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Speaker 1: Welcome to the Fear and Greed Business Interview. I'm sure Alma.

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Speaker 1: Fear and Greed is working with the team at trading

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Speaker 1: platform moomoo on a series of investors. Every Friday, we're

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Speaker 1: bringing you an episode exploring how to use technology in

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Speaker 1: data for smarter investing Today. It's all about using earnings

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Speaker 1: data to make good investment decisions. Remember, the information in

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Speaker 1: this episode is general in nature and doesn't take into

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Speaker 1: account your own circumstances. Michael McCarthy's the chief commercial officer

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Speaker 1: and market strategist at trading platform moumou, which is a

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Speaker 1: fantastic supporter of this podcast. Michael, welcome back to If

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Speaker 1: You're in Greed.

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Speaker 2: Thanks very much, so on always have to be on

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Speaker 2: my favorite podcast.

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Speaker 1: That sort of thing will get you a long, long way.

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Speaker 1: That's still a bit of in investing. One oh one

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Speaker 1: on earnings data. What do you look for when you

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Speaker 1: go through company's earnings because there's a lot of information there, Michael.

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Speaker 2: Exactly, and let me cut right through its on.

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Speaker 3: Study after study over decades has shown the surest predictor

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Speaker 3: of share price movement is changes to earnings expectations. And

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Speaker 3: that's why earnings reports are watched so closely. Statistically, we

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Speaker 3: know when the market's view on the earnings of a

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Speaker 3: company change, whether they go up or down, the share

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Speaker 3: price tends to do the same thing. And that's why

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Speaker 3: it's important to keep track of earnings, but also to

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Speaker 3: keep track of earnings expectations, and that's what we do

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Speaker 3: on the moon MOOO platform. Before or release, you can

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Speaker 3: see what the market expects. As the numbers drop, you

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Speaker 3: can immediately compare those earnings numbers the key ones, the profit,

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Speaker 3: the revenue, the cash flows, and get a quick idea

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Speaker 3: of to whether or not that company has beaten earnings. Now,

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Speaker 3: if you're an investor and you've got a long term view,

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Speaker 3: you might want to take in more information before you

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Speaker 3: make your jump into the market. But if you've got

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Speaker 3: short term trading ideals, for example, you might want to

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Speaker 3: be able to react immediately to any change to earnings

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Speaker 3: expectations because of the fact that has on share prices.

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Speaker 1: Okay, so I mean that's why sometimes you have a

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Speaker 1: really poor result in the share price goes up or

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Speaker 1: a good result in the share price goes down. Doesn't

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Speaker 1: even make sense, but it's as per expectations, how does

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Speaker 1: the move Move platform find those expectations. Is it all

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Speaker 1: about what the company has said previously or is it

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Speaker 1: analyst consensus? How do you get those expectations well?

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Speaker 3: Momoved, through its global partnerships, has access to a lot

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Speaker 3: of analysts, recommendations, earnings reports, at earnings estimates, and we

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Speaker 3: take consensus earnings estimates right, the average of what all

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Speaker 3: the analysts say to arrive at a consensus. Now, we're

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Speaker 3: also aware that sometimes outliers could affect averages. We have

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Speaker 3: our own proprietary algorithms that create what we see as

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Speaker 3: the consensus. It's generally inlign with what you'll see on

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Speaker 3: professional trading platforms. So we're pretty confident about the numbers

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Speaker 3: we're putting forward, but the market reaction is often a

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Speaker 3: good gauge. And generally speaking, if we something well away

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Speaker 3: from one of our numbers, either above or below the

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Speaker 3: expectation we've estimated as consensus, we see the sort of

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Speaker 3: market reaction we'd expect to see.

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Speaker 1: Okay, So this is instant access to company earnings data

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Speaker 1: and also instant access to expectations. How important is that

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Speaker 1: to get that quickly early on, as opposed to worry

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Speaker 1: about it in a week's time.

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Speaker 3: Well, if you're investing on a time frame of ten

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Speaker 3: twenty forty years, if you're starting out in your working career,

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Speaker 3: you might not be too worried about a simple quarterly

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Speaker 3: or semi and your report from an Australian company, a

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Speaker 3: Hong Kong company, or a US company, But if you've

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Speaker 3: got short term trading interests, you might want to know instantly.

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Speaker 3: It really depends on what the individual investor or trader

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Speaker 3: is looking for.

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Speaker 2: It's important if you're trying to time and entry.

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Speaker 3: You might have a stock on your watch list and

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Speaker 3: you wait for the earnings report, and if it does

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Speaker 3: miss earnings, then you're investing for a long time frame.

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Speaker 3: That might be good news for you because the share

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Speaker 3: price falls and you get your long term investment at

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Speaker 3: a better price. If you're a trader and at missus

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Speaker 3: and and you've gone in with positive expectations, you might

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Speaker 3: be facing a bit of a loss in your trading

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Speaker 3: account on that particular day. So whell or not a

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Speaker 3: company beats its earnings and the reaction to that depends

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Speaker 3: very much on the individual circumstances that everyone brings to

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Speaker 3: the market themselves.

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Speaker 1: Okay, so to interpreting these earnings reports against expectations. Who

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Speaker 1: has visual tools, don't you, which actually helps you do that?

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Speaker 2: Absolutely right.

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Speaker 3: We do price analysis too, to show when shares have

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Speaker 3: been bought or sold. We make analysis based on assumptions

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Speaker 3: around which side of the bid offer spread transactions are happening,

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Speaker 3: on which we use to accompany the data.

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Speaker 2: So the idea is to.

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Speaker 3: Give investors a full suite of tools if that's what

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Speaker 3: they're looking for, to help them quickly understand the earnings analysis.

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Speaker 3: But yes, straightforward graphs of some of the key metrics

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Speaker 3: also available. We aggregate them in ways that we believe

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Speaker 3: makes sense from an investment or trading point of view,

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Speaker 3: or not a particular tool that we've created is useful

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Speaker 3: to you. Is the decision entirely for you.

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Speaker 1: Stay with me, Michael, we'll be back in a minute.

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Speaker 1: My guest this morning is Michael McCarthy from MUMU. Okay,

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Speaker 1: so let's think of it in a different way. Now,

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Speaker 1: what are some of the common mistakes investors make when

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Speaker 1: looking at earnings data?

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Speaker 3: Well, once again, it depends what investment goals are involved.

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Speaker 3: But one mistake we often see is misreading the numbers.

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Speaker 3: In particular profit numbers. Now, profit numbers can be impacted

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Speaker 3: by a lot of one off effects, so it's important

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Speaker 3: to understand the headlines that are dropping with the numbers,

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Speaker 3: so that if the numbers are well away from expectations,

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Speaker 3: you quickly get an idea of what's going on. So

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Speaker 3: you'll see as earnings reports are dropping, a lot of

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Speaker 3: news reports come through on the Moonmoo platform that are

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Speaker 3: simply headlines, because we understand that a speed of understanding

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Speaker 3: around an earnings report is very important so investors can

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Speaker 3: gauge the right reaction for them. So, if for example,

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Speaker 3: a company has written down one of its key projects,

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Speaker 3: or one of the shareholdings that it has in another

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Speaker 3: company has been has gone up in value and they

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Speaker 3: want to report that and that hits the earnings for

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Speaker 3: that half year or quarter year, then people want to

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Speaker 3: know what it is that's driving that big divergence from

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Speaker 3: what they are expecting. Now, if it's just a bad

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Speaker 3: operating result, that's very important, but if it's due to

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Speaker 3: some one off factors that aren't expected to recur, that's

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Speaker 3: also important. And being able to gauge that quickly from

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Speaker 3: the headlines that are dropping at the same time as

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Speaker 3: the numbers adds a dimension of extra care around reacting

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Speaker 3: to earnings reports.

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Speaker 1: I suppose something I always found as a journalist it

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Speaker 1: was sometimes really difficult to work out what the actual

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Speaker 1: earnings report was saying. So you have net profit, and

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Speaker 1: you have underlying earnings, and when we have been so

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Speaker 1: you've got cash profits, and there's all sorts of bills

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Speaker 1: and whistles that I'm probably totally wrong, Michael, but sometimes

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Speaker 1: it doesn't seem that they're totally consistent between earning season.

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Speaker 1: How do you get through all that muck and know

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Speaker 1: what to do?

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Speaker 2: Se let me heard, let me let you in on

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Speaker 2: a trade of secret.

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Speaker 3: The harder an earnings report is to understand, the more

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Speaker 3: likely it is management doesn't want you to understand it.

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Speaker 3: It's something a little bit cynical, perhaps, but it's often

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Speaker 3: proven to be the case. If an earnings report is

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Speaker 3: well away from expectations and it's very complex and takes

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Speaker 3: a lot of study to understand, that's a concern. Transparency

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Speaker 3: is a virtue in the corporate well, just as it

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Speaker 3: is in the government world. So anytime companies are less

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Speaker 3: than transparent, it sets off alarm bells amongst analysts and

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Speaker 3: professional investors.

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Speaker 1: And mostly when we're talking about right downs, mostly they're

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Speaker 1: announced ahead of the earnings results. So a company might,

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Speaker 1: I mean, there's been one in the last couple of weeks,

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Speaker 1: whereas I think was the big miner wrote down a

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Speaker 1: an asset overseas, and that meant that they have made

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Speaker 1: a loss, which is fine, but that had been pre announced.

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Speaker 1: So mostly that sort of stuff's been pre announced, hasn't it.

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Speaker 3: Generally speaking, it is because most corporate boards these days

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Speaker 3: follow the maxim that you underpromise and overdeliver when it

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Speaker 3: comes to earnings, and that's what they're seeking to do.

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Speaker 2: There are a couple of companies in the United States

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Speaker 2: and are.

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Speaker 3: Notorious for beating earnings estimates by one penny, as they

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Speaker 3: say in the US, or one cent. So that is

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Speaker 3: the that's the structure that the management leadership of companies

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Speaker 3: are working to. They want to tell investors truly about

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Speaker 3: what's happening in the company, but they tend to slightly underestimate,

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Speaker 3: so when the time comes to deliver the numbers, they've.

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Speaker 2: Over delivered, and that can lead to.

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Speaker 3: Some mistakes in the way they go about that, but

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Speaker 3: it's one of the key reasons why big items are

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Speaker 3: often reported ahead of the result, it's so that they

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Speaker 3: don't come as a shock to the market and that

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Speaker 3: too easily misinterpreted in what can sometimes be a very

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Speaker 3: heated atmosphere around it earnings report for a major company.

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Speaker 1: We've talked lots in the last few weeks about Memur's

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Speaker 1: use of artificial intelligence AI using data to hopefully create

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Speaker 1: much well certainly create much better investment decisions. So we

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Speaker 1: do insist that all listeners should go and get advice

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Speaker 1: when it comes to investing. How can investors use this

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Speaker 1: earnings data we're talking about with all the other stuff

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Speaker 1: that we've spoken about in the last week, bad AI

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Speaker 1: bead investment strategies to kind of make a decision about

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Speaker 1: how a firm is going.

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Speaker 3: It's a fair question, and one of the keys here

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Speaker 3: is to understand that in the case of earnings report,

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Speaker 3: AI is working behind the scenes. It's not your fund

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Speaker 3: of house tool that you're going to then feed data

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Speaker 3: into and get a result from. The way we use

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Speaker 3: AI in the case of earnings reports is to most prominent.

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Speaker 2: What is most important.

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Speaker 3: So often, with say a large mining company reporting, it's

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Speaker 3: actually the production report, the number of tons of all

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Speaker 3: or the ounces of gold that they've produced, rather than

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Speaker 3: the actual cash flow and earnings and profit numbers, so

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Speaker 3: we try and make those more prominent. Now, AI algorithms

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Speaker 3: understand this that the type of industry and the type

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Speaker 3: of company it is can determine what are the most

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Speaker 3: important numbers. So rather than having to sort that out

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Speaker 3: yourself and go through pages and pages to pick out

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Speaker 3: the key numbers, we use AI to bring those most

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Speaker 3: important numbers to your attention. Others, we do sensitivity analysis

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Speaker 3: using computation power, and so we've got a profile of

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Speaker 3: what we should be putting forward. Now, like any analysis,

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Speaker 3: it's not one hundred percent perfect. Sometimes even AI makes

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Speaker 3: the mistake, believe it or not, but it does give

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Speaker 3: you a better chance of one seeing the numbers that

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Speaker 3: you need to see immediately and giving you a jump

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Speaker 3: on those investors or traders who are still sorting their

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Speaker 3: way through the full earnings report.

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Speaker 1: I suppose that's the point. It's immediate. So the result

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Speaker 1: comes out, it hits exchange. You know exactly what's going

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Speaker 1: on as per your strategy. Hopefully, Well that's right.

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Speaker 3: So the key to it is what's important is put

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Speaker 3: straight in front of you. It happens as the numbers drop,

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Speaker 3: and you'll have the framework the expectations around that number

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Speaker 3: in front of you, so that you've got a good

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Speaker 3: idea what it is that you want to do when

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Speaker 3: everything is right in front of you.

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Speaker 1: So if you've got the right strategy, technology, I'm guessing Michael,

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Speaker 1: is a big competitive advantage for an investor.

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Speaker 2: Absolutely.

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Speaker 3: I mean this started in the nineteen ninety sort. I mean,

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Speaker 3: that's how long automated trading has been a feature of

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Speaker 3: the market landscape, and the developments over that almost thirty

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Speaker 3: year period are very strong, deep and powerful, and to

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Speaker 3: the point where we're now in a position to bring

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Speaker 3: a lot of that power to individual investors.

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Speaker 2: A lot of these tools were reserved.

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Speaker 3: Only professional investors who had the backing of large institutions

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Speaker 3: that it can make the investment necessary to build them.

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Speaker 3: But with groups like Technology First companies like Mumu, we

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Speaker 3: are able to bring that to individual investors. And as

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Speaker 3: I say, in a lot of cases, it works in

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Speaker 3: the background. You don't have to have professional level expertise

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Speaker 3: to understand what it is that Momour's AI is showing

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Speaker 3: you around earnings reports.

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Speaker 1: I reckon that's exactly what I've learned over the past

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Speaker 1: few weeks Michael is that the actual access as a journalist,

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Speaker 1: you could talk to analysts who had all sorts of

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Speaker 1: computational power. But what I think is quite amazing now

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Speaker 1: is it's an individual investor you can actually grab hold

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Speaker 1: of that, which hasn't been the case really up until well,

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Speaker 1: certainly your platform, but until recent years, really that's never

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Speaker 1: been available to a retail investor.

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Speaker 3: I would argue, Oh, I absolutely concur as a professional

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Speaker 3: trader and investor for many years, decades through Frank, I've

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Speaker 3: used almost every professional platform, plenty of proprietary platforms, and

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Speaker 3: a lot of the retail platforms. This is the most

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Speaker 3: powerful platform I've come across in the individual investor and

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Speaker 3: trade of space. It's at the cutting edge of technology

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Speaker 3: for people who invest in trade the way I do.

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Speaker 1: Michael, thank you for talking to Fear and Greed.

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Speaker 2: Thank you, Sean.

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Speaker 1: That was Michael McCarthy from mumou, a great supporter of

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Speaker 1: this podcast. For more information on the Moomoo platform, follow

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Speaker 1: the link in today's show notes, and remember that information

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Speaker 1: in this podcast is general in nature and you should

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Speaker 1: get professional advice to make sure a product is right

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Speaker 1: for you before proceeding. This is the Fear and Greed

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Speaker 1: Business Interview. Join us every morning for the full episode

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Speaker 1: of Fear and Greed. Daily business news for people who

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Speaker 1: make their own decisions. I'm sure the Elma enjoy your day.