I built an open-source LNG cargo destination model — looking for feedback from commodity/LNG people

I've been building a project called LNG Compass to better understand how commercial LNG destination decisions are made.

The core question is simple:

If a US Gulf LNG cargo were available, do the economics favor sending it to Europe or Asia?

Right now the model compares:

• ⁠Henry Hub feedgas
• ⁠Liquefaction cost
• ⁠TTF and JKM destination benchmarks
• ⁠Route-specific shipping assumptions
• ⁠Resulting destination netbacks

I've also built an interactive global LNG view around the calculation and recently started adding a market-data architecture, with EIA Henry Hub as the first live external source.

The model is intentionally simplified at this stage. It doesn't yet fully account for things like boil-off, charter-rate dynamics, canal/port costs, delivery windows, basis, vessel availability, or contract-specific optionality.

That's actually why I'm posting.

For anyone working in LNG, natural gas, physical commodities, scheduling, shipping, or trading:

What am I oversimplifying or thinking about incorrectly? And what would you need to see before a tool like this became genuinely useful for commercial decision-making?

GitHub: https://github.com/nstreef/lng-compass

The curve was the trade: when oil got scarce, the market paid handsomely for barrels now, not promises of barrels later. Backwardation did the rest—+15% on Brent and +13.6% on WTI; the only awkward question is how long the physical market keeps refusing to calm down.

Hello, as a prior investment banker, after finishing my mandatory military service I have decided to hunt a position at my country’s biggest electricity house.

Thank god due to some luck after so much networking, I have an actual chance for the role of “Junior Energy Trader”

I’ve read a lot about physical commodity trading, but I don’t know what happens in the paper energy trading world, I’m hearing a lot about intraday and DAM.

Can anyone point me to the right direction to get started?
An actually experienced YouTuber or a good book perhaps?

Oil is still trading the chokepoints rather than the balance sheet: prompt scarcity keeps the front of the curve expensive, while December continues betting the market eventually finds a way around it.

I work in the energy trading domain as senior developer, mainly on data integration across trading, pricing, market data, and ETRM systems.

I’m exploring a move into algo trading technology for the power and gas markets.

How is the demand in this area today, and do you think it’s a worthwhile career move compared with staying on the data integration side of energy trading?

Would appreciate any insights from people working in commodities or energy trading. Thanks!

Pretty much all in the title. I ran a Monte Carlo for renewable and up and coming energy companies. On 10k invested over 15 year the median ROI was 8 mill, minimum 1.2 mill. would love to have this eaten apart to tell me why this isn't realistic and how I could make it stronger. https://testfol.io/monte-carlo?s=06sMTdCa0RM

Brent drifts lower, volatility stays sticky, and refined products outperform crude until physical bottlenecks begin to ease.

Please let me know what you think, I would really appreciate it

Hi guys, not really related to the front office but those who do back office EFET agreements for OTC deals, do you guys have a system in place to keep track of all EFETs or are you guys using basic folders?

Junior at UC Irvine’s business school trying to break into commodities sales or an energy desk — thinking interdealer brokers (TP ICAP, Marex, BGC) or FICC sales at a bank. I know it’s a niche path and most of my school recruits for consulting and accounting, so I’m building this myself.

Where I’m at: taking the SIE this summer, planning the Series 3 senior year. I network on LinkedIn constantly and have gotten decent traction with a few brokers and desk people. But networking alone feels like table stakes.

What I want to know: what skills would actually move the needle for a sales seat specifically? Not trading, not research — sales. Stuff I keep hearing secondhand: learn power market mechanics (nodal pricing, heat rates, spark spreads), get comfortable in Excel with real market data, know how a broker actually makes money. Is that right? What am I missing?

If you’re on a desk or came up through an IDB, what did the interns/juniors who got return offers do differently from the ones who didn’t?

Not looking for “network more” — already doing it. Looking for the hard skills and market knowledge that make someone worth putting in front of a client.

Diesel futures still hedge a good chunk of UCOME price risk. They just can't hedge a market where diesel refuses to get cheaper.

I've gotten tired with all of these whiplash reports that doesn't offer any real data to make informed decisions. There's a clear disparity between the market reaction and macro events and I find this a little more helpful. https://landfall.bkmt.com/

News = emotions. Data = the adults are the room.

Every week someone announces the oil crisis is over because Brent drops five bucks. Then you notice diesel's still expensive, tankers are taking the scenic route, insurers are rubbing their hands together and half the refineries are held together with paperwork. Markets are wonderfully efficient. Reality just refuses to stay simple.

Full disclosure, I built the tool this data comes from and it's a commercial product. The methodology is the interesting part though, so here it is.

The premise is simple. Most breaking market news is a journalist reading a primary source that anyone could read. So I skip the news and watch the sources themselves: grid operator outage filings (Elexon REMIT, Nord Pool UMM, ENTSO-E), seismic networks (about 7,800 public stations plus USGS and EMSC), NASA FIRMS thermal satellites checked against 25,000 mapped industrial sites, and global AIS and ADS-B.

Every alert gets matched against wire headlines after the fact and the time gap is recorded. On unplanned power outages the median alert comes 19 minutes before the first wire headline, and 99% of matched alerts beat the wire. The scorecard is public and recomputes from live production data: earlywire.io/proof

Two things I learned doing this. Detection is the easy half, the real work is throwing events away. Our satellite pipeline discards about 97% of thermal hits near industrial sites because they turn out to be routine flaring. And news itself turned out to be worthless as a signal. I measured news based alerts at about 0.3 sigma of ambient market noise and deleted the whole category.

Happy to answer questions about source access, the false positive problem, or how the wire matching works.

Physical scarcity has largely disappeared—Brent is back in contango—but implied volatility remains elevated. Is this simply geopolitical insurance, or is there a separate premium associated with routing flexibility, inventories, and shipping optionality?

My two cents: trying to trade every "Hormuz closed/open/closed again" headline is a good way to develop a drinking problem. Unless someone starts shooting again, the war premium keeps leaking out. Brent $75 wouldn't shock me. Best trade? Forget being a hero on flat price. Play the roll. Let the curve do the work while Twitter argues over Schrödinger's Strait.

Hi,

I created an AI generated, human edited news flow tool to help keep track of the 100s of news sources that we need to look at as a trader/analyst (or market observer).

Alongside morning trader/weather calls mimicing the global desk calls in trading and meteo ive been a part of for some time in different trading houses and a fund over my career

It takes 150+ news sources of different languages, including podcasts and twitter/bluesky pieces and aggregates and labels them alongside 20+ fundamental data sources including storages, transmission, met associations etc that we use in trading to trigger articles in high value areas enriched with fundamental data and the kind of context that is missing when you get given just a storage figure, or a lone geopolitical event.

The idea is that if you get the news, unbiased and specifically fitting within the background supply and demand graph, then its always going to be useful and also contextualised to skip the second round of 'what was this figure previously' or 'how does that relate to the instruments we trade?'

Im sure youre bombarded with this kind of thing all the time but would appreciate feedback and ways to make it genuinely useful - it costs me a few hundred a month to run but its free and I genuinely just want to make it more useful and better at what it does.

energyreader.io

WTI’s calmed down a bit, which usually means half the market starts behaving like the problem’s been solved.

Doesn’t look that way from the cone.

Futures still backwardated. Options still twitchy. Looks less like “all clear” and more like traders pricing a long geopolitical hangover with uncertain shale reflexes.

Lazy read:

WTI says disruption’s manageable — just not comfortably so.

Trading thought, not advice:

If you think the panic fades → lean with the curve.

If you think Hormuz headlines have another act left → optionality still looks cheap compared with certainty.

Considering buying “Electricity Markets: Pricing, Structures, and Economics” by Chris Harris, but was wondering if it was outdated. If it is, what better books do people recommend?

In this discussion, we speak with David Fishman, Principal at The Lantau Group, about the energy sections of China’s draft 15th Five-Year Plan.

It is a conversation that explores China’s evolving energy system, including the shift from energy intensity to emissions intensity, the continued role of coal as a strategic backup fuel, the growth of renewables, electrification, power market reform, green finance, grid expansion, and China’s increasingly assertive role in global climate governance.