Models / Macro / trend_vol_target
Trend with a vol target
What does a hypothetical trend walk with a vol target look like on these prices, with no peek ahead, after costs?
Walks a hypothetical trend book through the prices sent: sign of the trailing return, sized to a vol target, capped, with each day's weight set from prices through the day before, after turnover costs. Reports vol, mean, drawdown, hit rate, gross, turnover and each market's part. It is a hypothetical walk on the caller's numbers, not a record of trading, a forecast or a signal to follow.
On these numbers, a hypothetical walk through the prices sent shows a mean of 7.13% a year on 12.42% annual vol against a 10% target, with a largest drawdown of 17.86%. It is not a record of trading.
Hypothetical, and on made-up numbers until you replace them. Nobody traded this, and nothing here is on offer.
Readings
The numbers, with their units.
Hypothetical annual mean
7.1326%a year
Hypothetical, after 1.1% a year of costs. Compounded end value: 109.99 per 100.
Hypothetical annual vol
watch12.42%
Target 10%.
Hypothetical mean to vol
0.5745
Annual mean over annual vol. No cash rate is subtracted.
Hypothetical largest drawdown
17.86%
Hypothetical hit rate
50.66%
Up days as a share of days with a non-zero return.
Hypothetical average gross
1.7506xNAV
Average net 0.92x.
Hypothetical turnover
21.97xNAV a year
Days walked
377
From point 127 of 504. Earlier points only fill the windows.
What flips it
The value of one input where the outcome changes, with the others held.
cost_bps
37.47bpsnow 5
At this cost the hypothetical mean return is zero. Above it, the mean is negative. Weights don't depend on cost.
target_vol_pct
28.31%now 10
Below this target, no market reaches the leverage cap on any day. From here up, the cap starts to cut weights, on any day the walk gets to.
Flags
What went past a line, and what to read before you trust the rest.
- watchThis is a hypothetical walk through the numbers sent. It is not a record of trading and says nothing about any other period. Nothing in it is a position to take. hypothetical_walk
- watchRealized vol of 12.42% is above the 10% target. Dividing by sqrt(N) assumes the markets are uncorrelated. vol_above_target
What this leaves out
What the formula leaves out, by name.
- Financing on leverage, margin, and interest on idle cash.
- Contract rolls, dividends and carry: returns are price changes only.
- Slippage beyond cost_bps, gaps, limit moves, and the time it takes to trade.
- Drift in weights between days: turnover counts target changes only.
- Correlation between markets when sizing. It shows up only in realized vol.
- The choice of markets and windows: this walk knows nothing of how many were tried.
- Fees and taxes.
What it took as given (10)
What it took as given to get here.
- No peek ahead: day t's weight uses prices through day t-1 only, and it earns day t's return. The direction and rolling vol stop one day before the return they are applied to.
- Returns are simple, close to close. Rolling vol is the sample stdev (n - 1) of the last vol_days returns.
- The walk starts at the first day both windows are full, from flat, so the first day pays to build the book.
- target_vol / sqrt(N) would hit the target only if the markets were uncorrelated and the vol estimates were right. Realized vol is reported beside the target.
- N is the number of markets sent, whether or not each has a position that day.
- Annual vol is stdev of daily returns times sqrt(periods_per_year). Annual mean is the mean daily return times periods_per_year. Mean to vol doesn't subtract any cash rate.
- A market whose rolling vol is zero, or whose trailing return is exactly zero, gets no position that day. Stale prices aren't read as low risk.
- Turnover is the sum of changes in target weights. Hit rate counts days with a non-zero return.
- If a day's loss takes equity to zero or below, the walk stops there.
- The weights stay inside the walk. The result gives averages and totals, and no market's weight or direction at the end of the series, because on current prices that would read as a position to take.
The data
The data
By market, percent a year, hypothetical
| name | contribution_pct | cost_pct | net_pct | average_weight | days_at_cap | days_no_position |
|---|---|---|---|---|---|---|
| Market A | 7.2449 | 0.2745 | 6.9703 | 0.1927 | 0 | 0 |
| Market B | -2.7202 | 0.417 | -3.1372 | 0.3026 | 0 | 0 |
| Market C | 6.2494 | 0.0593 | 6.1901 | 0.104 | 0 | 0 |
| Market D | -2.5431 | 0.3476 | -2.8907 | 0.3243 | 0 | 0 |
| Book | 8.2309 | 1.0984 | 7.1326 | 0.9235 | 0 | 0 |
Paste it into your agent
No connection needed. This prompt carries the method, the conventions and what this site's engine gives on the made-up numbers, so your agent can check its own work before it touches real ones. Every prompt, with its hash, is listed at /prompts.json. A copy that stays fixed for this version, for a stack to point at: /v/1.0/models/trend_vol_target.md.
# Trend with a vol target: a prompt from hedgefund.mdPaste this into your AI agent. It needs no connection to hedgefund.md. An agent that can run code should write and run it, and shouldn't work a long series by hand.**Question.** What does a hypothetical trend walk with a vol target look like on these prices, with no peek ahead, after costs?## Methodr_it = p_it / p_i,t-1 - 1. direction_it = sign(p_i,t-1 - p_i,t-1-L). vol_it = stdev(r_i,t-V ... r_i,t-1) * sqrt(periods_per_year). w_it = direction_it * (target / sqrt(N)) / vol_it, size capped at max_leverage. R_t = sum w_it r_it - cost * sum |w_it - w_i,t-1|. Equity_t = Equity_t-1 * (1 + R_t).## Conventions- No peek ahead: day t's weight uses prices through day t-1 only, and it earns day t's return. The direction and rolling vol stop one day before the return they are applied to.- Returns are simple, close to close. Rolling vol is the sample stdev (n - 1) of the last vol_days returns.- The walk starts at the first day both windows are full, from flat, so the first day pays to build the book.- target_vol / sqrt(N) would hit the target only if the markets were uncorrelated and the vol estimates were right. Realized vol is reported beside the target.- N is the number of markets sent, whether or not each has a position that day.- Annual vol is stdev of daily returns times sqrt(periods_per_year). Annual mean is the mean daily return times periods_per_year. Mean to vol doesn't subtract any cash rate.- A market whose rolling vol is zero, or whose trailing return is exactly zero, gets no position that day. Stale prices aren't read as low risk.- Turnover is the sum of changes in target weights. Hit rate counts days with a non-zero return.- If a day's loss takes equity to zero or below, the walk stops there.- The weights stay inside the walk. The result gives averages and totals, and no market's weight or direction at the end of the series, because on current prices that would read as a position to take.## Step 1: check your method on these made-up numbersThe numbers and names below are made up. They aren't market levels, typical values or anyone's real figures.```json{ "markets": [ { "name": "Market A", "prices": [ 100, 100.75, 101.5, 100.58, 100.6, 100.67, 100.47, 101.2, 101.41, 101.65, 101.94, 102.84, 105.17, 105.55, 105.61, 104.46, 103.6, 101.81, 101.97, 102.47, 101.82, 102.83, 102.63, 103.33, 103.71, 103.92, 105.19, 105.67, 106.18, 104.98, 104.41, 104.57, 104.43, 103.44, 103.42, 104.85, 105.56, 103.6, 102.56, 103.77, 103.04, 102.06, 101.88, 102.44, 103.09, 104.63, 105.06, 104.62, 107.61, 107.76, 107.08, 107.32, 107.97, 108.93, 109.2, 109.84, 111.49, 112.69, 113.29, 113.88, 113.95, 111.6, 110.9, 111.46, 113.46, 113.83, 111.87, 112.15, 113.03, 113.47, 114.16, 114.68, 114.23, 114.84, 116.6, 116.44, 116.68, 117.1, 117.12, 116.21, 115.73, 115.65, 115.04, 115.33, 114.9, 116.37, 115.62, 116.93, 117.77, 118.28, 119.32, 116.7, 114.84, 113.48, 112.14, 114.2, 113.23, 111.96, 112.44, 113.18, 113.66, 115.72, 116.51, 117.58, 118.9, 118.11, 119.46, 117.12, 116.18, 117.11, 115.91, 115.88, 115.89, 116.5, 118.34, 119.64, 119.61, 119.05, 118.45, 119.04, 118.26, 118.66, 119.54, 122.23, 123.01, 124.49, 124.53, 123.77, 122.91, 123.75, 125.02, 126.37, 127.02, 125.88, 126.2, 127.8, 126.41, 126.18, 127.78, 126.7, 127.73, 126.6, 127.41, 127.72, 126.63, 126.71, 128.44, 128.39, 128.32, 130.73, 133.16, 132.23, 132.48, 133.26, 133.23, 134.34, 132.26, 129.77, 129.75, 130.69, 131.68, 132.14, 132.26, 133.93, 133.05, 132.99, 131.49, 131.54, 134.37, 135.63, 136.33, 136.68, 136.64, 135.85, 136.7, 136.69, 138.63, 138.05, 137.48, 138.22, 137.24, 137.78, 139.63, 139.58, 142.4, 140.94, 141.49, 142.13, 144.49, 146.43, 147.69, 146.5, 147.79, 148.51, 149.6, 148.48, 150.1, 152.78, 155.12, 155.54, 155.2, 156.4, 157.75, 159.6, 159, 158.07, 157.95, 157.71, 158.75, 157.66, 157.33, 157.3, 155.53, 155.46, 155.65, 155.89, 156.05, 156.13, 155.14, 156.23, 155.64, 156.58, 156.11, 154.65, 155.08, 155.92, 158.2, 159.01, 160.73, 161.66, 161.4, 162.48, 165.56, 166.34, 164.35, 163.7, 163.78, 166.87, 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156.89, 154.73, 154.35, 153.59, 154.19, 153.79, 153.68, 154.21, 153.87, 153.55, 155.22, 153.65, 150.93, 150.6 ] }, { "name": "Market B", "prices": [ 100, 100.03, 100.41, 99.77, 99.15, 98.75, 98.47, 98.62, 98.52, 98.62, 99.11, 99.9, 100.37, 99.69, 99.74, 99.31, 99.65, 99.7, 99.54, 100, 99.36, 99.68, 99.93, 100.23, 101.25, 101.16, 101.61, 101.18, 100.76, 100.26, 100.73, 100.85, 100.66, 100.73, 101.06, 100.77, 100.2, 99.4, 99.17, 99.51, 99.32, 99.23, 99.22, 99.63, 100.07, 100.44, 100.08, 99.75, 99.94, 100.32, 99.79, 99.35, 98.88, 99.34, 99.15, 99.59, 99.81, 100.45, 100.35, 99.23, 99.33, 98.88, 98.11, 98.6, 98.31, 98.9, 99.13, 98.16, 98.24, 98.2, 98.62, 99.04, 98.43, 97.9, 98.6, 98.46, 98.5, 99.17, 98.86, 98.4, 98.87, 99.08, 98.95, 98.54, 97.91, 97.55, 97.2, 96.91, 98.2, 99.17, 99.5, 99.49, 99.42, 98.98, 98.39, 98.56, 98.5, 98.4, 97.92, 97.69, 98.5, 98.78, 99.4, 99.96, 100.79, 101.17, 100.43, 99.9, 99.99, 100.12, 99.54, 99.53, 98.58, 99.61, 100.63, 100.61, 101.44, 101.1, 101.01, 101.31, 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113.01, 113.02, 112.57, 112.58, 112.27 ] }, { "name": "Market C", "prices": [ 80, 79.43, 80.14, 80.44, 78.01, 77.12, 78.2, 78.74, 79.15, 81.07, 82.6, 84.21, 84.53, 82.38, 83.75, 82.32, 81.45, 78.5, 78.03, 81.04, 79.98, 80.23, 80.21, 80.4, 82.49, 83.22, 83.15, 83.06, 81.59, 79.86, 79.48, 79.37, 78.74, 79.19, 80.83, 81.47, 81.77, 80.17, 80.36, 81.36, 81.28, 82.72, 82.86, 82.74, 84, 84.54, 86.31, 86.97, 90.45, 92.64, 91.28, 90.29, 90.28, 91.73, 90.71, 91.48, 92.76, 93.23, 91.63, 89.64, 89.48, 89.69, 89.27, 89.51, 90.32, 93.17, 92.46, 91.73, 92.22, 91.03, 91.58, 92.16, 91.39, 92.18, 92.67, 93.09, 93.52, 93.08, 92.84, 92.13, 92.9, 92.72, 92.82, 91.14, 91.28, 92.43, 90.49, 91.85, 94.42, 95.49, 96.43, 95.25, 94.83, 94.3, 92.56, 93.05, 93.71, 91.74, 90.83, 91.75, 90.59, 89.12, 88.96, 89.31, 92.2, 91.29, 90.91, 91.1, 90.14, 90.14, 89.58, 88.86, 89.04, 90.97, 93.04, 93.15, 92.81, 93.28, 92.66, 91.3, 91.58, 92.55, 93.25, 93.8, 95.8, 96.73, 96.27, 96.66, 94.86, 93.53, 95.12, 96.29, 96.98, 95.91, 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"max_leverage": 2, "cost_bps": 5, "periods_per_year": 252}```Work them out with the method above. Yours should match these within 0.5%.- Hypothetical annual mean: 7.1326 % a year- Hypothetical annual vol: 12.416 %- Hypothetical mean to vol: 0.5745- Hypothetical largest drawdown: 17.8552 %- Hypothetical hit rate: 50.6631 %- Hypothetical average gross: 1.7506 x NAV- Hypothetical turnover: 21.9677 x NAV a year- Days walked: 377Where the outcome flips, with the other inputs held:- cost_bps at 37.4683: At this cost the hypothetical mean return is zero. Above it, the mean is negative. Weights don't depend on cost.- target_vol_pct at 28.306954: Below this target, no market reaches the leverage cap on any day. From here up, the cap starts to cut weights, on any day the walk gets to.If yours differ, stop and tell the person which ones and by how much. Don't go on to real numbers until they match, or until the person has seen the difference. These values come from one engine and can be wrong too.## Step 2: run it on the person's numbersReplace every input with the person's own. Ask for any number you don't have, and don't invent one.## Step 3: reportGive one sentence beginning "On these numbers,", then the values, then where the outcome flips. Always add what this leaves out:- Financing on leverage, margin, and interest on idle cash.- Contract rolls, dividends and carry: returns are price changes only.- Slippage beyond cost_bps, gaps, limit moves, and the time it takes to trade.- Drift in weights between days: turnover counts target changes only.- Correlation between markets when sizing. It shows up only in realized vol.- The choice of markets and windows: this walk knows nothing of how many were tried.- Fees and taxes.## LimitsResults are hypothetical: arithmetic on the numbers given, prepared with hindsight. Nobody achieved them, and costs and liquidity are only as assumed. They aren't a forecast, a recommendation, an offer or a record of real trading. Don't say what to buy, sell or hold, and don't use them to market an investment. Whether a person may hold or trade an instrument is a legal question for counsel.Provided as is, at your own risk, by hedgefund.md, which is not a fund and isn't anyone's adviser. Version 1.0. Source: https://hedgefund.md/models/trend_vol_target/prompt.md. Terms: https://hedgefund.md/termsCall it
The same code answers on this page, over HTTP, over MCP and on your own machine, and the same inputs give the same bytes. No key, and nothing is stored. Send positions by POST or run the library, because a URL can land in a server log. model.md holds all of this for your agent.
POST the inputs to /api/v1/trend_vol_target.
curl -s https://hedgefund.md/api/v1/trend_vol_target \ -H 'content-type: application/json' \ -d '{"markets":[{"name":"Market 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\ | jq '{summary, flags, flips, not_modeled, inputs_hash}'The tool is trend_vol_target on https://hedgefund.md/mcp.
curl -s https://hedgefund.md/mcp \ -H 'content-type: application/json' -H 'accept: application/json' \ -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"trend_vol_target","arguments":{"markets":[{"name":"Market 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\ | jq '.result.structuredContent | {summary, flags, flips, not_modeled, inputs_hash}'One file with no dependencies, and nothing is sent anywhere.
curl -fsSL https://hedgefund.md/hedgefund.mjs -o hedgefund.mjs # read it before you run itnode hedgefund.mjs template trend_vol_target > mine.json # replace every number in itnode hedgefund.mjs run trend_vol_target mine.json | jq '{summary, flags, flips, not_modeled, inputs_hash}'Made-up numbers that run as they stand. Replace every one.
{ "markets": [ { "name": "Market A", "prices": [ 100, 100.75, 101.5, 100.58, 100.6, 100.67, 100.47, 101.2, 101.41, 101.65, 101.94, 102.84, 105.17, 105.55, 105.61, 104.46, 103.6, 101.81, 101.97, 102.47, 101.82, 102.83, 102.63, 103.33, 103.71, 103.92, 105.19, 105.67, 106.18, 104.98, 104.41, 104.57, 104.43, 103.44, 103.42, 104.85, 105.56, 103.6, 102.56, 103.77, 103.04, 102.06, 101.88, 102.44, 103.09, 104.63, 105.06, 104.62, 107.61, 107.76, 107.08, 107.32, 107.97, 108.93, 109.2, 109.84, 111.49, 112.69, 113.29, 113.88, 113.95, 111.6, 110.9, 111.46, 113.46, 113.83, 111.87, 112.15, 113.03, 113.47, 114.16, 114.68, 114.23, 114.84, 116.6, 116.44, 116.68, 117.1, 117.12, 116.21, 115.73, 115.65, 115.04, 115.33, 114.9, 116.37, 115.62, 116.93, 117.77, 118.28, 119.32, 116.7, 114.84, 113.48, 112.14, 114.2, 113.23, 111.96, 112.44, 113.18, 113.66, 115.72, 116.51, 117.58, 118.9, 118.11, 119.46, 117.12, 116.18, 117.11, 115.91, 115.88, 115.89, 116.5, 118.34, 119.64, 119.61, 119.05, 118.45, 119.04, 118.26, 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155.22, 153.65, 150.93, 150.6 ] }, { "name": "Market B", "prices": [ 100, 100.03, 100.41, 99.77, 99.15, 98.75, 98.47, 98.62, 98.52, 98.62, 99.11, 99.9, 100.37, 99.69, 99.74, 99.31, 99.65, 99.7, 99.54, 100, 99.36, 99.68, 99.93, 100.23, 101.25, 101.16, 101.61, 101.18, 100.76, 100.26, 100.73, 100.85, 100.66, 100.73, 101.06, 100.77, 100.2, 99.4, 99.17, 99.51, 99.32, 99.23, 99.22, 99.63, 100.07, 100.44, 100.08, 99.75, 99.94, 100.32, 99.79, 99.35, 98.88, 99.34, 99.15, 99.59, 99.81, 100.45, 100.35, 99.23, 99.33, 98.88, 98.11, 98.6, 98.31, 98.9, 99.13, 98.16, 98.24, 98.2, 98.62, 99.04, 98.43, 97.9, 98.6, 98.46, 98.5, 99.17, 98.86, 98.4, 98.87, 99.08, 98.95, 98.54, 97.91, 97.55, 97.2, 96.91, 98.2, 99.17, 99.5, 99.49, 99.42, 98.98, 98.39, 98.56, 98.5, 98.4, 97.92, 97.69, 98.5, 98.78, 99.4, 99.96, 100.79, 101.17, 100.43, 99.9, 99.99, 100.12, 99.54, 99.53, 98.58, 99.61, 100.63, 100.61, 101.44, 101.1, 101.01, 101.31, 102.24, 102.28, 102.51, 103.3, 104.17, 105.27, 105.22, 105.36, 105.04, 104.7, 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| Input | Type | Range | Required | What it is |
|---|---|---|---|---|
| markets | array | 1 to 12 items | yes | The markets, up to 12, with equal numbers of prices. |
| markets[].name | string | yes | A label for the market, such as Market A. | |
| markets[].prices | array | 60 to 2000 items | yes | Prices, oldest first, above zero. 60 to 2000 points. |
| lookback_days | whole number | 1 to 1500 | no | Trailing window for the direction, in points. Default 126. |
| vol_days | whole number | 2 to 1500 | no | Trailing window for rolling vol, in points. Default 63. |
| target_vol_pct | number | 0.01 to 200 | yes | Annual vol target for the whole book, in percent. |
| max_leverage | number | 0.01 to 100 | yes | Cap on the size of each market's weight: 2 is 200% of NAV. |
| cost_bps | number | 0 to 1000 | yes | Cost per unit of turnover, in basis points. |
| periods_per_year | number | 1 to 366 | yes | Points per year, such as 252 for daily. |
Hypothetical, and on made-up numbers until you replace them. Nobody traded this, and nothing here is on offer.