u/FantasticShine4012

I was busy backtesting EURUSD changed source and got completely different results. Damn.... Same settings, same python same C++ , same parameters. Ducascopy 14 missing bars over 5 years, Histdata 8 missing bars that was my best free option, Broker Export Mt5 22 missing bars, Yahho finance basically unuseful. So 2 sources were really different from eachother. So what are you guys using for Forex?

probably a dumb question but genuinely don't know if this is just me

been running a london session breakout on EURUSD and GBPUSD. backtested on my broker's MT5 history export. looked fine, 61% win rate over 3 years.

switched to dukascopy data to double check. dropped to 54%. switched again to histdata. back up to 58%.

same EA, same everything. just different CSVs.

started comparing the raw files and found gaps i didn't expect. not just spread differences — actual missing 1-minute bars during low liquidity windows like late friday NY or early monday open. my EA was picking up "breakouts" that were just data holes

also found one source had wrong high/low values on like 12 bars across 3 years. sounds small but two of those were major false signals that made the whole 2022 period look better than it was

i'm not a data scientist, i just trade. but at this point i'm spending more time validating data than building strategies

is there a source people actually trust for clean forex OHLCV? doesn't have to be free, just has to be right

I've been down a rabbit hole on data quality lately and wanted to share what I found because I don't see this discussed enough.

Most M1 backtests are broken before you even write a single line of strategy logic. Here's why:

1. Broker data has survivorship bias in the spread

Backtested spread != live spread. Especially around rollover and news.

2. Missing bars get forward-filled silently

Most platforms don't warn you. Your "open" on bar N is actually the close of bar N-3.

3. Timezone misalignment

Broker exports often shift DST differently depending on server location. This alone can add or remove fake signals.

4. Volume data is often fabricated on Forex

It's tick count, not actual volume. Still useful, but treated as "volume" it misleads.

I tested this on 5 different data sources for EURUSD 2018-2023. The same strategy ranged from -12% to +34% drawdown depending purely on which dataset I used.

Anyone else done systematic comparisons? Curious what methodologies people use to validate their data before trusting a backtest.

I have been struggling to get my WR above 45% for allmost a year now. Tried many strategies  and build many engines. Only dissapointment.  I went back to my first strategy and tried to finetune. A few months ago i got introduced to backtesting, and then the journey started. My first strategy, entry and exit logica finally came through. Historical data (the good ones you can use) is hard to find. The free ones only give you hope and perfect figures but when going live it is a disaster.  So choose wise when backtesting.

I have been struggling to get my WR above 45% for allmost a year now. Tried many strategies  and build many engines. Only dissapointment.  I went back to my first strategy and tried to finetune. A few months ago i got introduced to backtesting, and then the journey started. My first strategy, entry and exit logica finally came through. Historical data (the good ones you can use) is hard to find. The free ones only give you hope and perfect figures but when going live it is a disaster.  So choose wise when backtesting.

After the discussions in this sub about data quality I put together a free sample pack.

What's included:

- EURUSD D1 (2015-2024)

- SPY D1 (2010-2024, split-adjusted)

- BTCUSDT D1 (2018-2024)

- Gold (XAUUSD) D1 (2015-2024)

All verified: no missing bars, no OHLC violations, DST-corrected, UTC timestamps.

Download: https://powakadata.com/

No signup required for the free pack. CSV format, works with pandas, MT4/MT5, TradingView, Excel — anything that reads CSV.

If you spot any issues with the data let me know. Planning to expand to M1 and M5 timeframes next.

I've been down a rabbit hole on data quality lately and wanted to share what I found because I don't see this discussed enough.

Most M1 backtests are broken before you even write a single line of strategy logic. Here's why:

1. Broker data has survivorship bias in the spread

Backtested spread != live spread. Especially around rollover and news.

2. Missing bars get forward-filled silently

Most platforms don't warn you. Your "open" on bar N is actually the close of bar N-3.

3. Timezone misalignment

Broker exports often shift DST differently depending on server location. This alone can add or remove fake signals.

4. Volume data is often fabricated on Forex

It's tick count, not actual volume. Still useful, but treated as "volume" it misleads.

I tested this on 5 different data sources for EURUSD 2018-2023. The same strategy ranged from -12% to +34% drawdown depending purely on which dataset I used.

Anyone else done systematic comparisons? Curious what methodologies people use to validate their data before trusting a backtest.

I've been down a rabbit hole on data quality lately and wanted to share what I found because I don't see this discussed enough.

Most M1 backtests are broken before you even write a single line of strategy logic. Here's why:

1. Broker data has survivorship bias in the spread
Backtested spread != live spread. Especially around rollover and news.

2. Missing bars get forward-filled silently
Most platforms don't warn you. Your "open" on bar N is actually the close of bar N-3.

3. Timezone misalignment
Broker exports often shift DST differently depending on server location. This alone can add or remove fake signals.

4. Volume data is often fabricated on Forex
It's tick count, not actual volume. Still useful, but treated as "volume" it misleads.

I tested this on 5 different data sources for EURUSD 2018-2023. The same strategy ranged from -12% to +34% drawdown depending purely on which dataset I used.

Anyone else done systematic comparisons? Curious what methodologies people use to validate their data before trusting a backtest.

I've been down a rabbit hole on data quality lately and wanted to share what I found because I don't see this discussed enough.

Most M1 backtests are broken before you even write a single line of strategy logic. Here's why:

1. Broker data has survivorship bias in the spread

Backtested spread != live spread. Especially around rollover and news.

2. Missing bars get forward-filled silently

Most platforms don't warn you. Your "open" on bar N is actually the close of bar N-3.

3. Timezone misalignment

Broker exports often shift DST differently depending on server location. This alone can add or remove fake signals.

4. Volume data is often fabricated on Forex

It's tick count, not actual volume. Still useful, but treated as "volume" it misleads.

I tested this on 5 different data sources for EURUSD 2018-2023. The same strategy ranged from -12% to +34% drawdown depending purely on which dataset I used.

Anyone else done systematic comparisons? Curious what methodologies people use to validate their data before trusting a backtest.

I've been down a rabbit hole on data quality lately and wanted to share what I found because I don't see this discussed enough.

Most M1 backtests are broken before you even write a single line of strategy logic. Here's why:

1. Broker data has survivorship bias in the spread
Backtested spread != live spread. Especially around rollover and news.

2. Missing bars get forward-filled silently
Most platforms don't warn you. Your "open" on bar N is actually the close of bar N-3.

3. Timezone misalignment
Broker exports often shift DST differently depending on server location. This alone can add or remove fake signals.

4. Volume data is often fabricated on Forex
It's tick count, not actual volume. Still useful, but treated as "volume" it misleads.

I tested this on 5 different data sources for EURUSD 2018-2023. The same strategy ranged from -12% to +34% drawdown depending purely on which dataset I used.

Anyone else done systematic comparisons? Curious what methodologies people use to validate their data before trusting a backtest.

Dit is pure waarde. Hoge upvote kans. In de comments na discussie: "I ended up building a cleaned dataset for my own use — happy to share a sample if anyone wants to test."

r/stocksr/Daytrading

I've been down a rabbit hole on data quality lately and wanted to share what I found because I don't see this discussed enough.

Most M1 backtests are broken before you even write a single line of strategy logic. Here's why:

1. Broker data has survivorship bias in the spread

Backtested spread != live spread. Especially around rollover and news.

2. Missing bars get forward-filled silently

Most platforms don't warn you. Your "open" on bar N is actually the close of bar N-3.

3. Timezone misalignment

Broker exports often shift DST differently depending on server location. This alone can add or remove fake signals.

4. Volume data is often fabricated on Forex

It's tick count, not actual volume. Still useful, but treated as "volume" it misleads.

I tested this on 5 different data sources for EURUSD 2018-2023. The same strategy ranged from -12% to +34% drawdown depending purely on which dataset I used.

Anyone else done systematic comparisons? Curious what methodologies people use to validate their data before trusting a backtest.

I've been down a rabbit hole on data quality lately and wanted to share what I found because I don't see this discussed enough.

Most M1 backtests are broken before you even write a single line of strategy logic. Here's why:

1. Broker data has survivorship bias in the spread
Backtested spread != live spread. Especially around rollover and news.

2. Missing bars get forward-filled silently
Most platforms don't warn you. Your "open" on bar N is actually the close of bar N-3.

3. Timezone misalignment
Broker exports often shift DST differently depending on server location. This alone can add or remove fake signals.

4. Volume data is often fabricated on Forex
It's tick count, not actual volume. Still useful, but treated as "volume" it misleads.

I tested this on 5 different data sources for EURUSD 2018-2023. The same strategy ranged from -12% to +34% drawdown depending purely on which dataset I used.

Anyone else done systematic comparisons? Curious what methodologies people use to validate their data before trusting a backtest.

I've been down a rabbit hole on data quality lately and wanted to share what I found because I don't see this discussed enough.

Most M1 backtests are broken before you even write a single line of strategy logic. Here's why:

1. Broker data has survivorship bias in the spread
Backtested spread != live spread. Especially around rollover and news.

2. Missing bars get forward-filled silently
Most platforms don't warn you. Your "open" on bar N is actually the close of bar N-3.

3. Timezone misalignment
Broker exports often shift DST differently depending on server location. This alone can add or remove fake signals.

4. Volume data is often fabricated on Forex
It's tick count, not actual volume. Still useful, but treated as "volume" it misleads.

I tested this on 5 different data sources for EURUSD 2018-2023. The same strategy ranged from -12% to +34% drawdown depending purely on which dataset I used.

Anyone else done systematic comparisons? Curious what methodologies people use to validate their data before trusting a backtest.

Been running backtests on EURUSD M1 and noticed consistent gaps in the Dukascopy data during high-impact news — NFP, FOMC, CPI releases.

Not talking about spreads. Actual missing bars. Sometimes 3-5 minutes just gone.

Ran the same period on a couple of other sources and the results were completely different — equity curve flipped from losing to profitable just by switching the data source.

Has anyone else run into this? Curious what data sources people are actually using for M1 Forex backtesting that hold up around news.

Also interested if anyone has compared Dukascopy vs Pepperstone vs any other tick/M1 provider head-to-head.

Been running backtests on EURUSD M1 and noticed consistent gaps in the Dukascopy data during high-impact news — NFP, FOMC, CPI releases.

Not talking about spreads. Actual missing bars. Sometimes 3-5 minutes just gone.

Ran the same period on a couple of other sources and the results were completely different — equity curve flipped from losing to profitable just by switching the data source.

Has anyone else run into this? Curious what data sources people are actually using for M1 Forex backtesting that hold up around news.

Also interested if anyone has compared Dukascopy vs Pepperstone vs any other tick/M1 provider head-to-head.

Been running backtests on EURUSD M1 and noticed consistent gaps in the Dukascopy data during high-impact news — NFP, FOMC, CPI releases.

Not talking about spreads. Actual missing bars. Sometimes 3-5 minutes just gone.

Ran the same period on a couple of other sources and the results were completely different — equity curve flipped from losing to profitable just by switching the data source.

Has anyone else run into this? Curious what data sources people are actually using for M1 Forex backtesting that hold up around news.

Also interested if anyone has compared Dukascopy vs Pepperstone vs any other tick/M1 provider head-to-head.

Been running backtests on EURUSD M1 and noticed consistent gaps in the Dukascopy data during high-impact news — NFP, FOMC, CPI releases.

Not talking about spreads. Actual missing bars. Sometimes 3-5 minutes just gone.

Ran the same period on a couple of other sources and the results were completely different — equity curve flipped from losing to profitable just by switching the data source.

Has anyone else run into this? Curious what data sources people are actually using for M1 Forex backtesting that hold up around news.

Also interested if anyone has compared Dukascopy vs Pepperstone vs any other tick/M1 provider head-to-head.

Been running backtests on EURUSD M1 and noticed consistent gaps in the Dukascopy data during high-impact news — NFP, FOMC, CPI releases.

Not talking about spreads. Actual missing bars. Sometimes 3-5 minutes just gone.

Ran the same period on a couple of other sources and the results were completely different — equity curve flipped from losing to profitable just by switching the data source.

Has anyone else run into this? Curious what data sources people are actually using for M1 Forex backtesting that hold up around news.

Also interested if anyone has compared Dukascopy vs Pepperstone vs any other tick/M1 provider head-to-head.

Can i promote a backtesting site here or does reddit not allow it????? Historical OHLCV data for forex, stocks, ETFs, commodities and crypto. Clean, verified, ready to use. CSV format compatible with any trading platform.All data is delivered as CSV files compressed in a ZIP archive. Each file contains: timestamp, open, high, low, close, volume. The timestamp is in UTC ISO 8601 format. Compatible with Python (pandas), R, MetaTrader, NinjaTrader, TradingView, and any platform that reads CSV.

Can i promote a backtesting site here or does reddit not allow it????? Historical OHLCV data for forex, stocks, ETFs, commodities and crypto. Clean, verified, ready to use. CSV format compatible with any trading platform.All data is delivered as CSV files compressed in a ZIP archive. Each file contains: timestamp, open, high, low, close, volume. The timestamp is in UTC ISO 8601 format. Compatible with Python (pandas), R, MetaTrader, NinjaTrader, TradingView, and any platform that reads CSV.