
Ask HN: Anyone making money through algorithmic trading? - charlesdm
Is there anyone here making money on smaller trading strategies (i.e. in the stock market or cryptocurrencies) that would not be interesting enough for larger algorithmic trading firms?<p>I&#x27;m aware the standard advice is that you will lose your shirt attempting to compete with algorithmic and HFT firms. But are there opportunities out there for smaller strategies to generate alpha? (I&#x27;m assuming yes, but would be great to find people who actually do this -- no need to disclose _how_ you actually do it, obviously)
======
mbroshi
I wonder whether the premise of your question is faulty. If you ask enough
people: "In your last 100 flips of a coin, did you get more than 60 heads?"
some will truthfully say "Yes." Unfortunately, that does not mean there's
anything special about their coin-flipping strategy, or that you will be able
to generate a successful coin-flipping strategy.

My guess is what you really want to know is "What is my expected gain if I try
to employ an algorithmic trading strategy?" I have my suspicion of the answer
to that question, but I don't believe your current question will shed any
light on the answer.

~~~
aerovistae
Mostly I believe this too, but I am familiar with some people who can
consistently make money year after year. From talking to them it becomes clear
that they understand things _very, very_ deeply.

See /u/Fletch71011 on reddit-- he's always happy to discuss things. He's made
millions trading options, mostly algorithmically as I've understood it. The
methods he uses are sufficiently complex that you need to be very well
acquainted with the intricacies of derivatives to follow along, but basically
he trades volatility instead of price movement. Regardless of whether the
price of the asset goes up or down, he makes money. In his opinion, it's
foolish to try to trade price direction, and you're basically flipping coins
and likely to lose money.

I tried understanding what he was doing and abandoned the attempt. I had to
conclude I was not quite so clever as he.

~~~
ww520
Be careful with volatility. I don't know what he's trading on exactly. But a
big part of volatility trading is selling insurance, i.e. selling insurance
against the direction of S&P. You can make a lot of money collecting insurance
premium, but on the event of a payout, like a sudden big drop in S&P, the loss
can be very substantial. See XIV and SVXY in February of this year.

~~~
nostromo
Trading volatility might imply that he's buying options in both directions.

Big moves either up or down would be profitable. The only unprofitable move
here would be no substantial moves in either direction. (In which case you
lose your entire bet, but no more.)

~~~
e12e
Could you expand on how that would work? If X is priced at 10 units of
currency, and I promise to buy 1 X for 11, and to sell 1 X for 9. And X stays
available for 10, I end up paying 11, receiving 9 - netting a loss of 2. If I
manage to promise a sell/buy at 10, I even out. What do I lose with low
volatility? And how do I make money "both ways"?

Clearly I lack a basic understanding of the concepts involved.

~~~
philipodonnell
"Volatility" in the term "Volatility Trading" does not mean the stock's
movements, it is a way of measuring the excess value in an option beyond what
the parameters of the option would imply. That excess value is usually
referred to as the market's assumption about the future volatility of the
stock, but really its just an error term influenced by market participants
based on supply and demand. Low volatility means "pretty close to its
theoretical value assuming no volatility" or to put it another way: "cheap"
i.e. good for buyers and bad for sellers.

Sort of like how different companies with the same cash flows can trade at
different multiples, otherwise identical options in two companies (or
different expirations/strikes in the same company) can trade at different
prices because of the opinions of market participants. Volatility traders act
when the different prices/error terms are too far apart, counting on the
prices/error terms to converge a.l.a. pairs trading.

Since they are trading the error term directly, they attempt to construct
positions that remain relatively flat in value as the stock moves around, but
are designed to only change in value when the error term changes. That is how
they can make money "both ways", because they can profit if the stock goes up,
down, or stays the same, as long as the error term moves in the correct
direction.

The reason you only see sophisticated people doing this kind of trading is
because you need a large and complex position with many hundreds of options to
be in a truly market-neutral environment. You can't take advantage of
mispricing without such a large position because buying/selling single options
involves a tremendous amount of risk, so you need to do that as a part of a
larger portfolio to spread that risk. Retail traders tend to spread the risk
by doing 2 transactions (the mispriced option and a well-priced but mirrored
hedge option), but that is a) much more expensive from a commissions
standpoint and b) really limits the range of market-neutrality forcing you to
adjust more frequently to stay market-neutral, again, with commission costs.

~~~
e12e
So it's "buy low, sell high" \- but for options, not stocks?

[ed: that's to say, you need a way to get more/accurate pricing information
than reflected in the market - but for options, not assets]

~~~
aerovistae
Yes, this is how the guy I was referring to explained it to me~ he created a
pricing model to predict errors/inaccuracies in the market's model, and was
thus able to know when an option was likely to move towards a different price
to correct itself.

------
headmelted
I hacked together my own scripted system that would arbitrage cryptocurrency
across exchanges.

It worked (for the most part), but it's been abandoned now. The best way I can
think of to describe why is to say that while the low hanging fruit exists,
there's far too little juice in it for it to be worth the squeeze.

Others have explained that the problem they've encountered is counter-party
risk in that some exchanges may not allow you to withdraw, or the prices may
be skewed because they're charging absurd withdrawal fees.

None of this was a problem for me - I found the exchange APIs almost
universally hold that information somewhere if you hunt around enough for it,
so I was able to account for this when scoring opportunities.

My reasoning was that from a birds-eye view it looked like the price
differences were allowing for trades that would have a 1-2% difference. I
reasoned that if I were to withdraw directly to the wallet of another exchange
I could have a turnaround time on some currencies of less than five minutes
start to finish - even 0.1% every hour would be an incredible rate of return
when extrapolated to a yearly ROI.

In reality, while currencies did (and do!) trade with that difference
frequently between exchanges, the volumes are tiny. Despite having funds to
spend, there weren't any big-money buyers at the destination exchange, and
within a couple of dollars (literally a _couple_ of dollars) the bids at the
destination exchange were back below the price of the source exchange, and I'd
be in the red on the transaction.

Add in the fees, and there was vanishingly little profit to be made while
taking bet-the-farm risks that whoever runs the exchange isn't going to elope
with your bitcoins.

It was a good learning experience, though - so I'm ultimately glad I took a
run at it.

~~~
simonhughes22
I spent the last few months trying to build an arbitrage bot and ran into
exactly the same issues. If there's a big price differences there's always a
reason, either deposits or withdrawals are temporarily offline, or the fee for
transferring or depositing is too high, or for some very small coins it can
takes ages to transfer (one transfer took 6 hours, another took a whole
week!). Otherwise the volume is so low that you basically lose any edge
crossing the spread and trying to find enough volume to close out the
transaction. I had a small number of trades that made a few pennies, but also
a lot more that just sat there and didn't execute at the expected price (based
on the bid and ask when my bot found the trade) forcing me to sell for a less
optimal price and end up with a loss. I am still sure there's money to be made
with this but it takes a lot of work and you would have to search across a lot
of coins and a lot of exchanges to find a viable option. Most people,
including some very smart people I've talked to, just assume it's pretty easy
to do this but if it was everyone would be doing it. Maybe it was 3-4 years
ago when crypto was much smaller and less well known, but nowadays most
opportunities are exploited as soon as they exist, I suspect a lot of time by
the exchanges themselves.

~~~
1_player
> for some very small coins it can takes ages to transfer

Why do you need to transfer between exchange?

Writing an arbitraging bot is in my bucket list of projects I'll one day work
on, and to avoid trasfer times, which are ridiculous with some
cryptocurrencies, the plan is to keep a balance of both sides on both
exchanges.

Example: if you're arbitraging ETH/USD between exchanges A and B, you have an
ETH balance on A, and a USD balance on B, and you concurrently buy/sell on
both.

Then you have the problem of managing dozens of balances across as many
exchanges, which is left as an exercise for the reader :)

~~~
fedecaccia
That's the point, you can't have so many balances in so many exchanges,
because, in that case, each return is going to be very small. Just to take
profit on an ETH USD arbitrage, you have to have 25% of your capital in ETH
and 25% USD in exchange A, and 25% ETH and 25% USD in exchange B. So, when you
take advantage of the opportunity to buy ETH at low price on exchange A and to
sell on exchange B, you are only earning an arbitrage profit on a 25% of your
capital. And that profit become less and less if you divide your capital into
more coins and more exchanges.

------
pfarnsworth
I lost about $100k doing algorithmic trading. I spent the better part of 2
years after work immersing myself in algorithmic trading, understanding the
architecture of the stock market, and getting very very deep into the topic.

I found an algorithm that was wildly positive, and traded it on 3 separate
markets every night. I learned a lot and I love everything I learned, but it
was a very expensive lesson. The #1 thing I learned was that algo trading is
mostly psychological, at least for me. I was making big bets (a few thousand
dollars per trade) every night and it was emotionally exhausting, and I
couldn't handle the pressure. The worst part is that I didn't trust the
algorithm, and would cut the trades short instead of waiting for the full
profit (or loss). That messed with my results, and in the end it turned into a
disaster.

But programming for myself and using real money was such an educational
experience. Any little bug meant that I could lose a lot of money so I bug-
tested the most I've ever done in my life. And I did things like write my own
multi-threaded backtester, working on hundreds of gigabytes of data, so I
learned a lot there too.

It was a lot of fun, very very expensive fun.

~~~
mirceal
if you've lost 100k, you had 100k to spare. agree it was an expensive lesson.

~~~
icebraining
_if you 've lost 100k, you had 100k to spare_

Not if you're leveraging! For an extreme example, this guy lost $210k of
borrowed money:
[https://www.bogleheads.org/forum/viewtopic.php?f=10&t=5934&s...](https://www.bogleheads.org/forum/viewtopic.php?f=10&t=5934&sid=e650e39b31b9f119b3a8da32242c7049)

~~~
downandout
Another example is Chris Sacca, who burned through $16 million - $12 million
in paper gains, and $4 million in borrowed money. From [1]:

 _Starting with around $10-$20,000 in what were college loans, Sacca realized
that brokers weren’t accounting for margin usage on a real-time basis. The
result was that even though firms were only allowing 50% margin, as long as a
customer closed a trade before the trade settled, T+3, and showed proper
equity in the account, positions larger than 50% margin usage could be opened.

Picking winners of stocks that by Sacca’s account had risen 40x, and betting
with positions well above his margin requirements, his account grew to $12
million in 18 months. But, as we all know, the record levels of the Nasdaq and
the dot com bubble of that time eventually burst....When it did burst, and
even though the damage was from holding just two stocks, Sacca found himself
in the hole with a $4 million negative balance._

[1] [https://www.financemagnates.com/forex/brokers/chris-
saccathe...](https://www.financemagnates.com/forex/brokers/chris-
saccathe-4million-negative-balance-salinger-group-twitter/)

------
schoen
A problem that people have pointed out in the past about cryptocurrency
exchange arbitrage is counterparty risk: different prices on different
exchanges may be taking into account the possibility that the exchange won't
allow withdrawals, will delay the withdrawals, or doesn't have enough assets
to satisfy all of its obligations. A large number of cryptocurrency exchanges
have defaulted and/or restricted withdrawals in the past. So, an arbitrage
strategy might appear very effective yet result in holding cryptocurrency or
fiat currency on an exchange that won't allow it to be withdrawn or redeemed
as expected.

This could happen because of fraud by the exchange, fraud against the
exchange, hacking of the exchange, or regulatory risks where other financial
intermediaries stop working with an exchange or regulators threaten to punish
an exchange if it processes certain transactions.

Some people have suggested that because arbitrage opportunities are pursued
aggressively, most price differences between cryptocurrencies and
cryptocurrency exchanges that persist are probably mainly due to people taking
account of counterparty risk. In that case you could still profit some of the
time by betting that a risky exchange will remain solvent, but you might be
taking a larger risk than you realize.

Another interpretation is that some apparent cryptocurrency arbitrage
opportunities are really opportunities to earn a premium for helping people
evade capital controls and other regulatory restrictions on moving money
around. For example, there are lots of people in China who would be happy to
pay you a premium if you'd accept a payment in China and make a corresponding
payment in Canada. In that case you might feel like you're being a clever
arbitrageur but you're largely receiving a payment for helping someone
circumvent regulations¹.

(The implicit moral opprobrium that might be read there isn't intended, but I
think it's interesting to consider how cryptocurrencies can sometimes make
people feel very clever when they aren't, in fact, the cleverest ones in the
situation!)

(¹ which isn't necessarily unreasonable to describe as arbitrage)

------
inputcoffee
There are a few things to watch out for:

1\. Systematic trading doesn't necessarily require an algorithm. For instance
this rule might work (over a 5 year horizon, don't try it monthly): "buy very
large cap stocks if their P/E goes below 4 and sell if it goes over 10." But
you don't need an algo.

2\. The market has long bull runs. So you might have an algo that has some
long bias. It will seem to perform above chance. You should compare it to just
holding the market.

2b. If the market is going through a bull run and your algo has some leverage
built in, it will outperform just holding the market.

3\. If the market had a massive crash in the data set and your algo has a
short bias, then you should check it against just shorting the market.

4\. The issue of models, markets and biases mirror the same debate in science
theories, data and statistics.

~~~
optimuspaul
maybe I'm being naive but "buy very large cap stocks if their P/E goes below 4
and sell if it goes over 10." sounds kind of like an algorithm to me. Maybe
it's just a ruleset?

~~~
lallysingh
I think they meant that it needn't be a software implementation. You could run
that rule by hand.

~~~
optimuspaul
I suppose you could, but there are a lot of stocks to look at... but that's
not the point, thanks for the insight.

------
fapjacks
I have been writing my own trading bots for about three years or so, maybe a
little less, all told. But exclusively on crypto exchanges. I think most
people familiar with crypto could see the latest bubble for what it was, but I
did manage to get out before it popped and I've been giving it some cooldown
time since. I typically do trade off the volatility. I've put many hours in
front of the exchanges (and put a ton of quarters in the machine, so to
speak), just watching it like television, and this is the way I learned my
strategies (incidentally this is the same exact way I taught myself about
networking, by watching tcpdump and ethereal/wireshark). I can do pretty well
if the volatility is fairly even. I do end up losing a big chunk of gains when
there's too much fluctuation. I've got failsafes in the form of floor/ceiling
prices at which my bots pull the cord, but this ends up being pretty expensive
and is one of the main ways I end up losing steady gains. I absolutely never
trade on margin. I see it as a puzzle, as a kind of game, and the challenge is
a substantial part of the reward for me. I will also warn you that pretty much
all the rules change once you start trading enough to make the price move
locally. It's almost a whole different ballgame. And at least with crypto,
it's fairly obvious that most of the trades on the exchanges are people doing
the same thing you're doing. You get to know "people" by their patterns of
trade.

------
jmhyer123
Yes. I've developed a simple strategy that algorithmically trades
cryptocurrencies (mainly ETH and BTC because volume, but it would apply
successfully to any of the others as well). The strategies are simple, they
are based on simple technical indicators, and result in about 2 trades
executed per day. The strategy can be applied to "normal" equities as well but
it performs particularly well on cryptocurrencies due to the amount of
volatility in the market. Also the amount of freely available data for
cryptocurrencies makes implementation much easier (and cheaper).

Over the last 3 months, January to March, I've had a return of just under 50%
(in spite of the massive down turn in the crypto market). Which sounds great,
but I only turned it loose on about $250 so we're not talking about buckets of
money here. With higher amounts of capital you run into other issues that
would need to be addressed in the algorithm/strategy.

I've often been told the same thing (you can't beat HFT, large firms, etc) but
in the end it's not about beating them. It's about finding a strategy that
works, that can be automated, and having the patience to let it run and do
it's thing. I only trade about 1 to 2 times per day (not HFT) and only rely on
fundamental data (no inside info, no "get the data before everybody else and
act on it", etc). Keep it simple.

Happy to answer any questions.

~~~
vinhboy
I have a strategy I wanted to try. Look at historical percentage difference
between currencies. See if there is any patterns like, every time BTC drop
10%, LTC drop 20%, or something like that...

Find those patterns and trade on them.

Do you know if people are doing this?

~~~
jmhyer123
I've seen people try that and I've noticed the correlation myself. Around the
end of last year (November/December 2017) it was possible to watch BTC jump
5-10% and jump over to ETH and catch the same wave 5-10 minutes later.

The problem is those patterns quickly disappear as automated trading picks
them up. The window goes from 5-10 minutes to seconds or less. Much harder to
act in such a small window.

------
module0000
Short answer: yes.

Long answer: not in the beginning, then a long period of breaking even, and
eventual profitability.

My algos trade commodity futures(nasdaq, 30-year bonds, etc). My platform is
Multicharts.NET, which supports writing your strategy components in C#.NET.
I'm not a .NET fan, but the platform is solid and this is about dollars, not
language preference.

Also...regarding HFT - those aren't likely what you think they are. In
commodity markets, HFT trading typically follows a simplistic algorithm of
"above or below XYZ bar EMA", which anyone can do. The HFT portion of it comes
in through the process bidding the inside bid(on the way up) or offering the
inside offer(on the way down) faster than the other HFT algo. So where a price
may eventually see 100 bids on the way up, and 20 of those will be filled, the
HFT's goal is to place bid #2 or #3 out of that 100 - competing with hundreds
of humans and other HFT's for that spot in the queue. Trying to compete with
HFT is very difficult unless you have enough capital to colo next to the
exchange(CME in my case), as well as handle commissions(through paying them,
or paying for a seat to negate them).

I've attached a screenshot of the chart output from my algorithm today. Assume
every time you see "SE" or "LE", that a long(LE) or short(SE) position was
established. Positions close when the first of 4 events happens: stop loss,
profit target(25pts for today), trailing stop(10pt), or an opposing signal is
generated. It's simple, it's not that sophisticated, but it is consistently
profitable. You can develop your own similar algorithms, or use many out-of-
the-box algorithms from places like iSystems, or strategies that come built-in
with your platform(Multicharts.NET has many). The key is backtesting, properly
scheduling around economic events, and having enough capital to survive the
inevitable drawdowns.

Link to screenshot of today's chart output from algo:
[https://www.dropbox.com/s/bms9kuqn529iyqg/Screen%20Shot%2020...](https://www.dropbox.com/s/bms9kuqn529iyqg/Screen%20Shot%202018-04-25%20at%2011.40.03%20AM.png?dl=0)

If you go down this road, I wish you the best of luck. It's fun, it's
difficult, and incredibly rewarding if you get it right.

~~~
ww520
That chart is very interesting. It looks as if you can predict where the trend
started and reversed. Any pointers on how to decide the LE and SE points?

------
herve76
I built my own intelligent algo trading platform for node.js. It uses market
data from Binance and Bitfinex. My best strategy uses unusual volume amounts
on Bitfinex to trade on Binance (mostly BTCUSDT and other USDT pairs), an
advanced dynamic arbitrage. It can make up to 500-1000 usd per day but not
really much more. I started testing a LSTM neural network to optimize the
gains and reduce the risks, still early but seems very promising.

I wrote this repo a few months ago for people to get started with
cryptocurrency algo trading: [https://github.com/jsappme/node-binance-
trader](https://github.com/jsappme/node-binance-trader)

Feel free to contact me at herve76@gmail.com if you need me to write your own
custom trading algorithm.

~~~
starpilot
> Feel free to contact me at herve76@gmail.com if you need me to write your
> own custom trading algorithm.

Why would you do this when you are already making $500/day ($182,500 per
year)?

~~~
tclancy
I'd have the same question, but note the word "can" in the $500-1000 range.
And the lack of how much it can lose in a day.

------
lisbakke
Right now I have one of (or the?) fastest HFT bot on gdax -- I define
"fastest" as being on average the first bot to re place maker orders at best
when the price moves. With 1 being the first order in line it's currently
averaging 1.39 on price changes -- so it gets a ton of matches.

The bot uses a NN for predicting the price. I've been working on it for 3
months and so far the bot is profitable.

If anyone out there is interested in this space I'm looking for a partner.
Also open to business offers.

The whole pipeline (data collection, data processing, trading bot,
backtesting, model training, etc.) is built on golang, aws, and training with
keras.

Shoot me an email [redacted]

~~~
jimbob21
How do you make any money when spreads are at 1 cent?

~~~
jakevoytko
A half a penny at a time

------
dotBen
I know a few people doing this, one person in particular who has discovered a
near-zero-risk quirk that can be exploited with algorithms for fractional %age
gain per transaction/cycle/ _(kind of being vague here sorry)_. He's been able
to deploy large $MM amounts of capital to create significant gain nonetheless.

However none of them will talk about it, certainly not on HN. I'm mentioning
it simply to highlight I think you'll find an anti-selection bias by asking
here.

~~~
Blackstone4
Crypto or the stock market?

~~~
infinite8s
Divulging that is probably too much detail.

------
andr
On the positive side, there is a number of algorithmic strategies which are
unscalable - they are only profitable with a small amount of money (up to a
few millions), and become unprofitable with more assets, because they move the
market too much. This makes them uninteresting for funds and banks, and great
for the home trader.

On the negative side, the spreads, fees, and latency funds and banks get are
smaller than what you can get on online trading platforms. So focus on longer-
term strategies (with a holding period of a few hours or more), because you'll
lose out to the big guys with any medium to high frequency trading strategies.

------
thrwyaltdata
Yes. I traded equity options. The methodology can be summarized as sentiment
analysis and "alternative" data gathering.

My algorithm earned about 127% on an initial outlay of $30,000 from August of
2016 to the beginning of January 2018. The algorithm only deployed 5% of
available capital (defined risk exposure) at any time and targeted an
aggregate win rate of 60% or greater. Its primary imperative was volatility
prediction to sell options on equities with overrated volatility. Selling
options is a good foundation for a strategy because you can easily make steady
returns over time. But one loss can eliminate a year of profit (or your entire
outlay); hence the volatility prediction is required to establish a
probabilistic win rate above 50%. The goal is to profit on many small
positions consistently, not to profit on fewer large positions. Risk is
defined to limit total exposure for each trade. There are explicit stop loss
and stop profit triggers, and leaving an indeterminate amount of profit "on
the table" (selling a position early) is preferable to risking any amount of
loss.

Volatility prediction happens in two stages. Stage one is this: first the
algorithm seeks all equities with only one or two sources of revenue and a
market cap above $1B. Next it crawls news and social media to assess the
amount of "hype" attention the equity is receiving. Then it ranks this list
according to the amount of hype, weighting social media (uninformed hype) and
source of news (informed hype) differently, in ascending order. Lower hype is
considered better (and to clarify this point: hype is considered a volatility
indicator whether negative or positive). This task is executed daily.

Stage two is alternative data gathering. For each equity going down the list,
common sources of financial data are crawled (analyst earnings consensus,
prior 10Qs and 10Ks, etc). I receive a notification with a list of which
companies are "candidates" for trading, and look into them to identify sources
of alternative data. This data is mostly found through web crawling to track
signals with a 1:1 indication to a given equity's revenue. Once I have
automated the method of collecting the data, it gets incubated for timeseries
analysis for at least two quarters. If it forecasts revenue correctly to
within 95% accuracy, the equity is formally whitelisted for trading
eligibility to the algorithm.

Finally the algorithm begins selling options on each whitelisted equity. On a
daily basis a volatility forecast is made for the equity based on weighted
social sentiment and the corresponding alternative data timeseries. When the
volatility prediction reaches a certain threshold, the algorithm ceases
selling options on that equity.

------
jtd64
We are seeing a number of market enthusiast coming up with trading strategies
that work. Most don't have the staying power to get them to work enought to
trade. Some do. Those that have the staying power often lack the financial
resources to trade those algos for themselves. Problems = Capital, Access,
Data, ...

To overcome that some are turning to CloudQuant (where I work). The CloudQuant
algo development environment, backtesting tool, and trading strategy incubator
is making it easy for people to take their trading ideas to funded trading
rapidly. So far they have announced $72M in risk capital allocated to
algorirthms created by individuals. Algos are licensed from the creator.

[https://info.cloudquant.com/](https://info.cloudquant.com/)

~~~
blackflame7000
What is CloudQuant's policy regarding data collection on algorithms tested on
their service? It'd be a shame if they farmed from the best and sold it as
their own but then again, that's probably what I would do. :)

~~~
jtd64
CloudQuant makes it clear that your Intellectual Property (IP) is yours. If
you develop an alpha signal, and you collect your data on the site through
backtesting, then that is part of your IP provided it isn't a copy CQ provided
proprietary or licensed data (Market Data, Alt-Data, Fundamental Data...)

We do limit the size of downloads to ensure that you are not copying these
licensed data sets.

------
madchops1
I've been experimenting with this a lot. My code is all public still because I
haven't made any giant gains or anything. But I have seen some success here
and there. I've even got this one bot that learns from its past trades via ML
and uses what it has learned to decide wether to make future trades or not.
[https://github.com/madchops1/Dutchess.ai](https://github.com/madchops1/Dutchess.ai)

------
cirgue
The problem with these questions is that those who talk don’t know and those
who know don’t talk. No one who has a working strategy wants to say anything
interesting about it in public.

~~~
baccredited
This guy talks:

    
    
      Gary Antonacci
      book: Dual Momentum Investing
      http://www.optimalmomentum.com/gem_trackrecord.html
    

Great algorithm. Great book. I have a big chunk of my own money in this.

------
samfisher83
You probably can't do HFT trading because you need to have capital to reduce
latency. Maybe you can rent servers very close to the trading centers, but
this still will cost money.

You can use [http://www.quantopian.com](http://www.quantopian.com) to try out
different algorithms. It will tell you how well your strategy works.

~~~
jeffreyrogers
There was a great post on HN fairly recently written by someone who used to
work in HFT. He talked about how they tapped the incoming network cable to
read the incoming prices on an FPGA faster than they could make it through the
OS's network stack. I think they were sending out trades in response to the
new prices before they would have even made it to userspace on an OS.

~~~
ah-
[https://meanderful.blogspot.com](https://meanderful.blogspot.com)

Worth a read.

~~~
jeffreyrogers
Yep, that's the blog. Specifically this post
[https://meanderful.blogspot.com/2018/01/the-accidental-
hft-f...](https://meanderful.blogspot.com/2018/01/the-accidental-hft-
firm.html)

------
simonhughes22
It's not hard to build a machine learning model that can predict the price
direction with slightly more than 50% accuracy. However, once you factor in
the trading fees, slippage and the spread, you will almost always lose money.
I built a number systems that looked like easy money making schemes that would
make small amounts on most trades, but once you factor in trading costs (which
most people forget about initially) you will lose money most of the time. That
applies to the stock market and also crypto currencies if you are trying to
predict the price direction. I have heard also that predicting volatility in
the equities market is easier and the better strategy. To make money off that
you would need to use derivatives. It's less clear how to do this in crypto
unless you are trading futures, and I think making money off the price
volatility there requires a different strategy, making heavy use of limit
orders and stop losses.

------
iliicit
I made some good money (millions) in 2017 by algo trading crypto. Now in 2018,
the bear market is on, but my pnl is still decent. I collected data, trained
models, wrote execution strategies, automated everything. I was successful
because I was moving fast, trying things, breaking things, etc.

While crypto was and still is my turf, I think I could also do well in the
stock market. The problem is that the entry barriers in the stock market are
quite large. By my estimates, it will cost between 10k and 100k a month to run
an HFT strategy fast enough to compete with the fastest players in the field
(e.g. running market making strategies). If you have good alpha you could
probably get away with slower and cheaper access.

In the crypto world, the market access is free for all, and everybody has
equal standing (from what I know). After implementing some WebSocket/JSON APIs
you get access to the market that turns around 100s of millions USD per day.
Of course, it's much smaller than the stock market, but it's real
nevertheless.

I think it's a myth that smaller strategies cannot compete with established
HFT firms. It's also a myth that you need grad level knowledge of
math/statistics. It might even hurt, becuase phds will be prone to "do things
the right way" as opposed to "do things that work". I think it's also a myth
that HFT firms hire exceptional talent. In fact, most firms have rather
mediocre staff. The reason is that most firms don't make exceptional money. So
they don't have a salary pool large enough to pay exceptional people
exceptional wages. I'm talking upward from 300k. Companies like Google will
happily pay skilled engineers around that watermark. The Google/startup jobs
might feel dull, but the finance jobs are way more boring and less
rewarding... I can rant on this forever - lol.

That being said, I consider myself mediocre developer as well. Couple months
ago I applied for Senior Developer jobs at 3 firms and didn't get a single job
offer. I didn't try hard, didn't prepare for the interviews, but still.

Edit: I applied for these jobs just to see what's up. Neve intended to take
the jobs.

~~~
jimbob21
Give me your secrets

~~~
theparanoid
I suspect hard work and smarts. I've made money in sports betting and it's
mostly grinding through looking opportunities and avoiding bad bets. The
smarts part is avoiding bad bets. If you don't know who the sucker is, you're
the sucker.

------
downandout
Here’s an interesting article about using Google Trends to beat the market
that may still work:

[https://www.nature.com/articles/srep01684](https://www.nature.com/articles/srep01684)

The article is from 2013, but if anything it may be more predictive today
given the ubiquity of Google search. At the very least, since it explains the
method they used to find this signal, even if the specific keywords they used
the trends for are no longer predictive, you may be able to find others that
are. The strategy yielded a theoretical (backtested) return of 326% over a 7
year period.

------
chad_strategic
I have been building a variety of algorithms for myself over the years for my
own person enjoyment. Currently a developer and significantly under
challenged, so in the evening I build algos. But before I became developer, I
have a significant background in traditional finance.

A little selfless promotion, but I can build algo and API for brokerages.
[https://www.upwork.com/o/profiles/users/_~0143cef0c7093f242d...](https://www.upwork.com/o/profiles/users/_~0143cef0c7093f242d/)

------
equalarrow
Short answer is - yes.

I have a few buddies using a bot from Crypto Profit Bot
([https://cryptoprofitbot.com](https://cryptoprofitbot.com)) and they
definitely make profits. Sorta varies though depending on the strategies used.

I played around with this late last year and was able to tune my bot to
anywhere from 4% on up. Some trades were ridiculous with 20% or 30% when the
bot caught the pumps. Of course, 4% means I was not scalping (a lot of people
prefer just 1%-2% on trades) and was in it longer term; trades usually lasted
days or longer.

I was with a bot group last year and there were guys that made well over
$100k. But, that's all they did, they just had to babysit it and adjust the
settings. Too labor intensive for me..

There is an add-on on CPB called Feeder which is pretty cool. It looks at the
market and adjusts the settings of the bot it works with (Profit Trailer). It
can get a bit complicated tho..

Anyway, this is still an interesting space. I turned my bots off in Feb when
things started going south, but I'm thinking of starting them back up now that
the market's recovering. I have this feeling that we're gonna beat last year,
so now is probably a pretty good time.

Edit: Heh, the CPB guys did an interview on Indie Hackers a few weeks back.
Interesting read!
[https://www.indiehackers.com/interview/8b6064d829](https://www.indiehackers.com/interview/8b6064d829)

~~~
charlesdm
$100k gains, on how much capital invested is that? $20k? $50k? $100k?

~~~
equalarrow
I don't know that, but my guess is probably anywhere between $20k - $50k. I
just hear mostly stuff like "I got over 100% returns on these accounts".

For what I put in, I started with 2btc and when I stopped I had about 4. I was
taking profits along the way of a few thousand every two weeks.

Of course, if you look at the crypto market last year, that's easy to see.

------
BeetleB
My question for everyone: Where do people get reliable data for back testing?
Ideally I'd like data that goes back over 20 years. And with relatively few
data integrity issues (e.g. does not exclude companies that no longer exist).

Even more important: How do I know my data is accurate?

~~~
jeffreyrogers
There isn't an easy answer for this. Large hedge funds have entire teams whose
only job is to collect, process, and clean data.

~~~
BeetleB
I know, which makes me wonder how/why people are doing algorithmic trading on
the side when they don't have a reliable way to backtest.

I don't want minute by minute data. Average price for the day is fine with me.
Or max/min/average.

~~~
origo
There's never a very 'reliable way' to backtest, as any interaction you would
have done with the market is not accounted for. If you intend to trade (very)
low volume it might work decently (on longer timeframes). Existing (open
source) and my own home-made backtester use tweaks like slippage to try and
'simulate' this market interaction.. A few I have seen actually use tick-by-
tick L2 data to try and get closer to the 'truth'. IMHO, the only really
reliable way to evaluate a trading algorithm is to trade it live. This will
cost you money, unless you get everything perfect the first time, but doesn't
any kind of passive income generation require an initial investment? And yes,
I have written, and currently operate, my own (quite basic) trading bot. Yes,
it's profitable.

~~~
BeetleB
If I ever get into it, I do want to do low volume, with a longer time frame
(minimum would be 5 years) - which is why I don't need minute by minute data.

I don't mind paying for data if it's not too expensive.

------
rthomas6
I wrote a triangular arbitrage bot for cryptocurrencies on Binance, and made
like 0.01 ETH with ~0.3 ETH. I think that was just luck though, because all
three trades would never go through right away because the price anomaly that
caused the arbitrage opportunity would be gone before I could make all three
trades. So I ended up holding some sketchy coins that happened to go up
relative to ETH before I sold them back.

I used Python and ccxt.

------
sgerrish
I am 100% convinced that there are people doing this. I know an ex-Google
engineer who's doing it for stock options. I think, however, that to be
successful, you'd need to have some comparative advantage, e.g. one or more of
the following:

1\. access to a data source others don't have easy access to;

2\. a reasonably deep understanding of statistics and, particularly, a deep
skepticism and conservatism about any data you look at; or

3\. time to invest in looking for oddities in the market.

(3) is probably the "easiest" for a newbie, although it's not as conducive to
algorithmic trading, since it requires manual research (though, if you were
clever, you could probably come up with something to make this algorithmic).
Here the example that comes to mind is the two guys Ledley and Mai mentioned
in this chapter of the Big Short: [http://www.bookcaps.com/the-big-short-
chapter-summaries---ch...](http://www.bookcaps.com/the-big-short-chapter-
summaries---chapter-5mdashcornwall-capital-unlikely-
captitalists.html#.WuJGTNPwYn0)

------
tathougies
Yes. I have a very simple algorithm. Expressed as a function

f(state of the market) = purchase shares in a fund that tracks the S&P 500

Total return: 12-20%/yr. Sometimes more, sometimes less

~~~
omarchowdhury
When does your algo close the position?

~~~
tathougies
Once 4% of the current value equals my expenditures for the year, it'll start
selling enough capital each month so that I recuperate all my personal living
expenses. I doubt the positions will ever be fully closed out until I'm dead.

------
gerdesj
I'm going to pull out some small bits from your AHN and ask in return: If you
think you might have found a niche that might work in your favour, why on
earth broadcast it?

"...that would not be interesting enough for larger algorithmic trading firms"

This could have been your potentially unique insight.

"... But are there opportunities ..."

There probably are but you wont find them being researched on AHN.

"no need to disclose _how_ you actually do it"

So, you don't think it is original anyway.

Before you went AHN, you had an idea but instead of doing some original
research on it, you dived straight in and published it here. No doubt you will
(have already) get lots of ideas and responses but the idea is out there now
whether you want it to be or not.

~~~
charlesdm
Honestly, I don't. I was merely wondering whether people are even able to make
money doing this.

This is akin to, "are indie devs making money on the App Store in 2018?"

~~~
gerdesj
Fair one mate. I suppose I read too much into it and I apologise for perhaps
being a bit aggressive.

I take you are more interested in the environment itself rather than actively
exploiting it - although that might become an option later 8)

------
tobyhinloopen
I tried some HFT between altcoins but order latencies killed my margins. Had a
few days with up to 6% profit (per day) but net loss was 10%, mostly due
failed attempts, bugs and transaction fees.

It felt just like gambling and ate my life away for a few weeks

------
androng
I don't recommend algorithmic trading. Interactive Brokers shows that less
than half of their forex traders are profitable and it's very consistent:
[https://www.interactivebrokers.com/en/index.php?f=3731](https://www.interactivebrokers.com/en/index.php?f=3731)

If you end up doing it then do it with a very small amount of money and scale
up SLOWLY. I don't think you will have fun in cryptocurrency markets either.
They are ridiculously volatile and your bot will probably be doing nothing for
a while as it waits for the price to come back.

~~~
myroon5
Forex seems like a market where the average trader would see less success than
something like equities because Forex seems zero-sum at best. Do they have
these statistics for other markets?

------
lettergram
I've made roughly 100% yoy returns for the past 5 years. It utilizes a method
I developed now partially implenebted on:

[https://projectpiglet.com/](https://projectpiglet.com/)

Basically, it tracks experts and makes decisions on investments given what the
experts say. Think about how many times you've seen someone say: "I work at
Google, our cloud is doing X" or something like that.

The fact insiders talk, let me track them and make money.

Unfortunately, that doesn't mean I'll make money tomorrow. The market is
always correcting.

~~~
dalacv
did u just admit to insider trading?

~~~
carbocation
That is absolutely not within the definition of insider trading.

~~~
cjbprime
It seems pretty close? Insider trading is any trade that exploits non-public
information, regardless of whether it's made by an employee.

~~~
carbocation
We could be interpreting this document differently [1], but keeping track of
public forum postings by people claiming to work at tech companies seems quite
far from a reasonable definition of illegal insider trading.

1 = [https://www.sec.gov/fast-
answers/answersinsiderhtm.html](https://www.sec.gov/fast-
answers/answersinsiderhtm.html)

------
aflagatopamoon
Yes, made more money last year trading, than for all my previous jobs
combined. Probably got lucky by betting big in an up-trending market, but I'll
take it.

I use an automated inter-day scalping bot and a collection of scripts to help
with manual longer-term technical trading or jumping into a P&D for quick
profits.

Generating alpha was easier for me than setting everything up. I did not use
any complicated model or strategy.

I suppose it will get more difficult, if not impossible, once the big boys
jump in, but right now it is a market for makers.

~~~
anonu
Your answer is confusing... it sounds like you traded actively by "scalping"
\- but you admit that you got lucky via buy-and-hold ... So you didnt get paid
on alpha - but just regular beta. Very few people have alpha....

~~~
aflagatopamoon
~0.1% lending bot, ~12% scalping bot, ~7800% algo-assisted technical trading.

The luck was that when you took a BTC profit on alts, BTC would have 5x in the
mean time, so you 5x your profits. And even if you made a loss on alts, you'd
still break even dollar-wise.

------
baccredited
Yeah I made 21.4% in 2017. I wrote my own algorithms and did back-testing with
custom ruby code and data from ycharts.com ($) and brokerage.tradier.com (free
if you have an account). Ruby is a weird choice in this area as most probably
use r or python, but I love ruby.

The key for me is to focus on long-term trading strategies that are at least a
year long. The HFT guys and people who spend their time on quantopia and the
like have a day trader mentality.

Let me know if you have any questions.

Thanks for asking this question, I will look for you on twitter.

~~~
kornish
Interesting note: the S&P 500 with dividend reinvestment returned 21.14% in
2017 [1].

[1]:
[https://dqydj.com/2017-sp-500-return/](https://dqydj.com/2017-sp-500-return/)

~~~
samfisher83
If you bought and held an index fund for a year you got taxed less as well.

~~~
baccredited
Yep if I can't overcome the drag of long-term capital gains over several years
I will pull the plug.

------
casecoded
I've been using an AWS EC2 instance to run a trading algorithm I put together
in Python for the last year or so. You can see the results at
[http://kandfx.com](http://kandfx.com) which I put together as a handy way to
track its progress on the go.

I've been trading with Oanda's API for over a year but originally traded using
Metatrader 4 and built the algorithm in the native MQL4 language. That ran for
around 2 years and the 3 years prior to that was learning and developing my
strategy.

Thanks to Docker containers, Python and Amazon EC2 I can finally say I have
got the whole pipeline to a stable state which was probably the biggest hurdle
after developing the algorithm in the first place.

As for the strategy I have been very reluctant to share it with anyone because
on the surface it is very simple. That being said there are some fundamental
reasons as to why I believe its been profitable which has more to do with
psychology than anything else but it did take learning a lot just to try and
distil the behaviour into something that could make money.

I've had some mild success with Crypto but I wouldn't ever try trading it the
way I do Forex. The market behaves very differently and not to mention being
in the UK any profits from Forex trading are non-taxable as I use a spread-
betting account.

Long story short… yes, I do believe you can make money algorithmic trading. Is
it easy? No, far from it especially when it comes to having a fault tolerant
system.

------
latencyloser
Yes. I "algo" trade equity options. It's strange to me that I don't see much
mention of this answer given all the argument about stocks being a 50-50 bet.

Options let you just roll the dice on probabilities off the assumption that
the market is effectively random. You can use them to push the 50-50
probability much further in your favor.

For example, I stand to profit nicely at the next expiration (May) of most of
my options as long as the market doesn't move more than a stddev in either
direction. It could go up, down, sideways, no matter. I will make money. If it
drops significantly, I will lose marginally until my "insurance" (far OTM
puts) kick in and I start marking money again.

Edit: A common beginner's option strategy is to write a put for a stock you'd
like to own. If the stock stays flat or goes up, you make money off the
premium. If it goes down, you now own that stock. You can now turn around and
sell calls against that stock, collecting premium until you're forced to sell
the stock because it's moved back up again. You only "lose" if the stock makes
an extremely large move down (like going bankrupt, or a GE style dividend) and
you're stuck with a stock you can't sell premium against. Far from the 50-50
bet most people think of when they think of stocks.

~~~
diminoten
I guess my question about what you've described is: can't I just give you my
money, you do this for me with my money, and you make a cut off of it?

In other words, what products can I buy that basically do what you're doing
already?

~~~
latencyloser
Not me, no. But if you've got a good money manager they can/will do this sort
of thing if you ask. Otherwise, this is sort of how a hedge fund works--delta
neutral portfolio management. You can always try to join one of those.

~~~
diminoten
Thanks for answering my question, but I was being hypothetical. I just wanted
to know what services do this sort of thing in theory, not like I have money I
need to get involved in this idea!

------
thisisit
When trades are placed using a fixed setup of rules or algorithms it is called
algorithmic trading. HFT is a type of algo trading where latency is one of the
important rules.

So, while all HFT trades are algo trades, reverse isn't true.

AFAIK some(maybe a lot) of algorithm or quant firms hire people who can read
the latest investment research, form a hypothesis and test out the hypothesis
to see whether there is a winning system.

A side tip - If someone says their algorithm relies on some sort of TA, run
for the hills.

~~~
jmhyer123
> If someone says their algorithm relies on some sort of TA, run for the
> hills.

Care to explain? I'm genuinely curious as I've had some success in this area.
Curious if I should be aware of something that I'm not...

~~~
pphysch
Fundamentally, the history of a price has nothing to do with its future price.
The laws of nature do not care if you are on a bull run. So TA is completely
bunk in that regard.

However, obviously many people do rely on TA, which means TA is influencing
the price (you can beat their TA algo with your own TA algo). The problem is,
you never really know what everyone else is doing. Relying on TA amounts to
playing rock-paper-scissors, blindly, with 1000 opponents, and hoping you
choose the winning move against most of them.

Keep in mind there are only 2 outcomes, win or lose, and they occur randomly,
so it’s really easy to fall victim to selection bias and think you have a
winning TA-based algorithm.

~~~
mathgenius
> Fundamentally, the history of a price has nothing to do with its future
> price.

This is not true at all. Price movements show auto-correlation, for example.

------
clevernapkins
I have an equities strategy that I run on IB. I think it is possible to
generate alpha with a small account if you do it right e.g. don't compete with
big funds in HFT.

There's a cool article about this by Robert Carver who used to be a portfolio
manager at one of the top quant funds.

[https://qoppac.blogspot.co.uk/2015/11/david-versus-
goliath.h...](https://qoppac.blogspot.co.uk/2015/11/david-versus-goliath.html)

~~~
arisAlexis
do you think IB would close an account for algo trading? I have bad experience
with sportsbooks

~~~
admiralg
no, we support it, there's an api that you can use. Brokerages live off of
volume.

------
ljubica
We have started something similar to the your question. It is project which
generates useful signals for trading with Bitcoin and improves existing
trading strategies with these signals. In case you would like to read more, we
wrote a blog: [https://www.smartcat.io/blog/2018/bitcoin-trade-
signals/](https://www.smartcat.io/blog/2018/bitcoin-trade-signals/)

------
stojano
If I would have developed an algo for very profitable trading, I wouldn't
share it with anyone or maybe with close friends, but just making the freaking
money...

That said, 99.99% out there claiming to have such a thing is just scam, crap,
bs and/or non-sense.

But to your question: "smaller strategies" and "not be interesting enough for
larger algorithmic trading firms": There is, but why would one tell??

------
nfriedly
I was until the exchange closed and kept everything. (I only had like $100
invested because I didn't fully trust my code yet...)

I had bigger plans for the project but lost interest after that.

Code is available if anyone is interested, though:
[https://github.com/nfriedly/Coin-Allocator](https://github.com/nfriedly/Coin-
Allocator)

------
csomar
Not algo trading but working and learning to automate things as automation,
speed and more sophisticated interfaces can help me a big deal. I made a six
figures trading last year manually last year. I won't really put a light into
the markets I trade and the strategies I use. But there is lots of money for
small fish in this market.

------
parallel_item
I would like to give my 2 cents on where I see any opportunity!

A newer quant will be incentivized to create an equity strategy because the
data is available and the markets are liquid. Because the equity markets have
been automated for so long, a lot of the inefficiencies and arbitrage
opportunities have been leveraged. If a user were to come across an
opportunity, it would most likely disappear quickly, which then can lead to
your strategy hemorrhaging capital.

An alternative would be to secure data feeds and invest time in less heavily
traded securities, trading liquidity for reduced competition. This becomes a
much scarier idea, because you may not be able to exit your positions if they
slide away from you. It would generally be hard to get the right to trade
these securities without large amounts of capital or a big name behind you,
but this is part of your advantage.

------
foobaw
I've built "successful" trading statregies. As some comment mentioned, trading
on volatility is the key but it's extremely risky.

Everyone is trying to build a successful trading strategy. Honestly, a lot of
my peers seem to be making the most from "insider trading" these days.

------
wslh
Is it "no" an accepted answer?

Our company works in the crypto space and we have a small research area that
includes trading. We played with arbitrage strategies and have not seen a
consistent return. Most times when you calculate a high return path it is
because some exchange is not working really well (e.g. delaying transactions).
Not saying that our observation is universal but I don't believe you can make
right now a lot of money with arbitrage except in very discrete opportunities.

BTW, highly recommend the CCXT library[1] to connect with multiple exchanges.

[1] [https://github.com/ccxt/ccxt](https://github.com/ccxt/ccxt)

------
notadoc
I know a few people who did this with commodities, but they gave it up after a
while to pursue something totally unrelated. It appeared their assessment was
that it can work for a while until suddenly it doesn't.

------
spatular
I was making 25$ per day trading manually during a specific 20-min time slot
for about a year. That wasn't simply by chance -- nearly monotonic increase in
total earned sum with 2-week averaging during the year. Though I didn't hedge
against black swan events, and I'm not sure it would be profitable if I've
tried to. That said my understanding was that nobody else cared to take those
money. I've eventually lost all intrest too since it was impossible to scale.

That was not algorithmic trading, but maybe-could-be-possible to automate.

------
adjkant
In crypto, yes, and there are tons of bots out there, many taking very
different approaches.

There are a few very big ones that are quite easy to spot if you sit and watch
GDAX for 5 minutes.

It's too high risk for most big firms to touch it, but I assure you many are
writing bots for it. Many HFT, many AI based predictions.

I've got one that's ranged in return per year estimates from 15,000% to 1000%
(the thing I capitalize on is decreasing steadily over time). Currently
sitting up 100% in 3.5 months with a relatively low amount put in.

------
atrexler
beware survivor bias on this thread.

------
pontifier
The technique I came up with is based on re-balancing. You do a calculation of
what prices you'd need to make a trade at to re-balance your portfolio. My
calculator spits out a high and low price to make limit orders at, and if
either of those trades happen, you're re-balanced. You can cancel the other
trade, and calculate 2 more prices.

Which ever way the market moves you're better off. It's kind of the opposite
of HFT.

------
anonu
I doubt there are systematic strategies you would run from home on a high
frequency scale.

There are plenty of longer time horizon non systematic strategies that the big
firms probably do not care so much about where you can make some money, mostly
in special sits.

I've run also run a medium term systematic options premium harvesting strategy
in my PA... It was profitable. But I ran out of discretionary ammo.

------
rajacombinator
Of course there are people doing it successfully ... but very different
industry than tech - those who know stay silent. It's really not worth getting
into unless you already have years of experience imo. Keep in mind you're
competing with the smartest people in the world who have much more resources
than you. There's just more low hanging fruit elsewhere.

------
esaym
HFT can really bite you if you are not experienced in that area. I'd suggest
sticking to trading based on 30 day moving averages.

~~~
melling
There are thousands of technical indicators. How and why do you use a 30 day
SMA?

~~~
ahagg
I assume they mean price > sma30 is bullish and price < sma30 is bearish.

PSA: Don't do this

------
jxm262
Well.. I'm trying :) Still backtesting, building my system, etc.. But I have
high hopes. Like others have mentioned, it's probably not worth pursuing HFT,
but it's still alot of work just dealing with micro second data (consuming all
the data, executing multiple strategies, multiple order books, etc..)

------
kusmi
I once hacked together AI to try and predict if cost of Bitcoin will go up or
down based only on time and history of price. The program worked, but I
remember it didn't predict very well. Maybe tinkering and reworking it would
lead to something, but the combining the AI with the exchange APIs is
daunting.

------
jacquesm
This should have an extra clause: and that properly accounted for their per-
trade profits in taxes.

------
cik
I was until my trading provider eliminated API based trades 10 days ago.
Commented on it here:
[https://news.ycombinator.com/item?id=16310321](https://news.ycombinator.com/item?id=16310321)

------
lee101
Check out [https://bitbank.nz](https://bitbank.nz) for high frequency
cryptocurrency price predictions, we also have an api and some open source
plugins for bots like gekko too

------
grizzles
I use neural networks to try to predict sports betting outcomes.

In financial markets, I badly wished there was a way to bet/lay a public
company's metrics. (eg. next month's sales figures)... That would be heaven.

~~~
arisAlexis
i have a huge database of historical data pm me

------
jason_slack
I am in this boat right now. I have been writing my own tools, refining my
algos and getting ready to try my ideas. If anyone wants to talk about it, I
am hap to share what I am working on to help others.

~~~
dssilver66
Hey Jason, I too have written my own tools and am hap to share. How do people
get in touch directly on this site?

~~~
jason_slack
My email is in my profile.

------
jusonchan81
Efficient market theory prevents predicting prices to a certain extent. But
algorithms can take out emotions in trading and can limit your losses.

~~~
beagle3
But efficient markets are not a law of nature. Depending on context (e.g. HFT)
it might be a wrong assumption.

~~~
nvarsj
HFT is what makes the markets efficient, at their own profit.

------
shyn3
I've been meaning to find a developer to build something for this. Anyone have
experience with the INteractive Brokers API?

------
joeyspn
I know cases of algo traders coming from capital markets that have been so
successful that they were banned in some crypto exchanges for using highly
efficient strategies. One of the guys (he works in a top market maker during
the day) told me he was making around 100btc/month back in Q1-Q2'17.

Edit: Not saying it's easy to reach that level of profits, just that it's
possible for professional/sophisticated traders.

~~~
crispyporkbites
I know a guy who makes so much money he got banned from the internet. He told
me he makes 1000000 Btc a day. Fact.

~~~
vezycash
So your guy makes $8,957,005,000 daily?

------
whatfollows
Anyone can make money while the markets rise, but HFT probably won't keep you
afloat when the markets fall.

------
arisAlexis
I was botting for arbitrage with sports betting. they will close your accounts
fast

------
imcoconut
Its possible to do so, but it is difficult. A few years of experience in a
successful systematic team is extremely helpful. Among many other things, you
learn that running a profitable strategy involves the coordination of a number
of different types of tasks, which are similar but different enough so that
its difficult for one person to be simultaneously good enough at all of them.

To run a successful strategy requires strong signals (indicators that dictate
what to buy/sell and when), execution (actual filling of orders on exchanges),
risk management (which can include statistical risk modelling as well as draw-
down controls), and infrastructure (the wrong type of bug can be costly enough
to kill the whole operation!).

As mentioned earlier, there is overlap in the skills and experience required
for these broad categories, but people in the quant hedge fund/asset
management industry typically specialize in one. This is where larger shops
have an advantage. The entire strategy is only as good as its weakest link.
Its common for people who haven't worked in the space to focus mostly, or even
exclusively, on the signals and infrastructure aspects.

If you were to group most of the successful quant funds out there by alpha
time horizon you would see that funds within the same bucket are generally
running very similar types of strategies using very similar signals (the
general concepts behind successful signals/execution of varying time horizons
are actually not that complicated, but just might take a while to explain).
Again, that's not say its easy to do. With most of the equities and
derivatives markets getting ever more efficient, tighter coordination and
implementation of the entire strategy pipeline (signals, execution, risk mgmt,
infrastructure) can lead to significant Sharpe/Information ratio improvements.

If you wanted to get a feel for how some successful people in the industry
think about the problem, I would recommend reading through the following books
in roughly the corresponding order:

1 - [https://www.amazon.com/Efficiently-Inefficient-Invests-
Marke...](https://www.amazon.com/Efficiently-Inefficient-Invests-Market-
Determined/dp/0691166196/ref=sr_1_1?s=books&ie=UTF8&qid=1524721261&sr=1-1&keywords=efficiently+inefficient)

2 - [https://www.amazon.com/s/ref=nb_sb_noss_1?url=search-
alias%3...](https://www.amazon.com/s/ref=nb_sb_noss_1?url=search-
alias%3Dstripbooks&field-keywords=risk+management+for+dummies)

3 - [https://www.amazon.com/Active-Equity-Management-Xinfeng-
Zhou...](https://www.amazon.com/Active-Equity-Management-Xinfeng-
Zhou/dp/0692297774)

And I didn't personally like this one so much but its quite popular among the
more "academic" types

4 - [https://www.amazon.com/Active-Portfolio-Management-
Quantitat...](https://www.amazon.com/Active-Portfolio-Management-Quantitative-
Controlling/dp/0070248826/ref=cm_cr_arp_d_product_top?ie=UTF8)

------
the_cat_kittles
wouldnt you rather _do_ something to earn money?

~~~
rabidrat
Doing things doesn't really earn money these days. Perhaps someone is better
off playing the game to earn money and then doing something positive for no
money.

~~~
the_cat_kittles
there are plenty of ways to make money doing things. playing the game and then
doing something positive is also a legitimate option, so long as the game has
no negative externalities (and it often does).

------
gwbas1c
Careful... If I was making a lot of money via an algorithm; I'd want to keep
it secret. Otherwise, once other people knew about my algorithm, they'd try to
game the system.

~~~
origo
There are a lot of people using the very same algorithms for trading, and
still make money.

Using a simple EMA crossover signal with RSI and volume support is quite
sufficient to make lots of good trades, one big reason being the fact that a
lot of traders actually use the very same indicators, and self-fulfilling the
prophecy.

It takes more than just reading a few indicators to consistently trade
successfully, but my point is that many 'algorithms' and 'trading systems'
only really work when they are well known.

