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Tralek23


Total Posts: 5
Joined: May 2020
 
Posted: 2020-05-19 12:15

Hi everyone, this is my first post in this community and I hope it could be beneficial for any other trader that is facing the same situation.

After more than a year spent in learning algotrading, I’ve developed a long-term strategy with 12% CAGR and prudent risk management.

I’ve started to invest my own money on the strategy and I’m building a track record on it.
The strategy is developed in python and the code is running on a QuantConnect server.

I’ve found different online platforms (Quantopian, QuantConnect itself) that allows you to license your strategy, but performance requirements are high and strict in the short-term.

From my experience with banks, ”long-term low-risk investment” rarely achieve 12% CAGR, so I thought that these results were more than good.
Good, but not enough to have a sustainable income with my savings, so I’m looking for different business models.
 
My business model ideas are:
-License the algorithm 
-Sell the signals 
-Open or make a deal with a Hedge fund. 

Do you have any experience or suggestions?
Who could be interested in these strategies?

Thanks in advance

tradeking


Total Posts: 30
Joined: May 2016
 
Posted: 2020-05-19 15:12
What asset class and sharpe ratio?

Tralek23


Total Posts: 5
Joined: May 2020
 
Posted: 2020-05-19 16:51
The strategy trades the S&P 500 constituents as assets.
Some stats for the 2008-2020 period.
Sharpe Ratio: 0.9
Win Rate: 63%
Profit Loss Ratio: 1.14
Max Drawdown: 18%
Annual Standard Deviation: 0.11

tradeking


Total Posts: 30
Joined: May 2016
 
Posted: 2020-05-20 02:46
How correlated is it to equities and common style factors?

A backtest sharpe of under 1.5 would not gain much interest from institutions I'm afraid, especially if coming from a non-professional background. The easiest route would be to break into the industry first (perhaps as an entry level quant), and then gain enough reputation over time to be allowed to run the strategy. By then you would most likely have improved on it many times based on the extra professional experience.

Tralek23


Total Posts: 5
Joined: May 2020
 
Posted: 2020-05-20 10:23
Hi Tradeking, thanks for your response,

It’s a long-only strategy so it tends to be correlated with the market, but it reduces the effects of negative periods with lower drawdowns (18% vs 55% of SPY) and has a faster recovery time.

About the common style factors, sorry but I don’t know how to estimate a correlation with them.

EspressoLover


Total Posts: 437
Joined: Jan 2015
 
Posted: 2020-05-21 21:25
Have you tried neutralizing the beta (and possibly the industry and factor exposure as well) to raise the Sharpe ratio?

Long-only trading of orthogonal signals on single-names in the S&P 500 is inefficient from a mean-variance objective. Without knowing more about your strat, I'd guess the sizable bulk of your vol is probably beta. Whereas it's pretty unlikely that you're deriving any serious alpha from market exposure. (Or at the very least if your backtest tells you are, it's probably spurious.)

Try looking down this route. To echo Tradeking, it's *way* easier to sell a 2+ Sharpe strategy than a 0.9 one. Distilling more alpha's always arduous, but oftentimes there's a (nearly) free lunch when it comes to reducing vol.

Good questions outrank easy answers. -Paul Samuelson

NeroTulip


Total Posts: 1075
Joined: May 2004
 
Posted: 2020-05-22 00:52
Have you looked at your strategy's alpha, beta and correlation to S&P?

"Earth: some bacteria and basic life forms, no sign of intelligent life" (Message from a type III civilization probe sent to the solar system circa 2016)

rickyvic


Total Posts: 217
Joined: Jul 2013
 
Posted: 2020-05-22 09:09
No I just wanted to ask you guys one question:
any hedge fund has a total (not single strategy) sharpe ratio of more than 0.9 over the course of 5-10 years?

Yes it is true that people chose by sharpe ratio but it is also true that most of them are incapable of producing alpha with a decent capacity (rentech and a few stars aside).

So this is the bs going on.

Then what I would say is that 0.9 if it is real and sustainable is good especially if this means high capacity and long horizons.
Will you sell it? Probably not. Background is key.

Another suggestion: now that you have something long term focus the next steps on the short term intraday focusing on non directional. If you have questions pm.

Hopefully I added some colour to what @espressolover said

"amicus Plato sed magis amica Veritas"

svisstack


Total Posts: 351
Joined: Feb 2014
 
Posted: 2020-05-22 09:25
If you will be interested in backtesting/trading crypto from QuantConnect then drop me a line.

We (CoinAPI) are already integrated with QuantConnect in terms of market data and will expand this integration to the trading with our self-hosted order management api, so the end goal will be backtesting and trading directly from QuantConnect on crypto markets and as an added bonus you can connect to our OMS API to get information about the orders from all exchanges to make eg. risks calculations outside QuantConnect or smth.

It will be useful to have stakeholders feeding us feedback.

First Commander of the USS Enterprise

gaj


Total Posts: 103
Joined: Apr 2018
 
Posted: 2020-05-22 10:19
Is 12 years even enough to conclude anything statistically significant about a long term strategy? Say if your holding period is 1 year, then you only have 12 independent data points. Any strategy can be overfitted to such a small dataset.

DouglasP


Total Posts: 12
Joined: Jan 2014
 
Posted: 2020-05-22 14:39
Would it be feasible to achieve this by using a min-tracking error optimization around the original portfolio (including a short side, be it index futures or actual single stock positions), with beta/factor exposure constraints? That way you'd try to remain as close as possible to the original idea.

Tralek23


Total Posts: 5
Joined: May 2020
 
Posted: 2020-05-22 15:05
Thanks for all the replies, I’ll try to sum up on one post.

@EspressoLover
>> Have you tried neutralizing the beta…
Yes, I tried but my strategy operates mainly (but not only) on bullish market phases, so being beta neutral is not beneficial to the strategy.

>> but oftentimes there's a (nearly) free lunch when it comes to reducing lunch.
Sorry, I can’t fully understand the meaning, what do you mean by reducing lunch?

@NeroTulip
>> Have you looked at your strategy's alpha, beta, and correlation to S&P?
Here some stats I’ve calculated:
beta 0.51
alpha 0.061
volatility 0.103
correlation 0.73


@rickyvic
Thanks for your useful suggestions, I’ll pm you in the next days,

@svisstack
Currently I operate only on the stock market, anyway I'll contact you in case I'll create a crypto one.

@gaj
The strategy performs about a trade per week, it is a long term strategy but the positions are not held more than a few days.

@DouglasP
I’ve not tried the mean-tracking optimization. Anyway the strategy signals are not overlapping so I’ve never focused too much on portfolio optimization strategies.

Its Grisha


Total Posts: 56
Joined: Nov 2019
 
Posted: 2020-05-22 16:04
> it is a long term strategy but the positions are not held more than a few days

If you are holding positions for only a few days, transaction costs (both explicit and implicit) become a very serious consideration. Plenty of alphas disappear after accounting for them.

Its Grisha


Total Posts: 56
Joined: Nov 2019
 
Posted: 2020-05-22 16:04
edit: sorry double post

EspressoLover


Total Posts: 437
Joined: Jan 2015
 
Posted: 2020-05-22 17:22
@tralek

(Sorry, previous comment had a typo should have said "reducing vol" not "reducing lunch")

Effectively you don't have a 0.9 Sharpe strat. You have a 0.6 Sharpe strat (alpha/volatility). The additional 0.3 (and lower drawdown vis-a-vis the market) comes from diversifying its exposure with the market portfolio. But that doesn't "count", because nobody is going to pay you to provide beta. If a big investor wants long exposure to the S&P 500, she's going to do it through Vanguard at 5 basis points. Or Bridgewater at 100 basis points. But definitely not you at any cost.

I really want to emphasize this, because the only chance you have of selling this to a serious investor is as an absolute return product. And a 0.6 Sharpe absolute return product may be sellable, but not unless you have a pedigree. It is absolutely essential that you boost the Sharpe to at least 1.0, if not higher.

You mention that the strategy only seems to do well during bullish expansions? Are you sure that's not just because of the long-only nature of your positions? If you think of what you've been trading as a mixture of S&P 500 + [your unique signals], then maybe it's the S&P 500 that's making it bullish-bias. Try backtesting again, but beta-neutralizing every position. (I.e. short an equivalent amount of SPY on every long trade).

Beyond this, I see three likely avenues to boost the Sharpe. The first is turning over your positions more frequently. You say you hold a few days, but why? How frequently are you rebalancing the portfolio? If you're just using end-of-day data, it's possible that intraday rebalancing may reveal more trading opportunities.

Have you evaluated what the alpha realization curve looks like? It's frequently the case that 50% of the alpha realizes in a few hours. If you can exit trades much faster and still get most of the profit, that means less exposure and/or more capital available to do other trades that would otherwise be tied up in long-term positions.

The second option is to simply diversify across a larger basket of trades. I assume that your signals gives you something like a ranking of stocks in your universe? And then you go long the best stock? What about buying the top 5 names? Or top 100? Or all the stocks with positive signals in proportion to the signal magnitude? If you're long-only that doesn't help that much, because you still have market exposure regardless. But if you're beta neutral, then diverisfying the single-name exposure is a big win.

Also, have you evaluated the signal in terms of the short-side? What if you hedge the beta by shorting the bottom ranked stocks (instead of shorting SPY)? Now you're getting an alpha both from the short and long side. In most anomalies the short-side has larger alpha than the long-side. That would naively double the Sharpe. (Not completely because single names have higher t-costs than index hedges, cost of borrow, etc.)

Third, can you expand the size of the universe? Right now you look at S&P 500 single names. Can you do the Russell 3000? Can you add ETFs? Can you expand internationally to Europe, Asia or emerging markets? Commodities? Currencies? Bonds? If you can find 4 different markets or countries with orthogonal performance, you've just doubled the Sharpe ratio.

Finally I want to second @gaj. I'm not convinced that the strategy's performance isn't spurious. I don't want to be negative, but any potential investor will ask the same thing. At 0.6 Sharpe with 12 years of history, the null hypothesis barely clears statistical significance of 2.0 t-stat. And that doesn't account for any lookback bias. Was this the very first thesis you tried? Is any of that performance using in-sample trained parameters? Did you tweak the strategy parameters based on historical performance?

This is a secondary, but very convenient benefit of higher-Sharpe strategies. They can be statistically validated with less historical data. The upshot is if performance is spurious, then all of the previous suggestions will tend to make the strategy look worse. If the strategy is real, then diversifying and hedging will distill the signal. But if you've just overfit noise, then removing any of the vol will just dampen the noise.

This is one of the biggest pitfalls even seasoned practitioners fall into. It's tough to call it when a strategy you've worked hard on ends up being a dead end. But it happens all the time. A tell-tale sign is when performance seems to evaporate when you make any changes. Real signals are usually robust. It's way too easy to be defensive and declare "my particular strategy just doesn't work in a beta-neutral context" or "it has to be rebalanced at market close" or "it just doesn't work outside the US". In reality, you should probably interpret it as a sign that there's just nothing there.

Good questions outrank easy answers. -Paul Samuelson

sharpe_machine


Total Posts: 60
Joined: Feb 2018
 
Posted: 2020-05-22 18:20
> Or all the stocks with positive signals in proportion to the signal magnitude?

One interesting question is what to do with rankings when you have the majority of the liquidity outside of top10 (or whatever border you like) positions and alpha is skewed towards top-ranked stocks.

wquant


Total Posts: 5
Joined: Nov 2019
 
Posted: 2020-05-24 12:45
I'm interested in how this would work in practice. Let us say you had a solid strategy, what's the best way to garner interest with a hedge fund (assuming no existing contacts)

Are there firms out there actively looking to seed early-stage strategies or be otherwise helpful in terms of data/ordering infrastructure?

NeroTulip


Total Posts: 1075
Joined: May 2004
 
Posted: 2020-05-25 03:52
@Tralek23: I don't want you to think I am not responding to you, but EspressoLover has made my point and much more. Nothing to add, except reread his post and get to work.

"Earth: some bacteria and basic life forms, no sign of intelligent life" (Message from a type III civilization probe sent to the solar system circa 2016)

svisstack


Total Posts: 351
Joined: Feb 2014
 
Posted: 2020-05-31 20:38
BTW. Escalated this to the QuantConnect CEO as we have a contact to check if this misalignment between alpha measurement is on purpose or not. It may be a bug in the QuantConnect that you can't monetize some type of edges (long term mid-Sharpe).

First Commander of the USS Enterprise

Tralek23


Total Posts: 5
Joined: May 2020
 
Posted: 2020-06-04 14:39
@EspressoLover I would like to thank you for your long and comprehensive reply, I hope it could be a helpful resource for others in the same situation.

@Its Grisha
In my algorithm, I account for commissions, bid/ask spread and I trade liquid assets only so that the total slippage will not impact too much on the strategy.

@NeroTulip, ok thanks for your suggestions in any case.

@wquant
>> Are there firms out there actively looking to seed early-stage strategies or be otherwise helpful in terms of data/ordering infrastructure?

I’m contacting small fund and asset manager that are showing interest in the strategy.


Thank you all, you gave me a lot of ideas and feedback, I’ll work on it and I’ll update this thread in case of relevant developments.
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