Model

Use cases · Individuals

Students and universities: 20 ways to use Ora

Finance classes and student funds learning indicators, events and forecasts on real data. Each example is a complete, runnable request with the real answers it returned (26 requests, captured 2026-10-31), what they mean and, where it fits, the action it would send.

Run withAnswers were captured on ora-fin-0.1.1. Another model changes the request JSON and the Playground link; run it there to see its answers.

Rule functions and facts used by this player (63)

sma 6 ref 3 ema 2 rsi 2 atr 2 log 2 offset 2 bblower 2 swinglow 2 avg 2 wma 1 doji 1 engulfing_bull 1 hammer 1 inside_bar 1 marubozu 1 outside_bar 1 beat_eps_last 1 beat_revenue_last 1 eps_growth_yoy 1 eps_surprise_pct 1 div_count_ttm 1 div_yield_ttm 1 raised_last 1 years_of_growth 1 days_since_split 1 days_to_split 1 last_split_ratio 1 reverse_split_last 1 splits_5y 1 atr_pct 1 sqrt 1 std 1 tr 1 bbmid 1 bbupper 1 macd 1 macdhist 1 macdsignal 1 swinghigh 1 adx 1 cci 1 diminus 1 diplus 1 stochd 1 stochk 1 willr 1 median 1 obv 1 percentrank 1 highest 1 highestbars 1 max 1 crossup 1 zscore 1 cum 1 rec 1 rma 1 days_to_earnings 1 roc 1 between 1 crossdown 1 dark_cloud 1

Examples 11–20 of 20 · page 2 of 2

Students and universities · example 11

Lesson 11: trend strength with ADX on XLE

Learn the difference between trend strength (ADX) and trend direction (+DI and -DI).

ora-fin-0.1.1XLE5 questions

StateXLE
Questions5 asked
Answersreal, captured
Actionsnone

State

{"symbol":"XLE"} The server fills in the latest completed session.

Questions

`adx`	rule	`adx(14) > 25` Trending (ADX above 25)
`up`	rule	`adx(14) > 20 and diplus(14) > diminus(14)` Trending up (ADX over 20 and +DI over −DI)
`dn`	rule	`diminus(14) > diplus(14)` -DI above +DI (sellers in control)
`cci`	rule	`cci(20) < -100` CCI(20) under -100
`up_week`	forecast	Will the stock be higher in a week? Higher in a week

Answers

Question	Answer	Reading
`adx` Trending (ADX above 25)	0.0708	false
`up` Trending up (ADX over 20 and +DI over −DI)	0.2133	false
`dn` -DI above +DI (sellers in control)	0.1748	false
`cci` CCI(20) under -100	0.0614	false
`up_week` Higher in a week	0.592	59% · close to even

What it means

For XLE on the session of 2026-10-30: Not true: Trending (ADX above 25); Trending up (ADX over 20 and +DI over −DI); -DI above +DI (sellers in control); CCI(20) under -100. Forecasts: Higher in a week 59%.

A high ADX with -DI on top is a strong downtrend; a low ADX means trend tools are unreliable whatever the DI lines say.

Request JSON

{
  "model": "ora-fin-0.1.1",
  "state": {
    "symbol": "XLE"
  },
  "questions": {
    "adx": {
      "type": "yes_no",
      "ask": "adx(14) > 25"
    },
    "up": {
      "type": "yes_no",
      "ask": "adx(14) > 20 and diplus(14) > diminus(14)"
    },
    "dn": {
      "type": "yes_no",
      "ask": "diminus(14) > diplus(14)"
    },
    "cci": {
      "type": "yes_no",
      "ask": "cci(20) < -100"
    },
    "up_week": {
      "type": "yes_no",
      "instructions": "Will the stock be higher in a week?"
    }
  }
}

Response JSON (XLE, real)

{
  "model": "ora-fin-0.1.1",
  "answers": {
    "adx": {
      "yes_no": 0.0708,
      "rule": "adx(14) > 25",
      "basis": "rule"
    },
    "up": {
      "yes_no": 0.2133,
      "rule": "adx(14) > 20 and diplus(14) > diminus(14)",
      "basis": "rule"
    },
    "dn": {
      "yes_no": 0.1748,
      "rule": "diminus(14) > diplus(14)",
      "basis": "rule"
    },
    "cci": {
      "yes_no": 0.0614,
      "rule": "cci(20) < -100",
      "basis": "rule"
    },
    "up_week": {
      "yes_no": 0.592
    }
  },
  "context": {
    "symbol": "XLE",
    "as_of": "2026-10-30"
  }
}

adx cci diminus diplus

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Students and universities · example 12

Lesson 12: stochastic and Williams %R on WMT

Two oscillators that compare the close with the recent range, at their classic thresholds.

ora-fin-0.1.1WMT5 questions

StateWMT
Questions5 asked
Answersreal, captured
Actionsnone

State

{"symbol":"WMT"} The server fills in the latest completed session.

Questions

`k_low`	rule	`stochk(14) < 20` Stochastic %K under 20
`kd`	English → rule	Is stochastic %K above %D?
`d_hi`	rule	`stochd(14) > 80` Stochastic %D above 80
`willr`	rule	`willr(14) > -20` Williams %R above −20
`willr_low`	rule	`willr(14) < -80` Williams %R under -80

Answers

Question	Answer	Reading
`k_low` Stochastic %K under 20	0.0613	false
`kd` Is stochastic %K above %D compiled to `stochk(14, 3, 3) > stochd(14, 3, 3)`	0.7083	true
`d_hi` Stochastic %D above 80	0.5154	on the line (true)
`willr` Williams %R above −20	0.7076	true
`willr_low` Williams %R under -80	0.0606	false

What it means

For WMT on the session of 2026-10-30: True now: Is stochastic %K above %D; Williams %R above −20. Not true: Stochastic %K under 20; Williams %R under -80. On the line: Stochastic %D above 80.

Both oscillators read where the close sits in its range; Williams %R runs from 0 to -100, the stochastic from 0 to 100.

Request JSON

{
  "model": "ora-fin-0.1.1",
  "state": {
    "symbol": "WMT"
  },
  "questions": {
    "k_low": {
      "type": "yes_no",
      "ask": "stochk(14) < 20"
    },
    "kd": {
      "type": "yes_no",
      "instructions": "Is stochastic %K above %D?"
    },
    "d_hi": {
      "type": "yes_no",
      "ask": "stochd(14) > 80"
    },
    "willr": {
      "type": "yes_no",
      "ask": "willr(14) > -20"
    },
    "willr_low": {
      "type": "yes_no",
      "ask": "willr(14) < -80"
    }
  }
}

Response JSON (WMT, real)

{
  "model": "ora-fin-0.1.1",
  "answers": {
    "k_low": {
      "yes_no": 0.0613,
      "rule": "stochk(14) < 20",
      "basis": "rule"
    },
    "kd": {
      "yes_no": 0.7083,
      "rule": "stochk(14, 3, 3) > stochd(14, 3, 3)",
      "basis": "comparison"
    },
    "d_hi": {
      "yes_no": 0.5154,
      "rule": "stochd(14) > 80",
      "basis": "rule"
    },
    "willr": {
      "yes_no": 0.7076,
      "rule": "willr(14) > -20",
      "basis": "rule"
    },
    "willr_low": {
      "yes_no": 0.0606,
      "rule": "willr(14) < -80",
      "basis": "rule"
    }
  },
  "context": {
    "symbol": "WMT",
    "as_of": "2026-10-30"
  }
}

stochd stochk willr

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Students and universities · example 13

Lesson 13: volume tells you who showed up (BAC)

Learn volume rules: against the average, against the median, percentile rank and on-balance volume.

ora-fin-0.1.1BAC5 questions

StateBAC
Questions5 asked
Answersreal, captured
Actionsnone

State

{"symbol":"BAC"} The server fills in the latest completed session.

Questions

`avg`	rule	`V > avg(V, 20)` Volume above its 20-day average
`median`	rule	`V > 2 * median(V, 20)` Volume more than twice its 20-day median
`rank`	rule	`percentrank(V, 50) > 90` Volume in the top tenth of 50 sessions
`obv`	rule	`obv() > sma(obv(), 20)` On-balance volume above its 20-day average
`spike`	forecast	Will volume spike tomorrow? A volume spike tomorrow

Answers

Question	Answer	Reading
`avg` Volume above its 20-day average	0.5704	on the line (true)
`median` Volume more than twice its 20-day median	0.0741	false
`rank` Volume in the top tenth of 50 sessions	0.2089	false
`obv` On-balance volume above its 20-day average	0.3948	false
`spike` A volume spike tomorrow	0.022	2% · unlikely

What it means

For BAC on the session of 2026-10-30: Not true: Volume more than twice its 20-day median; Volume in the top tenth of 50 sessions; On-balance volume above its 20-day average. On the line: Volume above its 20-day average. Forecasts: A volume spike tomorrow 2%.

The median ignores one huge day better than the average does; percentrank() tells you how unusual today is against recent history.

Request JSON

{
  "model": "ora-fin-0.1.1",
  "state": {
    "symbol": "BAC"
  },
  "questions": {
    "avg": {
      "type": "yes_no",
      "ask": "V > avg(V, 20)"
    },
    "median": {
      "type": "yes_no",
      "ask": "V > 2 * median(V, 20)"
    },
    "rank": {
      "type": "yes_no",
      "ask": "percentrank(V, 50) > 90"
    },
    "obv": {
      "type": "yes_no",
      "ask": "obv() > sma(obv(), 20)"
    },
    "spike": {
      "type": "yes_no",
      "instructions": "Will volume spike tomorrow?"
    }
  }
}

Response JSON (BAC, real)

{
  "model": "ora-fin-0.1.1",
  "answers": {
    "avg": {
      "yes_no": 0.5704,
      "rule": "V > avg(V, 20)",
      "basis": "rule"
    },
    "median": {
      "yes_no": 0.0741,
      "rule": "V > 2 * median(V, 20)",
      "basis": "rule"
    },
    "rank": {
      "yes_no": 0.2089,
      "rule": "percentrank(V, 50) > 90",
      "basis": "rule"
    },
    "obv": {
      "yes_no": 0.3948,
      "rule": "obv() > sma(obv(), 20)",
      "basis": "rule"
    },
    "spike": {
      "yes_no": 0.022
    }
  },
  "context": {
    "symbol": "BAC",
    "as_of": "2026-10-30"
  }
}

avg median obv percentrank sma

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Students and universities · example 14

Lesson 14: highest() vs max(), the breakout trap (NVDA)

Learn why C > max(C, 20) can never be true and C > highest(C, 20) is the correct breakout rule.

ora-fin-0.1.1NVDA5 questions

StateNVDA
Questions5 asked
Answersreal, captured
Actionsnone

State

{"symbol":"NVDA"} The server fills in the latest completed session.

Questions

`right`	rule	`C > highest(C, 20)` 20-day closing breakout
`wrong`	rule	`C > max(C, 20)` Close above max(C, 20), which includes today
`near`	rule	`C >= 0.98 * max(H, 20)` Within 2% of the 20-day high
`bars`	rule	`highestbars(H, 20) <= 3` The 20-day high is at most 3 bars old
`new_high`	forecast	Will it make a new 20-day high in the next week? A new 20-day high next week

Answers

Question	Answer	Reading
`right` 20-day closing breakout	0.0537	false
`wrong` Close above max(C, 20), which includes today	0.0537	false
`near` Within 2% of the 20-day high	0.0537	false
`bars` The 20-day high is at most 3 bars old	0.0566	false
`new_high` A new 20-day high next week	0.027	3% · unlikely

What it means

For NVDA on the session of 2026-10-30: Not true: 20-day closing breakout; Close above max(C, 20), which includes today; Within 2% of the 20-day high; The 20-day high is at most 3 bars old. Forecasts: A new 20-day high next week 3%.

max() includes the current bar, highest() looks only at the bars before; the always-false rule is the lesson.

Request JSON

{
  "model": "ora-fin-0.1.1",
  "state": {
    "symbol": "NVDA"
  },
  "questions": {
    "right": {
      "type": "yes_no",
      "ask": "C > highest(C, 20)"
    },
    "wrong": {
      "type": "yes_no",
      "ask": "C > max(C, 20)"
    },
    "near": {
      "type": "yes_no",
      "ask": "C >= 0.98 * max(H, 20)"
    },
    "bars": {
      "type": "yes_no",
      "ask": "highestbars(H, 20) <= 3"
    },
    "new_high": {
      "type": "yes_no",
      "instructions": "Will it make a new 20-day high in the next week?"
    }
  }
}

Response JSON (NVDA, real)

{
  "model": "ora-fin-0.1.1",
  "answers": {
    "right": {
      "yes_no": 0.0537,
      "rule": "C > highest(C, 20)",
      "basis": "rule"
    },
    "wrong": {
      "yes_no": 0.0537,
      "rule": "C > max(C, 20)",
      "basis": "rule"
    },
    "near": {
      "yes_no": 0.0537,
      "rule": "C >= 0.98 * max(H, 20)",
      "basis": "rule"
    },
    "bars": {
      "yes_no": 0.0566,
      "rule": "highestbars(H, 20) <= 3",
      "basis": "rule"
    },
    "new_high": {
      "yes_no": 0.027
    }
  },
  "context": {
    "symbol": "NVDA",
    "as_of": "2026-10-30"
  }
}

highest highestbars max

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Students and universities · example 15

Lesson 15: z-scores and mean reversion on GLD

Measure how far price is from its mean in standard deviations, and compare with Bollinger and RSI readings.

ora-fin-0.1.1GLD5 questions

StateGLD
Questions5 asked
Answersreal, captured
Actionsnone

State

{"symbol":"GLD"} The server fills in the latest completed session.

Questions

`z_low`	rule	`zscore(C, 20) < -2` Two deviations under the 20-day mean
`z_high`	rule	`zscore(C, 20) > 2` Close more than 2 standard deviations above its 20-day mean
`band`	rule	`C < bblower(C, 20, 2)` Closed under the lower Bollinger band
`back_in`	rule	`crossup(C, bblower(C, 20, 2))` Crossed back above the lower band
`bounce`	forecast	Will it rally at least 5% at some point in the next month? A 5% rally within a month

Answers

Question	Answer	Reading
`z_low` Two deviations under the 20-day mean	0.7743	true
`z_high` Close more than 2 standard deviations above its 20-day mean	0.0537	false
`band` Closed under the lower Bollinger band	0.6655	true
`back_in` Crossed back above the lower band	0.05	false
`bounce` A 5% rally within a month	0.503	50% · close to even

What it means

For GLD on the session of 2026-10-30: True now: Two deviations under the 20-day mean; Closed under the lower Bollinger band. Not true: Close more than 2 standard deviations above its 20-day mean; Crossed back above the lower band. Forecasts: A 5% rally within a month 50%.

A z-score beyond two is rare by construction; whether it reverts is a forecast question, not something the z-score knows.

Request JSON

{
  "model": "ora-fin-0.1.1",
  "state": {
    "symbol": "GLD"
  },
  "questions": {
    "z_low": {
      "type": "yes_no",
      "ask": "zscore(C, 20) < -2"
    },
    "z_high": {
      "type": "yes_no",
      "ask": "zscore(C, 20) > 2"
    },
    "band": {
      "type": "yes_no",
      "ask": "C < bblower(C, 20, 2)"
    },
    "back_in": {
      "type": "yes_no",
      "ask": "crossup(C, bblower(C, 20, 2))"
    },
    "bounce": {
      "type": "yes_no",
      "instructions": "Will it rally at least 5% at some point in the next month?"
    }
  }
}

Response JSON (GLD, real)

{
  "model": "ora-fin-0.1.1",
  "answers": {
    "z_low": {
      "yes_no": 0.7743,
      "rule": "zscore(C, 20) < -2",
      "basis": "rule"
    },
    "z_high": {
      "yes_no": 0.0537,
      "rule": "zscore(C, 20) > 2",
      "basis": "rule"
    },
    "band": {
      "yes_no": 0.6655,
      "rule": "C < bblower(C, 20, 2)",
      "basis": "rule"
    },
    "back_in": {
      "yes_no": 0.05,
      "rule": "crossup(C, bblower(C, 20, 2))",
      "basis": "rule"
    },
    "bounce": {
      "yes_no": 0.503
    }
  },
  "context": {
    "symbol": "GLD",
    "as_of": "2026-10-30"
  }
}

bblower crossup zscore

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Students and universities · example 16

Lesson 16: build your own indicator with rec() and cum() (SPY)

Write an exponential average by hand with rec(), check it against ema(), and count up days with cum().

ora-fin-0.1.1SPY5 questions

StateSPY
Questions5 asked
Answersreal, captured
Actionsnone

State

{"symbol":"SPY"} The server fills in the latest completed session.

Questions

`rec`	rule	`C > rec(C, self + 0.1 * (C - self))` Close above a hand-built smoothing (alpha 0.1)
`ema`	rule	`C > ema(C, 19)` Close above the 19-day EMA (the same alpha)
`rma`	rule	`C > rma(C, 10)` Close above the 10-day Wilder average (also alpha 0.1)
`cum`	rule	`cum(C > C[-1]) > cum(C < C[-1])` More up closes than down closes over the whole history
`logret`	rule	`log(C / C[-20]) > 0.02` 20-day log return above 2%

Answers

Question	Answer	Reading
`rec` Close above a hand-built smoothing (alpha 0.1)	0.0786	false
`ema` Close above the 19-day EMA (the same alpha)	0.0786	false
`rma` Close above the 10-day Wilder average (also alpha 0.1)	0.0786	false
`cum` More up closes than down closes over the whole history	0.9463	true
`logret` 20-day log return above 2%	0.0665	false

What it means

For SPY on the session of 2026-10-30: True now: More up closes than down closes over the whole history. Not true: Close above a hand-built smoothing (alpha 0.1); Close above the 19-day EMA (the same alpha); Close above the 10-day Wilder average (also alpha 0.1); 20-day log return above 2%.

An EMA with alpha 0.1 is a 19-day EMA and a 10-day Wilder average; rec() lets you build that, or anything else, step by step.

Request JSON

{
  "model": "ora-fin-0.1.1",
  "state": {
    "symbol": "SPY"
  },
  "questions": {
    "rec": {
      "type": "yes_no",
      "ask": "C > rec(C, self + 0.1 * (C - self))"
    },
    "ema": {
      "type": "yes_no",
      "ask": "C > ema(C, 19)"
    },
    "rma": {
      "type": "yes_no",
      "ask": "C > rma(C, 10)"
    },
    "cum": {
      "type": "yes_no",
      "ask": "cum(C > C[-1]) > cum(C < C[-1])"
    },
    "logret": {
      "type": "yes_no",
      "ask": "log(C / C[-20]) > 0.02"
    }
  }
}

Response JSON (SPY, real)

{
  "model": "ora-fin-0.1.1",
  "answers": {
    "rec": {
      "yes_no": 0.0786,
      "rule": "C > rec(C, self + 0.1 * (C - self))",
      "basis": "rule"
    },
    "ema": {
      "yes_no": 0.0786,
      "rule": "C > ema(C, 19)",
      "basis": "rule"
    },
    "rma": {
      "yes_no": 0.0786,
      "rule": "C > rma(C, 10)",
      "basis": "rule"
    },
    "cum": {
      "yes_no": 0.9463,
      "rule": "cum(C > C[-1]) > cum(C < C[-1])",
      "basis": "rule"
    },
    "logret": {
      "yes_no": 0.0665,
      "rule": "log(C / C[-20]) > 0.02",
      "basis": "rule"
    }
  },
  "context": {
    "symbol": "SPY",
    "as_of": "2026-10-30"
  }
}

cum ema log offset rec rma

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Students and universities · example 17

Student investment fund: pre-trade checklist for LLY

The fund's committee requires liquidity, trend, stop distance and an earnings check before any buy. The result is emailed to the committee.

ora-fin-0.1.1LLY5 questions2 actions

StateLLY
Questions5 asked
Answersreal, captured
Actions2 rules · dry run

State

{"symbol":"LLY"} The server fills in the latest completed session.

Questions

`liquid`	English → rule	Does the stock trade more than $50 million a day on average?
`trend`	rule	`C > sma(C, 50)` Above the 50-day average
`stop`	rule	`C > swinglow(5) and C - swinglow(5) < 1.5 * atr(14)` A stop under the last swing low is within 1.5 ATR
`earn`	English → rule	Is the next earnings report more than 10 days away?
`drop5`	forecast	Will it drop at least 5% at some point in the next month? A 5% drawdown within a month

Answers

Question	Answer	Reading
`liquid` Does the stock trade more than $50 million a day on average compiled to `avg(C * V, 20) > 50000000`	0.9463	true
`trend` Above the 50-day average	0.9463	true
`stop` A stop under the last swing low is within 1.5 ATR	0.0537	false
`earn` Is the next earnings report more than 10 days away compiled to `days_to_earnings > 10`	0.9463	true
`drop5` A 5% drawdown within a month	0.583	58% · close to even

Actions

Rules on the answers decide what to send.

liquid >= 0.6 and trend >= 0.6 and earn >= 0.6→Emailstudent-fund-committee

else→Emailstudent-fund-committee

What each action would send 1 of 2 fired · dry run, nothing sent

passwould send (dry run)Email → student-fund-committee

{
  "subject": "LLY passes the pre-trade checklist",
  "text": "LLY (2026-10-30): liquid, above the 50-day, no earnings in 10 days. Stop near swing low 5%. Drawdown odds 58%. Committee vote can proceed."
}

failrule false: skipped

What it means

For LLY on the session of 2026-10-30: True now: Does the stock trade more than $50 million a day on average; Above the 50-day average; Is the next earnings report more than 10 days away. Not true: A stop under the last swing low is within 1.5 ATR. Forecasts: A 5% drawdown within a month 58%. Fired: pass (Email → student-fund-committee).

A written, rule-based checklist is what a real investment committee keeps; the email is the record of the check.

Request JSON

{
  "model": "ora-fin-0.1.1",
  "state": {
    "symbol": "LLY"
  },
  "questions": {
    "liquid": {
      "type": "yes_no",
      "instructions": "Does the stock trade more than $50 million a day on average?"
    },
    "trend": {
      "type": "yes_no",
      "ask": "C > sma(C, 50)"
    },
    "stop": {
      "type": "yes_no",
      "ask": "C > swinglow(5) and C - swinglow(5) < 1.5 * atr(14)"
    },
    "earn": {
      "type": "yes_no",
      "instructions": "Is the next earnings report more than 10 days away?"
    },
    "drop5": {
      "type": "yes_no",
      "instructions": "Will it drop at least 5% at some point in the next month?"
    }
  },
  "actions": [
    {
      "id": "pass",
      "when": "liquid >= 0.6 and trend >= 0.6 and earn >= 0.6",
      "do": "email",
      "connection": "student-fund-committee",
      "subject": "{{symbol}} passes the pre-trade checklist",
      "message": "{{symbol}} ({{as_of}}): liquid, above the 50-day, no earnings in 10 days. Stop near swing low {{stop|pct}}. Drawdown odds {{drop5|pct}}. Committee vote can proceed."
    },
    {
      "id": "fail",
      "when": "else",
      "do": "email",
      "connection": "student-fund-committee",
      "subject": "{{symbol}} fails the checklist",
      "message": "{{symbol}} ({{as_of}}): trend {{trend|pct}}, earnings clear {{earn|pct}}, liquid {{liquid|pct}}. Revisit next week."
    }
  ],
  "dry_run": true
}

Response JSON (LLY, real)

{
  "model": "ora-fin-0.1.1",
  "answers": {
    "liquid": {
      "yes_no": 0.9463,
      "rule": "avg(C * V, 20) > 50000000",
      "basis": "pattern"
    },
    "trend": {
      "yes_no": 0.9463,
      "rule": "C > sma(C, 50)",
      "basis": "rule"
    },
    "stop": {
      "yes_no": 0.0537,
      "rule": "C > swinglow(5) and C - swinglow(5) < 1.5 * atr(14)",
      "basis": "rule"
    },
    "earn": {
      "yes_no": 0.9463,
      "rule": "days_to_earnings > 10",
      "basis": "pattern"
    },
    "drop5": {
      "yes_no": 0.583
    }
  },
  "context": {
    "symbol": "LLY",
    "as_of": "2026-10-30"
  },
  "actions": [
    {
      "id": "pass",
      "fired": true,
      "status": "dry_run",
      "do": "email",
      "connection": "student-fund-committee",
      "preview": {
        "subject": "LLY passes the pre-trade checklist",
        "text": "LLY (2026-10-30): liquid, above the 50-day, no earnings in 10 days. Stop near swing low 5%. Drawdown odds 58%. Committee vote can proceed."
      }
    },
    {
      "id": "fail",
      "fired": false,
      "status": "skipped"
    }
  ]
}

atr avg days_to_earnings sma swinglow

Try it in the Playground

Students and universities · example 18

Class assignment: weekly sector scan (XLK, XLF, XLE, XLV, XLU)

Every Friday the class gets one email per sector ETF with the same four answers, to write up the week's market.

ora-fin-0.1.15 symbols, one request each4 questions1 actionworkflow · Fri at 17:00 ET

ScheduleFri at 17:00 ET
State5 symbols
Questions4 asked
Answersreal, captured
Actions1 rule · dry run

State

{"symbol":"XLK"} then XLF, XLE, XLV, XLU, one request each. The server fills in the latest completed session.

Questions

`trend`	English → rule	Is the stock above its 200-day moving average?
`momentum`	rule	`roc(C, 20) > 5` Up more than 5% in 20 sessions
`rsi50`	rule	`rsi(C, 14) > 50` RSI above 50
`beat_spy`	forecast	Will it beat SPY over the next month? Beating SPY over a month

Answers

Symbol	`trend`rule	`momentum`rule	`rsi50`rule	`beat_spy`forecast	Fired
`XLK`	0.92	0.0537	0.0957	0.498	`report`
`XLF`	0.919	0.606	0.7929	0.448	`report`
`XLE`	0.9463	0.897	0.9318	0.55	`report`
`XLV`	0.9463	0.9157	0.9415	0.534	`report`
`XLU`	0.2572	0.8282	0.8929	0.445	`report`

true false not known for rules; forecasts are odds. Hover a column for its question.