Get married: yes me and kihyun have decided yes

64. Career: death

WHICH IS BETTER?:

65. Hugs or kisses: kisses pls kihyun

66. Lips or eyes: eyes probably but idk both good

67. Shorter or taller: taller (please im an amazon woman)

68. Older or younger: older i guess

70. Nice arms or nice stomach: stomach and by stomach i mean a pudgy cute lil tum!!!!

71. Sensitive or loud: sensitive but a balance of both is nice

72. Hook up or relationship: relationship

73. Troublemaker or hesitant: i like me a bad boi but i also like me a good boi so???

HAVE YOU EVER:

74. Kissed a stranger: no

75. Drank hard liquor: idk what this is but maybe

76. Lost glasses/contact lenses: no

77. Turned someone down: yes eek

78. Sex in the first date: no

79. Broken someones heart: yes lmao hahhaha

80. Had your heart broken: i guess but teen years dont count anymore

81. Been arrested: no

82. Cried when someone died: yes

83. Fallen for a friend: no

DO YOU BELIEVE IN:

84. Yourself: no

85. Miracles: no

86. Love at first sight: no

87. Santa Claus: no

88. Kiss in the first date: if its kihyun

89. Angels: no (wow i really am a skeptic)

OTHER:

90. Current best friends name: elou

91. Eyecolor: light brown (it looks gold in some lights)

92. Favorite movie: look idk this is a hard one

ok done!!! that was a long one but it was fun!! so i understand if you don’t wanna do this, but i’m gonna tag @moonbebe @limechangkyun (focus on ur exams bith) @chaerismatic @kihyunswife @wonhosflower @m0nst4x @supersaiyum @smol-kihyuns @ukihyunnie @c-kyunjpg @amorjeon @kihynh @baeker @jiminieji 🌼🌷🌹🌻

sorry if i’m like always tagging the same ppl?????? so i tagged a few newer mutuals 💜💜💜

ignore this if you dont wanna do it !!!!!

#i luv u guys #tagged in

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chara-killer-bear · 8 years

Note

All

1. WHO WAS THE LAST PERSON YOU HELD HANDS WITH?

Last person I held hands with is my fam Marco because he was leading me outta ROP after catching me at a bad time lmao

2. ARE YOU OUTGOING OR SHY?

Can I say both? o;v;o

3. WHO ARE YOU LOOKING FORWARD TO SEEING?

@static–things ewe

4. ARE YOU EASY TO GET ALONG WITH?

I’m not sure tbh–

5. IF YOU WERE DRUNK WOULD THE PERSON YOU LIKE TAKE CARE OF YOU?

Hopefully if they don’t get drunk themselves–

6. WHAT KIND OF PEOPLE ARE YOU ATTRACTED TO?

Let’s see-

- at least sweet and honest

- always there for me no matter what

- ultimate memes

7. DO YOU THINK YOU’LL BE IN A RELATIONSHIP TWO MONTHS FROM NOW?

@static–things ewe

8. WHO FROM THE OPPOSITE GENDER IS ON YOUR MIND?

Either Marco or Blake

9. DOES TALKING ABOUT SEX MAKE YOU UNCOMFORTABLE?

Well no shit

10. WHO WAS THE LAST PERSON YOU HAD A DEEP CONVERSATION WITH?

@static–things tbh

11. WHAT DOES THE MOST RECENT TEXT THAT YOU SENT SAY?

r ip my soul “don’t you mean your selfie”

12. WHAT ARE YOUR 5 FAVORITE SONGS RIGHT NOW?

- Jenny by Studio Killers

- Can’t Sleep Love by Pentatonix

- Pretend by Bad Suns

- Rather Be by Clean Bandit

- Never Gonna Give You Up by Rick Astley

13. DO YOU LIKE IT WHEN PEOPLE PLAY WITH YOUR HAIR?

Nothing really ‘cause I don’t really play with my hair that much :”)

14. DO YOU BELIEVE IN LUCK AND MIRACLES?

If I’m lucky enough to meet the bae, then ye I do believe in luck and miracles~

15. WHAT GOOD THING HAPPENED THIS SUMMER?

- August 1, 2016

- Joined a whole bunch of AUs

- So many memes going on and roasting bigoted ass

16. WOULD YOU KISS THE LAST PERSON YOU KISSED AGAIN?

I would likely stab their sucker before they even lay a hand on me.

17. DO YOU THINK THERE IS LIFE ON OTHER PLANETS?

It’s possible- I mean, there’s so many unknown plants out there in the galaxy and we just haven’t discovered them or they haven’t discovered us–

18. DO YOU STILL TALK TO YOUR FIRST CRUSH?

Let’s see- my first crush was a guy named Aaron, and hell no.

19. DO YOU LIKE BUBBLE BATHS?

It’s sad I never had one before :”)

20. DO YOU LIKE YOUR NEIGHBORS?

Let’s see-

1st neighbor- Grandma (meh)

2nd neighbor- Vy, the girl who goes to the same high school as me (meh)

3rd neighbor- Loudy af Latinos and had the police on their butts twice or thrice (nah)

4th neighbor- Basically Vy’s uncle I assume (nah, considering they keep blocking the driveway way too many times)

5th neighbor- Another Latino family that I haven’t quite known yet (They chill, plus their parrot and their dog is cute)

6th neighbor- Latina woman (I honestly feel sad for her, considering she’s schizophrenic, her college counselor is an ass, her boyfriend steals money from her, and her mom is a rude lady. She honestly doesn’t deserve all that, and despite all her troubles, she’s a really sweet lady.)

7th neighbor- Bella and her family (I hate them and especially Bella. Honestly, Bella used to be kind, like she let me pet her dog before when me and my mom first moved in. But now I don’t see her dog anymore, and Bella acted like I never even existed. Like there was that one time at night where Bella was talking to my mom about wigs and it was around 10-12 at night, plus I was holding all the groceries, so it should be a dead ass clue that I looked like shit, right? WELP, Bella never even batted an eye at me, when I waved hi she didn’t even acknowledge my existence, and basically kept talking to my mom for at least 1-2 straight hours before my mom actually opened the door to our apartment so I can drop down the fucking groceries–)

21. WHAT ARE YOU BAD HABITS?

Welp-

- Procrastination

- Sleeping

- Anxiety

The OT3 PSA

22. WHERE WOULD YOU LIKE TO TRAVEL?

Texas so I can see the bae

Or probs New York because honestly there’s so many places that look especially wonderful to look at~

23. DO YOU HAVE TRUST ISSUES?

Sometimes but not all the time- usually it’s started anxiety: it either starts from-

- someone breaks my trust > anxiety > trust issues

- someone says something > starts to question myself or others > anxiety > trust issues

24. FAVORITE PART OF YOUR DAILY ROUTINE?

Talking to the bae~

25. WHAT PART OF YOUR BODY ARE YOU MOST UNCOMFORTABLE WITH?

Uncomfortable with? I mean, I guess I could say my arms or my face–

26. WHAT DO YOU DO WHEN YOU WAKE UP?

Talk to the bae, stalk Tumblr, and go on from there :”)

27. DO YOU WISH YOUR SKIN WAS LIGHTER OR DARKER?

Lighter

28. WHO ARE YOU MOST COMFORTABLE AROUND?

@static–things @aph-slovakia

other than that, mostly my IRL friends such as Marco, Blake, Glend, etc.

29. HAVE ANY OF YOUR EX’S TOLD YOU THEY REGRET BREAKING UP?

Well there’s always ex from hell, considering he stalked me a good amount of time after we broke up and kinda is atm

30. DO YOU EVER WANT TO GET MARRIED?

Maybe

31. IS YOUR HAIR LONG ENOUGH FOR A PONY TAIL?

Yeeeeee–

I mean, it’s up to my posterior–

32. WHICH CELEBRITIES WOULD YOU HAVE A THREESOME WITH?

First off, ew

Second off, no

33. SPELL YOUR NAME WITH YOUR CHIN.

sally jasn cvhhhhhhhhhhhesd

34. DO YOU PLAY SPORTS? WHAT SPORTS?

No sports here :”)

35. WOULD YOU RATHER LIVE WITHOUT TV OR MUSIC?

Without TV– it’s not like I watched TV in the first place anyway :”)

36. HAVE YOU EVER LIKED SOMEONE AND NEVER TOLD THEM?

Meh- what of it?

It is what it is and I’m content with who I’m with now~

37. WHAT DO YOU SAY DURING AWKWARD SILENCES?

I s2g there was this awkward silence in a group and I whispered “wait so everyone is thinking of the same plan- we gonna do the murder?” and then the group blew up :”)

38. DESCRIBE YOUR DREAM GIRL/GUY?

@static–things

39. WHAT ARE YOUR FAVORITE STORES TO SHOP IN?

Starbucks or Target–

40. WHAT DO YOU WANT TO DO AFTER HIGH SCHOOL?

Visit the bae~

41. DO YOU BELIEVE EVERYONE DESERVES A SECOND CHANCE?

I mean, ye

I can’t waste a chance that they changed, and if they didn’t, I can always stab them in the ass

42. IF YOUR BEING EXTREMELY QUIET WHAT DOES IT MEAN?

Either depression, crying, sleepy, hiding from someone, lost in deep thought, etc.

43. DO YOU SMILE AT STRANGERS?

Sometimes– Like if they look like they’re in a good mood and are friendly enough to wave at me, I just give ‘em a friendly nod and even a smile back–

44. TRIP TO OUTER SPACE OR BOTTOM OF THE OCEAN?

O U T E R S P A C E LET’S GO

45. WHAT MAKES YOU GET OUT OF BED IN THE MORNING?

Either my mom yelling at me to do something and rarely my own will either because I feel really hungry, feel disgusting and want to wash my face repeatedly, or roam around the apartment and enjoy the silence.

46. WHAT ARE YOU PARANOID ABOUT?

Honestly many things but one of the most notorious ones would be people hating me, fucking up, etc.

47. HAVE YOU EVER BEEN HIGH?

Nah–

48. HAVE YOU EVER BEEN DRUNK?

Nah–

49. HAVE YOU DONE ANYTHING RECENTLY THAT YOU HOPE NOBODY FINDS OUT ABOUT?

Maybe

50. WHAT WAS THE COLOUR OF THE LAST HOODIE YOU WORE?

Blue~

51. EVER WISHED YOU WERE SOMEONE ELSE?

Honestly one of my top scenarios, but hella scary, so it��s a maybe–

52. ONE THING YOU WISH YOU COULD CHANGE ABOUT YOURSELF?

- procrastinating

53. FAVOURITE MAKEUP BRAND?

There’s no specific brand I have in mind tbh– Like ye, I use lipstick every now and then, but I don’t really pay much attention to the brand, practically speaking I rarely use makeup in the first place–

54. FAVOURITE STORE?

I would say Target or Starbucks

55. FAVOURITE BLOG?

@static–things

56. FAVOURITE COLOUR?

Redish-pink or a really dark shade of blue~

57. FAVOURITE FOOD?

SPAM MASUBI, DUMPLINGS, PIZZA, CANDIED SWEET POTATOES, PALABOK

58. LAST THING YOU ATE?

Pizza :”)

59. FIRST THING YOU ATE THIS MORNING?

Crispy Noodles- the one they sell at Panda Express as a snack

60. EVER WON A COMPETITION? FOR WHAT?

There was like this hula-hoop competition we had a lot in 3rd grade where the one who hula-hoops the last out of everyone wins and gets candy and usually it was my friends who would always win; however in the very last hula-hoop competition I was the last one standing and I honestly still feel that victory every time I think of that memory–

61. BEEN SUSPENDED/EXPELLED? FOR WHAT?

… h eh- I mean, ye, I did, but p sure you know the story–

62. BEEN ARRESTED? FOR WHAT?

Technically not arrested, more like caught and got scot-free

63. EVER BEEN IN LOVE?

@static–things

64. TELL US THE STORY OF YOUR FIRST KISS?

…ew

65. ARE YOU HUNGRY RIGHT NOW?

Not really, considering I’m barely finishing breakfast :”)

66. DO YOU LIKE YOUR TUMBLR FRIENDS MORE THAN YOUR REAL FRIENDS?

Meh– so so–

Tbh most of my Tumblr friends I either get in an argument with or they leave me behind, and I only have a good few of them who still talks to me to this day.

However, my IRL friends I can see and hear whenever I go to school, and I can go do after school adventures with them, but it invites drama, and once you go into drama you really can’t escape it because you have to face them- IRL.

So in other words, it’s a so-so situation–

67. FACEBOOK OR TWITTER?

Facebook.

68. TWITTER OR TUMBLR?

Tumblr.

69. ARE YOU WATCHING TV RIGHT NOW?

Nah–

70. NAMES OF YOUR BESTFRIENDS?

- Jessica

- Blake

- Emely

- @static--things

71. CRAVING SOMETHING? WHAT?

Craving sleep most of the time and maybe even bae cuddles but sh

72. WHAT COLOUR ARE YOUR TOWELS?

At the moment, purple–

72. HOW MANY PILLOWS DO YOU SLEEP WITH?

0. 1 at most–

73. DO YOU SLEEP WITH STUFFED ANIMALS?

Sometimes :”)

74. HOW MANY STUFFED ANIMALS DO YOU THINK YOU HAVE?

More than 10 that’s for sure :”)

75. FAVOURITE ANIMAL?

Penguin or a Panda :”)

76. WHAT COLOUR IS YOUR UNDERWEAR?

wtf

77. CHOCOLATE OR VANILLA?

Vanilla~

78. FAVOURITE ICE CREAM FLAVOUR?

VANILLA

79. WHAT COLOUR SHIRT ARE YOU WEARING?

Black

80. WHAT COLOUR PANTS?

Black

81. FAVOURITE TV SHOW?

One of my alltime favorites would be Whose Line Is It Anyway

82. FAVOURITE MOVIE?

Coraline

83. MEAN GIRLS OR MEAN GIRLS 2?

Mean Girls–

84. MEAN GIRLS OR 21 JUMP STREET?

I would say Mean Girls for now, considering I haven’t watched 21 Jump Street before :”)

85. FAVOURITE CHARACTER FROM MEAN GIRLS?

I don’t know– I guess the main protagonist..?

86. FAVOURITE CHARACTER FROM FINDING NEMO?

DORY

87. FIRST PERSON YOU TALKED TO TODAY?

@static–things

88. LAST PERSON YOU TALKED TO TODAY?

@static–things :”)

89. NAME A PERSON YOU HATE?

Jonah, Steven, etc.

90. NAME A PERSON YOU LOVE?

Luther~

91. IS THERE ANYONE YOU WANT TO PUNCH IN THE FACE RIGHT NOW?

Well other than Jonah, I would love to punch someone in the ballsack, but can’t

92. IN A FIGHT WITH SOMEONE?

Technically, considering it’s a kinda a game of cat and mouse but much more dangerous, but there’s no way the cat can catch the mouse so it okey

93. HOW MANY SWEATPANTS DO YOU HAVE?

None

94. HOW MANY SWEATERS/HOODIES DO YOU HAVE?

A LOT

95. LAST MOVIE YOU WATCHED?

Last movie I watched would probs be There Will Be Blood

96. FAVOURITE ACTRESS?

I don’t really have one :”)

97. FAVOURITE ACTOR?

Don’t have one either :”)

98. DO YOU TAN A LOT?

Nah, although I tan easily–

99. HAVE ANY PETS?

My cat named Peter + goldfish

100. HOW ARE YOU FEELING?

Happy but a tinge of depression slipping here and there, but still otherwise fine uvu

101. DO YOU TYPE FAST?

Let’s see-

Just retook the Typing Test and I got 72.9 WPM

102. DO YOU REGRET ANYTHING FROM YOUR PAST?

A lot of things really–

103. CAN YOU SPELL WELL?

Welcome to the Penumbra, my dear Traveler. We hope you enjoy your stay.

104. DO YOU MISS ANYONE FROM YOUR PAST?

A few particular individuals, one of them I know for sure I’ll never hear from them again. I just hope the rest are doing fine like I am.

105. EVER BEEN TO A BONFIRE PARTY?

Nope :”)

106. EVER BROKEN SOMEONE’S HEART?

I’m not entirely sure–

107. HAVE YOU EVER BEEN ON A HORSE?

Boy I wish I had :”)

108. WHAT SHOULD YOU BE DOING?

Doing homework and working on this art project but procrastination is kicking me so go me :”)

109. IS SOMETHING IRRITATING YOU RIGHT NOW?

A bunch of things a particular person said to me during a call but it’s slowly fading away–

110. HAVE YOU EVER LIKED SOMEONE SO MUCH IT HURT?

Nah– Well kinda– But it was a few months ago and shibam the problem cleared anyway–

111. DO YOU HAVE TRUST ISSUES?

Not at the moment–

112. WHO WAS THE LAST PERSON YOU CRIED IN FRONT OF?

Well, excluding over the internet, I would say Marco–

But if not, then it would be Luther

113. WHAT WAS YOUR CHILDHOOD NICKNAME?

Sophie–

114. HAVE YOU EVER BEEN OUT OF YOUR PROVINCE/STATE?

Only for a week-

It was a history field trip we had in 8th grade where we got to travel all the way across the country to where New York, Virginia, Pennsylvania, and other states were at and it was amazing~

115. DO YOU PLAY THE WII?

Nope :”)

I don’t even have a game console :”)

116. ARE YOU LISTENING TO MUSIC RIGHT NOW?

Ye–

117. DO YOU LIKE CHICKEN NOODLE SOUP?

H ELL YE S

118. DO YOU LIKE CHINESE FOOD?

Not particularly, but I would say orange chicken is delicious~

119. FAVOURITE BOOK?

I would still say either One Hundred Years of Solitude or The Adventures of Edward Tulane

120. ARE YOU AFRAID OF THE DARK?

Nah

121. ARE YOU MEAN?

Maybe, I’m not sure myself– It depends on what others think of me–

122. IS CHEATING EVER OKAY?

No. It’s heart-breaking-

123. CAN YOU KEEP WHITE SHOES CLEAN?

Nah– Not like I always want it to be clean in the first place–

124. DO YOU BELIEVE IN LOVE AT FIRST SIGHT?

Maybe and maybe not

125. DO YOU BELIEVE IN TRUE LOVE?

Probs not anymore

126. ARE YOU CURRENTLY BORED?

Nah–

127. WHAT MAKES YOU HAPPY?

The bae and being with them

Joining AUs, spreading my ideas, eating sweet things, being with friends, etc.

128. WOULD YOU CHANGE YOUR NAME?

Ye– I’d probs change it to Sally or Ally, maybe even Shawn if I felt like it

129. WHAT YOUR ZODIAC SIGN?

Aquarius~

130. DO YOU LIKE SUBWAY?

Can’t say for sure, since I probs never rode a subway before :”)

131. YOUR BESTFRIEND OF THE OPPOSITE SEX LIKES YOU, WHAT DO YOU DO?

Bleh-

I mean, if I just heard that from just a rumor, then I’d let them be

However if they told me in person, then I’d probs just let them down easily and then hope for the best they don’t become a stalker but continue as if everything’s normal

132. WHO’S THE LAST PERSON YOU HAD A DEEP CONVERSATION WITH?

I s2g I think some of these are repeat questions-

@static–things

133. FAVOURITE LYRICS RIGHT NOW?

From the song I’m listening to now-

“I’m never going down, I’m never giving up,

I’m never gonna leave, so put your hands up

If you like me, then say you like me”

134. CAN YOU COUNT TO ONE MILLION?

I can try– I’d probably get side-tracked–

135. DUMBEST LIE YOU EVER TOLD?

“o ye I’m at my grandma’s”

136. DO YOU SLEEP WITH YOUR DOORS OPEN OR CLOSED?

Almost every time open–

I feel like I can’t breathe or it’s too stuffy or I find it creepy whenever the door is closed

I mean, on some occasions such as wanting privacy and such the like, I don’t mind having the door closed-

But most of the time I prefer the door open

137. HOW TALL ARE YOU?

Sadly 4′9″ to 4′11″ :”)

138. CURLY OR STRAIGHT HAIR?

Curly hair seems pretty~

139. BRUNETTE OR BLONDE?

Both?

140. SUMMER OR WINTER?

BOTH

141. NIGHT OR DAY?

Night~

142. FAVOURITE MONTH?

Either January or July

143. ARE YOU A VEGETARIAN?

Technically nah- since I eat chicken a lot :”)

144. DARK, MILK OR WHITE CHOCOLATE?

White chocolate~

145. TEA OR COFFEE?

Tea!

146. WAS TODAY A GOOD DAY?

Today’s a lovely day~

147. MARS OR SNICKERS?

Snickers– I never quite tasted a Mars bar before–

148. WHAT’S YOUR FAVOURITE QUOTE?

“I reject your reality and replace it with my own.”

149. DO YOU BELIEVE IN GHOSTS?

Ye–

150. GET THE CLOSEST BOOK NEXT TO YOU, OPEN IT TO PAGE 42, WHAT’S THE FIRST LINE ON THAT PAGE?

“That was no good.”

PLEASE ASK ME THESE

(VIA ALUNIT)

DO IT!!!

(VIA MADDISONKENNEDY)

PLEASE

(VIA TAYBCATO)

#Mun speaks

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