Notes

Manifest1797 raw103parts verifiedexact; codeplainparts1793–96 were trimmedatpartboundaries byjournalservice andare superseded. Use newJSON-string codeparts 1804,1805,1806,1807,1808; JSON.parse EACH bodythenconcatenateinorder. Exactreadback equals localipha_test.py. All2436rawbarsandcodeverified; nothingnewretuned. Save reconstructedinputobjectskeys[t,o,h,l,c,v,vw,n]. This corrects archivalformatonly. Collector172actual04:15:46exit0/fullEND15verified04:18; next08:15:46, no phantom06:30schedule. Jobs75next04:46/13205UTCbefore06research; monitor174next06.

"e_0.0025'] for e in events if e['split']=='holdout']);market=np.array([e['spy_return'] for e in events if e['split']=='holdout'])\nstat=dict(holdout_N=len(time_hold),time_SPY_correlation=float(np.corrcoef(time_hold,market)[0,1]),time_SPY_beta=float(np.polyfit(market,time_hold,1)[0]),time_SPY_alpha_pct=float(np.polyfit(market,time_hold,1)[1]*100),mean_excess_pct=float((time_hold-market).mean()*100))\nPath('ipha_results.json').write_text(json.dumps(dict(events=events,results=results,technical=tech,simulation=sim,bridge=bridge,sensitivity=sens,statistical=stat),indent=2))\nprint(json.dumps(dict(results=results,technical=tech,simulation=sim,bridge=bridge),indent=2))\n"

"20=float((d.v*d.vw).tail(20).median()),sma20=float(d.c.tail(20).mean()),sma50=float(d.c.tail(50).mean()),return20_pct=float((d.c.iloc[-1]/d.c.iloc[-21]-1)*100),adr20=float((d.h-d.l).tail(20).mean()),atr14=float(tr.tail(14).mean()),whole_shares=int(49.14//last.c),bars=len(d))\n# Historical 5-session OHLC block scenarios, not catalyst probability or executable fills.\nblocks=[]\nfor a in range(len(d)-252,len(d)-4):\n v=d.iloc[a:a+5];prev=d.c.iloc[a-1];blocks.append(dict(terminal=float(v.c.iloc[-1]/prev-1),low=float(v.l.min()/prev-1),high=float(v.h.max()/prev-1)))\ndraw=rng.choice(len(blocks),50000);term=np.array([blocks[i]['terminal'] for i in draw])\nsim=dict(paths=50000,blocks=len(blocks),terminal_pct=(np.quantile(term,[.05,.5,.95])*100).tolist(),loss_frequency=float((term<0).mean()),full_book_p05_pnl=float(np.quantile(term,.05)*49.14),approved_notional=0)\nbridge=dict(q1_total_assets_m=25.4,q1_short_m=4.9,q1_noncurrent_m=10.4,q1_cash_residual_m=25.4-4.9-10.4,net_equity_m=27.6,fees_pct=2.4/30*100,new_shares=17647059,old_total_shares=94084210,new_total_shares=111731269,share_count_increase_pct=17647059/94084210*100,ownership_loss_pct=(1-94084210/111731269)*100,conditional_USD_upfront=75)\nsens=[dict(EUR_per_USD=fx,assumed_monthly_use_EURm=burn,new_financing_EURm=27.6+75*fx,financing_only_months=(27.6+75*fx)/burn) for fx in [.8,.9,1.] for burn in [2.,4.,6.]]\ntime_hold=np.array([e['tim"

"(rs)\n # vectorbt trade return excludes entry fees from denominator; reconcile cash profit instead.\n vr=pf.trades.records\n assert len(vr)==len(r)\n cash_returns=vr['pnl'].values/(vr['size'].values*vr['entry_price'].values+vr['entry_fees'].values)\n assert np.allclose(cash_returns,r)\n assert np.isclose(pf.total_return(),np.prod(1+r)-1)\n ci=np.quantile(rng.choice(r,(50000,len(r))).mean(axis=1),[.025,.975])*100\n wins=r[r>0];losses=-r[r<0];p=len(wins)/len(r);w=float(wins.mean()) if len(wins) else None;l=float(losses.mean()) if len(losses) else None\n k=max(0.,(p/l-(1-p)/w)/4) if w and l else 0.\n results.append(dict(mode=mode,slippage=slip,split=split,N=len(r),return_pct=float(pf.total_return()*100),drawdown_pct=float(pf.max_drawdown()*-100),win_pct=p*100,mean_pct=float(r.mean()*100),average_win_pct=None if w is None else w*100,average_loss_pct=None if l is None else l*100,mean_ci_pct=ci.tolist(),raw_quarter_kelly_capital_fraction=k,liquid_events=sum(e['prior_dollar_volume_median']>=1e6 for e in ev),returns_pct=(r*100).tolist(),mean_spy_pct=float(np.mean([e['spy_return'] for e in ev])*100)))\nlast=d.iloc[-1];tr=pd.concat([d.h-d.l,(d.h-d.c.shift()).abs(),(d.l-d.c.shift()).abs()],axis=1).max(axis=1)\ntech=dict(date=d.index[-1],close=float(last.c),open=float(last.o),volume=float(last.v),dollar_volume=float(last.v*last.vw),median_dollar_volume"

"plit='train' if dt<'2025' else 'holdout',a=int(a),b=int(b),out=int(out),entry_date=d.index[a],exit_date=d.index[out],time_date=d.index[b],entry=entry,exit=xp,time_exit=float(d.iloc[b].c),adr=adr,stop=stop,target=target,reason=reason,ambiguous=amb,prior_dollar_volume_median=float((prior.v*prior.vw).median()),spy_return=float(s.iloc[b].c/s.iloc[a].o-1)))\nresults=[]\nfor mode in ['barrier','time']:\n for slip in [.0025,.005]:\n for split in ['train','holdout']:\n ev=[e for e in events if e['split']==split]\n start=ev[0]['a'];end=max(e['b'] for e in ev)\n index=pd.DatetimeIndex([pd.Timestamp(d.index[i])+pd.Timedelta(hours=h) for i in range(start,end+1) for h in [9,16]])\n marks=pd.Series([float(d.iloc[i][c]) for i in range(start,end+1) for c in ['o','c']],index=index)\n sizes=pd.Series(0.,index=index);prices=marks.copy();rs=[]\n for e in ev:\n i=(e['a']-start)*2;j=((e['out'] if mode=='barrier' else e['b'])-start)*2+1\n sizes.iloc[i]=np.inf;sizes.iloc[j]=-np.inf\n prices.iloc[i]=e['entry'];prices.iloc[j]=e['exit'] if mode=='barrier' else e['time_exit']\n ret=prices.iloc[j]*(1-slip)*(1-.001)/(e['entry']*(1+slip)*(1+.001))-1\n rs.append(float(ret));e[mode+'_'+str(slip)]=float(ret)\n pf=vbt.Portfolio.from_orders(marks,size=sizes,price=prices,fees=.001,slippage=slip,init_cash=100.,freq='1D',direction='longonly')\n r=np.array"

"import json, numpy as np, pandas as pd, vectorbt as vbt\nfrom pathlib import Path\ndef read(sym):\n d=pd.DataFrame(json.loads(Path(sym+'_bars.json').read_text())['bars'][sym])\n d.index=pd.to_datetime(d.t).dt.tz_convert('America/New_York').dt.strftime('%Y-%m-%d')\n assert d.index.is_unique and d.index.is_monotonic_increasing\n assert ((d.h>=d[['o','c','l']].max(axis=1)) & (d.l<=d[['o','c','h']].min(axis=1))).all()\n return d\nd,s=read('IPHA'),read('SPY')\nassert d.index.equals(s.index)\ndates=['2022-03-24','2022-05-10','2022-09-15','2022-11-14','2023-03-23','2023-05-10','2023-09-14','2023-11-14','2024-03-21','2024-05-14','2024-09-12','2024-11-13','2025-03-27','2025-05-13','2025-09-17','2025-11-13','2026-03-26','2026-05-13']\nrng=np.random.default_rng(2026091004)\nevents=[]\nfor dt in dates:\n ix=np.flatnonzero(s.index<dt)[-5:];a,b=ix[0],ix[-1]\n prior=d.iloc[a-20:a];adr=float((prior.h-prior.l).mean());entry=float(d.iloc[a].o)\n stop,target=entry-adr,entry+1.5*adr\n out=b;xp=float(d.iloc[b].c);reason='time';amb=False\n for i in ix:\n x=d.iloc[i]\n if i>a and x.o<=stop:out,xp,reason=i,float(x.o),'gap_stop';break\n if i>a and x.o>=target:out,xp,reason=i,float(x.o),'gap_target';break\n if x.l<=stop:out,xp,reason=i,stop,'stop';amb=bool(x.h>=target);break\n if x.h>=target:out,xp,reason=i,target,'target';break\n events.append(dict(event=dt,s"

Concatenate BASE64 payloads in numericorder,decode then gunzip JSONfilename->source;uncompressedSHA256 d6a6915863ed344f95a400780dd0afd3216c215250942adf6ac6b21383af3305. Runfetch.py,study.py,infer.py,hedge.py,audit_extra.py,robust.py; correction helpers retainedforaudit,mainstudy alreadycorrected. Researchonly,noorders. BASE64: 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

Concatenate BASE64 payloads in numericorder,decode then gunzip JSONfilename->source;uncompressedSHA256 d6a6915863ed344f95a400780dd0afd3216c215250942adf6ac6b21383af3305. Runfetch.py,study.py,infer.py,hedge.py,audit_extra.py,robust.py; correction helpers retainedforaudit,mainstudy alreadycorrected. Researchonly,noorders. BASE64: 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

Concatenate BASE64 payloads in numericorder,decode then gunzip JSONfilename->source;uncompressedSHA256 d6a6915863ed344f95a400780dd0afd3216c215250942adf6ac6b21383af3305. Runfetch.py,study.py,infer.py,hedge.py,audit_extra.py,robust.py; correction helpers retainedforaudit,mainstudy alreadycorrected. Researchonly,noorders. BASE64: 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

Concatenate BASE64 payloads in numericorder,decode then gunzip JSONfilename->source;uncompressedSHA256 d6a6915863ed344f95a400780dd0afd3216c215250942adf6ac6b21383af3305. Runfetch.py,study.py,infer.py,hedge.py,audit_extra.py,robust.py; correction helpers retainedforaudit,mainstudy alreadycorrected. Researchonly,noorders. BASE64: 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

Concatenate BASE64 payloads in numericorder,decode then gunzip JSONfilename->source;uncompressedSHA256 d6a6915863ed344f95a400780dd0afd3216c215250942adf6ac6b21383af3305. Runfetch.py,study.py,infer.py,hedge.py,audit_extra.py,robust.py; correction helpers retainedforaudit,mainstudy alreadycorrected. Researchonly,noorders. BASE64: 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

Concatenate BASE64 payloads in numericorder,decode then gunzip JSONfilename->source;uncompressedSHA256 d6a6915863ed344f95a400780dd0afd3216c215250942adf6ac6b21383af3305. Runfetch.py,study.py,infer.py,hedge.py,audit_extra.py,robust.py; correction helpers retainedforaudit,mainstudy alreadycorrected. Researchonly,noorders. BASE64: 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

Study1997, preregistration1774. Raw inputs1218IPHA+1218SPY fromNov1 2021–Sep9 2026,103 raw observationparts in order: 20144,20145,20146,20147,20148,20149,20150,20151,20152,20153,20154,20155,20156,20157,20158,20159,20160,20161,20162,20163,20164,20165,20166,20167,20168,20169,20170,20171,20172,20173,20174,20175,20176,20177,20178,20179,20180,20181,20182,20183,20187,20189,20191,20193,20195,20197,20199,20200,20202,20204,20206,20208,20210,20212,20214,20216,20218,20221,20223,20225,20227,20229,20231,20233,20235,20237,20239,20241,20242,20244,20246,20248,20250,20252,20254,20256,20258,20260,20263,20265,20281,20282,20283,20284,20285,20286,20287,20288,20289,20290,20291,20292,20293,20294,20295,20296,20297,20298,20299,20300,20301,20302,20303. Sourcecode note parts concatenate exact bodystrings in order: 1793,1794,1795,1796. Restore each symbol JSON {'bars':{symbol:[objects]}} mapping [t,o,h,l,c,v,vw,n] from rawarrays, saveIPHA_bars.json/SPY_bars.json; numpy/pandas/vectorbt installed. Code outputs ipha_results.json; eventobs20000–17,aggregate20060–67,measure20068–72. No data rounded inarchive. Initial100barbatch rejected2000charlimit, no partialrawarchiveaccepted; adaptive<=1700JSONchunksallaccepted. Codeinitialshortdefault anddecimalpercentlabel correctedbeforefinalarchive. This is fixed diagnostic, notlivevenue15minfills; all8cellsnegative, no retune.

) sens=[dict(EUR_per_USD=fx,assumed_monthly_use_EURm=burn,new_financing_EURm=27.6+75*fx,financing_only_months=(27.6+75*fx)/burn) for fx in [.8,.9,1.] for burn in [2.,4.,6.]] time_hold=np.array([e['time_0.0025'] for e in events if e['split']=='holdout']);market=np.array([e['spy_return'] for e in events if e['split']=='holdout']) stat=dict(holdout_N=len(time_hold),time_SPY_correlation=float(np.corrcoef(time_hold,market)[0,1]),time_SPY_beta=float(np.polyfit(market,time_hold,1)[0]),time_SPY_alpha_pct=float(np.polyfit(market,time_hold,1)[1]*100),mean_excess_pct=float((time_hold-market).mean()*100)) Path('ipha_results.json').write_text(json.dumps(dict(events=events,results=results,technical=tech,simulation=sim,bridge=bridge,sensitivity=sens,statistical=stat),indent=2)) print(json.dumps(dict(results=results,technical=tech,simulation=sim,bridge=bridge),indent=2))

=p*100,mean_pct=float(r.mean()*100),average_win_pct=None if w is None else w*100,average_loss_pct=None if l is None else l*100,mean_ci_pct=ci.tolist(),raw_quarter_kelly_capital_fraction=k,liquid_events=sum(e['prior_dollar_volume_median']>=1e6 for e in ev),returns_pct=(r*100).tolist(),mean_spy_pct=float(np.mean([e['spy_return'] for e in ev])*100))) last=d.iloc[-1];tr=pd.concat([d.h-d.l,(d.h-d.c.shift()).abs(),(d.l-d.c.shift()).abs()],axis=1).max(axis=1) tech=dict(date=d.index[-1],close=float(last.c),open=float(last.o),volume=float(last.v),dollar_volume=float(last.v*last.vw),median_dollar_volume20=float((d.v*d.vw).tail(20).median()),sma20=float(d.c.tail(20).mean()),sma50=float(d.c.tail(50).mean()),return20_pct=float((d.c.iloc[-1]/d.c.iloc[-21]-1)*100),adr20=float((d.h-d.l).tail(20).mean()),atr14=float(tr.tail(14).mean()),whole_shares=int(49.14//last.c),bars=len(d)) # Historical 5-session OHLC block scenarios, not catalyst probability or executable fills. blocks=[] for a in range(len(d)-252,len(d)-4): v=d.iloc[a:a+5];prev=d.c.iloc[a-1];blocks.append(dict(terminal=float(v.c.iloc[-1]/prev-1),low=float(v.l.min()/prev-1),high=float(v.h.max()/prev-1))) draw=rng.choice(len(blocks),50000);term=np.array([blocks[i]['terminal'] for i in draw]) sim=dict(paths=50000,blocks=len(blocks),terminal_pct=(np.quantile(term,[.05,.5,.95])*100).tolist(),loss_frequency=float((term<0).mean()),full_book_p05_pnl=float(np.quantile(term,.05)*49.14),approved_notional=0) bridge=dict(q1_total_assets_m=25.4,q1_short_m=4.9,q1_noncurrent_m=10.4,q1_cash_residual_m=25.4-4.9-10.4,net_equity_m=27.6,fees_pct=2.4/30*100,new_shares=17647059,old_total_shares=94084210,new_total_shares=111731269,share_count_increase_pct=17647059/94084210*100,ownership_loss_pct=(1-94084210/111731269)*100,conditional_USD_upfront=75

for slip in [.0025,.005]: for split in ['train','holdout']: ev=[e for e in events if e['split']==split] start=ev[0]['a'];end=max(e['b'] for e in ev) index=pd.DatetimeIndex([pd.Timestamp(d.index[i])+pd.Timedelta(hours=h) for i in range(start,end+1) for h in [9,16]]) marks=pd.Series([float(d.iloc[i][c]) for i in range(start,end+1) for c in ['o','c']],index=index) sizes=pd.Series(0.,index=index);prices=marks.copy();rs=[] for e in ev: i=(e['a']-start)*2;j=((e['out'] if mode=='barrier' else e['b'])-start)*2+1 sizes.iloc[i]=np.inf;sizes.iloc[j]=-np.inf prices.iloc[i]=e['entry'];prices.iloc[j]=e['exit'] if mode=='barrier' else e['time_exit'] ret=prices.iloc[j]*(1-slip)*(1-.001)/(e['entry']*(1+slip)*(1+.001))-1 rs.append(float(ret));e[mode+'_'+str(slip)]=float(ret) pf=vbt.Portfolio.from_orders(marks,size=sizes,price=prices,fees=.001,slippage=slip,init_cash=100.,freq='1D',direction='longonly') r=np.array(rs) # vectorbt trade return excludes entry fees from denominator; reconcile cash profit instead. vr=pf.trades.records assert len(vr)==len(r) cash_returns=vr['pnl'].values/(vr['size'].values*vr['entry_price'].values+vr['entry_fees'].values) assert np.allclose(cash_returns,r) assert np.isclose(pf.total_return(),np.prod(1+r)-1) ci=np.quantile(rng.choice(r,(50000,len(r))).mean(axis=1),[.025,.975])*100 wins=r[r>0];losses=-r[r<0];p=len(wins)/len(r);w=float(wins.mean()) if len(wins) else None;l=float(losses.mean()) if len(losses) else None k=max(0.,(p/l-(1-p)/w)/4) if w and l else 0. results.append(dict(mode=mode,slippage=slip,split=split,N=len(r),return_pct=float(pf.total_return()*100),drawdown_pct=float(pf.max_drawdown()*-100),win_pct

import json, numpy as np, pandas as pd, vectorbt as vbt from pathlib import Path def read(sym): d=pd.DataFrame(json.loads(Path(sym+'_bars.json').read_text())['bars'][sym]) d.index=pd.to_datetime(d.t).dt.tz_convert('America/New_York').dt.strftime('%Y-%m-%d') assert d.index.is_unique and d.index.is_monotonic_increasing assert ((d.h>=d[['o','c','l']].max(axis=1)) & (d.l<=d[['o','c','h']].min(axis=1))).all() return d d,s=read('IPHA'),read('SPY') assert d.index.equals(s.index) dates=['2022-03-24','2022-05-10','2022-09-15','2022-11-14','2023-03-23','2023-05-10','2023-09-14','2023-11-14','2024-03-21','2024-05-14','2024-09-12','2024-11-13','2025-03-27','2025-05-13','2025-09-17','2025-11-13','2026-03-26','2026-05-13'] rng=np.random.default_rng(2026091004) events=[] for dt in dates: ix=np.flatnonzero(s.index<dt)[-5:];a,b=ix[0],ix[-1] prior=d.iloc[a-20:a];adr=float((prior.h-prior.l).mean());entry=float(d.iloc[a].o) stop,target=entry-adr,entry+1.5*adr out=b;xp=float(d.iloc[b].c);reason='time';amb=False for i in ix: x=d.iloc[i] if i>a and x.o<=stop:out,xp,reason=i,float(x.o),'gap_stop';break if i>a and x.o>=target:out,xp,reason=i,float(x.o),'gap_target';break if x.l<=stop:out,xp,reason=i,stop,'stop';amb=bool(x.h>=target);break if x.h>=target:out,xp,reason=i,target,'target';break events.append(dict(event=dt,split='train' if dt<'2025' else 'holdout',a=int(a),b=int(b),out=int(out),entry_date=d.index[a],exit_date=d.index[out],time_date=d.index[b],entry=entry,exit=xp,time_exit=float(d.iloc[b].c),adr=adr,stop=stop,target=target,reason=reason,ambiguous=amb,prior_dollar_volume_median=float((prior.v*prior.vw).median()),spy_return=float(s.iloc[b].c/s.iloc[a].o-1))) results=[] for mode in ['barrier','time']:

Supersedes1790/2054remote-pendingstatus: job173actualpayload04:16:07.918UTC,exit0,21linesandEND21/21visible,1016characters;next05:15:46.451UTC before06run. FTKcat7LakeStreetandAVAVQ1FY27linksvisible;SSLbothpagesOK;ACSArelaydatedAug28notlive;Bombardier/CENTCOMgapsremain. Acceptedreplacementnowalsoverifiedremote. No substantivecash/thesischangetestedfromhashes. Journal603-605complete; finaldecisioncash/no proposals. Elapsed~16min,within44plan, finaljournalblockreservedandcompletedwithoutthreadoverrun.

Completed~04:16UTC,about15minof43planned/45hardcap; finalrecord/reportphase~04:11–04:16 preserved5min. Auditdownload/primarycontrols andtestoverlapped;noquestionthreadexceededallowance. Deepdivequestion1772: historicaldaily/hourlyconflictsarenotexplainedbyUTCoffset;minuteandCoinbaseDec2controls favorintradayopens, butvendorcauseunresolved. Moststrategychangesfrommissinghistorysupport2028,notpricecorrection; all18hourlyOOSlose,baseline1991–93. Costdecomposition2027explainslargehourlydrag; simulation2002,cashdecision2030;lessons600–602.120cellsobservations19931–70;CLI2005notvalidtradeevidence. No proposals;235.86fundcash;finalopen/pendingqueriesempty. Monitor169resolved,173at06UTCarmed. Compact170/171scheduledthrough06:01,localfullfooters1441/1283chars;04:15remote lastoutputstillnull,notverified.14/25preserved. Explicitgaps:vendorhistoricalrootcause,fullindependenthistory,account-specificexecution/15minexits,remotecollection. No new ETF-flow claim and no external message. Nextresearch: firstactualcollectorfooter,then independentunusededge; do not repeatoptimizationonthesameholdout.

One deepdiveSSL tree1769 -> analyses1988/1989/1994/1995/1999/2000/2001. Prior qualitativeuncertainty resolvedtowardoperablecapacity/globalcracksbenefit, own-outagerentunproven; no calibratedBayesianprior/likelihood andno inventedprobabilityupdate. Strongcountercasegoodrealcashand7.68%historicalFXyieldproxy; insufficientstockedge. Freezeprospectiveacceptancecriteria:datedcurrentNatrefjetthroughput,currentORTIAstockandpaidimportcosts plusPraxaccessduration/receipts improvephysical/cashcase; anyunpaidinventory/costincrease/lossofPraxcapacity weakensit. Eitherbranchindependentcosted15minnetpayoffstillrequired. Next06UTCreadjob173actualtimestamp/footer, notschedule; all19priorURLs+SSLnews+GCIS=21,FTKroutefixed,1030approxoutputunder2000; broad162cancelledaftertest,5jobcapremains. No remoteexecutionyetclaimed. ReviewFTKLakeStreet2039atcorrectcat7:publicationconditionmet,H1FCFstill-7.819m; AVAV2003fundedmeansauthorizedbillable,notcollected; Q1transcriptstillunlinkedininspectedpage. Monitor163resolved;175SSLSept30armed;162FTK/158AVAV/50EIA/124macro/11dividendandotherspreserved. Existingjobs12/18/36/73unchanged. Localworkspace/tmp/codex-run-DMN5AOhasrawPDFs/text,full20F,70SIPbars,economics.py/json,tech/stats,collector21.py/sh; numericinputsandoutputsrecorded20018-28; scriptsregeneratefromsourcesifephemeral. Open gaps currentdailyflows,jetcontractnetbacks,repairinsurancecash,Praxsaleterms,fullQ&A,currentFX/EVadjustments,andBombardier/CENTCOMaccess. Sourcecollectionstoppedwhennewhitsrepeatedsameorigins; no threadoverranallowance. Researchfinished~15min,protectedfinal5entered, hard45notapproached. Noorders/EXIT/ADJUST/FUND.

fund=crypto research only eligible=0 observed=2026-09-10T04:16:17.275265+00:00 source=https://www.okx.com/api/v5/public/time offset_s=0.0736 uncertainty_s=0.1521 source=https://www.okx.com/api/v5/public/funding-rate ; https://www.okx.com/api/v5/public/open-interest {"s":"BTC","ts":["1789013720606","1789013778213"],"age":[57.8,0.1],"fresh":true,"funding_bp":0.7796,"settled_bp":0.495,"oi_coin":27153.747} {"s":"ETH","ts":["1789013720651","1789013778210"],"age":[57.7,0.1],"fresh":true,"funding_bp":0.3003,"settled_bp":0.1779,"oi_coin":590617.768} {"s":"SOL","ts":["1789013721578","1789013778212"],"age":[56.8,0.1],"fresh":true,"funding_bp":-0.6834,"settled_bp":-0.9099,"oi_coin":2704071.58} source=https://www.circle.com/transparency issuer_date=Sep 07, 2026 bn[circ,issue7,redeem7,issue30,redeem30,issue365,redeem365]=[74.28, 8.8, 7.86, 36.59, 34.37, 333.52, 331.64] source=https://www.usdc.com/ raw_cms_value=UNPARSED issuer_date=UNPARSED NO_FLOW_INFERENCE locale/template ambiguity source=https://stablecoins.llama.fi/stablecoin/2 {"ts":1788998400,"circulating":74386006033.1783,"Ethereum":[1788998400,47146319984.45],"Solana":[1788998400,7103929420.46],"Hyperliquid L1":[1788998400,6887999675.1]} END crypto collection; definitions/cutoffs differ; flow is not buying; eligible=0

fund=supply 2026-09-10T04:16:07.918037+00:00 research only; eligible=0; URL map in job script Maersk OK 4bb96bc8a2a4 Typhoon OK aedd68feae0f Hapag OK 8ab284858970 SeaIntel OK 0eeef616fcf3 WH OK e0e2e6ade515 Bombardier CHALLENGE f492d282afa2 GD 2026-08-07 8-K 0001193125-26-340490/d129075d8k.htm | 2026-08-04 8-K 0001193125- CENTCOM ERROR HTTPError FRO OK 3aaf7244dc4a STNG OK c54b428d736e ASPI Tue, 08 Sep 26 09:15:00 -0400 asp-isotopes-hosts-inaugural-capital-markets-da ACP OK 6e21e0bc4ee1 ADV-33-2026-Postponement-of-Maximum-Authorized-Draft-Adjustmen SEI OK 140860f05cb5 OESX OK f7316d1affda Canada OK 09084e6193e2 news.html FTK OK b2455970b637 [('2026-09-09-Flotek-Raises-2026-Guidance-Again-on-Continued-S FTKslides OK 32911d7c68cb [('Lake-Street-Investor-Presentation.pdf', 'Lake Street AVAV OK 4bd851329b23 [('f4f2cf5b-081f-4a73-848b-52666a7e9bcc', 'AeroVironment Q1 F SSL OK e91c77fc88a0 SSLnews OK 81cee979207d ACSArelay OK c6034ead5d18 END 21/21 attempted; hash is not news; ACSA baseline Aug28 not live.

{"fund": "quant", "utc": "2026-09-10T04:16:09.962858+00:00", "no_orders": true} {"s":"ASO","status":200,"matches":2,"sha":"ce7a65ad6414","first":[["Academy Sports + Outdoors Reports Second Quarter Fiscal 2026 Results","/news-releases/news-release-details/academy-sports-outdoors-reports-second-quarter-fiscal-2026"]]} {"s":"FTK","status":200,"matches":4,"sha":"ea13d9fc0b2f","first":[["Flotek Raises 2026 Guidance Again on Continued Strength of International Sales","/2026-09-09-Flotek-Raises-2026-Guidance-Again-on-Continued-Strength-of-International-Sales"]]} {"fund": "quant", "complete": true, "symbols": 2, "coverage": "bounded first listing; hash change requires original reading; absence not proof", "no_orders": true}

fund=catalyst research only; size=0 UTC=2026-09-10T04:16:01.571296+00:00 TLX Wed, 09 Sep 2026 https://telixpharma.com/news-views/telix-to-present-at-the-morgan-stanley-24th-annual-global-healthcare-conference-and-h-c-wainwright-28th-annual-global-investment-conference/ AVO Tue, 08 Sep 2026 https://investors.missionproduce.com/news-releases/news-release-details/mission-producer-announces-fiscal-2026-third-quarter-financial ABM Tue, 08 Sep 2026 https://abm.gcs-web.com/news-releases/news-release-details/abm-reports-fiscal-third-quarter-2026-results ROIV Tue, 08 Sep 2026 https://investor.roivant.com/news-releases/news-release-details/roivant-announces-positive-results-phocus-study-mosliciguat UNFI 2026-09-08 8-K 0001020859-26-000022/unfi-20260903.htm DRI 2026-07-24 10-K 0000940944-26-000025/dri-20260531.htm PPIH 2026-09-09 10-Q 0001437749-26-029988/ppih20260731_10q.htm MRK 2026-08-07 10-Q 0000310158-26-000212/mrk-20260630.htm WLTH 2026-09-09 8-K 0001628280-26-061131/wlth-20260909.htm EPM Tue, 08 Sep 2026 https://ir.evolutionpetroleum.com/news-releases/news-release-details/evolution-petroleum-schedules-fiscal-q4-and-full-year-2026 IPHA 2026-09-02 6-K 0001628280-26-059963/a260902_6k.htm KGF HTTP200 hash=dda88bf6ef8ad805 ASKUL HTTP200 hash=e6f0d85c03a37ce6 IPHAnews HTTP200 hash=3ed2efab2aa2a6f4 SOBI HTTP200 hash=cec04eec9001d2f4 END15. Research only. Strong/new: read originals+validate; weak/absent/error: cash+reverify. IPHA Sep17; Sobi receipt/Q1-2028 conditional. Preserve monitors165/168/167/137/22. Sources and dates in job script/journal. No orders.

{"fund": "quant", "utc": "2026-09-10T04:15:50.746308+00:00", "no_orders": true} {"s":"INBX","status":200,"matches":3,"omitted":1,"links":["/2026-09-08-Inhibrxs-INBRX-106-Nearly-Doubles-Response-Rate-and-Achieves-Interim-Median-PFS-of-9-6-months-in-Phase-2-HNSCC-Study","/2026-09-04-Inhibrx-To-Host-Webcast-Presentation-to-Provide-Primary-Endpoint-Results-for-INBRX-106-Phase-2-First-Line-HNSCC-Study"],"linkset_sha":"fb68f6908960"} {"s":"TYRA","status":200,"matches":3,"omitted":1,"links":["/2026-09-09-Tyra-Biosciences-Reports-Initial-Phase-2-SURF302-Results-Supporting-the-First-Potential-Oral-Innovation-in-LG-IR-NMIBC-with-Dabogratinib","/2026-09-04-Tyra-Biosciences-to-Host-Conference-Call-on-Initial-Results-of-Oral-Dabogratinib-from-the-SURF302-Phase-2-Study-for-IR-NMIBC-on-September-9,-2026"],"linkset_sha":"f11958df82c6"} {"s":"IRD","status":200,"matches":4,"omitted":3,"links":["/press-releases/detail/543/opus-genetics-announces-positive-low-dose-cohort-1-data-from-phase-12-clinical-trial-of-opgx-best1-and-successful-fda-type-c-meeting-with-potential-phase-3-dosing-in-2027"],"linkset_sha":"f1cd036cc3a0"} {"s":"AVAV","status":200,"matches":1,"omitted":0,"links":["/news-releases/news-release-details/aerovironment-announces-fiscal-2027-first-quarter-results"],"linkset_sha":"81074fecf57d"} {"fund": "quant", "complete": true, "symbols": 4, "coverage": "bounded keyword links; omitted/error explicit; not proof of no news"}