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Former investment bank FX trader: News trading and second order thinking part 2/2

Former investment bank FX trader: News trading and second order thinking part 2/2
Thanks for all the upvotes and comments on the previous pieces:
From the first half of the news trading note we learned some ways to estimate what is priced in by the market. We learned that we are trading any gap in market expectations rather than the result itself. A good result when the market expected a fantastic result is disappointing! We also looked at second order thinking. After all that, I hope the reaction of prices to events is starting to make more sense to you.

Before you understand the core concepts of pricing in and second order thinking, price reactions to events can seem mystifying at times
We'll add one thought-provoking quote. Keynes (that rare economist who also managed institutional money) offered this analogy. He compared selecting investments to a beauty contest in which newspaper readers would write in with their votes and win a prize if their votes most closely matched the six most popularly selected women across all readers:
It is not a case of choosing those (faces) which, to the best of one’s judgment, are really the prettiest, nor even those which average opinions genuinely thinks the prettiest. We have reached the third degree where we devote our intelligences to anticipating what average opinion expects the average opinion to be.
Trading is no different. You are trying to anticipate how other traders will react to news and how that will move prices. Perhaps you disagree with their reaction. Still, if you can anticipate what it will be you would be sensible to act upon it. Don't forget: meanwhile they are also trying to anticipate what you and everyone else will do.

Part II
  • Preparing for quantitative and qualitative releases
  • Data surprise index
  • Using recent events to predict future reactions
  • Buy the rumour, sell the fact
  • The trimming position effect
  • Reversals
  • Some key FX releases

Preparing for quantitative and qualitative releases

The majority of releases are quantitative. All that means is there’s some number. Like unemployment figures or GDP.
Historic results provide interesting context. We are looking below the Australian unemployment rate which is released monthly. If you plot it out a few years back you can spot a clear trend, which got massively reversed. Knowing this trend gives you additional information when the figure is released. In the same way prices can trend so do economic data.

A great resource that's totally free to use
This makes sense: if for example things are getting steadily better in the economy you’d expect to see unemployment steadily going down.
Knowing the trend and how much noise there is in the data gives you an informational edge over lazy traders.
For example, when we see the spike above 6% on the above you’d instantly know it was crazy and a huge trading opportunity since a) the fluctuations month on month are normally tiny and b) it is a huge reversal of the long-term trend.
Would all the other AUDUSD traders know and react proportionately? If not and yet they still trade, their laziness may be an opportunity for more informed traders to make some money.
Tradingeconomics.com offers really high quality analysis. You can see all the major indicators for each country. Clicking them brings up their history as well as an explanation of what they show.
For example, here’s German Consumer Confidence.

Helpful context
There are also qualitative events. Normally these are speeches by Central Bankers.
There are whole blogs dedicated to closely reading such texts and looking for subtle changes in direction or opinion on the economy. Stuff like how often does the phrase "in a good place" come up when the Chair of the Fed speaks. It is pretty dry stuff. Yet these are leading indicators of how each member may vote to set interest rates. Ed Yardeni is the go-to guy on central banks.

Data surprise index

The other thing you might look at is something investment banks produce for their customers. A data surprise index. I am not sure if these are available in retail land - there's no reason they shouldn't be but the economic calendars online are very basic.
You’ll remember we talked about data not being good or bad of itself but good or bad relative to what was expected. These indices measure this difference.
If results are consistently better than analysts expect then you’ll see a positive number. If they are consistently worse than analysts expect a negative number. You can see they tend to swing from positive to negative.

Mean reversion at its best! Data surprise indices measure how much better or worse data came in vs forecast
There are many theories for this but in general people consider that analysts herd around the consensus. They are scared to be outliers and look ‘wrong’ or ‘stupid’ so they instead place estimates close to the pack of their peers.
When economic conditions change they may therefore be slow to update. When they are wrong consistently - say too bearish - they eventually flip the other way and become too bullish.
These charts can be interesting to give you an idea of how the recent data releases have been versus market expectations. You may try to spot the turning points in macroeconomic data that drive long term currency prices and trends.

Using recent events to predict future reactions

The market reaction function is the most important thing on an economic calendar in many ways. It means: what will happen to the price if the data is better or worse than the market expects?
That seems easy to answer but it is not.
Consider the example of consumer confidence we had earlier.
  • Many times the market will shrug and ignore it.
  • But when the economic recovery is predicated on a strong consumer it may move markets a lot.
Or consider the S&P index of US stocks (Wall Street).
  • If you get good economic data that beats analyst estimates surely it should go up? Well, sometimes that is certainly the case.
  • But good economic data might result in the US Central Bank raising interest rates. Raising interest rates will generally make the stock market go down!
So better than expected data could make the S&P go up (“the economy is great”) or down (“the Fed is more likely to raise rates”). It depends. The market can interpret the same data totally differently at different times.
One clue is to look at what happened to the price of risk assets at the last event.
For example, let’s say we looked at unemployment and it came in a lot worse than forecast last month. What happened to the S&P back then?

2% drop last time on a 'worse than expected' number ... so it it is 'better than expected' best guess is we rally 2% higher
So this tells us that - at least for our most recent event - the S&P moved 2% lower on a far worse than expected number. This gives us some guidance as to what it might do next time and the direction. Bad number = lower S&P. For a huge surprise 2% is the size of move we’d expect.
Again - this is a real limitation of online calendars. They should show next to the historic results (expected/actual) the reaction of various instruments.

Buy the rumour, sell the fact

A final example of an unpredictable reaction relates to the old rule of ‘Buy the rumour, sell the fact.’ This captures the tendency for markets to anticipate events and then reverse when they occur.

Buy the rumour, sell the fact
In short: people take profit and close their positions when what they expected to happen is confirmed.
So we have to decide which driver is most important to the market at any point in time. You obviously cannot ask every participant. The best way to do it is to look at what happened recently. Look at the price action during recent releases and you will get a feel for how much the market moves and in which direction.

Trimming or taking off positions

One thing to note is that events sometimes give smart participants information about positioning. This is because many traders take off or reduce positions ahead of big news events for risk management purposes.
Imagine we see GBPUSD rises in the hour before GDP release. That probably indicates the market is short and has taken off / flattened its positions.

The price action before an event can tell you about speculative positioning
If GDP is merely in line with expectations those same people are likely to add back their positions. They avoided a potential banana skin. This is why sometimes the market moves on an event that seemingly was bang on consensus.
But you have learned something. The speculative market is short and may prove vulnerable to a squeeze.

Two kinds of reversals

Fairly often you’ll see the market move in one direction on a release then turn around and go the other way.
These are known as reversals. Traders will often ‘fade’ a move, meaning bet against it and expect it to reverse.

Logical reversals

Sometimes this happens when the data looks good at first glance but the details don’t support it.
For example, say the headline is very bullish on German manufacturing numbers but then a minute later it becomes clear the company who releases the data has changed methodology or believes the number is driven by a one-off event. Or maybe the headline number is positive but buried in the detail there is a very negative revision to previous numbers.
Fading the initial spike is one way to trade news. Try looking at what the price action is one minute after the event and thirty minutes afterwards on historic releases.

Crazy reversals


Some reversals don't make sense
Sometimes a reversal happens for seemingly no fundamental reason. Say you get clearly positive news that is better than anyone expects. There are no caveats to the positive number. Yet the price briefly spikes up and then falls hard. What on earth?
This is a pure supply and demand thing. Even on bullish news the market cannot sustain a rally. The market is telling you it wants to sell this asset. Try not to get in its way.

Some key releases

As we have already discussed, different releases are important at different times. However, we’ll look at some consistently important ones in this final section.

Interest rates decisions

These can sometimes be unscheduled. However, normally the decisions are announced monthly. The exact process varies for each central bank. Typically there’s a headline decision e.g. maintain 0.75% rate.
You may also see “minutes” of the meeting in which the decision was reached and a vote tally e.g. 7 for maintain, 2 for lower rates. These are always top-tier data releases and have capacity to move the currency a lot.
A hawkish central bank (higher rates) will tend to move a currency higher whilst a dovish central bank (lower rates) will tend to move a currency lower.
A central banker speaking is always a big event

Non farm payrolls

These are released once per month. This is another top-tier release that will move all USD pairs as well as equities.
There are three numbers:
  • The headline number of jobs created (bigger is better)
  • The unemployment rate (smaller is better)
  • Average hourly earnings (depends)
Bear in mind these headline numbers are often off by around 75,000. If a report comes in +/- 25,000 of the forecast, that is probably a non event.
In general a positive response should move the USD higher but check recent price action.
Other countries each have their own unemployment data releases but this is the single most important release.

Surveys

There are various types of surveys: consumer confidence; house price expectations; purchasing managers index etc.
Each one basically asks a group of people if they expect to make more purchases or activity in their area of expertise to rise. There are so many we won’t go into each one here.
A really useful tool is the tradingeconomics.com economic indicators for each country. You can see all the major indicators and an explanation of each plus the historic results.

GDP

Gross Domestic Product is another big release. It is a measure of how much a country’s economy is growing.
In general the market focuses more on ‘advance’ GDP forecasts more than ‘final’ numbers, which are often released at the same time.
This is because the final figures are accurate but by the time they come around the market has already seen all the inputs. The advance figure tends to be less accurate but incorporates new information that the market may not have known before the release.
In general a strong GDP number is good for the domestic currency.

Inflation

Countries tend to release measures of inflation (increase in prices) each month. These releases are important mainly because they may influence the future decisions of the central bank, when setting the interest rate.
See the FX fundamentals section for more details.

Industrial data

Things like factory orders or or inventory levels. These can provide a leading indicator of the strength of the economy.
These numbers can be extremely volatile. This is because a one-off large order can drive the numbers well outside usual levels.
Pay careful attention to previous releases so you have a sense of how noisy each release is and what kind of moves might be expected.

Comments

Often there is really good stuff in the comments/replies. Check out 'squitstoomuch' for some excellent observations on why some news sources are noisy but early (think: Twitter, ZeroHedge). The Softbank story is a good recent example: was in ZeroHedge a day before the FT but the market moved on the FT. Also an interesting comment on mistakes, which definitely happen on breaking news, and can cause massive reversals.

submitted by getmrmarket to Forex [link] [comments]

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Choose from a large selection of price analysis tools, including, but not limited to, indicators, strategies, drawing objects (i.e. Gann, Elliot Wave, moving averages) and more.
Individual watchlists and alerts You can track major global indices, stocks, currency pairs, bonds, futures, mutual funds, commodities and cryptocurrencies all in real-time.
Alerts will help you not to miss the smallest of changes in the market and will allow you to react in time to invest or sell profitably, increasing your overall profit.
Flexible settings help you to track the indices you need and also group them in a way that is convenient for you.
Syncing your accounts All saved changes, notifications, charts, and technical analysis, which you began on the TradingView platform will be automatically accessible from your mobile device through the app.
Real-time data from global exchanges Gain access to data in real-time on more than 100,000 instruments from over 50 exchanges from the United States, Russia, the East, and countries in Asia and Europe, such as: NYSE, LSE, TSE, SSE, HKEx, Euronext, TSX, SZSE, FWB, SIX, ASX, KRX, NASDAQ, JSE, Bolsa de Madrid, TWSE, BM&F/B3, MOEX and many others!
Commodity prices In real-time, you can track prices for gold, silver, oil, natural gas, cotton, sugar, wheat, corn, and many other products.
Global indices Track major indices of the world stock market in real-time: ■ North and South America: Dow Jones, S&P 500, NYSE, NASDAQ Composite, SmallCap 2000, NASDAQ 100, Merval, Bovespa, RUSSELL 2000, IPC, IPSA; ■ Europe: CAC 40, FTSE MIB, IBEX 35, ATX, BEL 20, DAX, BSE Sofia, PX, РТС, ММВБ (MOEX); ■ Asian-Pacific Ocean Regions: NIKKEI 225, SENSEX, NIFTY, SHANGHAI COMPOSITE, S&P/ASX 200, HANG SENG, KOSPI, KLCI, NZSE 50; ■ Africa: Kenya NSE 20, Semdex, Moroccan All Shares, South Africa 40; and ■ Middle East: EGX 30, Amman SE General, Kuwait Main, TA 25.
Cryptocurrency Get the opportunity to compare prices from leading cryptocurrency exchanges, such as HitBTC, Binance, BitBay, Coinbase, Mercado Gemini, Kraken, Huobi, OkCoin, and many others. Get information on prices for: ■ Bitcoin (BTC), Litecoin (LTC), Ripple (XRP); ■ Ethereum ( ETH), Ethereum Classic (ETC), IOTA; ■ Dogecoin (DOGE), USD Coin (USDC), Tron (TRX); ■ Stellar (XLM), Tether (USDT), Cardano (ADA); ■ Monero (XMR), ZCash (ZEC), Dash.
Playstore Link: https://play.google.com/store/apps/details?id=com.tradingview.tradingviewapp
Mod Features: Additional indicators available in pro version of this app
submitted by shinigamidoge to moddedandroidapps [link] [comments]

How to derive historical financial data for forex instrument backtesting

Hello,
If you believe backtesting strategies for forex major currency pairs is unhopeful please leave a comment with an explanation.
I'm a CS major at Columbia with internships in back office global bank infrastructure positions here in NY and have great interest in trading algorithmically because I can't trust my behavior to enter trades, among other obvious reasons.
I would like to know what the best sources are for obtaining historical data (OHLCV, etc) for (forex) backtesting purposes. Is a large excel file used in practice, or are historical prices derived via API's? It seems that I need to pay after some research online, but I know you redditors can deliver.

edit
I found a free source here for EURUSD. There are other pairs available too.
submitted by Reciprocates to algotrading [link] [comments]

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  802. venmo
  803. IllegalLifeProTips
  804. HitBoxPorn
  805. Shrek
  806. weirdnews
  807. specialed
  808. EndgameSpoilers
  809. specialeducation
  810. antivax
  811. AntiVaxxers
  812. u_purpleyellowpaint
  813. bi_irl
  814. sugarfreemua
  815. lanadelrey
  816. volleyball
  817. muacjdiscussion
  818. ThisButUnironically
  819. ShitLiberalsSay
  820. brokeabone
  821. discord_irl
  822. excitingdystopia
  823. BenBashiroLore
  824. VaushV
  825. ABoringDystopia
  826. FristOfAllHowDareYou
  827. hamsters
  828. SubredditSimMeta
  829. TropicalWeather
  830. Landlord
  831. AntifascistsofReddit
  832. hamstercare
  833. vexillologycirclejerk
  834. therewasnoattempt
  835. ennnnnnnnnnnnbbbbbby
  836. RealSolarSystem
  837. u_CondomCrusader69
  838. band
  839. FlexSealFanClub
  840. Armor
  841. MemeFormats
  842. Puberty
  843. conceptart
  844. CondomKingdom
  845. u_Some16yoLosr
  846. FireEmblemHeroes
  847. FondantLove
  848. LaCrescentMN
  849. u_PugMage101
  850. darkvideos
  851. u_Sadness92
  852. PERSoNA
  853. JacksFilms
  854. jschlatt
  855. castlevania
  856. stfuretard
  857. CloneWarsMemes
  858. DeepFried
  859. legostarwars
  860. u_DVproductions64
  861. KamikazeByWords
  862. ImGoingToHellForThis
  863. linuxmemes
  864. codes
  865. crypto
  866. cpp_questions
  867. Laptop
  868. debian
  869. Kalilinux
  870. PHP
  871. TOR
  872. Doomers
  873. learnpython
  874. RecRoom
  875. orbusvr
  876. VirtualDesktop
  877. bigscreen
  878. ProTubeVR
  879. VRchat
  880. OculusQuestModding
  881. Borderlands2
  882. DeathToBuzzfeed
  883. deadbabyjokes
  884. u_MCT1233
  885. kpop
  886. crystalclear
  887. GIDLE
  888. pokemongoyellow
  889. bidle
  890. unpopularkpopopinions
  891. HermitCraft
  892. ItHadToBeBrazil
  893. grian
  894. MumboJumboYouTube
  895. recycling
  896. usernamefamily
  897. BirdsArentReal
  898. u_Gay_Papa
  899. BSA
  900. u_ConsumeSyrup
  901. ModdedMinecraft
  902. ROBLOXmemes
  903. gangbeasts
  904. Discussion
  905. CrossCountry
  906. fuck
  907. FML
  908. TonightsBigLosers
  909. skeppy
  910. mcservers
  911. pussypassdenied
  912. backgrounds
  913. IsThereASubredditFor
  914. BulletHellMonday
  915. u_whyMYpeepeeGREEN
  916. marchingband
  917. TuberSimulator
  918. FosterTheCirclejerk
  919. GiftofGames
  920. deadmeatjames
  921. AshVsEvilDead
  922. GachaLifeCringe
  923. IntotheDarkHulu
  924. ChernobylMemes
  925. asl
  926. Hong_Kong
  927. vexillology
  928. imaginarymaps
  929. mountaindew
  930. SurrealApprovals
  931. Blessed_Images
  932. Metallica
  933. ainbow
  934. u_Mr-Damaged
  935. SmallYTChannel
  936. skype
  937. FamilyIssues
  938. FellowTeens
  939. MinecraftParodyMemes
  940. BloodyLegends
  941. DankMemes_Circlejerk
  942. cursedminecraftimages
  943. TeenagersUnrelatable
  944. reddeadfashion
  945. reddeadmemes
  946. itswooshwith2os
  947. phones
  948. Fishers
  949. Quizlet_Live_Raids
  950. CutePuppyPics
  951. u_Wakeless_place
  952. SeenElsewhere
  953. GreyStillPlays
  954. LazarBeam
  955. FUCKYOUINPARTICULAR
  956. stein_world
  957. perfectphotos
  958. PhoenixSC
  959. Crayfish
  960. MinecraftVsFortnite
  961. CallOfDutyWorldWarTwo
  962. hypixel
  963. videomemes
  964. KeanuReeves
  965. ubisoft
  966. jacksepticeye
  967. Filmora
  968. montreal
  969. ComradeSShow
  970. InsiderMemeTrading
  971. unnamedfanbase
  972. LoomianLegacyTrading
  973. AnimalCrossingNewLeaf
  974. AdoptMyVillager
  975. papermario
  976. Memeconomy
  977. TooCuteForPorn
  978. ben
  979. GTAV
  980. smplive
  981. galaxybuds
  982. AMCsAList
  983. TwitchClips
  984. Spellbreak
  985. QueerEye
  986. jesuschristouija
  987. u_randomflyingcars
  988. onebag
  989. networking
  990. Dappermemes
  991. CrazyIdeas
  992. hardware
  993. beagle
  994. BoomerTears
  995. keto
  996. european_dankmemes
  997. QuantumSubreddits
  998. TeenMomOGandTeenMom2
  999. WeightLossAdvice
  1000. RLFashionAdvice
  1001. MetalMemes
  1002. systemofadown
  1003. guitarcirclejerk
  1004. drums
  1005. Megadeth
  1006. weightlifting
  1007. gmod
  1008. avengedsevenfold
  1009. airsoftcirclejerk
  1010. paintball
  1011. arma
  1012. joinsquad
  1013. AOC
  1014. fakeobituary
  1015. fuckmanny
  1016. JustBeWhite
  1017. GODUS
  1018. fuckalinity
  1019. adventurerscodex
  1020. slavbot
  1021. Meme_Battles
  1022. u_Trollium2166
  1023. gtavcustoms
  1024. 350z
  1025. Hawaii
  1026. Scootering
  1027. skate3
  1028. bmx
  1029. arizona
  1030. Sunsets
  1031. projectcar
  1032. Mustang
  1033. snowboarding
  1034. Boxing
  1035. u_slyone05
  1036. gank
  1037. ForHonorWuLin
  1038. bruhfunny
  1039. ForHonorRants
  1040. ProjectJojo
  1041. ProGreenStarPlatinum
  1042. fanStands
  1043. nothingeverhappens
  1044. imveryedgy
  1045. stupidquestions
  1046. forhonorknights
  1047. UnexpectedForHonor
  1048. ShootingFishInABarrel
  1049. RubberSoulMains
  1050. JojoHFTF
  1051. UnexpectedJoJo
  1052. undetectedsabaton
  1053. Battlefield
  1054. MillenniumDawn
  1055. fightsticks
  1056. okuyasu_irl
  1057. Stepmania
  1058. WOOOOOOSHED
  1059. shigechi_appreciation
  1060. completelyrealtexts
  1061. SteamScams
  1062. Powerwolf
  1063. u_KindStrangerOnReddit
  1064. PvZHeroes
  1065. Fish
  1066. JuiceWRLD
  1067. Gatorade
  1068. SelfHate
  1069. UgandaKnuckles
  1070. depressed
  1071. walouija
  1072. WeirdQuites
  1073. askdoctors
  1074. u_White0000
  1075. TrollXChromosomes
  1076. NarutoBlazing
  1077. u_Datnotguy17
  1078. howtokeepanidiotbusy
  1079. AyyMD
  1080. Jreg
  1081. wheresMwaldo
  1082. Political_Tumor
  1083. Purdue
  1084. GamingDetails
  1085. Handwriting
  1086. CrossView
  1087. SharedBPM
  1088. test
  1089. Stonetossingjuice
  1090. PictureGame
  1091. explainabookplotbadly
  1092. DuwangGang
  1093. Meemagers
  1094. CallMeCarson
  1095. ToolJerk
  1096. cursedmemes
  1097. virtualbeggar
  1098. left4dead
  1099. bigbangedmemes
  1100. whatintarnation
  1101. comicbookcollecting
  1102. Trophies
  1103. u_lilsusnibba
  1104. subredditwithnorules
  1105. homestuck
  1106. lux
  1107. TeamfightTactics
  1108. Wukongmains
  1109. LeagueofFailures
  1110. LeagueOfMemes
  1111. ezrealmains
  1112. akalimains
  1113. yuumimains
  1114. YIMO
  1115. botlanetinder
  1116. supportlol
  1117. MordekaiserMains
  1118. YasuoMains
  1119. neekomains
  1120. ApheliousMains
  1121. LEMMiNO
  1122. space
  1123. wwiipics
  1124. u_alt_1236
  1125. FiftyFiftyDev
  1126. MercyClub
  1127. Normies
  1128. wooooshwith4os
  1129. DungeonsAndDragons
  1130. spongebob
  1131. FromTheDepths
  1132. SpaceflightSimulator
  1133. BeardedDragons
  1134. Spore
  1135. TeenAstronomy
  1136. HistoryPorn
  1137. u_OneStrikeyBoi
  1138. tylerthecreator
  1139. PictureRap
  1140. CryptoftheNecrodancer
  1141. Teens4Teens
  1142. freenagers
  1143. RamenRegime
  1144. SemenTeam
  1145. Pitland
  1146. insaneparents
  1147. 90DayFiance
  1148. Chinesetourists
  1149. interracialdating
  1150. PutAnEggOnIt
  1151. drawings
  1152. u_kayasphotographs
  1153. mildlycreepy
  1154. likeothergirls
  1155. kahootgames
  1156. PoliticalCompassMemes
  1157. mood
  1158. cfbsober
  1159. TIGoogled
  1160. fsusports
  1161. rolltide
  1162. NewYorkMets
  1163. HuntsvilleAlabama
  1164. nfl
  1165. minnesotavikings
  1166. KarmaCourt
  1167. CFBOffTopic
  1168. Teenageers
  1169. 3BeansAndABeerCap
  1170. popheadscirclejerk
  1171. PuppySmiles
  1172. Komi_san
  1173. freebies
  1174. zerowondering
  1175. 177013
  1176. untrustworthypoptarts
  1177. subredditcancer
  1178. SubwayHentai
  1179. TsundereSharks
  1180. bee_irl
  1181. banned
  1182. LGBTOpenModmail
  1183. u_Rulx8
  1184. The_Dedede
  1185. NintendoWaifus
  1186. pchelp
  1187. SweetHomeAlabama
  1188. SmallYoutubers
  1189. Advertise
  1190. Suddenlybabyimyours
  1191. Lolitary
  1192. PornoMemes
  1193. clevercomebacks
  1194. SpaceMemes
  1195. TankPorn
  1196. AbandonedPorn
  1197. Hbonds
  1198. Jewdank
  1199. LiveLikeLarry
  1200. birdswitharms
  1201. SchoolSystemBroke
  1202. popping
  1203. okboomerretard
  1204. plants
  1205. PhonesAreBad
  1206. SavageGarden
  1207. airplaneears
  1208. shutthefuckup
  1209. mermaids
  1210. OriginalCharacters
  1211. tuckedinkitties
  1212. RoastMyCat
  1213. curledfeetsies
  1214. Hellenism
  1215. yandere_simulator
  1216. catsareliquid
  1217. trichotillomania
  1218. lazarbeamsubmissions
  1219. dark_humor
  1220. fucksauerkraut
  1221. TheBeatles
  1222. produce
  1223. French
  1224. LilPeep
  1225. GitCommitDie
  1226. u_Brisingr_105
  1227. MarioMaker
  1228. gamingsuggestions
  1229. animation
  1230. FortniteCreative
  1231. ShrineOfFishstick
  1232. FortNiteMobile
  1233. FortniteSwitch
  1234. mariokart
  1235. u_Rodolfo20
  1236. jordancambridge
  1237. emu
  1238. beermoney
  1239. badminton
  1240. vlone
  1241. TimHortons
  1242. Repsneakers
  1243. TakashiMurakami
  1244. stamps
  1245. yeezys
  1246. DesignerReps
  1247. Rabbits
  1248. DesignMyRoom
  1249. LegitCheck
  1250. Hypebeasts
  1251. Bape
  1252. bapeheads
  1253. kaws
  1254. painting
  1255. vintage
  1256. insects
  1257. fossilid
  1258. Crystals
  1259. u_HanzAAli
  1260. PixelPeople
  1261. lifeisnotjust
  1262. RedditTrollss
  1263. notsureifgoodadvice
  1264. speedrun
  1265. gtavmodding
  1266. JJBA
  1267. whoooosh
  1268. Conrandom
  1269. Birbs
  1270. u_trash5652
  1271. BattleJackets
  1272. guitarlessons
  1273. virginvschad
  1274. Ghostbc
  1275. oldinternet
  1276. Moomins
  1277. Shuffles_Deck
  1278. Vent
  1279. Sims4
  1280. ShittyAdverts
  1281. saudiarabia
  1282. stopsmoking
  1283. ProRevenge
  1284. yaris
  1285. carporn
  1286. u_ThePinkPanda205
  1287. MadeOfStyrofoam
  1288. 5sos
  1289. GAAB350
  1290. formuladank
  1291. xqcow
  1292. whatsthisworth
  1293. GenZ
  1294. danduscirclejerk
  1295. andyterracianofanclub
  1296. radicalcentrism
  1297. killthosewhodisagree
  1298. onlinemischief
  1299. aromantic
  1300. u_TheAceOfToasters
  1301. javahelp
  1302. TheArcana
  1303. AquaticAsFuck
  1304. JohnMulaney
  1305. Assistance
  1306. doodles
  1307. sadcats
  1308. April11Gang
  1309. tomodachilife
  1310. Chonkers
  1311. Multicopter
  1312. ElectricSkateboarding
  1313. subaru
  1314. radiocontrol
  1315. Battlecars
  1316. CafeRacers
  1317. Jeep
  1318. AwesomeCarMods
  1319. rccars
  1320. whatsthissnake
  1321. CalamariRaceTeam
  1322. HotWheels
  1323. outrun
  1324. FPVvideos
  1325. PraiseTheCameraMan
  1326. saladsmiles
  1327. MobileGaming
  1328. techhelp
  1329. Competitiveoverwatch
  1330. Boblin
  1331. PlayINGRust
  1332. WarframeRunway
  1333. u_haggartt
  1334. earthbound
  1335. VizzedGames
  1336. OldReposts
  1337. misheard
  1338. area51
  1339. sharktank
  1340. awesome
  1341. u_PragatiBuffett
  1342. mediawiki
  1343. robertdowneyjr
  1344. JoJoMemes
  1345. u_Gameman740
  1346. ExpandDong
  1347. KarmaSacrifice
  1348. Minecraftbuilds
  1349. Foodlottery
  1350. MisfitShitposts
  1351. JellesMarbleRuns
  1352. Marblelympics
  1353. u_Donghoon
  1354. DhruvTheKid
  1355. RushWars
  1356. RicoGang
  1357. The4KMegaBox
  1358. shittybrawlstars
  1359. SmashLand
  1360. Cosmic_Clash
  1361. barleygang
  1362. DrMarioWorld
  1363. Archero
  1364. golfblitz
  1365. TickGang
  1366. NewSkaters
  1367. TheLetterH
  1368. Crushes
  1369. KarmaRoulette
  1370. u_Manasveer
  1371. UnexpectedThanos
  1372. depression_memes
  1373. u_Banapple101
  1374. drphil
  1375. ShittyPhotoshop
  1376. ft86
  1377. iilluminaughtii
  1378. showerthoughs
  1379. TheBrotherhoodofBros
  1380. MyBloodyValentine
  1381. SamandTolki
  1382. radiohead
  1383. radioheadcirclejerk
  1384. rantgrumps
  1385. googletranslate
  1386. ConspiracyGrumps
  1387. shoegaze
  1388. MichaelJackson
  1389. ClubPenguin
  1390. Toontown
  1391. rumney_marsh_academy
  1392. saplings
  1393. Pomade
  1394. playboicarti
  1395. Adorable_Animals
  1396. OverwatchUniversity
  1397. u_IOPasGhoulTrooper
  1398. CitadelOfSkins
  1399. heathernotpleased
  1400. comingout
  1401. ShitFortNiteBRSays
  1402. fortniteparentsclub
  1403. Cello
  1404. Golfwang
  1405. EveryoneIsAMod
  1406. LightModePatrol
  1407. JadenSmith
  1408. SuddenlyHitler
  1409. FilthyFrank
  1410. VeronaNJ
  1411. evilbuildings
  1412. cursedvideos
  1413. danktintinmemes
  1414. AwardSpeechEdits
  1415. AgainstHateSubreddits
  1416. deepweb
  1417. TeenagersTalkPolitics
  1418. shortcels
  1419. CURRENCY
  1420. WarriorCats
  1421. thedawnpatrol
  1422. upvote
  1423. theydidthemonstermath
  1424. u_ii_karmakun_ii
  1425. HumanTippyTaps
  1426. SamePicOfSteveHarvey
  1427. onionhate
  1428. redbubble
  1429. Tennessee
  1430. singapore
  1431. NuclearRevenge
  1432. JUSTNOMIL
  1433. jesuschristreddit
  1434. FlashTV
  1435. LegendsOfTomorrow
  1436. westworld
  1437. boringdystopia
  1438. dankjewishmemes
  1439. crazystories
  1440. calculators
  1441. LatinoPeopleTwitter
  1442. Dachshund
  1443. AdrenalinePorn
  1444. Dance
  1445. u_Santolmo
  1446. hardwaregore
  1447. dankgentina
  1448. fake90skids
  1449. reactionpics
  1450. ImagesYouCanHear
  1451. tf2shitposterclub
  1452. Nightmares
  1453. themonkeysotherpaw
  1454. transpositive
  1455. FifaCareers
  1456. PremierLeague
  1457. spiders
  1458. downvotesreally
  1459. coldshowers
  1460. puppy101
  1461. chanceme
  1462. trackandfield
  1463. architecture
  1464. orlando
  1465. ACT
  1466. YeetingKids
  1467. ParentsAreFuckingDumb
  1468. peopleofwalmart
  1469. donaldtrump
  1470. aethism
  1471. Relatable_RC
  1472. NewVegasMemes
  1473. CursedMinecraft
  1474. Area51memes
  1475. admincraft
  1476. fnv
  1477. humblebundles
  1478. blackmagicdesign
  1479. Crouton
  1480. promotereddit
  1481. itplaysit
  1482. youtubecomments
  1483. Ebay
  1484. gamecollecting
  1485. smashmemes
  1486. Mordhau
  1487. namenerds
  1488. greatpyrenees
  1489. sexyoffbrands
  1490. bottlephilia
  1491. u_limeylucio
  1492. sodapoppin
  1493. feminazi
  1494. yiffinhell
  1495. gravityfallsmemes
  1496. rmeme
  1497. u_I_am_Inevitable_Boi
  1498. awardbrag
  1499. redstone
  1500. Lightmodevsdark
  1501. PunPatrol
  1502. CrazyHand
  1503. e46
  1504. EngineBuilding
  1505. E46M3
  1506. Cartalk
  1507. KarmaConspiracy
  1508. MobileWallpaper
  1509. firstworldanarchists
  1510. Tabs
  1511. apolloapp
  1512. futurama
  1513. puzzles
  1514. SundaraKarma
  1515. Dreamers
  1516. programminghelp
  1517. firebrigade
  1518. drumcorpscirclejerk
  1519. fonts
  1520. OverwatchLeague
  1521. ChurchofFroppy
  1522. webhosting
  1523. Wordpress
  1524. PlantsVSZombies
  1525. StreetOutlaws
  1526. lgv30
  1527. Parents
  1528. MarioMaker2
  1529. TheWeeknd
  1530. u_Mind_The_PePe
  1531. DDLCMods
  1532. parrots
  1533. donthelpjustfilm
  1534. AccidentalRacism
  1535. u_Jimcuchim
  1536. Teachers
  1537. Amberlynn
  1538. TaylorSwift
  1539. UnlockedRedditAds
  1540. GTBAE
  1541. TouchThaFishy
  1542. That70sRetard
  1543. Indiana
  1544. ARK
  1545. shitpostbound
  1546. Philippines
  1547. DoctorBright
  1548. goodboys
  1549. blop
  1550. ThatsWhatSheSaid
  1551. watch_dogs
  1552. unexpectedoffice
  1553. birthofasub
  1554. unexpectedskyrim
  1555. Peopleoftwitch
  1556. ModSupport
  1557. CoolPetNames
  1558. amazonreviews
  1559. TwoRedditorsOneCup
  1560. CameHereToSayThis
  1561. WOSH
  1562. smartwatch
  1563. Reddit69420
  1564. u_Its-Ya-Boi-Satan
  1565. Boomer
  1566. InstaPoliceHere
  1567. FanStorytime
  1568. stories
  1569. bullying
  1570. MachineLearning
  1571. redsox
  1572. PrettyGirls
  1573. ChickenRunsAtMidnight
  1574. LimeOfTheCentury
  1575. SnapLenses
  1576. IRLEasterEggs
  1577. garfield
  1578. OkBubbyRetard
  1579. Ascendedfaketexts
  1580. matt
  1581. Patriots
  1582. nonutnovember
  1583. u_u-u_u-u_u
  1584. HeadphoneAdvice
  1585. SequelMemes
  1586. u_2006pow
  1587. YeetlordYT
  1588. CarlTheHedgehog
  1589. tall
  1590. aftergifted
  1591. EUR_irl
  1592. teenmartialarts
  1593. FostTalicska
  1594. u_Hm_Moonlight
  1595. MildlyVandalised
  1596. PhantomForces
  1597. OfficialSlazo
  1598. AJR
  1599. pokemongotrades
  1600. FreePlatinum
  1601. SnowTheGame
  1602. ggggg
  1603. GayTeensGoneMild
  1604. ruralporn
  1605. CityPorn
  1606. Surface
  1607. flightsim
  1608. AndroidWear
  1609. u_GamerWick
  1610. Myles_is_lonely
  1611. u_lesqie
  1612. UnexpectedHamilton
  1613. ComedySeasoning
  1614. AmateurPhotography
  1615. oldpeoplefacebook
  1616. Ticos
  1617. LemonySnicket
  1618. accidentalswastica
  1619. VACCINES
  1620. nealstephenson
  1621. sexualhealth
  1622. Forgotten_Realms
  1623. makeaband
  1624. AskLosAngeles
  1625. musicians
  1626. Guiltygear
  1627. MyHeroAcademiaRPG
  1628. AdventurersLeague
  1629. sallyface
  1630. TikTokCringe
  1631. darkmemes
  1632. EntitledBitch
  1633. Trufemcels
  1634. sad
  1635. PanPorn
  1636. BeautyBoxes
  1637. Ipsy
  1638. u_cottonorwool
  1639. pcmusic
  1640. intermittentfasting
  1641. angry
  1642. socialanxiety
  1643. u_Jumpspider74
  1644. cowboys
  1645. Mavericks
  1646. dolphinconspiracy
  1647. rule34
  1648. ImaginaryHorrors
  1649. DarkDeception
  1650. fuckea
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submitted by CaesarNaples2 to copypastapublishin [link] [comments]

Elaborating on Datadash's 50k BTC Prediction: Why We Endorse the Call

As originally published via CoinLive
I am the Co-Founder at CoinLive. Prior to founding Coinlive.io, my area of expertise was inter-market analysis. I came across Datadash 50k BTC prediction this week, and I must take my hats off to what I believe is an excellent interpretation of the inter-connectivity of various markets.
At your own convenience, you can find a sample of Intermarket analysis I've written in the past before immersing myself into cryptos full-time.
Gold inter-market: 'Out of sync' with VIX, takes lead from USD/JPY
USD/JPY inter-market: Watch divergence US-Japan yield spread
EUUSD intermarket: US yields collapse amid supply environment
Inter-market analysis: Risk back in vogue, but for how long?
USD/JPY intermarket: Bulls need higher adj in 10-y US-JP spread
The purpose of this article is to dive deeper into the factors Datadash presents in his video and how they can help us draw certain conclusions about the potential flows of capital into crypto markets and the need that will exist for a BTC ETF.
Before I do so, as a brief explainer, let's touch on what exactly Intermarket analysis refers to:
Intermarket analysis is the global interconnectivity between equities, bonds, currencies, commodities, and any other asset class; Global markets are an ever-evolving discounting and constant valuation mechanism and by studying their interconnectivity, we are much better positioned to explain and elaborate on why certain moves occur, future directions and gain insights on potential misalignments that the market may not have picked up on yet or might be ignoring/manipulating.
While such interconnectivity has proven to be quite limiting when it comes to the value one can extract from analyzing traditional financial assets and the crypto market, Datadash has eloquently been able to build a hypothesis, which as an Intermarket analyst, I consider very valid, and that matches up my own views. Nicolas Merten constructs a scenario which leads him to believe that a Bitcoin ETF is coming. Let's explore this hypothesis.
I will attempt to summarize and provide further clarity on why the current events in traditional asset classes, as described by Datadash, will inevitably result in a Bitcoin ETF. Make no mistake, Datadash's call for Bitcoin at 50k by the end of 2018 will be well justified once a BTC ETF is approved. While the timing is the most challenging part t get right, the end result won't vary.
If one wishes to learn more about my personal views on why a BTC ETF is such a big deal, I encourage you to read my article from late March this year.
Don't Be Misled by Low Liquidity/Volume - Fundamentals Never Stronger
The first point Nicholas Merten makes is that despite depressed volume levels, the fundamentals are very sound. That, I must say, is a point I couldn't agree more. In fact, I recently wrote an article titled The Paradox: Bitcoin Keeps Selling as Intrinsic Value Set to Explode where I state "the latest developments in Bitcoin's technology makes it paradoxically an ever increasingly interesting investment proposition the cheaper it gets."
However, no article better defines where we stand in terms of fundamentals than the one I wrote back on May 15th titled Find Out Why Institutions Will Flood the Bitcoin Market, where I look at the ever-growing list of evidence that shows why a new type of investors, the institutional ones, looks set to enter the market in mass.
Nicholas believes that based on the supply of Bitcoin, the market capitalization can reach about $800b. He makes a case that with the fundamentals in bitcoin much stronger, it wouldn't be that hard to envision the market cap more than double from its most recent all-time high of more than $300b.
Interest Rates Set to Rise Further
First of all, one of the most immediate implications of higher rates is the increased difficulty to bear the costs by borrowers, which leads Nicholas to believe that banks the likes of Deutsche Bank will face a tough environment going forward. The CEO of the giant German lender has actually warned that second-quarter results would reflect a “revenue environment [that] remains challenging."
Nicholas refers to the historical chart of Eurodollar LIBOR rates as illustrated below to strengthen the case that interest rates are set to follow an upward trajectory in the years to come as Central Banks continue to normalize monetary policies after a decade since the global financial crisis. I'd say, that is a correct assumption, although one must take into account the Italian crisis to be aware that a delay in higher European rates is a real possibility now.
![](https://coinlive.io/ckeditor_assets/pictures/947/content_2018-05-30_1100.png)
Let's look at the following combinations: Fed Fund Rate Contract (green), German 2-year bond yields (black) and Italy's 10-year bond yield (blue) to help us clarify what's the outlook for interest rates both in Europe and the United States in the foreseeable future. The chart suggests that while the Federal Reserve remains on track to keep increasing interest rates at a gradual pace, there has been a sudden change in the outlook for European rates in the short-end of the curve.
While the European Central Bank is no longer endorsing proactive policies as part of its long-standing QE narrative, President Mario Draghi is still not ready to communicate an exit strategy to its unconventional stimulus program due to protectionism threats in the euro-area, with Italy the latest nightmare episode.
Until such major step is taken in the form of a formal QE conclusion, interest rates in the European Union will remain depressed; the latest drastic spike in Italy's benchmark bond yield to default levels is pre-emptive of lower rates for longer, an environment that on one hand may benefit the likes of Deutsche Bank on lower borrowing costs, but on the other hand, sets in motion a bigger headache as risk aversion is set to dominate financial markets, which leads to worse financial consequences such as loss of confidence and hence in equity valuations.
![](https://coinlive.io/ckeditor_assets/pictures/948/content_2018-05-30_1113.png)
Deutsche Bank - End of the Road?
Nicholas argues that as part of the re-restructuring process in Deutsche Bank, they will be facing a much more challenging environment as lending becomes more difficult on higher interest rates. At CoinLive, we still believe this to be a logical scenario to expect, even if a delay happens as the ECB tries to deal with the Italian political crisis which once again raises the question of whether or not Italy should be part of the EU. Reference to an article by Zerohedge is given, where it states:
"One day after the WSJ reported that the biggest German bank is set to "decimate" its workforce, firing 10,000 workers or one in ten, this morning Deutsche Bank confirmed plans to cut thousands of jobs as part of new CEO Christian Sewing's restructuring and cost-cutting effort. The German bank said its headcount would fall “well below” 90,000, from just over 97,000. But the biggest gut punch to employee morale is that the bank would reduce headcount in its equities sales and trading business by about 25%."
There is an undeniably ongoing phenomenon of a migration in job positions from traditional financial markets into blockchain, which as we have reported in the past, it appears to be a logical and rational step to be taken, especially in light of the new revenue streams the blockchain sector has to offer. Proof of that is the fact that Binance, a crypto exchange with around 200 employees and less than 1 year of operations has overcome Deutsche Bank, in total profits. What this communicates is that the opportunities to grow an institution’s revenue stream are formidable once they decide to integrate cryptocurrencies into their business models.
One can find an illustration of Deutsche Bank's free-fall in prices below:
![](https://coinlive.io/ckeditor_assets/pictures/946/content_2018-05-30_1052.png)
Nicholas takes notes of a chart in which one can clearly notice a worrying trend for Italian debt. "Just about every other major investor type has become a net seller (to the ECB) or a non-buyer of BTPs over the last couple of years. Said differently, for well over a year, the only marginal buyer of Italian bonds has been the ECB!", the team of Economists at Citi explained. One can find the article via ZeroHedge here.
![](https://coinlive.io/ckeditor_assets/pictures/953/content_2018-05-30_1451.png)
Equities & Housing to Suffer the Consequences
Nicholas notes that trillions of dollars need to exit these artificially-inflated equity markets. He even mentions a legendary investor such as George Soros, who has recently warned that the world could be on the brink of another devastating financial crisis, on lingering debt concerns in Europe and a strengthening US dollar, as a destabilizing factor for both the US's emerging- and developed-market rivals.
Ray Dalio, another legend in the investing world and Founder of Bridgewater Associates, the world’s largest hedge fund, "has ramped up its short positions in European equities in recent weeks, bringing their total value to an estimated $22 billion", MarketWatch reports.
Nicholas extracts a chart by John Del Vecchio at lmtr.com where it illustrates the ratio between stocks and commodities at the lowest in over 50 years.
As the author states:
"I like to look for extremes in the markets. Extremes often pinpoint areas where returns can be higher and risk lower than in other time periods. Take the relationship between commodities and stocks. The chart below shows that commodities haven not been cheaper than stocks in a generation. We often hear this time it is different” to justify what’s going on in the world. But, one thing that never changes is human nature. People push markets to extremes. Then they revert. "
![](https://coinlive.io/ckeditor_assets/pictures/954/content_2018-05-30_1459.png)
Bitcoin ETF the Holy Grail for a Cyclical Multi-Year Bull Run
It is precisely from this last chart above that leads Nicholas to believe we are on the verge of a resurgence in commodity prices. Not only that but amid the need of all this capital to exit stocks and to a certain extent risky bonds (Italian), a new commodity-based digital currency ETF based on Bitcoin will emerge in 2018.
The author of Datadash highlights the consideration to launching a Bitcoin ETF by the SEC. At CoinLive, our reporting of the subject can be found below:
"Back in April, it was reported that the US Securities and Exchange Commission (SEC) has put back on the table two Bitcoin ETF proposals, according to public documents. The agency is under formal proceedings to approve a rule change that would allow NYSE Arca to list two exchange-traded funds (ETFs) proposed by fund provider ProShares. The introduction of an ETF would make Bitcoin available to a much wider share of market participants, with the ability to directly buy the asset at the click of a button, essentially simplifying the current complexity that involves having to deal with all the cumbersome steps currently in place."
Nicholas refers to the support the Bitcoin ETF has been receiving by the Cboe president Chris Concannon, which is a major positive development. CoinLive reported on the story back in late March, noting that "a Bitcoin ETF will without a doubt open the floodgates to an enormous tsunami of fresh capital entering the space, which based on the latest hints by Concannon, the willingness to keep pushing for it remains unabated as the evolution of digital assets keeps its course."
It has been for quite some time CoinLive's conviction, now supported by no other than Nicholas Merten from Datadash, that over the next 6 months, markets will start factoring in the event of the year, that is, the approval of a Bitcoin ETF that will serve as a alternative vehicle to accommodate the massive flows of capital leaving some of the traditional asset classes. As Nicholas suggests, the SEC will have little choice but to provide alternative investments.
Bitcoin as a Hedge to Lower Portfolios' Volatility
Last but not least, crypto assets such as Bitcoin and the likes have an almost non-existent correlation to other traditional assets such as stocks, bonds, and commodities, which makes for a very attractive and broadly-applicable diversification strategy for the professional money as it reduces one’s portfolio volatility. The moment a Bitcoin ETF is confirmed, expect the non-correlation element of Bitcoin as a major driving force to attract further capital.
Anyone Can Be Wrong Datadash, But You Won't be Wrong Alone
Having analyzed the hypothesis by Nicholas Merten, at CoinLive we believe that the conclusion reached, that is, the creation of a Bitcoin ETF that will provide shelter to a tsunami of capital motivated by the diversification and store of value appeal of Bitcoin, is the next logical step. As per the timing of it, we also anticipate, as Nicholas notes, that it will most likely be subject to the price action in traditional assets. Should equities and credit markets hold steady, it may result in a potential delay, whereas disruption in the capital market may see the need for a BTC ETF accelerate. Either scenario, we will conclude with a quote we wrote back in March.
"It appears as though an ETF on Bitcoin is moving from a state of "If" to "When."
Datadash is certainly not alone on his 50k call. BitMEX CEO Arthur Hayes appears to think along the same line.
On behalf of the CoinLive Team, we want to thank Nicholas Merten at Datadash for such enlightening insights.
submitted by Ivo333 to BitcoinMarkets [link] [comments]

b

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submitted by confluencefx to u/confluencefx [link] [comments]

reminder

Here's a collection of random tools you might find useful in your trading. If you guys could post other things that you've found useful too, that'd be awesome.
submitted by confluencefx to u/confluencefx [link] [comments]

HIRE ME I am a freelance content writer ready to work with you on your desired project.

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 General research about the topic to look for additional material that can be added
 Gathering the relevant information regarding the subject project at hand
 Planning the general structure of the article
 Organising the gathered information and editing for errors
 Creating media for the article
 Proof Reading
 Optimizing for SEO [on-page-SEO]
 This optimization includes making sure that the keyword density is between 0.5-5percent
 Headings
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submitted by TheChiefcat to writersforhire [link] [comments]

[Hire Me] I am an exceptional ghostwriter with strong expertise over a wide array of topics extending from Finance, real estate, health, and fitness.

Hi! l do hope that you are doing fantastic today.l am very keen on writing articles for you; l am an exceptional ghostwriter with vast knowledge in topics like finance, marketing, health & fitness, and e-commerce. My SEO skills are excellent, and so is my keyword research. Here is a summary of what l will do for you provided you give me the chance to work with you The working process as a Freelance write:
 Receiving lists of articles and project guidelines
 General research about the topic to look for additional material that can be added; keyword research
 Gathering the relevant information regarding the subject project at hand
 Planning the general structure of the article
 Organising the gathered information and editing for errors
 SEO optimizing the articles: for SEO optimizing I optimize the articles around Yoast SEO, it’s the best SEO plugin in my own opinion.
 This optimization includes making sure that the keyword density is between 0.5-5percent
 Headings
 Reducing the passive sentences within the whole article.
 Creating media for the article: for this l use Canva, Pixel bay, and Pexels
 Proof Reading
 Submitting the completed articles to the editors
The working process as a freelance website content writer
 Understanding the fundamentals of the website at hand and its future projection
 Search and study of completion or potential competitors using spy tools like SEMrush and spy
 Keyword research; this is important for getting the best out of SEO
 General research about the topic to look for additional material that can be added
 Gathering the relevant information regarding the subject project at hand
 Planning the general structure of the article
 Organising the gathered information and editing for errors
 Creating media for the article
 Proof Reading
 Optimizing for SEO [on-page-SEO]
 This optimization includes making sure that the keyword density is between 0.5-5percent
 Headings
 Reducing the passive sentences within the whole article.
 Publishing the article online
Websites worked on 1. https://thechiefcat.com/
Sample article :
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I usually work on a per word basis and my quote is $0.08/word, however, depending on the project a per hour quote might make more sense.
I am very confident that my skill set and expertise is going to be very profitable to you.
Feel free to contact me via my email ([email protected]) so that we can discuss further, and hopefully start working together.
submitted by TheChiefcat to HireaWriter [link] [comments]

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Demo to stream Excel XLQ forex data into Matlab via FREE Yahoo Finance

Price of the quote currency (when different from account currency) ... FREE Forex Lot Size Calculator: How to use the Right Lot Size for your Trades! - Duration: 6:48. TraderNick Recommended for ... Demo to stream Excel XLQ forex data into Matlab via FREE Yahoo Finance Si tratta di un foglio di calcolo excel che rispetto alla precedente versione comprende un catalogo, indicizzato per data, che registra le quote passate di resistenza e di supporto. Real time forex rates in Excel form True FX. Very fast and easy. Includes real time bid and offer quotes from selected brokers. Please check the newest video... See MyforexDashboard in action!. The software tool that easily converts your broker's account statement files into key information to help you improve your forex results, shorten your learning ... In this tutorial, we will learn how to obtain JSON data (in Excel with VBA) from the IEX API as an alternative to the Yahoo API that was widely used but is now defunct. Links ... Download the Excel spreadsheet that can automatically get stock quotes from Yahoo Finance - no VBA coding required! http://www.excelclout.com/stock-quotes-in...

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